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VOLUME 13, ISSUE 6, JUNE 2025
DEVELOPMENT OF CLOUD-BASED SMART PLANT WATERING SYSTEM
Ronneil P. Babis
Smart Translation For Physically Challenged People
Malashree M S, Sujal N Murthy, Thejaswini J, Yashapradha M, Yashwanth K
A novel, heart diagnosis tool, based on Electro-cardiogram (ECG), using VHDL and FPGAs
Dr Evangelos I. Dimitriadis, Leonidas Dimitriadis
IONIZATION AND ELECTROPLATING EFFECTS OF DISSOLVED SUBSTANCE IN LIQUID SLUTIONS
Onyeyili T. 1, Ezeagwu C.O, Onuzulike V.C, Anyigor, I. S, Ugwuanyi, P. O and Ugwuanyi Gilbert
Bridging Knowledge and Practice: Enhancing Financial Well-being through Financial Planning, Literacy, and Digital Tools
Srujan Kumar Ganta, Abdul Faiyaz Shaik, Syed Waheeduddin Khadri, Sruthi Balammagary
QUALITY EVALUATION OF PEC 2017-COMPLIANT ELECTRICAL WIRING SOFTWARE: ISO/IEC 25010-BASED APPROACH
SHANE GREY H. BELDIA
Development of HiL (Hardware-in-Loop) Technique for MCU Testing and BLDC Motor Simulation
Vighnaraj Dinkar Mohite
ADVERSE IMPACT OF COVID-19 ON SPORTS PARTICIPATION
Pravind Kumar, Dr. Chandrakant Karad
Stress Factors Among Married Women Teachers
Ranjan Kumar Pandey, Chandrakant Karad
“A STUDY OF SOCIAL-EMOTIONAL DEVELOPMENT IN YOGIC PRACTITIONERS”
Bharat Bhusan, Dilip Bhadke
Service Provider Application
Nandini G R,Sevanthi M, S Yashswini G tilak, Yashwitha P R, Unnatha D R
Accident detection and alert system using embedded system
BHAGYASHREE, KUSMANJALI MANTHALE, LALITA PATIL, NANDITA MUDHOL, PROF. SARA ANJUM
Integrating AI and IoT for Enhanced Safety in Household Electrical Appliances
Meshal Mohammed Saleem Albalawi
TECH-ENABLED WALKING STICK FOR VISION IMPAIRED
Mrs. Y. Aruna Suhasini Devi, Royyala Priyanka, Cherlapalli Swathi, Keerthi Mani Teja
Detecting Wild Animals Using VGG-19 And GRU
Y. ARUNA SUHASINI DEVI, L. ARAVIND REDDY, D. NITHIN, D. GANESH
FACIAL RECOGNITION BASED VEHICLE AUTHENTICATION SYSTEM
Prof. Dr. Minal V. Gade, Md Afroj, Sahil kadaskar, Pratik Wagh
MUSCULAR ANALYSIS OF FUNDAMENTAL HUMAN MOVEMENTS: A BIOMECHANICAL PERSPECTIVE
Jai Bhagwan Singh Goun
Microcontroller based automatic water level controller- A Review
Purva Trivedi, Dr. Arun Parakh, Shurbhit Surage
AI-Driven Predictive Maintenance for Electrical Machines and Systems
Anjali Sachin Alkanti, Prof. Dnyaneshwar Shivaji Waghmode
“Automatic Temperature control fan”
Kajal Lalchand Kate, Prof. Dnyaneshwar Shivaji Waghmode
Electric Power Generation From Solar Electric Vehicles
Sakshi Chandrakant Kamble, Prof. Dnyaneshwar Shivaji Waghmode
Enhancing Renewable Energy Infrastructure with Robotic Predictive Maintenance System
Ms. Vaishnavi Narwade, Prof. Dnyaneshwar Shivaji Waghmode
Efficiency and Innovation in Hydrogen-Powered Electric Vehicles
Arpita Subhash Inamdar, Prof. Dnyaneshwar Shivaji Waghmode
Mono Electrical Vehicle
Priyanka Sanjay Bhadange, Prof. Dnyaneshwar Shivaji Waghmode
Development of a Sensor-Based Smart Irrigation Framework for Sustainable Agriculture
Priti Bilambe, Prof. Dnyaneshwar Shivaji Waghmode
Smart Grid Technology
Akshata Swami, Prof. Dnyaneshwar Shivaji Waghmode
Design and Implementation of IoT-Based Prepaid Smart Energy Meter for Efficient Power Management
Vaishnavi Vishwas Kale, Prof. Dnyaneshwar Shivaji Waghmode
The Role of Smart Grid in the Efficiency Management of Renewable Energy
Kirti Shridhar Pasnur, Prof. Dnyaneshwar Shivaji Waghmode
Solar Tree: Sustainable Tree by SolarBotanic
Sneha B Gaikwad, Prof. Dnyaneshwar Shivaji Waghmode
Virtual Electrical Labs Powered by AR
Ms. Pratiksha Dixit, Prof. Dnyaneshwar Shivaji Waghmode
Wireless Power Transfer for EV Charging
Shweta Irappa Tadaval, Prof. Dnyaneshwar Shivaji Waghmode
Forecasting the Future: AI-Driven Resilience in Renewable Energy Grids
Priyanka Nagesh Kadam, Prof. Dnyaneshwar Shivaji Waghmode
Design and Implementation of a Mobile-Controlled Electric Bulb System Using IoT Technology
Ms. Zeba Choudhari, Prof. Dnyaneshwar Shivaji Waghmode
Design and Application of Wireless Transmission Systems for Modern Communication Networks
Ms. Rutuja Mudholkar, Prof. Dnyaneshwar Shivaji Waghmode
Real World Uses of OCR for Modernization of Traffic system
Dr. Saurabh A Ghogare, Prof. Abhijit G Kalbande
Understanding 5G Technology: The future of wireless communication
Bhargavi Konda, Surabhi Kale, P.K.Digge
Enhancing Workplace Safety through Effective Use of Personal Protective Equipment (PPE)
Bhanu Balaji Katkam, Poonam Shrimant Belbhandare, Prof. P. K. Digge
Solar Based Electrical vehicles (EV’s) Charging Station
Amruta Rajendra Bhutekar, Prof. P. K. Digge
Tracking System for Soldiers
Vaishnavi Shriniwas Mithapalli, J.A.Patil
Microprocessor Based motor speed controller
Ruchita Pegdyal, J. A. Patil
HOME AUTOMATION SYSTEM
Sakshi Sandip Kavade, Vaishnavi Shrinivas Koppul, Prof. P. K. Digge
Automatic fruit sorting machine based on weight
Gauri Vasant Pawar, Gayatri Shrinivas Posham, Prof. P. K. Digge
IoT-Based Aquaponics System for Sustainable Farming
Mrs. Zubeda Begum, Shaik Qasim Ahmed, Md Saif Khan, Syed Abdul Gaffar
Cyber-Driven Surveillance and Alert System for Illegal Logging Detection in Protected Forest Areas
Dr. Abdul Mateen Ahmed, Syed Shah Akber Hussaini, Shaik Abdul Rahman, Shaikh Azeemuddin
“Design and Implementation of a Microcontroller-Based Borewell Rescue System with Drone-Assisted Monitoring.”
Shaikh Azeemuddin, Mohd Hassan, Abdul Razzaq
Optical Satellite Communication
Ms. Pradnya Kumri, Prof. J.A. Patil
Monthly Electricity Billing Display With SMS Feature
Krishnaveni Naresh Kolpyak, Prof. J.A.Patil
"Advanced Technologies In Electric And Hybrid Vehicles"
Vidya Gour, Prof. P. K. Digge
Artificial Intelligence In Healthcare
Ms. Aarti Chivadshetti, Prof. J. A. Patil
THERMOELECTRIC COOLING SYSTEM USING PELTIER EFFECT
Sanchita .R. Devakte, Prof.J.A.Patil
Data Acquisition and Control System Using LabVIEW
Banumathi K L, Ruchitha Mahesh Dasareddy, Shreenikha H S,Vijayalaxmi Sthavarmath, Yashavanth K S
Desgin of Low Power Asynchronous SAR ADC in CMOS Technology
Savithri G R, Shashank M Jadhav, Rohan B K, Naveen R D, Prajwal C Malagi
Skin Disease Classification Using Multi-Model Optimization and Augmentation
Shivani R Shankar, Pavan Gudi, Anil Prasad, Kalyanaraman Raju, Yogapriya Rajalingam
Abstract
DEVELOPMENT OF CLOUD-BASED SMART PLANT WATERING SYSTEM
Ronneil P. Babis
DOI: 10.17148/IJIREEICE.2025.13601
Abstract: This research investigated the development and evaluation of a cloud-based smart plant watering system designed to automate plant irrigation based on real-time environmental conditions. The purpose of this study was to address the inefficiencies and inconsistencies associated with manual plant watering by integrating environmental sensing technologies, cloud computing, and user-friendly applications. The methodology followed a developmental research approach, incorporating stages such as conceptualization, system design, prototyping, testing, and evaluation. Data was collected using environmental sensors, with the system architecture based on a Raspberry Pi Model 3B controller and cloud services for data storage and monitoring. The evaluation process included 32 evaluators (13 in-person and 19 online), who assessed the system's hardware (interface circuits) and software (desktop and mobile applications). Evaluation instruments comprised a five-point Likert scale and ISO/IEC 25010 standards, with statistical analysis performed using SPSS version 27.
The system demonstrated effective automation of irrigation using a modular setup of environmental sensors, a microcontroller, and cloud-based monitoring accessible via desktop and mobile platforms. Performance testing revealed the system’s rapid and responsive moisture regulation, with Sensor 3 recording a moisture increase of 78.33% in 29 seconds (162.07%/s), confirming high efficiency in water delivery. Despite some sensor anomalies and environmental variability, consistent trends in data validated the system’s reliability. User evaluation of the external interface circuit yielded an average satisfaction score of 4.77, while application usability under ISO/IEC 20510 standards averaged 4.59, both categorized as “Very Acceptable.” Limitations included the absence of backup power and local monitoring options, though future enhancements involving AI and blockchain were identified to improve precision and data security.
Keywords: Cloud-Based, Watering, Automation, Sensor data, Development, Evaluation.
The system demonstrated effective automation of irrigation using a modular setup of environmental sensors, a microcontroller, and cloud-based monitoring accessible via desktop and mobile platforms. Performance testing revealed the system’s rapid and responsive moisture regulation, with Sensor 3 recording a moisture increase of 78.33% in 29 seconds (162.07%/s), confirming high efficiency in water delivery. Despite some sensor anomalies and environmental variability, consistent trends in data validated the system’s reliability. User evaluation of the external interface circuit yielded an average satisfaction score of 4.77, while application usability under ISO/IEC 20510 standards averaged 4.59, both categorized as “Very Acceptable.” Limitations included the absence of backup power and local monitoring options, though future enhancements involving AI and blockchain were identified to improve precision and data security.
Keywords: Cloud-Based, Watering, Automation, Sensor data, Development, Evaluation.
Abstract
Smart Translation For Physically Challenged People
Malashree M S, Sujal N Murthy, Thejaswini J, Yashapradha M, Yashwanth K
DOI: 10.17148/IJIREEICE.2025.13602
Abstract: This paper introduces an AI-driven translation platform developed to enhance communication for individuals with speech and hearing disabilities. The solution integrates advanced technologies such as Natural Language Processing (NLP), gesture recognition using MediaPipe, and Artificial Neural Networks (ANNs) to enable seamless two-way interaction. It supports real-time conversion of spoken language into Indian Sign Language (ISL) through animated GIFs, while also interpreting gestures captured via webcam into coherent text. The system is deployed using a Django-based web application, ensuring both usability and scalability. Unlike conventional tools, this integrated solution enables dynamic, real-time, bidirectional communication, making it highly applicable in fields like education, healthcare, and public services. Experimental evaluations indicate the system achieves an 85% accuracy rate in recognizing gestures and a 92% accuracy rate for speech-to-sign translation, marking a notable advancement over existing approaches
Keywords: Sign Language Translation, Assistive Technology, Artificial Neural Networks, Natural Language Processing, Accessibility, Gesture Recognition, Indian Sign Language
Keywords: Sign Language Translation, Assistive Technology, Artificial Neural Networks, Natural Language Processing, Accessibility, Gesture Recognition, Indian Sign Language
Abstract
A novel, heart diagnosis tool, based on Electro-cardiogram (ECG), using VHDL and FPGAs
Dr Evangelos I. Dimitriadis, Leonidas Dimitriadis
DOI: 10.17148/IJIREEICE.2025.13603
Abstract: An FPGA-based system is presented here, capable of simultaneous measuring electrocardiogram (ECG) in- put values and display them in seven-segment displays, while it also derives a heart diagnosis, based on the above ECG. Heart diagnosis activates corresponding LED alarm system, providing information about several heart problems such as hypercalcemia, hypocalcemia, hyperkalemia, coronary ischemia, bundle-branch block and AV node block, all of them derived from critical time values of the ECG. Our system has also the ability of calculating and presenting in seven-segment displays, heart beat rate in pulses/min, with simultaneous activation of corresponding alarm system, which is responsible of lighting three respective heart beat rate LEDs, for vradycardia, normal heart beat rate and tach- ycardia. Additionally, buzzer alarm and all FPGA board LEDs are also simultaneously activated, if pulses/min values are less than 60 (vradycardia) or higher than 100 (tachycardia). The system uses DE10-Lite FPGA board with an HW 827 sensor connected to it. The above sensor output is also connected to a blinking LED system, in order to have visual information of heart beat rate. Our system can work with a variety of heart pulse sensors and it is clear that deriving a successful heart diagnosis requires an electrocardiogram recording that is as accurate as possible. The system can also be combined with IoT technology, offering doctors the ability to remotely monitor patients online.
Keywords: Heart beat rate, Sensors, Heart diagnosis, VHDL, Buzzer, LEDs
Keywords: Heart beat rate, Sensors, Heart diagnosis, VHDL, Buzzer, LEDs
Abstract
IONIZATION AND ELECTROPLATING EFFECTS OF DISSOLVED SUBSTANCE IN LIQUID SLUTIONS
Onyeyili T. 1, Ezeagwu C.O, Onuzulike V.C, Anyigor, I. S, Ugwuanyi, P. O and Ugwuanyi Gilbert
DOI: 10.17148/IJIREEICE.2025.13604
Abstract: The application of electrical conductivity in liquids in electroplating process is investigated. Electrolysis is a process of separating elements electrically. A great many liquids are decomposed when an electric current passes through them, and this process is known was electrolysis. Elements are often chemically combined with other elements and must be separated. Electrolysis is employed in the industry for electroplating of metal, purification of metals, and extraction of metals from their ores. Generally, electrolysis is a process by which electric current is passed through a substance to effect chemical change. The chemical change is one in which the substance loses or gains an electron (oxidation and reduction). The term electrolysis was first popularized in the 19th century by Michael Faraday, and it is a process that helped in the study of chemical reactions in obtaining pure elements. It is further defined as a process of decomposing ionic compounds into their elements by passing a direct electric current through a compound in a fluid form (solution). In the process of electrolysis, the cations are reduced at cathode and anions are oxidized at the anode. The main components required in the electrolysis process are electrolyte, electrodes, and some form of external power sources (DC power source). The process is of course done in a vessel called the “electrolytic cell”, containing two electrodes (cathode and anode), which are connected to a direct current (DC) source and an electrolyte which is an ionic compound undergoing decomposition, in either molten form or in a dissolved state in a suitable solvent (liquid). Generally, electrodes that are made from metal graphite, and semiconductor materials are used. However, the choice of a suitable electrode is done based on chemical reactivity between the electrode and electrolyte as well as the manufacturing cost. Usually, in electrolysis process, there is the interchange of ions and atoms due to the addition and removal of electrons from the external circuit. On passing current through the electrolyte via the electrodes, cations move to the cathode, take electrons from the cathode (given by the supply voltage source), and discharged into the neutral atom. If it is so the neutral atom is solid, it is deposited on the cathode, but if it is gas, it moves upwards and this process is called a reduction process, and the cation is reduced at the cathode. Similarly, anions give up their extra electrons to the anode and it is oxidized to neutral atoms at the anode. The electrons released by the carriers travel across the electrical circuit and reach the cathode, thereby completing the circuit. It is worthy to note very important role the cell voltage (potential) plays in electrolysis process which largely depends on the ability of the individual ions to absorb or release electrons. It is also sometimes referred to as the decomposition potential, which is the minimum voltage difference in electrode potential, between anode and cathode for an electrolytic cell that enables electrolysis to occur. To simplify the understanding of electrolysis, discussed in a very simple term, the electrolysis of Copper Sulphate solution.
Keywords: Conductivity, Oxidation, Electrolysis, Electroplating, Electrolyte, Electrode.
Keywords: Conductivity, Oxidation, Electrolysis, Electroplating, Electrolyte, Electrode.
Abstract
Bridging Knowledge and Practice: Enhancing Financial Well-being through Financial Planning, Literacy, and Digital Tools
Srujan Kumar Ganta, Abdul Faiyaz Shaik, Syed Waheeduddin Khadri, Sruthi Balammagary
DOI: 10.17148/IJIREEICE.2025.13605
Abstract: As the economic environment becomes more and more complex and dynamic, the need for personal finance management and financial planning has expanded by leaps and bounds. The citizens have to make smart financial decisions in an attempt to be financially healthy, reach life milestones, and have a secure future. This essay looks at the basics of financial planning, including budgeting, saving, investing, debt management, retirement planning, tax effectiveness, and protection from risk. It also looks at the necessity for personal finance management in creating discipline in finances and allowing individuals to live within their means and avoid the consequences of poor financial management. Among the general issues of the paper is convergence between financial behaviour and financial literacy. What is found through research is that low financial literacy is associated with adverse financial outcomes, such as high debt levels, poor retirement savings, and investment decisions. The paper confirms the importance of offering extensive financial education and literacy courses to equip people with abilities and proficiency in making effective financial decisions across the life cycles. Furthermore, the research examines digital technology's role in personal finance, such as mobile applications, robo-advisors, and planning websites on the internet. These are increasingly accessible, automated, and information-intensive, thus more accessible and affordable. Nevertheless, the article also takes into account shortcomings in the form of behavioral biases, inconsistency, information overload, and financial risk that still make it challenging to manage personal finance. By the convergence of theoretical concepts and practical solutions, the paper provides strategic suggestions for individuals, teachers, and policymakers to enhance financial decision-making, become financially resilient, and achieve long-term financial well-being. Based on case studies, models, and empirical evidence, this paper highlights the life-changing potential of financial planning to enhance quality of life and alleviate financial distress.
Keywords: Financial Planning, Personal Finance Management, Financial Literacy, Saving, Budgeting, Financial Behaviour, Digital Financial Tools, Investment Strategies, Retirement Planning, Debt Management, Risk Management, Financial Education, Financial Well-being, Economic Resilience
Keywords: Financial Planning, Personal Finance Management, Financial Literacy, Saving, Budgeting, Financial Behaviour, Digital Financial Tools, Investment Strategies, Retirement Planning, Debt Management, Risk Management, Financial Education, Financial Well-being, Economic Resilience
Abstract
QUALITY EVALUATION OF PEC 2017-COMPLIANT ELECTRICAL WIRING SOFTWARE: ISO/IEC 25010-BASED APPROACH
SHANE GREY H. BELDIA
DOI: 10.17148/IJIREEICE.2025.13606
Abstract: The growing accessibility of simulation systems, applications, and software for electrical wiring has been especially noticeable in recent years. These digital solutions are frequently created to address increasing demands for efficiency and reliability in performance. Nevertheless, when electrical materials are calculated by hand, errors can arise—frequently going unnoticed because of the intricate and accuracy-focused nature of these computations, which are prone to human mistakes. The rise of numerous simulation tools has made evaluating their quality a significant issue. This research assesses the quality of an electrical wiring software adhering to PEC 2017 standards, utilizing specific objective metrics grounded in the ISO/IEC 25010 software product quality framework. Four essential quality attributes— functional appropriateness, performance effectiveness, interaction ability, and dependability—were evaluated. Fifty evaluators, including experts, students, academics, electrical engineers, and technologists, took part in the assessment. The findings indicated that the software garnered outstanding ratings in all four categories, with reliability obtaining the top score. The results show that the electrical wiring software is effective and dependable. It is advised that the software undergo frequent updates to stay in accordance with the progressing standards of the Philippine Electrical Code (PEC) and be broadly embraced in both educational and industrial environments to enhance awareness and utilization of dependable digital tools in electrical system design.
Keywords: electrical wiring software, simulation, standards compliance, electrical system design
Keywords: electrical wiring software, simulation, standards compliance, electrical system design
Abstract
Development of HiL (Hardware-in-Loop) Technique for MCU Testing and BLDC Motor Simulation
Vighnaraj Dinkar Mohite
DOI: 10.17148/IJIREEICE.2025.13607
Abstract: Air pollution is significantly driven by harmful exhaust gases emitted from automotive engines. Conventional vehicles predominantly rely on petrol and diesel, which not only release hazardous pollutants but are also derived from non-renewable resources. To mitigate air pollution and address the finite availability of fossil fuels, transitioning to Electric Vehicles (EVs) is imperative. EVs do not depend on crude oil and emit no harmful gases, making them a sustainable alternative. This paper focuses on the essential components of EVs, including the battery for energy storage, the motor for propulsion, and the Motor Control Unit (MCU), which regulates motor speed and torque. The MCU interprets driver inputs and controls the inverter that generates signals to operate the Brushless DC (BLDC) motor efficiently. To ensure optimal performance of EVs, it is essential to test and validate both the vehicle and its individual components. Traditional testing methods are costly and time-consuming, as they require physical vehicle prototypes and iterative installation and removal of components. To address these limitations, this research proposes the design and implementation of a Hardware-in-the-Loop (HiL) system. The HiL system enables simulation-based validation of EV components in a controlled environment, significantly reducing development time and costs while enhancing testing efficiency.
Keywords: Motor Control Unit, Hardware-in-Loop Technique, Closed-Loop Tests Simulation, VT system, BLDC motor Simulation, Automated Test Bench Setup
Keywords: Motor Control Unit, Hardware-in-Loop Technique, Closed-Loop Tests Simulation, VT system, BLDC motor Simulation, Automated Test Bench Setup
Abstract
ADVERSE IMPACT OF COVID-19 ON SPORTS PARTICIPATION
Pravind Kumar, Dr. Chandrakant Karad
DOI: 10.17148/IJIREEICE.2025.13608
Abstract: The COVID-19 pandemic significantly disrupted sports participation worldwide, affecting individuals, communities, and institutions across all levels of physical engagement. Lockdowns, social distancing mandates, and the closure of public spaces led to the suspension of organized sports activities—from local school competitions to international mega-events like the Olympic Games Tokyo 2020. The closure of gyms, stadiums, and sports clubs curtailed access to training facilities, limiting both professional athletes and amateur participants. This sudden disruption had a cascading effect on physical activity, particularly among youth, students, and vulnerable groups such as women, persons with disabilities, and rural populations.
Beyond physical health, the pandemic imposed psychological strain on athletes, coaches, and sports professionals due to prolonged isolation, canceled careers, and financial uncertainty. Many grassroots and community sports organizations faced economic challenges, leading to closures and reduced access to sports infrastructure. School and collegiate sports development programs were also halted, causing long-term gaps in athlete development and physical education. As digital alternatives attempted to fill the void, disparities in access to technology further widened inequalities in participation. This paper explores the adverse impacts of COVID-19 on sports participation with a focus on physical, psychological, economic, and social dimensions.
Keywords: COVID-19, Sports Participation, Physical Activity, Mental Health, Lockdown, Youth Sports, Athlete Well- being, Sports Facilities, Economic Impact, Grassroots Sports, Inequality in Sports, Post-pandemic Recovery
Beyond physical health, the pandemic imposed psychological strain on athletes, coaches, and sports professionals due to prolonged isolation, canceled careers, and financial uncertainty. Many grassroots and community sports organizations faced economic challenges, leading to closures and reduced access to sports infrastructure. School and collegiate sports development programs were also halted, causing long-term gaps in athlete development and physical education. As digital alternatives attempted to fill the void, disparities in access to technology further widened inequalities in participation. This paper explores the adverse impacts of COVID-19 on sports participation with a focus on physical, psychological, economic, and social dimensions.
Keywords: COVID-19, Sports Participation, Physical Activity, Mental Health, Lockdown, Youth Sports, Athlete Well- being, Sports Facilities, Economic Impact, Grassroots Sports, Inequality in Sports, Post-pandemic Recovery
Abstract
Stress Factors Among Married Women Teachers
Ranjan Kumar Pandey, Chandrakant Karad
DOI: 10.17148/IJIREEICE.2025.13609
Abstract: The role of women in modern society has significantly evolved, with increasing numbers of married women actively contributing to the education sector. However, this dual responsibility of managing professional duties and familial obligations often subjects them to high levels of stress. This study aims to investigate the major stress factors affecting married women teachers in India, focusing on work-life balance, time constraints, lack of administrative support, societal expectations, and family responsibilities.
A survey was conducted among 200 married women teachers working in primary, secondary, and higher secondary schools across Delhi NCR. The data were analyzed using descriptive statistics and visualized through graphs and tables to assess the distribution and intensity of stress factors. The findings reveal that time management between home and work, excessive workload, and inadequate recognition are the top stressors among respondents.
The literature review supports these results, indicating that Indian married women teachers face significant psychological and emotional strain due to their multifaceted roles. This paper discusses the implications of such stress on teachers’ job satisfaction, performance, and mental health. It concludes with practical recommendations to reduce stress levels through institutional support, time management training, and family counseling services.
This study contributes to understanding the psychosocial challenges faced by female educators and underscores the need for reforms in both institutional and domestic spheres to enable a more supportive work environment for women. Further longitudinal research is recommended to evaluate the long-term effects of such stress and the effectiveness of interventions.
Keywords: Stress, Married women, Teachers, Work-life balance, Time management, Indian education, Job satisfaction, Family responsibilities, Emotional well-being, Gender roles
A survey was conducted among 200 married women teachers working in primary, secondary, and higher secondary schools across Delhi NCR. The data were analyzed using descriptive statistics and visualized through graphs and tables to assess the distribution and intensity of stress factors. The findings reveal that time management between home and work, excessive workload, and inadequate recognition are the top stressors among respondents.
The literature review supports these results, indicating that Indian married women teachers face significant psychological and emotional strain due to their multifaceted roles. This paper discusses the implications of such stress on teachers’ job satisfaction, performance, and mental health. It concludes with practical recommendations to reduce stress levels through institutional support, time management training, and family counseling services.
This study contributes to understanding the psychosocial challenges faced by female educators and underscores the need for reforms in both institutional and domestic spheres to enable a more supportive work environment for women. Further longitudinal research is recommended to evaluate the long-term effects of such stress and the effectiveness of interventions.
Keywords: Stress, Married women, Teachers, Work-life balance, Time management, Indian education, Job satisfaction, Family responsibilities, Emotional well-being, Gender roles
Abstract
“A STUDY OF SOCIAL-EMOTIONAL DEVELOPMENT IN YOGIC PRACTITIONERS”
Bharat Bhusan, Dilip Bhadke
DOI: 10.17148/IJIREEICE.2025.13610
Abstract: Social-emotional development encompasses self-awareness, emotional regulation, social skills, and empathy—elements vital for psychological resilience and interpersonal effectiveness. In the face of rising stress and mental health issues, there is growing interest in holistic practices such as yoga to promote mental and emotional well- being. Yoga, a discipline rooted in Indian philosophy, integrates physical postures (asanas), breathing techniques (pranayama), and meditation (dhyana), offering a comprehensive mind-body approach to self-regulation and emotional balance.
This study investigates the impact of yogic practices on social-emotional development among adult practitioners. Using a comparative cross-sectional design, the study includes 150 participants—75 regular yoga practitioners (minimum one year of continuous practice) and 75 non-practitioners, selected from wellness centers and community organizations in Delhi NCR, India. The Social Emotional Competence Questionnaire (SECQ) and Emotional Quotient Inventory (EQ-i) were used to assess competencies such as self-regulation, emotional awareness, and social interaction. Qualitative data were also collected through semi-structured interviews.
Findings indicate that yoga practitioners scored significantly higher in emotional intelligence, empathy, and interpersonal communication. Qualitative narratives revealed that regular engagement with yoga improved stress management, increased patience, and fostered deeper self-reflection. These results align with previous studies highlighting yoga's benefits in enhancing mental and emotional health (Riley & Park, 2015; Telles et al., 2019).
This study supports the integration of yogic interventions into mental health and educational programs, suggesting that regular practice contributes positively to social-emotional growth. It also underscores yoga’s potential role in fostering community well-being and emotional literacy. Further longitudinal research is recommended to examine causality and broader applicability across populations.
Keywords: Social-emotional development, Yoga practitioners, Emotional intelligence, Mindfulness, Self-regulation
This study investigates the impact of yogic practices on social-emotional development among adult practitioners. Using a comparative cross-sectional design, the study includes 150 participants—75 regular yoga practitioners (minimum one year of continuous practice) and 75 non-practitioners, selected from wellness centers and community organizations in Delhi NCR, India. The Social Emotional Competence Questionnaire (SECQ) and Emotional Quotient Inventory (EQ-i) were used to assess competencies such as self-regulation, emotional awareness, and social interaction. Qualitative data were also collected through semi-structured interviews.
Findings indicate that yoga practitioners scored significantly higher in emotional intelligence, empathy, and interpersonal communication. Qualitative narratives revealed that regular engagement with yoga improved stress management, increased patience, and fostered deeper self-reflection. These results align with previous studies highlighting yoga's benefits in enhancing mental and emotional health (Riley & Park, 2015; Telles et al., 2019).
This study supports the integration of yogic interventions into mental health and educational programs, suggesting that regular practice contributes positively to social-emotional growth. It also underscores yoga’s potential role in fostering community well-being and emotional literacy. Further longitudinal research is recommended to examine causality and broader applicability across populations.
Keywords: Social-emotional development, Yoga practitioners, Emotional intelligence, Mindfulness, Self-regulation
Abstract
Service Provider Application
Nandini G R,Sevanthi M, S Yashswini G tilak, Yashwitha P R, Unnatha D R
DOI: 10.17148/IJIREEICE.2025.13611
Abstract: This project, Service Master, is an Android-based mobile application designed to simplify the process of booking essential home services. Users can browse, select, and schedule appointments with professionals such as electricians, barbers, carpenters, and other service providers through a clean and intuitive interface. The application offers user authentication, service categorization, a shopping cart mechanism, and a final booking confirmation feature to deliver a seamless user experience.
Developed using Kotlin and the Android SDK, the app follows a modular architecture where each service category is handled via dedicated adapter classes and views. Users can register or log in securely, explore service options, add desired services to a cart, and confirm bookings with ease. Firebase integration provides backend support for authentication and data handling, while a local database helper may manage cart or user preferences offline.
Additional features such as splash screens and thank-you messages contribute to a professional user experience. The project showcases practical implementation of RecyclerViews, Intents, Firebase services, and Gradle configuration using Kotlin DSL. Ultimately, Service Master serves as a digital bridge between customers and service providers, offering a fast and user-friendly solution for managing day-to-day service needs.
Keywords: Android Application, Home Services Booking, Kotlin , Firebase Integration, Recycler View, Service Categories, User Authentication, Cart System ,Mobile App Development, On-Demand Services, Gradle Kotlin DSL, Android SDK,Service Provider Platform, Booking Confirmation, User Interface Design
Developed using Kotlin and the Android SDK, the app follows a modular architecture where each service category is handled via dedicated adapter classes and views. Users can register or log in securely, explore service options, add desired services to a cart, and confirm bookings with ease. Firebase integration provides backend support for authentication and data handling, while a local database helper may manage cart or user preferences offline.
Additional features such as splash screens and thank-you messages contribute to a professional user experience. The project showcases practical implementation of RecyclerViews, Intents, Firebase services, and Gradle configuration using Kotlin DSL. Ultimately, Service Master serves as a digital bridge between customers and service providers, offering a fast and user-friendly solution for managing day-to-day service needs.
Keywords: Android Application, Home Services Booking, Kotlin , Firebase Integration, Recycler View, Service Categories, User Authentication, Cart System ,Mobile App Development, On-Demand Services, Gradle Kotlin DSL, Android SDK,Service Provider Platform, Booking Confirmation, User Interface Design
Abstract
Accident detection and alert system using embedded system
BHAGYASHREE, KUSMANJALI MANTHALE, LALITA PATIL, NANDITA MUDHOL, PROF. SARA ANJUM
DOI: 10.17148/IJIREEICE.2025.13612
Abstract: Car accidents are becoming more frequent, especially in remote areas where emergency help takes too long to arrive, leading to preventable injuries and deaths. To solve this problem, we developed an intelligent car safety system that automatically detects crashes and immediately calls for help. The system uses several smart sensors working together: impact sensors that feel when your car hits something, distance sensors that spot obstacles and blind spots around your vehicle, and GPS technology that knows exactly where you are at all times. When a crash happens, the system's built-in cell phone module automatically sends emergency text messages with your precise location to rescue services, helping ambulances and police find you much faster. The device is controlled by an Arduino computer chip and includes a small screen to display information, a buzzer for loud warning sounds, and Bluetooth capability for testing purposes. Think of it as a smart guardian angel for your car that works even in remote areas with poor cell service - the moment something goes wrong, it immediately alerts emergency responders with your exact location, potentially saving precious minutes that could mean the difference between life and death. This automatic response system is especially valuable when drivers are unconscious or unable to call for help themselves, ensuring that emergency assistance arrives as quickly as possible.
Keywords: GPS, GSM, Piezo, ultrasonic sensor, Arduino uno, embedded system, smart transportation and accident detection.
Keywords: GPS, GSM, Piezo, ultrasonic sensor, Arduino uno, embedded system, smart transportation and accident detection.
Abstract
Integrating AI and IoT for Enhanced Safety in Household Electrical Appliances
Meshal Mohammed Saleem Albalawi
DOI: 10.17148/IJIREEICE.2025.13613
Abstract: The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has emerged as a transformative approach to enhancing safety in household electrical appliances. This review explores how AI-driven predictive maintenance, real-time anomaly detection, and automated responses, combined with IoT-enabled sensor networks and cloud analytics, mitigate risks such as electrical faults, overheating, and fire hazards. By analyzing current technological advancements, we highlight the efficacy of AI models (e.g., deep learning, federated learning) and IoT frameworks (e.g., edge computing, 5G) in reducing appliance-related accidents. Case studies from industry leaders (e.g., Samsung SmartThings, Nest Protect) demonstrate reductions in false alarms (85%) and emergency response times (63%). However, challenges like data privacy, interoperability, and cost barriers persist. Future directions include quantum AI, self-healing materials, and policy initiatives to bridge socioeconomic disparities in access to smart safety technologies.
Abstract
TECH-ENABLED WALKING STICK FOR VISION IMPAIRED
Mrs. Y. Aruna Suhasini Devi, Royyala Priyanka, Cherlapalli Swathi, Keerthi Mani Teja
DOI: 10.17148/IJIREEICE.2025.13614
Abstract: This paper introduces a tech-enabled walking stick that supports visually impaired people by improving mobility and security. The gadget is prepared with diverse sensors, counting ESP32-based farther checking framework, Apr voice module, and GPS following. The stick provides a real-time language arm through the APR module to ensure that users receive immediate feedback from their surroundings. Additionally, Guardians can monitor sensor data via a web-based interface for improved safety and monitoring. The light and rechargeable design of the stick is extremely practical for everyday use. This innovation is aimed at providing greater independence and improved navigation to people with visual impairments.
Keywords: Arduino Uno, ESP32, GPS, Ultrasonic Sensor, ARP Voice Module, IOT, Remote Monitoring.
Keywords: Arduino Uno, ESP32, GPS, Ultrasonic Sensor, ARP Voice Module, IOT, Remote Monitoring.
Abstract
Detecting Wild Animals Using VGG-19 And GRU
Y. ARUNA SUHASINI DEVI, L. ARAVIND REDDY, D. NITHIN, D. GANESH
DOI: 10.17148/IJIREEICE.2025.13615
Abstract: Detecting and keeping tabs on wild animals is super important for protecting wildlife preventing human- wildlife conflicts and keeping an eye on our forests traditional methods like basic CNN object detection and machine learning can really struggle with busy backgrounds tracking movement and working in real-time to tackle these issues our project introduces a hybrid deep neural learning model that brings together VGG-19, Bi-LSTM and CNN-GRU to accurately and efficiently identify wildlife we use VGG-19 to pull out key spatial features making it easier to recognize different species Bi- LSTM helps us capture temporal relationships allowing us to analyze movement patterns across video sequences on top of that we employ CNN-GRU to optimize computation performance enabling smooth real-time processing while keeping accuracy high our model is trained on large datasets that cover a variety of animal types and environmental conditions. Our test results confirm that VGG- 19, Bi- LSTM and CNN-GRU model nails a classification accuracy of 98.2 greatly beating out traditional CNN methods and popular detection systems like yolo and faster r-cnn this system with its low false positives and negatives is ready for real-world uses in forest monitoring and wildlife conservation this study really emphasizes how deep learning can step up wildlife detection tracking and classification finally boosting safety and conservation efforts.
Keywords: VGG-19, Bi-LSTM, CNN, CNN-GRU, Object Detection, Deep Learning, Accuracy, Spatial features, Human- Wildlife Conflict, Environmental conditions.
Keywords: VGG-19, Bi-LSTM, CNN, CNN-GRU, Object Detection, Deep Learning, Accuracy, Spatial features, Human- Wildlife Conflict, Environmental conditions.
Abstract
FACIAL RECOGNITION BASED VEHICLE AUTHENTICATION SYSTEM
Prof. Dr. Minal V. Gade, Md Afroj, Sahil kadaskar, Pratik Wagh
DOI: 10.17148/IJIREEICE.2025.13616
Abstract: The "Facial Recognition-Based Vehicle Authentication System" uses facial recognition to improve vehicle security. It works by scanning the face of the person trying to start the vehicle and only allows ignition if the face matches that of an authorized user, like the owner. This system aims to prevent vehicle theft by blocking unauthorized users from starting the vehicle. If an unauthorized face is detected, it triggers an alert to notify the owner, enhancing overall security and reducing theft risks. Although significant progress has been made in using facial recognition and detection techniques for authentication purposes, including security and identity verification, some lingering issues still need to be addressed to reach outstanding precision on par with human-level performance. The proposed system uses face detection for Identity Verification and gives full access to authorized vehicle drivers based on the interface of Raspberry Pi 4B development board, pi-camera. In an era where security and convenience are paramount, facial recognition technology has emerged as a powerful tool in various applications, including vehicle authentication.
Keywords: Open cv, Face recognition, Raspberry pi, Servo motor
Keywords: Open cv, Face recognition, Raspberry pi, Servo motor
Abstract
MUSCULAR ANALYSIS OF FUNDAMENTAL HUMAN MOVEMENTS: A BIOMECHANICAL PERSPECTIVE
Jai Bhagwan Singh Goun
DOI: 10.17148/IJIREEICE.2025.13617
Abstract: Fundamental human movements form the foundation of all physical activity and are essential for functional independence, athletic performance, and rehabilitation. This paper presents a comprehensive analysis of these movements from both muscular perspectives, integrating principles of biomechanics and physiology to explore how the human body generates and controls movement. The study emphasizes the critical role of major muscle groups and neuromuscular coordination in producing basic movement patterns such as walking, running, jumping, lifting, pushing, and pulling. It further investigates the mechanical principles underlying these actions, including Newton’s laws of motion, levers, torque, center of gravity, and force application. A detailed examination of how muscle contractions—agonists, antagonists, synergists, and stabilizers—interact to produce efficient and coordinated motion is presented using case studies of locomotion, manipulation, and postural control.
Keywords: biomechanics, fundamental movements, muscle analysis, sports science, rehabilitation.
Keywords: biomechanics, fundamental movements, muscle analysis, sports science, rehabilitation.
Abstract
Microcontroller based automatic water level controller- A Review
Purva Trivedi, Dr. Arun Parakh, Shurbhit Surage
DOI: 10.17148/IJIREEICE.2025.13618
Abstract: The water crises is increasing globally. Hence it is of utmost importance to preserve water on earth. In many domestic, commercial places lot of water is being wasted daily due to overflow of water tanks. An automatic water level controller is beneficial in preventing overflow of water tank. As water level rises or fall below maximum or minimum values different sensors installed inside water tank send signals. These signals are used to turn on or turn off the motor pump.
Keywords: Automatic water level indicator, sensors, Controller, water.
Keywords: Automatic water level indicator, sensors, Controller, water.
Abstract
AI-Driven Predictive Maintenance for Electrical Machines and Systems
Anjali Sachin Alkanti, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13619
Abstract: Artificial Intelligence (AI) is transforming the domain of electrical engineering by facilitating smart decision- making, predictive analytics, and automation in a vast variety of applications. This paper offers an exhaustive discussion of the adoption of AI methodologies like machine learning, deep learning, fuzzy logic, and evolutionary algorithms in prominent areas of electrical engineering such as power systems, smart grids, renewable energy, electrical machines, and power electronics. The research examines how AI improves system efficiency, reliability, and fault tolerance using intelligent load forecasting, predictive maintenance, adaptive control, and fault diagnosis. Additionally, the paper identifies current developments, recent achievements, challenges, and future directions in AI-based electrical engineering solutions. The results indicate that ongoing development and integration of AI can play an important role in the development of more sustainable, efficient, and smart electrical infrastructures.
Keywords: Artificial Intelligence (AI), Electrical Engineering, Predictive Maintenance, Fault Detection, Renewable Energy Integration, Fuzzy Logic, Neural Networks, Energy Management, Genetic Algorithm.
Keywords: Artificial Intelligence (AI), Electrical Engineering, Predictive Maintenance, Fault Detection, Renewable Energy Integration, Fuzzy Logic, Neural Networks, Energy Management, Genetic Algorithm.
Abstract
“Automatic Temperature control fan”
Kajal Lalchand Kate, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13620
Abstract: This project presents the design and implementation of a temperature control fan system that automatically adjusts its speed based on the surrounding temperature. The primary objective is to provide an energy-efficient solution for maintaining optimal environmental conditions, especially in areas where temperature fluctuations can affect comfort, safety, or equipment performance. The system utilizes a temperature sensor (such as LM35 or DHT11) to continuously monitor ambient temperature. The sensor data is processed by a microcontroller (e.g., Arduino), which controls the fan speed using pulse-width modulation (PWM) or relay switching mechanisms. The fan activates or increases its speed proportionally when the temperature exceeds a predefined threshold, but slows down as the temperature decreases. This intelligent fan system is applicable in-home automation, electronics cooling, greenhouses, and other temperature- sensitive environments. The project demonstrates the effective use of sensors and automation to create a responsive and energy-saving cooling solution.
Keywords: temperature sensor, PWM control, microcontroller, fan, HVAC automation
Keywords: temperature sensor, PWM control, microcontroller, fan, HVAC automation
Abstract
Electric Power Generation From Solar Electric Vehicles
Sakshi Chandrakant Kamble, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13621
Abstract: As the global demand for sustainable and renewable energy solutions increases, solar electric vehicles (SEVs) offer a promising innovation by integrating photovoltaic (PV) technology into electric mobility. This paper explores the concept of electric power generation from SEV shighlighting how embedded solar panels can convert sunlight into usable electrical energy for vehicle propulsion, battery charging, and even grid support through bidirectional energy systems.While current technological limitations—such as low surface area, variable solar efficiency, and high costs— pose challenges to large-scale adoption, advancements in lightweight materials, high-efficiency PV cells, and intelligent energy management systems are steadily improving SEV viability. This study examines the design considerations, power output potential, and real-world implementations of solar-powered electric vehicles, including case studies like Lightyear, Aptera, and Sono Motors. The integration of SEVs into smart grids and decentralized energy systems represents a significant step toward reducing carbon emissions and enhancing energy resilience. Overall, this paper provides a comprehensive overview of the technical, environmental, and economic aspects of power generation from SEVs, highlighting their potential role in a sustainable transportation future.
Keywords: Solar Electric Vehicles (SEVs), Photovoltaic Systems, Renewable Energy, Electric Vehicle
Keywords: Solar Electric Vehicles (SEVs), Photovoltaic Systems, Renewable Energy, Electric Vehicle
Abstract
Enhancing Renewable Energy Infrastructure with Robotic Predictive Maintenance System
Ms. Vaishnavi Narwade, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13622
Abstract: The global shift towards renewable energy is a vital step in fostering sustainability and reducing our dependence on fossil fuels. Nevertheless, maintaining the infrastructure of renewable energy systems, such as wind turbines, solar panels, and energy storage technologies, presents ongoing challenges. Traditional maintenance strategies, including periodic inspections and reactive repairs, are often expensive and lead to considerable downtime. This study explores the potential of robotic systems in implementing predictive maintenance (PdM) within renewable energy networks, emphasizing their capacity to enhance operational efficiency and reduce costs. By integrating cutting-edge robotics with predictive data analytics, these systems facilitate continuous monitoring, anticipate failures before they occur, and automate inspection tasks, even in difficult-to-reach or isolated environments. The paper examines different robotic solutions, including drones, autonomous robots, and robotic manipulators, alongside the use of IoT sensors, machine learning, and AI to refine maintenance strategies. Additionally, it investigates the challenges associated with system integration, scalability, and ensuring operational safety. The findings indicate that robotic PdM technologies not only increase the lifespan of renewable energy assets but also help lower maintenance costs and boost energy production efficiency. In conclusion, the paper proposes a comprehensive framework for incorporating robotic PdM solutions into renewable energy infrastructures, presenting a path to more efficient and reliable management of these critical systems.
Keywords: Robotic Maintenance Solution, Predictive Energy Management, Automation in Renewable Infrastructure, Condition-Based Monitoring in Energy Systems, Intelligent Maintenance Technologies
Keywords: Robotic Maintenance Solution, Predictive Energy Management, Automation in Renewable Infrastructure, Condition-Based Monitoring in Energy Systems, Intelligent Maintenance Technologies
Abstract
Efficiency and Innovation in Hydrogen-Powered Electric Vehicles
Arpita Subhash Inamdar, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13623
Abstract: Hydrogen-powered electric vehicles (FCEVs) have emerged as a transformative solution for sustainable transportation, leveraging the high energy efficiency of electric drivetrains combined with the zero-emission potential of hydrogen fuel. This paper presents a comprehensive review of recent innovations in proton exchange membrane (PEM) fuel cell technologies, advanced system integration approaches, and intelligent energy management strategies that collectively enhance the performance and efficiency of FCEVs. Significant advancements in high-performance catalysts, durable membrane electrode assemblies (MEAs), and next-generation bipolar plates have substantially improved fuel cell durability, energy density, and cost-effectiveness. Concurrently, developments in lightweight composite materials, optimized aerodynamic designs, and vehicle control systems contribute to reduced energy consumption and extended driving ranges. Smart energy management systems incorporating regenerative braking, thermal management, and hybridization with auxiliary battery storage systems further elevate operational efficiency. In addition to technical advancements, this study critically examines persistent challenges including hydrogen production pathways, high- pressure storage solutions, safety concerns, and the limited refuelling infrastructure. It also underscores the importance of robust policy frameworks, strategic investments, and financial incentives aimed at fostering both infrastructure growth and consumer adoption. A coordinated effort among governments, industries, researchers, and consumers is vital to overcome existing barriers and drive large-scale deployment. Future research directions are proposed, focusing on improving hydrogen supply chain sustainability, enhancing fuel cell recycling processes, and integrating FCEVs into smart grid systems. Ultimately, the widespread adoption of hydrogen-powered electric vehicles will depend on continuous innovation, cross-sector collaboration, and a global commitment to achieving carbon-neutral transportation.
Keywords: Hydrogen Fuel Cell Vehicles (FCEVs), Energy Efficiency, Fuel Cell Technology, Sustainable Mobility, Hydrogen Storage, Smart Energy Management, Clean Transportation, Renewable Energy Integration.
Keywords: Hydrogen Fuel Cell Vehicles (FCEVs), Energy Efficiency, Fuel Cell Technology, Sustainable Mobility, Hydrogen Storage, Smart Energy Management, Clean Transportation, Renewable Energy Integration.
Abstract
Mono Electrical Vehicle
Priyanka Sanjay Bhadange, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13624
Abstract: The monowheel electric vehicle (MEV) is an innovative, single-wheeled, self-balancing personal transportation device powered by electric propulsion. Designed for individual users, the MEV combines the agility and compactness of traditional unicycles with modern electric motor technology. These vehicles rely on a combination of gyroscopes, accelerometers, and tilt sensors to maintain dynamic balance, allowing riders to intuitively control speed, acceleration, and direction through subtle body movements and leaning.
Keywords: Urban micro-mobility, Zero-emission transportation, Lightweight electric vehicle, Self-balancing vehicle
Keywords: Urban micro-mobility, Zero-emission transportation, Lightweight electric vehicle, Self-balancing vehicle
Abstract
Development of a Sensor-Based Smart Irrigation Framework for Sustainable Agriculture
Priti Bilambe, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13625
Abstract: Efficient water management is a critical challenge in modern agriculture, especially under the pressures of climate change and increasing food demands. This research presents the design and implementation of a Smart Irrigation System leveraging Internet of Things (IoT) technology, real-time sensor networks, and cloud-based analytics. The system utilizes soil moisture sensors, temperature sensors, and weather forecasting data to automate irrigation schedules, significantly reducing water consumption while enhancing crop productivity.
A microcontroller-based architecture (using Arduino/ESP32) processes sensor inputs and triggers irrigation actions through wireless communication protocols. A mobile application and web dashboard provide farmers with real-time monitoring and remote -control capabilities. Field tests demonstrate that the proposed smart system can save up to 40– 60% of water compared to traditional irrigation methods.
This study also highlights the scalability, cost-effectiveness, and environmental benefits of smart irrigation, paving the way for broader adoption of precision agriculture technologies. Future work will focus on integrating machine learning algorithms for predictive irrigation and expanding the system to accommodate large-scale farming operations.
Keywords: Precision Agriculture, Soil Moisture Monitoring, Sensor Networks, Climate-Adaptive Irrigation, Water Conservation
A microcontroller-based architecture (using Arduino/ESP32) processes sensor inputs and triggers irrigation actions through wireless communication protocols. A mobile application and web dashboard provide farmers with real-time monitoring and remote -control capabilities. Field tests demonstrate that the proposed smart system can save up to 40– 60% of water compared to traditional irrigation methods.
This study also highlights the scalability, cost-effectiveness, and environmental benefits of smart irrigation, paving the way for broader adoption of precision agriculture technologies. Future work will focus on integrating machine learning algorithms for predictive irrigation and expanding the system to accommodate large-scale farming operations.
Keywords: Precision Agriculture, Soil Moisture Monitoring, Sensor Networks, Climate-Adaptive Irrigation, Water Conservation
Abstract
Smart Grid Technology
Akshata Swami, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13626
Abstract: The evolution of global energy systems involves a shift from conventional, centralized power grids to more intelligent, responsive, and sustainable infrastructures. Smart Grid Technology has emerged as a crucial solution to the increasing challenges of energy efficiency, reliability, environmental sustainability, and the integration of renewable energy sources. A smart grid is an advanced electrical system that enhances power generation, transmission, distribution, and consumption by utilizing digital communication, real-time data analytics, automation, and control technologies.
Smart grids allow for two-way communication, unlike traditional power networks that function through a one-way flow of electricity with no contact between utility suppliers and users. This makes it possible to perform dynamic load balancing, perform real-time monitoring, and have flexible reactions to changes in the supply and demand for energy. Advanced Metering Infrastructure (AMI), distributed energy resources (DERs), smart sensors, Supervisory Control and Data Acquisition (SCADA) systems, and strong cybersecurity are essential parts of smart grid systems.
While maintaining stability and dependability, smart grids make it easier to integrate sporadic renewable energy sources like wind and solar into the electrical system. Additionally, they encourage the growth of smart homes, decentralized energy storage systems, and electric vehicles (EVs), all of which lower greenhouse gas emissions and improve grid resilience. From the standpoint of the consumer, smart grids enable users to actively engage in energy markets, offer actionable insights into energy usage, and encourage cost reductions through dynamic pricing.
Keywords: Smart Grid, Renewable Energy Integration, Grid Automation, Energy Efficiency.
Smart grids allow for two-way communication, unlike traditional power networks that function through a one-way flow of electricity with no contact between utility suppliers and users. This makes it possible to perform dynamic load balancing, perform real-time monitoring, and have flexible reactions to changes in the supply and demand for energy. Advanced Metering Infrastructure (AMI), distributed energy resources (DERs), smart sensors, Supervisory Control and Data Acquisition (SCADA) systems, and strong cybersecurity are essential parts of smart grid systems.
While maintaining stability and dependability, smart grids make it easier to integrate sporadic renewable energy sources like wind and solar into the electrical system. Additionally, they encourage the growth of smart homes, decentralized energy storage systems, and electric vehicles (EVs), all of which lower greenhouse gas emissions and improve grid resilience. From the standpoint of the consumer, smart grids enable users to actively engage in energy markets, offer actionable insights into energy usage, and encourage cost reductions through dynamic pricing.
Keywords: Smart Grid, Renewable Energy Integration, Grid Automation, Energy Efficiency.
Abstract
Design and Implementation of IoT-Based Prepaid Smart Energy Meter for Efficient Power Management
Vaishnavi Vishwas Kale, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13627
Abstract: The increasing demand for smarter and more efficient energy management systems has led to the emergence of prepaid smart energy meters integrated with Internet of Things (IoT) technologies. This paper presents the design and implementation of an IoT-based prepaid smart energy meter intended to enable real-time consumption monitoring, remote billing management, and automated power control. The system allows consumers to purchase electricity credits in advance and track their usage through a user-friendly mobile or web interface, fostering energy awareness and promoting conservation.
The hardware architecture incorporates a digital energy metering IC for accurate measurement, an ESP32 microcontroller for processing and control, and Wi-Fi/GSM modules to ensure seamless data transmission. The system communicates with a cloud-based platform that manages user profiles, stores consumption data, and facilitates remote credit recharges. Key functionalities include real-time usage alerts, automatic disconnection when credit is depleted, tamper detection, and support for dynamic tariff structures based on time-of-use pricing.
This IoT-enabled solution benefits consumers by providing transparency and control over their electricity consumption while also helping utility providers reduce revenue loss from manual errors, billing delays, and electricity theft. Furthermore, the integration of real-time analytics supports predictive load forecasting and demand-side energy management, contributing to the stability and scalability of smart grid infrastructures.
Performance evaluations demonstrate the system’s effectiveness in energy regulation, user convenience, and operational reliability. Cost analysis indicates the feasibility of deploying such systems in both urban and rural settings, particularly in regions with unreliable billing practices or limited access to on-site utility services. Additionally, this approach aligns with global sustainability goals by encouraging responsible energy usage, facilitating renewable energy integration, and minimizing environmental impact.
It lays the foundation for the development of smart, self-regulating cities that prioritize resilience, economic efficiency, and environmental stewardship. Future improvements could include AI-based consumption forecasting, blockchain- enabled secure transactions, and integration with smart home systems for a fully automated energy ecosystem.
Keywords: IoT-based Energy, Metering Prepaid smart Energy Meter, Real-time Energy Monitoring, Smart Grid Integration
The hardware architecture incorporates a digital energy metering IC for accurate measurement, an ESP32 microcontroller for processing and control, and Wi-Fi/GSM modules to ensure seamless data transmission. The system communicates with a cloud-based platform that manages user profiles, stores consumption data, and facilitates remote credit recharges. Key functionalities include real-time usage alerts, automatic disconnection when credit is depleted, tamper detection, and support for dynamic tariff structures based on time-of-use pricing.
This IoT-enabled solution benefits consumers by providing transparency and control over their electricity consumption while also helping utility providers reduce revenue loss from manual errors, billing delays, and electricity theft. Furthermore, the integration of real-time analytics supports predictive load forecasting and demand-side energy management, contributing to the stability and scalability of smart grid infrastructures.
Performance evaluations demonstrate the system’s effectiveness in energy regulation, user convenience, and operational reliability. Cost analysis indicates the feasibility of deploying such systems in both urban and rural settings, particularly in regions with unreliable billing practices or limited access to on-site utility services. Additionally, this approach aligns with global sustainability goals by encouraging responsible energy usage, facilitating renewable energy integration, and minimizing environmental impact.
It lays the foundation for the development of smart, self-regulating cities that prioritize resilience, economic efficiency, and environmental stewardship. Future improvements could include AI-based consumption forecasting, blockchain- enabled secure transactions, and integration with smart home systems for a fully automated energy ecosystem.
Keywords: IoT-based Energy, Metering Prepaid smart Energy Meter, Real-time Energy Monitoring, Smart Grid Integration
Abstract
The Role of Smart Grid in the Efficiency Management of Renewable Energy
Kirti Shridhar Pasnur, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13628
Abstract: The increasing adoption of renewable energy sources (RES) such as solar and wind power presents new opportunities and challenges for modern power systems. Due to their inherent variability and intermittency, the effective integration of RES requires a fundamental shift from traditional grid infrastructure to a more intelligent and adaptive system. The smart grid, characterized by advanced sensing, communication, and control capabilities, offers a robust platform for managing these complexities. This paper explores the role of smart grid technologies in the efficient management of renewable energy, focusing on real-time monitoring, load balancing, distributed generation, and energy storage integration. Emphasis is placed on how smart grids enhance grid reliability, optimize energy flows, and support sustainable development. Case studies and current implementations are examined to illustrate practical benefits and challenges. The paper concludes with insights into future developments and the critical factors influencing smart grid deployment in renewable-centric energy systems.
Keywords: Smart Grid, Renewable Energy Integration, Energy Management, Distributed Energy Resources (DERs)
Keywords: Smart Grid, Renewable Energy Integration, Energy Management, Distributed Energy Resources (DERs)
Abstract
Solar Tree: Sustainable Tree by SolarBotanic
Sneha B Gaikwad, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13629
Abstract: The SolarBotanic Tree, also known as the Sustainable Tree by SolarBotanic, represents a cutting-edge fusion of renewable energy technology and biomimetic design. Developed to emulate the natural form of a tree, this solar structure integrates advanced thin-film photovoltaic nanotechnology to harness solar energy efficiently in urban and residential environments. In addition to energy generation, it offers features such as integrated battery storage, environmental sensors, and optional electric vehicle (EV) charging capabilities, making it a multifunctional asset for smart cities. This paper explores the design, functionality, and potential applications of the SolarBotanic Tree, evaluating its role in promoting sustainable infrastructure. Comparative insights against traditional solar panels highlight its advantages in terms of spatial efficiency, aesthetics, and public engagement. The study concludes that solar trees like the SolarBotanic Tree have the potential to redefine urban energy landscapes and support broader environmental goals.
Keywords: SolarBotanic tree, Biomimetic design, traditional solar panels.
Keywords: SolarBotanic tree, Biomimetic design, traditional solar panels.
Abstract
Virtual Electrical Labs Powered by AR
Ms. Pratiksha Dixit, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13630
Abstract: Traditional Electrical laboratories require huge investments for Physical equipment and machines and also large infrastructure for laboratories. Augmented reality in electrical transforming solution by enabling portable virtual lab experience, interactive environment, simulation and engagement. This paper presents the design and development of an AR-Based Virtual Electrical Lab that allows students to visualize and interact with electrical lab equipment through marker-based AR technology. By integrating 3D models of instruments with real world environments via mobile devices, the system enhances practical understanding while eliminating the risks and limitations of physical setups. Initial findings suggest that AR can significantly improve learning outcomes in electrical engineering offering a scalable and engaging alternative to conventional laboratory sessions.
Keywords: Augmented Reality. Electrical laboratories, Virtual labs.
Keywords: Augmented Reality. Electrical laboratories, Virtual labs.
Abstract
Wireless Power Transfer for EV Charging
Shweta Irappa Tadaval, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13631
Abstract: The rapid adoption of electric vehicles (EVs) necessitates advancements in charging infrastructure to address limitations in convenience, safety, and efficiency. Wireless Power Transfer (WPT) emerges as a transformative technology enabling contactless energy transmission from a power source to a vehicle, eliminating the need for physical connectors. This paper reviews the principles, design considerations, and challenges of WPT systems tailored for EV charging, focusing on resonant inductive coupling, coil alignment, power conversion, and electromagnetic compatibility. Furthermore, it evaluates recent developments in dynamic charging, where vehicles receive power while in motion, thus extending driving range and reducing battery size requirements. The integration of WPT with smart grid systems and the potential for interoperability across various vehicle models are also discussed. Simulation and experimental results demonstrate the feasibility of achieving high transfer efficiency under practical conditions. The paper concludes by highlighting key areas for future research, including standardization, system miniaturization, and cost reduction, to enable widespread adoption of WPT in sustainable transportation ecosystems.
Keywords: Wireless power transfer, electric vehicles, resonant inductive coupling, dynamic charging, smart grid, EV infrastructure.
Keywords: Wireless power transfer, electric vehicles, resonant inductive coupling, dynamic charging, smart grid, EV infrastructure.
Abstract
Forecasting the Future: AI-Driven Resilience in Renewable Energy Grids
Priyanka Nagesh Kadam, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13632
Abstract: The integration of renewable energy sources into electrical power systems presents significant challenges due to their intermittent and variable nature. Artificial Intelligence (AI) has emerged as a powerful tool to address these challenges by enabling smarter, more adaptive management of renewable energy generation and grid operations. This research paper investigates the application of AI techniques—including machine learning, deep learning, and predictive analytics—in optimizing the integration of renewable energy sources such as solar, wind, and hydroelectric power into existing electrical grids.AI-driven models improve forecasting accuracy for renewable energy output and load demand, enhancing grid stability and operational efficiency. Techniques such as neural networks and support vector machines are employed to predict short-term and long-term energy generation, while reinforcement learning algorithms enable dynamic energy management and storage optimization. Furthermore, AI aids in fault detection, real-time grid monitoring, and demand response management, helping to mitigate the impact of renewable energy variability.
The paper also discusses challenges related to data quality, computational complexity, and the need for scalable AI solutions that can operate in real-time within complex power systems. Case studies and simulations demonstrate the effectiveness of AI approaches in improving renewable penetration while maintaining power quality and system reliability. This study underscores the transformative potential of AI in accelerating the adoption of renewable energy technologies, promoting sustainable energy systems, and enabling the transition towards a low-carbon, smart grid future.
Keywords: Artificial intelligence, renewable energy integration, machine learning, power systems, energy forecasting, grid stability, smart grid.
The paper also discusses challenges related to data quality, computational complexity, and the need for scalable AI solutions that can operate in real-time within complex power systems. Case studies and simulations demonstrate the effectiveness of AI approaches in improving renewable penetration while maintaining power quality and system reliability. This study underscores the transformative potential of AI in accelerating the adoption of renewable energy technologies, promoting sustainable energy systems, and enabling the transition towards a low-carbon, smart grid future.
Keywords: Artificial intelligence, renewable energy integration, machine learning, power systems, energy forecasting, grid stability, smart grid.
Abstract
Design and Implementation of a Mobile-Controlled Electric Bulb System Using IoT Technology
Ms. Zeba Choudhari, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13633
Abstract: The increasing demand for smart home technologies has led to the development of various IoT-based systems that aim to provide greater control and automation of everyday household devices. This paper presents a mobile-controlled electric bulb system that allows users to remotely control the lighting in their homes using a smartphone application. The system utilizes wireless communication technologies such as Wi-Fi and Bluetooth, offering an intuitive interface for users. Through the use of IoT protocols, this system can be easily integrated with other smart home devices, contributing to energy conservation, comfort, and enhanced user convenience. The architecture, components, and functionalities of the system are detailed, followed by an analysis of its performance and future applications.
Keywords: Mobile control, Electric bulb, IoT, Smart home, Wi-Fi, Bluetooth, Energy efficiency, Home automation
Keywords: Mobile control, Electric bulb, IoT, Smart home, Wi-Fi, Bluetooth, Energy efficiency, Home automation
Abstract
Design and Application of Wireless Transmission Systems for Modern Communication Networks
Ms. Rutuja Mudholkar, Prof. Dnyaneshwar Shivaji Waghmode
DOI: 10.17148/IJIREEICE.2025.13634
Abstract: The development of wireless transmission systems has been pivotal in revolutionizing modern communication networks, enabling seamless data transfer across vast distances. This paper explores the design and implementation of wireless transmission systems, with an emphasis on their applications in various fields such as mobile communication, IoT, satellite communication, and smart cities. The study discusses the different types of wireless transmission technologies, including radio frequency (RF), optical communication, and millimeter-wave systems, and compares their respective advantages and limitations. Furthermore, the paper investigates real-world applications and challenges, including network optimization, security, and scalability, offering insights into future trends in wireless communication. The exponential growth in wireless communication technologies has significantly influenced the architecture and efficiency of modern communication networks. Wireless transmission systems, through the use of radio frequency, microwave, and optical signals, have enabled flexible, scalable, and cost-effective communication infrastructures. This paper provides a comprehensive review of the design principles and real-world applications of wireless transmission systems, with a focus on 5G, Wi-Fi 6, satellite communication, and IoT-enabled networks. It also explores the challenges posed by spectrum congestion, interference, energy consumption, and security. Future directions including 6G networks and quantum communication are discussed to provide insights into the evolving landscape of wireless systems.
Keywords: Wireless transmission, communication systems, mobile networks, IoT, satellite communication, network optimization, security.
Keywords: Wireless transmission, communication systems, mobile networks, IoT, satellite communication, network optimization, security.
Abstract
Real World Uses of OCR for Modernization of Traffic system
Dr. Saurabh A Ghogare, Prof. Abhijit G Kalbande
DOI: 10.17148/IJIREEICE.2025.13635
Abstract: Normally complete OCR methodology for recognizing documents, either printed or handwritten without any knowledge of the font, is presented. This methodology consists of three steps: The first two steps refer to creating a database for training using a set of documents, while the third one refers to recognition of new document images. First, a preprocessing step that includes image binarization and enhancement takes place. At a second step a top-down segmentation approach is used in order to detect text lines, words and characters. A clustering scheme is then adopted in order to group characters of similar shape. This is a semi-automatic procedure since the user is able to interact at any time in order to correct possible errors of clustering and assign an ASCII label. After this step, a database is created in order to be used for recognition. Finally, in the third step, for every new document image the above segmentation approach takes place while the recognition is based on the character database that has been produced at the previous step.
Keywords: Digital conversion, Handwritten or printed text, Image conversion.
Keywords: Digital conversion, Handwritten or printed text, Image conversion.
Abstract
Understanding 5G Technology: The future of wireless communication
Bhargavi Konda, Surabhi Kale, P.K.Digge
DOI: 10.17148/IJIREEICE.2025.13636
Abstract: 5G technology, short for fifth-generation technology, is the latest advancement in mobile wireless communication. As internet usage continues to grow rapidly in our everyday lives, people now expect faster and more reliable connectivity. 5G builds upon the earlier generations—1G, 2G, 3G, and 4G—by offering major improvements like ultra-high speed, extremely low latency, massive capacity, and increased reliability.
5G has been designed to meet not just today’s needs, but also future demands that we may not even know about yet. It promises to revolutionize how we live, work, and connect with technology.
This paper presents a short overview of 5G wireless technology, its journey from 1G to 5G, along with its key benefits and limitations.
Keywords: 5G, Wireless Networks, Mobile Evolution (1G to 5G), Network Architecture, Pros and Cons.
5G has been designed to meet not just today’s needs, but also future demands that we may not even know about yet. It promises to revolutionize how we live, work, and connect with technology.
This paper presents a short overview of 5G wireless technology, its journey from 1G to 5G, along with its key benefits and limitations.
Keywords: 5G, Wireless Networks, Mobile Evolution (1G to 5G), Network Architecture, Pros and Cons.
Abstract
AI in Wind Turbine
Shivranjani Nagesh Battul, J.A.Patil
DOI: 10.17148/IJIREEICE.2025.13637
Abstract: With the increasing global demand for clean and renewable energy, wind power has proven to be one of the most promising renewable energy sources. Maximizing the efficiency and reliability of wind turbines, however, poses several challenges, such as unstable weather patterns, mechanical stresses, and the intricacies of handling large wind farm operations. To overcome these challenges, Artificial Intelligence (AI) is being increasingly deployed in wind energy systems, allowing for more intelligent, data-driven decision-making and automation.
This seminar paper discusses the application of AI to convert conventional wind turbines to intelligent machines that are capable of self-detection, self-optimization, and predictive control. Utilizing sophisticated AI methods like machine learning, neural networks, fuzzy logic, and genetic algorithms, wind turbine operations can be improved to a considerable extent. AI is implemented in several areas such as predictive maintenance, where it is used to predict component failures ahead of time, hence minimizing downtime and maintenance expenses. In performance optimization, AI dynamically regulates turbine parameters to ensure optimal energy output as per real-time environmental conditions. AI is also crucial in fault detection and diagnosis, allowing for an early detection of system anomalies, and wind energy forecasting, which helps improve grid integration and planning.
Case studies from the real world demonstrate that AI deployment results in quantifiable improvements in energy production, operating efficiency, and cost savings. Though they are significant, issues such as the quality of data, model complexity, and cybersecurity need to be overcome for broader acceptance. However, continued research and technological innovations point towards a robust future for AI-equipped wind turbines, the precursor to more decentralized and durable renewable energy systems.
This report gives an in-depth analysis of how AI is transforming the wind energy industry and provides an insight into future trends and innovations that will define the next generation of wind power technology.
Keywords: Artificial Intelligence (AI), Wind Turbines, Renewable Energy, Predictive Maintenance, Performance Optimization, Fault Detection.
This seminar paper discusses the application of AI to convert conventional wind turbines to intelligent machines that are capable of self-detection, self-optimization, and predictive control. Utilizing sophisticated AI methods like machine learning, neural networks, fuzzy logic, and genetic algorithms, wind turbine operations can be improved to a considerable extent. AI is implemented in several areas such as predictive maintenance, where it is used to predict component failures ahead of time, hence minimizing downtime and maintenance expenses. In performance optimization, AI dynamically regulates turbine parameters to ensure optimal energy output as per real-time environmental conditions. AI is also crucial in fault detection and diagnosis, allowing for an early detection of system anomalies, and wind energy forecasting, which helps improve grid integration and planning.
Case studies from the real world demonstrate that AI deployment results in quantifiable improvements in energy production, operating efficiency, and cost savings. Though they are significant, issues such as the quality of data, model complexity, and cybersecurity need to be overcome for broader acceptance. However, continued research and technological innovations point towards a robust future for AI-equipped wind turbines, the precursor to more decentralized and durable renewable energy systems.
This report gives an in-depth analysis of how AI is transforming the wind energy industry and provides an insight into future trends and innovations that will define the next generation of wind power technology.
Keywords: Artificial Intelligence (AI), Wind Turbines, Renewable Energy, Predictive Maintenance, Performance Optimization, Fault Detection.
Abstract
Enhancing Workplace Safety through Effective Use of Personal Protective Equipment (PPE)
Bhanu Balaji Katkam, Poonam Shrimant Belbhandare, Prof. P. K. Digge
DOI: 10.17148/IJIREEICE.2025.13638
Abstract: Electrical workplaces present significant dangers such as electric shocks, arc flashes, and burns. Personal Protective Equipment (PPE) is crucial in reducing the severity of these risks. This paper discusses the critical role of PPE in safeguarding electrical workers, the process of selecting appropriate equipment, and best practices for its maintenance and use. It also explores technological advancements that can enhance safety standards in the future. The objective is to emphasize the importance of PPE as an essential component of a comprehensive electrical safety program.
Keywords: Electrical Safety, Personal Protective Equipment, Arc Flash, Workplace Hazards, Occupational Protection, Safety Standards, Electrical Engineering, Hazard Prevention.
Keywords: Electrical Safety, Personal Protective Equipment, Arc Flash, Workplace Hazards, Occupational Protection, Safety Standards, Electrical Engineering, Hazard Prevention.
Abstract
Solar Based Electrical vehicles (EV’s) Charging Station
Amruta Rajendra Bhutekar, Prof. P. K. Digge
DOI: 10.17148/IJIREEICE.2025.13639
Abstract: The increasing adoption of electric vehicles (EVs) has necessitated the development of sustainable charging infrastructure to reduce reliance on fossil fuels and mitigate environmental impacts. This paper presents a comprehensive study and design of a solar-based EV charging station that harnesses photovoltaic (PV) energy for charging electric vehicles. The proposed system comprises solar PV arrays, energy storage units, charging interfaces, and a smart controller for efficient energy management. The design focuses on optimizing PV array configuration, load management, and charge scheduling to ensure seamless operation under variable solar irradiance. Simulation results and economic analyses demonstrate the feasibility, reliability, and cost-effectiveness of the proposed charging station, making it a promising solution for promoting clean transportation and reducing carbon emissions. This work aims to provide valuable insights for researchers, engineers, and policymakers engaged in sustainable energy and transportation infrastructure.
Keywords: Electric Vehicles (EV), Solar Charging Station, Photovoltaic (PV) System, Energy Storage (Battery), Smart Charging Controller, Renewable Energy Integration: Off-Grid and Grid-Tied Systems
Keywords: Electric Vehicles (EV), Solar Charging Station, Photovoltaic (PV) System, Energy Storage (Battery), Smart Charging Controller, Renewable Energy Integration: Off-Grid and Grid-Tied Systems
Abstract
Tracking System for Soldiers
Vaishnavi Shriniwas Mithapalli, J.A.Patil
DOI: 10.17148/IJIREEICE.2025.13640
Abstract: The overall health and performance of military personnel can now be improved with the Soldier's Health Monitoring and Position Tracking System, which is employing new technology in an integrated way. With a health monitoring and position tracking function, military commanders will now have full situational awareness, as, additionally using real-time monitoring of health and accurate position tracking, they can obtain the following health indicators (heart rate, temperature and blood oxygen levels) for each soldier, as well health status of individuals enlisted to implement the mission they are working on (mission parameters proscribed in terms of performance metrics), either by alerting them of a potential health problem at the command centre (i.e., soldiers in the field are always monitored) which can be acted upon from the command centre that is exercised in response to abnormal health indicators. The system relies on new global positioning (GPS) and inertial navigation systems (INS) to accurately report each soldier's position in the field, and the geographic data acquired can track and disseminate their health information in real-time. The integrated capability of geo-spatial information and health monitoring information gives commanders the full picture of the troops' health status and location. Commanders and their command teams, with the health and tracking information provided by the system, can make informed decisions and health status of soldiers based on real-time health monitoring and positional data, and, through the System's user interface, be visible with an intuitive dashboard. The data is relayed through the Internet of Things (IoT) to the command centre. Specific components of the proposed system include gearbox modules, portable physiological monitoring devices, and sensors and senders.
Keywords: Health,Position,Tracking, GPS (Global Positioning System), Monitor.
Keywords: Health,Position,Tracking, GPS (Global Positioning System), Monitor.
Abstract
Ai In Power System
Dhanashri Siddheshwar Dindure, J.A.Patil
DOI: 10.17148/IJIREEICE.2025.13641
Abstract: The inclusion of Artificial Intelligence (AI) in power systems is transforming electrical power generation, transmission, distribution, and consumption. AI algorithms like machine learning, deep learning, expert systems, and evolutionary algorithms are being used to make modern power grids more efficient, reliable, and sustainable. These technologies facilitate precise forecasting of demand, fault detection at real-time, optimal control of power flow, predictive maintenance, and integration of renewable resources. In addition to this, AI facilitates the creation of smart grids by making it possible for automatic decision-making, adaptive control, and improved system resilience. This paper discusses the major applications, advantages, challenges, and future directions of AI for power systems, with a focus on its contribution to the creation of the next generation of intelligent energy infrastructure.
Keywords: Artificial Intelligence (AI), Power system engineering
Keywords: Artificial Intelligence (AI), Power system engineering
Abstract
Microprocessor Based motor speed controller
Ruchita Pegdyal, J. A. Patil
DOI: 10.17148/IJIREEICE.2025.13642
Abstract: A Microprocessor-Based Motor Speed Controller is an intelligent electronic system designed to precisely control the speed of electric motors using a microprocessor or microcontroller. The primary objective of this system is to achieve accurate, efficient, and automated control of motor speed for various industrial, commercial, and domestic applications. This is accomplished by interfacing sensors, power electronics, and control algorithms with a programmable microprocessor. In traditional motor control systems, speed regulation is typically done manually or using analog control circuits, which are prone to inaccuracy, drift, and lack of flexibility. A microprocessor-based system offers higher precision, programmability, and real-time adaptability. It can monitor various inputs such as desired speed (from a user interface), actual motor speed (from sensors like tachometers or encoders), load conditions, and environmental parameters. Based on this feedback, it dynamically adjusts the power delivered to the motor using techniques like Pulse Width Modulation (PWM), Phase Control, or Variable Frequency Drive (VFD), depending on the motor type (DC, AC, or Stepper). The microprocessor serves as the core controller, executing an algorithm to compare the setpoint (desired speed) with the measured speed, and generating appropriate control signals to reduce the error. This closed-loop control improves system performance, minimizes power loss, and extends motor life. In this project, hardware components such as motor driver circuits, analog-to-digital converters (ADC), digital-to- analog converters (DAC), power supplies, and displays are integrated with the microprocessor. Software is developed (typically in assembly or embedded C) to implement the control algorithm, user interface, and diagnostic features.
Keywords: Microprocessor, Motor Speed Control, PWM (Pulse Width Modulation), DC Motor, Sensor Feedback, Embedded Systems, Speed Regulation, Microcontroller, Automation, PID Control
Keywords: Microprocessor, Motor Speed Control, PWM (Pulse Width Modulation), DC Motor, Sensor Feedback, Embedded Systems, Speed Regulation, Microcontroller, Automation, PID Control
Abstract
Electric Traction System
Bhavana Dattu kadagi, J.A. Patil
DOI: 10.17148/IJIREEICE.2025.13643
Abstract: Electric traction systems represent a pivotal advancement in the field of Transportation, enabling the use of electrical energy for vehicle propulsion across a Wide range of applications including railways, metros, trams, trolleybuses, and Electric vehicles. These systems employ electric motors, powered either by external Sources such as overhead lines or third rails, or by onboard systems like batteries And diesel-electric generators, to produce the tractive force necessary for movement.The shift towards electric traction is driven by several critical factors, including the Demand for higher energy efficiency, the need to reduce greenhouse gas emissions, And the push for modernization of transport infrastructure. Unlike conventional Internal combustion systems, electric traction offers significant benefits such as Lower environmental impact, enhanced acceleration and braking performance, Regenerative energy recovery, reduced operational noise, and lower maintenance Costs.This report explores the fundamental principles of electric traction, its historical Evolution, and the various technologies that underpin modern systems. It also Examines different types of electric traction configurations, key components Involved, and the comparative advantages and challenges. In doing so, it provides a Comprehensive understanding of how electric traction is shaping the future of Sustainable and intelligent transportation systems.
Keywords: Health,Position,Tracking, GPS (Global Positioning System), Monitor.
Keywords: Health,Position,Tracking, GPS (Global Positioning System), Monitor.
Abstract
HOME AUTOMATION SYSTEM
Sakshi Sandip Kavade, Vaishnavi Shrinivas Koppul, Prof. P. K. Digge
DOI: 10.17148/IJIREEICE.2025.13644
Abstract: The Voice Command Home Automation System is an intelligent and convenient solution that allows users to control household appliances and lighting through voice commands. In this system, a voice recognition module captures spoken commands and processes them to trigger specific devices, such as lights, fans, or TVs, via a microcontroller. The system is implemented using a microcontroller (e.g., Arduino or ESP32), a Bluetooth or WiFi interface, and a voice assistant application (such as a mobile app or dedicated voice recognition hardware). The design focuses on providing seamless interaction for the user, especially for the elderly or people with disabilities, making it an ideal choice for smart homes. The proposed system offers benefits such as improved accessibility, convenience, and energy efficiency, while ensuring reliability and ease of implementation. The results demonstrate that voice-based control significantly simplifies daily household activities, making it a vital component of the growing trend in smart home technology If you want, I can also help you write variations of the abstract all like making it more technical, adding more details about the components used, or making it concise for a conference paper.
Keywords: Voice Command, Home Automation, Smart Home, Arduino, ESP32 Bluetooth/Wi-Fi, Voice Recognition, IoT (Web of Things), Assistive Technology
Keywords: Voice Command, Home Automation, Smart Home, Arduino, ESP32 Bluetooth/Wi-Fi, Voice Recognition, IoT (Web of Things), Assistive Technology
Abstract
Automatic fruit sorting machine based on weight
Gauri Vasant Pawar, Gayatri Shrinivas Posham, Prof. P. K. Digge
DOI: 10.17148/IJIREEICE.2025.13645
Abstract: The growing demand for efficient post-harvest processing has led to the development of automated fruit sorting systems. This paper presents a fruit sorting machine that categorizes fruits based on their weight. The system is designed to enhance productivity, reduce human error, and maintain consistency in grading. It utilizes a microcontroller to weigh individual fruits and sort them into predefined categories using actuated mechanisms. The machine is cost- effective, easy to operate, and suitable for small- to medium-scale agricultural applications. This innovation not only reduces manual labour but also ensures uniformity in fruit quality for market distribution.
Keywords: Automatic sorting, fruit grading, weight-based classification, agricultural automation, microcontroller system, post-harvest technology, smart farming, quality control, embedded system, productivity enhancement.
Keywords: Automatic sorting, fruit grading, weight-based classification, agricultural automation, microcontroller system, post-harvest technology, smart farming, quality control, embedded system, productivity enhancement.
Abstract
IoT-Based Aquaponics System for Sustainable Farming
Mrs. Zubeda Begum, Shaik Qasim Ahmed, Md Saif Khan, Syed Abdul Gaffar
DOI: 10.17148/IJIREEICE.2025.13646
Abstract: Aquaponics integrates aquaculture and hydroponics into a closed-loop sustainable farming system. The Internet of Things (IoT) enhances this integration by providing real-time monitoring and automated control, improving efficiency, productivity, and sustainability. This paper presents the design and implementation of an IoT-based aquaponics system that monitors water quality, temperature, pH, humidity, and nutrient cycles while automating feeding and irrigation. The system utilizes Arduino and NodeMCU microcontrollers, sensors (pH, temperature, DHT11), and a cloud platform for data logging and alerting. Experimental deployment demonstrates improved water quality control, plant health, and fish survival rates with minimal manual intervention. The proposed system supports precision agriculture, reduces resource wastage, and is scalable for small-to-medium farming environments.
Keywords: IoT, Aquaponics, Sustainable Farming, Smart Agriculture, Real-time Monitoring
Keywords: IoT, Aquaponics, Sustainable Farming, Smart Agriculture, Real-time Monitoring
Abstract
Cyber-Driven Surveillance and Alert System for Illegal Logging Detection in Protected Forest Areas
Dr. Abdul Mateen Ahmed, Syed Shah Akber Hussaini, Shaik Abdul Rahman, Shaikh Azeemuddin
DOI: 10.17148/IJIREEICE.2025.13647
Abstract: Illegal logging poses a significant threat to biodiversity, forest ecosystems, and climate stability. In this paper, we propose a cyber-driven surveillance and alert system designed to detect and report illegal logging activities in real time. The system integrates Internet of Things (IoT) sensors, edge computing, and artificial intelligence (AI) to monitor protected forest zones continuously. Acoustic sensors detect chainsaw sounds, while visual sensors capture unauthorized human activity. AI algorithms classify the threats and generate alerts for forest officials via secure communication protocols. Field tests demonstrate high accuracy in detection and timely alert delivery. This work enhances environmental protection efforts through technology-driven monitoring and intervention.
Keywords: Illegal logging, Cyber-physical systems, Forest surveillance, AI detection, IoT, Edge computing, Environmental monitoring
Keywords: Illegal logging, Cyber-physical systems, Forest surveillance, AI detection, IoT, Edge computing, Environmental monitoring
Abstract
“Design and Implementation of a Microcontroller-Based Borewell Rescue System with Drone-Assisted Monitoring.”
Shaikh Azeemuddin, Mohd Hassan, Abdul Razzaq
DOI: 10.17148/IJIREEICE.2025.13648
Abstract: Borewell accidents involving children have become a distressing and recurring tragedy, particularly in developing regions. Traditional rescue methods are time-consuming and often life-threatening. This paper presents the design and implementation of an innovative, cost-effective, and modular Microcontroller-Based Borewell Rescue System integrated with Drone-Assisted Monitoring. The system uses a NodeMCU microcontroller to control mechanical components such as a motorized rescue platform and a gripper unit, while a drone provides real-time visual surveillance. The proposed system was successfully tested under simulated conditions and offers a significant step toward safer and more efficient borewell rescue operations.
Abstract
Optical Satellite Communication
Ms. Pradnya Kumri, Prof. J.A. Patil
DOI: 10.17148/IJIREEICE.2025.13649
Abstract: The rapidly growing demand for high-speed data services, global connectivity, and efficient information exchange has made optical satellite communication a crucial area of focus in modern telecommunication research. As digital applications continue to expand from streaming and cloud services to real-time remote sensing and defence operations traditional radio frequency (RF) systems are increasingly facing limitations in bandwidth, latency, and spectrum congestion. Optical satellite communication offers a promising alternative by utilizing light waves, particularly laser beams, to transmit information across space. Unlike RF-based systems, optical communication offers significantly higher data transmission rates due to the broader bandwidth of optical frequencies. Additionally, the highly directional nature of laser beams ensures reduced signal loss, lower chances of interception, and enhanced data security. The compact nature of optical hardware also contributes to reduced payload weights, making it suitable for modern satellite platforms. This paper provides an in-depth exploration of the underlying principles, working mechanisms, and system components involved in optical satellite communication. It further highlights the technological challenges such as atmospheric interference and precision alignment, while also examining practical solutions and emerging advancements in this field. Finally, the paper evaluates real-world applications, ongoing developments, and the future potential of optical communication systems in transforming global communication infrastructure.
Keywords: Optical satellite communication, free-space optics, inter-satellite link, laser communication, space communication, bandwidth, RF limitations, photodetector, adaptive optics.
Keywords: Optical satellite communication, free-space optics, inter-satellite link, laser communication, space communication, bandwidth, RF limitations, photodetector, adaptive optics.
Abstract
Monthly Electricity Billing Display With SMS Feature
Krishnaveni Naresh Kolpyak, Prof. J.A.Patil
DOI: 10.17148/IJIREEICE.2025.13650
Abstract: This paper presents the design and implementation of a Monthly Electricity Billing Display System integrated with SMS features. The system provides real-time usage information to consumers and sends periodic billing updates via SMS. This not only enhances transparency but also enables users to monitor and manage their electricity consumption efficiently. The increasing demand for energy-efficient and user-friendly solutions in the power sector has led to the development of smart billing systems. This project presents a Monthly Electricity Billing Display System with SMS Feature, designed to automate and simplify the process of energy monitoring and billing. The system continuously monitors the electricity consumption using a digital energy meter and displays the consumed units and billing amount on an LCD screen. A microcontroller processes the data and sends the billing information to the consumer's mobile phone via a GSM module. This real-time SMS alert system enhances billing transparency, reduces manual effort, and helps users stay informed about their energy usage. The proposed system not only improves efficiency for utility providers but also promotes energy awareness and timely bill payments among consumers. It is a step toward smart energy management in line with modern digital infrastructure.
Keywords: Sola—electricity billing, SMS feature, real-time display, embedded systems, energy metering
Keywords: Sola—electricity billing, SMS feature, real-time display, embedded systems, energy metering
Abstract
"Advanced Technologies In Electric And Hybrid Vehicles"
Vidya Gour, Prof. P. K. Digge
DOI: 10.17148/IJIREEICE.2025.13651
Abstract: The global automotive industry is shifting towards electric and hybrid vehicles to address environmental concerns and reduce fossil fuel dependence. Key advancements in battery technology, such as lithium-ion and solid- state batteries, have improved energy capacity, safety, and charging times. Enhanced power electronics, motor designs, and regenerative braking systems increase overall efficiency and performance. The use of lightweight materials and development of fast-charging networks extend vehicle range and usability. Furthermore, the integration of digital tools like artificial intelligence and vehicle-to-grid communication is revolutionizing vehicle connectivity and energy management. This paper examines these innovations and their role in driving the future of sustainable transportation.
Keywords: Electric Vehicles (EVs), Hybrid Electric Vehicles (HEVs), Battery Technology, Lithium-ion Batteries, Solid- State Batteries, Battery Management Systems (BMS), Power Electronics, Electric Motors, Regenerative Braking, Lightweight Materials, Fast Charging, Vehicle-to-Grid (V2G), Artificial Intelligence (AI), Sustainable Transportation, Energy Efficiency.
Keywords: Electric Vehicles (EVs), Hybrid Electric Vehicles (HEVs), Battery Technology, Lithium-ion Batteries, Solid- State Batteries, Battery Management Systems (BMS), Power Electronics, Electric Motors, Regenerative Braking, Lightweight Materials, Fast Charging, Vehicle-to-Grid (V2G), Artificial Intelligence (AI), Sustainable Transportation, Energy Efficiency.
Abstract
“BIOCHIP”
Ms. Shrushti Ghante, Prof. J.A. Patil
DOI: 10.17148/IJIREEICE.2025.13652
Abstract: Biochips are compact, highly sophisticated analytical devices that function as miniaturized laboratories, capable of performing numerous biochemical reactions simultaneously on a single platform. These systems represent a groundbreaking convergence of electrical engineering and biotechnology, enabling rapid and precise analysis of biological samples. Through the integration of microelectronics, sensors, and microfluidic technology, biochips offer powerful tools for applications such as disease diagnosis, drug discovery, genetic screening, and forensic analysis.
At the core of biochip technology is the ability to detect and process minute quantities of biological material with high accuracy and speed. This functionality is achieved by combining biological recognition elements with electronic components that interpret biochemical interactions in real time. By miniaturizing laboratory functions onto a chip, biochips significantly reduce analysis time, reagent consumption, and costs, making them ideal for point-of-care testing and personalized medicine.
This paper explores the fundamental principles behind biochip operation, including their structural design, the working mechanisms of integrated biosensors, and the role of microfluidic networks in sample manipulation. In addition, the paper examines current technological advancements, diverse applications in various sectors, and the advantages and limitations of biochip deployment. Special focus is given to the interdisciplinary collaboration that drives this innovation and to the expanding potential of biochips in future healthcare solutions, particularly in remote diagnostics and real-time health monitoring systems.
Keywords: Biochip Microfluidics, DNA ANALSIS Biomedical devices
At the core of biochip technology is the ability to detect and process minute quantities of biological material with high accuracy and speed. This functionality is achieved by combining biological recognition elements with electronic components that interpret biochemical interactions in real time. By miniaturizing laboratory functions onto a chip, biochips significantly reduce analysis time, reagent consumption, and costs, making them ideal for point-of-care testing and personalized medicine.
This paper explores the fundamental principles behind biochip operation, including their structural design, the working mechanisms of integrated biosensors, and the role of microfluidic networks in sample manipulation. In addition, the paper examines current technological advancements, diverse applications in various sectors, and the advantages and limitations of biochip deployment. Special focus is given to the interdisciplinary collaboration that drives this innovation and to the expanding potential of biochips in future healthcare solutions, particularly in remote diagnostics and real-time health monitoring systems.
Keywords: Biochip Microfluidics, DNA ANALSIS Biomedical devices
Abstract
Research Paper on Cybersecurity
Sneha Karre, P.K. Digge
DOI: 10.17148/IJIREEICE.2025.13653
Abstract: Cybersecurity encompasses a broad range of practices, tools and concepts related closely to those of information and operational technology (OT) security. Cybersecurity is distinctive in its inclusion of the offensive use of information technology to attack adversaryes.
Cybersecurity refers to the practices, technologies, and processes designed to protect networks, devices, programs, and data from attack, damage, or unauthorized access. In an increasingly digital world, cybersecurity has become critical for safeguarding sensitive information across industries such as finance, healthcare, government, and education. With the growing sophistication of cyber threats including malware, ransomware, phishing, and advanced persistent threats organizations face significant challenges in ensuring data integrity and privacy.
This abstract outlines the key aspects of cybersecurity, including threat identification, risk management, encryption, and policy enforcement. It also highlights the importance of user awareness, continuous monitoring, and the implementation of strong security frameworks to mitigate cyber risks. As cyber threats evolve, so must the approaches to defense, necessitating ongoing research, investment, and collaboration in the cybersecurity domain. Cybersecurity encompasses a broad range of practices, tools and concepts related closely to those of information and operational technology (OT) security.
Keywords: Malware, Phishing, Ransomware, Firewall.
Cybersecurity refers to the practices, technologies, and processes designed to protect networks, devices, programs, and data from attack, damage, or unauthorized access. In an increasingly digital world, cybersecurity has become critical for safeguarding sensitive information across industries such as finance, healthcare, government, and education. With the growing sophistication of cyber threats including malware, ransomware, phishing, and advanced persistent threats organizations face significant challenges in ensuring data integrity and privacy.
This abstract outlines the key aspects of cybersecurity, including threat identification, risk management, encryption, and policy enforcement. It also highlights the importance of user awareness, continuous monitoring, and the implementation of strong security frameworks to mitigate cyber risks. As cyber threats evolve, so must the approaches to defense, necessitating ongoing research, investment, and collaboration in the cybersecurity domain. Cybersecurity encompasses a broad range of practices, tools and concepts related closely to those of information and operational technology (OT) security.
Keywords: Malware, Phishing, Ransomware, Firewall.
Abstract
Nanotechnology
Shweta Vhankamble, P.K. Digge
DOI: 10.17148/IJIREEICE.2025.13654
Abstract: Nanotechnology involves the manipulation of matter at the atomic and molecular scale, typically between 1 and 100 nanometers. As a rapidly advancing field, it has the potential to revolutionize diverse sectors including medicine, electronics, energy, and environmental science. This paper explores the fundamentals of nanotechnology, its applications, benefits, challenges, and future prospects, offering a comprehensive perspective on its role in shaping the future of science and technology.
Keywords: nanomaterials, nanoparticles, nanostructures, nanoscale, nanoelectronics, nanomedicine,nanomanufacturing, nanobiosensors, quantum dots, graphene, carbon nanotubes, self-assembly, top-down, bottom-up, biocompatibility, and sustainability.
Keywords: nanomaterials, nanoparticles, nanostructures, nanoscale, nanoelectronics, nanomedicine,nanomanufacturing, nanobiosensors, quantum dots, graphene, carbon nanotubes, self-assembly, top-down, bottom-up, biocompatibility, and sustainability.
Abstract
Artificial Intelligence In Healthcare
Ms. Aarti Chivadshetti, Prof. J. A. Patil
DOI: 10.17148/IJIREEICE.2025.13655
Abstract: Artificial Intelligence (AI) is transforming the healthcare industry by enabling faster, more accurate, and cost- effective solutions. An AI healthcare system integrates advanced technologies like machine learning, deep learning, and natural language processing to assist in diagnosis, treatment planning, patient monitoring, and medical research. These systems can analyze vast amounts of medical data, detect patterns, and provide predictive insights that support clinical decision-making. AI also enhances administrative efficiency, reduces human error, and enables personalized patient care. While challenges such as data privacy, ethical concerns, and system integration remain, the adoption of AI in healthcare holds immense potential to improve patient outcomes and revolutionize the delivery of medical services.
Keywords: Artificial Intelligence, Healthcare. Diagnostic Assistance. Treatment Personalization, Data Privacy, Ethical Considerations
Keywords: Artificial Intelligence, Healthcare. Diagnostic Assistance. Treatment Personalization, Data Privacy, Ethical Considerations
Abstract
THERMOELECTRIC COOLING SYSTEM USING PELTIER EFFECT
Sanchita .R. Devakte, Prof.J.A.Patil
DOI: 10.17148/IJIREEICE.2025.13656
Abstract: The continuous advancement in science and technology has led to the development of various systems capable of producing refrigeration effects. Conventional refrigerators commonly use refrigerants such as Ammonia and R12, which are harmful to the environment. This project proposes the development of compact cooling units designed for applications such as medicine storage in medical shops and hospitals, preservation of food for patients, and use in small pan-shops, hotel rooms, and guest houses. These units utilize thermoelectric modules based on the Peltier effect, thereby eliminating the need for harmful refrigerants and mechanical components like compressors and evaporators. This eco- friendly refrigeration approach not only helps in protecting the ozone layer but also reduces the overall cost of the refrigerator. The system is capable of effectively cooling a storage volume of up to 48 liters.
Keywords: Portable, Eco-Friendly, Thermoelectric Cooling, Peltier Effect, Refrigerant-Free
Keywords: Portable, Eco-Friendly, Thermoelectric Cooling, Peltier Effect, Refrigerant-Free
Abstract
Data Acquisition and Control System Using LabVIEW
Banumathi K L, Ruchitha Mahesh Dasareddy, Shreenikha H S,Vijayalaxmi Sthavarmath, Yashavanth K S
DOI: 10.17148/IJIREEICE.2025.13657
Abstract: The project aims to use LabVIEW, a National Instruments-created graphical programming environment, to design and implement a data acquisition and control system for monitoring and regulating physical characteristics. The system emphasizes automation, modularity, and user-friendly visualization, and is used in various applications such as laboratory testing, prototype creation, and industrial automation. The results demonstrate how LabVIEW's powerful tools can enhance system configuration ease, accuracy, and efficiency.
Keywords: National Instruments, LabVIEW, data acquisition, system, control.
Keywords: National Instruments, LabVIEW, data acquisition, system, control.
Abstract
Desgin of Low Power Asynchronous SAR ADC in CMOS Technology
Savithri G R, Shashank M Jadhav, Rohan B K, Naveen R D, Prajwal C Malagi
DOI: 10.17148/IJIREEICE.2025.13658
Abstract: This project presents the design of a low power Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) using asynchronous techniques. Traditional synchronous SAR ADCs suffer from clock-related power consumption and timing issues, especially at low sampling rates. By adopting an asynchronous architecture, this design eliminates the need for a global clock, thereby reducing dynamic power dissipation. The circuit employs event-driven control logic to trigger operations, resulting in improved energy efficiency. A capacitor-based DAC and a dynamic comparator are used to further minimize power usage. The proposed ADC achieves high resolution and low latency while maintaining a compact layout. Simulations are performed to validate the power-performance trade-offs. The design is suitable for low-power applications such as biomedical devices and IoT sensors. The project demonstrates how asynchronous design can significantly enhance SAR ADC efficiency for modern low-energy systems.
Keywords: SAR ADC, Synchronous SAR ADC, Energy efficiency, Capacitor-based DAC, Dynamic comparator, Compact layout, Simulations, Biomedical devices, IoT sensors
Keywords: SAR ADC, Synchronous SAR ADC, Energy efficiency, Capacitor-based DAC, Dynamic comparator, Compact layout, Simulations, Biomedical devices, IoT sensors
Abstract
Skin Disease Classification Using Multi-Model Optimization and Augmentation
Shivani R Shankar, Pavan Gudi, Anil Prasad, Kalyanaraman Raju, Yogapriya Rajalingam
DOI: 10.17148/IJIREEICE.2025.13659
Abstract: Skin diseases affect millions globally, posing screening challenges due to complex lesion characteristics and limited access to medical expertise. Traditional screening methods are time consuming, often requiring extensive laboratory testing. Deep learning and machine learning techniques have gained significant traction in recent years, serving as powerful tools in tackling complex problems, particularly in areas requiring substantial prior knowledge, such as biomedicine. With the challenge of inadequate medical resources, these methods have found impactful applications in disease screening, emerging as a pivotal research focus on dermatology. This project aims to develop an automated skin disease screening system using machine learning and deep learning techniques. The system is designed to accurately identify skin diseases, enhance early detection, address existing challenges in screening and ensure accessibility and affordability for all. This provides a concise review of the classification of skin diseases, leveraging Convolutional Neural Networks (CNN) and K-Nearest Neighbors (KNN) to analyse skin lesion characteristics and evaluate imaging technologies. By exploring the strengths of CNNs due to its high performance in image classification and feature extraction. KNN providing evidence by identifying similar images, making it an explainable AI model. This study presents an Evidence based screening system a virtual dermatology platform leveraging cutting-edge artificial intelligence and deep learning techniques for efficient skin disease classification. Using pre-trained models like GoogleNet, EfficientNet, ResNet, DenseNet, MobileNet and achieving a classification accuracy of 97% through EfficientNet. significantly reducing screening time and cost. The proposed system optimizes preprocessing, transfer learning, model training and cross-validation, significantly improving accuracy. The results highlight AI's potential to revolutionize dermatological screening, reducing costs and improving early detection.
Keywords: Convolutional Neural Network; K-Nearest Neighbors; Evidence based screening; EfficientNet;
Keywords: Convolutional Neural Network; K-Nearest Neighbors; Evidence based screening; EfficientNet;