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VOLUME 14, ISSUE 7, JULY 2026
Publishing in progress.
Power Factor Correction Using STATCOM with LCL Filter and PI Controller
Dighe Akshay Adinath, Prof.V. R. Aranke, Prof. S.S.Hadpe, Prof.S.S.Khule
Investigation of the Glimn-Kirchmayer Input-Output Method for Hydropower Plant Modelling using Swarming Intelligence Computing Techniques
Wokoma, B. A., Blue-Jack, K. Q.
IoT-Based Saline Bottle Monitoring and Control System Using Wi-Fi and Android Application
RASHMI TANDI, NIDHI SHARMA, AAKANKSHA SAHU
Comparative Review of Wind Turbine Generators and Power Electronic Converters for Grid Integration
Hedra Saleeb, Ahmed M. Kassem, Farid N. Abdelbar, Aml E. Rofaeel, Heba A. Mahmoud
LoRa-Based Wireless Emergency Alert and Response System for Tribal and Rural Areas
K. Srilekha, Dr. P. Sreesudha, Dr. Rajkumar L. Biradar, Dr. T. Sunitha, Mrs. A. Rajitha
A novel system for comparing viscosity of two liquids via flow time delays and providing indications about liquid quality, using photo-interrupter sensors and implemented with FPGAs and VHDL
Dr Evangelos I. Dimitriadis, Leonidas Dimitriadis
AI-Powered Robotics for Intelligent Industrial
Mr.P.U.Palkar, Pratik Rameshwar Dahale, Kaustubh Shivajirao Deshpande
Detection of Peak Peripheral Blood Flow
Sabiha G. Shaikh, Uttam R. Bagal
Lathe CNC Machine Tool Evaluation by Exploring Grey Set based Full Multiplicative Form Approach
Ms. Varsha Kailas Ladke* & Dr. Hulas Raj A. Tonday
Machine Learning Based Retail Profit Prediction for Business Decision Support – A Comparative Model Analysis
Purnithaa B R, Maneeswar K G, Dr. Roselin A
Abstract
Power Factor Correction Using STATCOM with LCL Filter and PI Controller
Dighe Akshay Adinath, Prof.V. R. Aranke, Prof. S.S.Hadpe, Prof.S.S.Khule
DOI: 10.17148/IJIREEICE.2026.14701
Abstract: Power quality degradation caused by reactive power demand and harmonic distortion has become a major concern in modern electrical distribution systems with increasing penetration of nonlinear and inductive loads. This paper proposes a Static Synchronous Compensator (STATCOM) integrated with an LCL filter and a cascaded dq-axis PI control strategy to achieve effective reactive power compensation and dynamic power factor correction. The proposed controller employs a Synchronous Reference Frame Phase-Locked Loop (SRF-PLL) for accurate grid synchronization and decoupled active–reactive power regulation, ensuring stable operation under varying load conditions. The complete system is developed and validated in MATLAB/Simulink, where the LCL filter significantly suppresses switching harmonics while the PI controller provides fast transient response and robust DC-link voltage regulation. Simulation results demonstrate a substantial improvement in grid power factor from 0.894 (lagging) to unity, with load current and voltage THD values of 0.01% and 0.02%, respectively.The proposed STATCOM configuration exhibits excellent dynamic performance, superior power quality enhancement, and reliable reactive power compensation, making it a practical solution for modern industrial and utility distribution networks.
Keywords: STATCOM, Power Factor Correction, LCL Filter, PI Controller, dq-Frame, SRF-PLL, Reactive Power Compensation, VSC, FACTS, MATLAB/Simulink.
Keywords: STATCOM, Power Factor Correction, LCL Filter, PI Controller, dq-Frame, SRF-PLL, Reactive Power Compensation, VSC, FACTS, MATLAB/Simulink.
Abstract
Investigation of the Glimn-Kirchmayer Input-Output Method for Hydropower Plant Modelling using Swarming Intelligence Computing Techniques
Wokoma, B. A., Blue-Jack, K. Q.
DOI: 10.17148/IJIREEICE.2026.14702
Abstract: In order to model a modern power system generation, optimization is typically performed with the aim of improving the relative Input-Output (I-O) performance such as the efficiency, energy, and input-output response while considering certain underlying constraints and system objectives. While the Nigerian hydro power plants have been proven to be a somewhat more reliable and more enviro-friendly energy base with some recent improvement in generation capacity, the system has been reported to operate sub-optimally leading to huge power losses and systems malfunction. In this research paper, the optimization of an existing Nigerian Hydro-Power Plant – the Shiroro Hydro Power Station (SHPP) is simulated using the MATLAB programming language and considering several swarm intelligence hybridized optimizers – the PSO, SMO, BBO and the ABCO. The reported results showed the BBO as the best method while the SMO as the least performing.
Keywords: Hydro Power, Intelligence, Optimization, Simulation, Swarm.
Keywords: Hydro Power, Intelligence, Optimization, Simulation, Swarm.
Abstract
The Operational Technology Exposure Budget: A Business Value Model for Industrial Connectivity Decisions
Daniel Ward
DOI: 10.17148/IJIREEICE.2026.14703
Abstract: Industrial organizations increasingly connect operational technology (OT) to enterprise analytics, remote access platforms, maintenance systems, cloud services, and artificial intelligence pipelines. These connections may provide operational visibility, but they can also create control-path exposure in systems that monitor or control physical processes. This paper proposes the Operational Technology Exposure Budget, a design-science decision model for evaluating whether OT connectivity and industrial data flows are justified by measurable business value. The model separates business-value scoring from exposure-burden scoring and classifies connectivity decisions into four outcomes: approve, re-architect, reduce, or remove. Using public OT security guidance, secure-connectivity principles, data governance literature, AI-in-OT guidance, and synthetic industrial connectivity scenarios, the paper demonstrates how organizations can preserve useful telemetry while minimizing unnecessary exposure. The contribution is a practical engineering-management artifact that challenges unjustified OT connectivity before organizations attempt to secure it after the fact.
Keywords: business value, industrial connectivity, industrial control systems, operational technology, OT exposure budget, telemetry governance
Keywords: business value, industrial connectivity, industrial control systems, operational technology, OT exposure budget, telemetry governance
Abstract
IoT-Based Saline Bottle Monitoring and Control System Using Wi-Fi and Android Application
RASHMI TANDI, NIDHI SHARMA, AAKANKSHA SAHU
DOI: 10.17148/IJIREEICE.2026.14704
Abstract: Continuous monitoring of Intravenous (IV) saline bottles is an important requirement in healthcare environments to ensure uninterrupted fluid administration and patient safety. Conventional saline monitoring methods rely primarily on manual observation by healthcare personnel, which may lead to delayed detection of low saline levels, increased workload, and potential risks such as blood backflow. To address these challenges, numerous researchers have proposed Internet of Things (IoT)-based saline monitoring systems employing different sensing technologies, wireless communication techniques, and mobile monitoring platforms.
This review paper presents a comprehensive analysis of existing IoT-based saline bottle monitoring systems reported in the literature. Various approaches, including Infrared (IR) sensor-based systems, load cell-based monitoring techniques, and capacitive sensing methods, are examined and compared. The advantages, limitations, practical challenges, and control mechanisms such as automatic flow control, valve operation, and blood backflow prevention associated with these technologies are also discussed. Furthermore, the paper identifies research gaps and highlights future directions for developing reliable, cost-effective, and intelligent saline monitoring solutions for modern healthcare applications. The review emphasizes the growing role of IoT technologies in improving patient safety, reducing healthcare workload, and enhancing the efficiency of medical monitoring systems.
Keywords: IoT, Saline Bottle Monitoring, Saline Flow Control, ESP32, Capacitive Sensor, Wi-Fi, Android Application, Smart Healthcare.
This review paper presents a comprehensive analysis of existing IoT-based saline bottle monitoring systems reported in the literature. Various approaches, including Infrared (IR) sensor-based systems, load cell-based monitoring techniques, and capacitive sensing methods, are examined and compared. The advantages, limitations, practical challenges, and control mechanisms such as automatic flow control, valve operation, and blood backflow prevention associated with these technologies are also discussed. Furthermore, the paper identifies research gaps and highlights future directions for developing reliable, cost-effective, and intelligent saline monitoring solutions for modern healthcare applications. The review emphasizes the growing role of IoT technologies in improving patient safety, reducing healthcare workload, and enhancing the efficiency of medical monitoring systems.
Keywords: IoT, Saline Bottle Monitoring, Saline Flow Control, ESP32, Capacitive Sensor, Wi-Fi, Android Application, Smart Healthcare.
Abstract
Comparative Review of Wind Turbine Generators and Power Electronic Converters for Grid Integration
Hedra Saleeb, Ahmed M. Kassem, Farid N. Abdelbar, Aml E. Rofaeel, Heba A. Mahmoud
DOI: 10.17148/IJIREEICE.2026.14705
Abstract: Coal-fired power plants (PPs) are one of the biggest causes of today's catastrophic climate crisis. To deal with this problem, there is a need to completely decarbonize the energy segment using zero-emission renewable energy sources (RES). Wind turbine (WT) farms are one of the fastest-growing energy solutions globally. These massive complexes consist of huge WT that harness wind energy, convert it into electricity, and send it to the utility grid (UG) for use alongside traditional energy sources. Integration of WT energy into the UG is interesting and could be a valuable solution for dealing with future energy challenges. Given the challenges faced regarding the connection between large WT farms and the UG using induction and synchronous generators (I&SGs), it is necessary to study and compare varying WT generator systems. This research analyzes and compares the connections of varying WT generators and their control using varying power electronics converters (PECs). This paper also discusses the current status of generators and PEC in WT concepts. He showed that a double-fed induction generator (DFIG) driving a variable-speed WT is more efficient compared to other generators.
Keywords: Renewable Energy, Wind Energy, Wind Turbines, Wind Generator System, Grid Connection.
Keywords: Renewable Energy, Wind Energy, Wind Turbines, Wind Generator System, Grid Connection.
Abstract
LoRa-Based Wireless Emergency Alert and Response System for Tribal and Rural Areas
K. Srilekha, Dr. P. Sreesudha, Dr. Rajkumar L. Biradar, Dr. T. Sunitha, Mrs. A. Rajitha
DOI: 10.17148/IJIREEICE.2026.14706
Abstract: Cellular coverage for wide areas within India’s hilly and tribal interiors is sparse or non-existent, and even if there is a limited cellular network coverage, this too is the first thing to be affected by any natural calamity like flood, landslide, etc. Thus, the people living in such areas have no way of contacting their medical and police services during any emergency situation. This paper describes an economical and low power emergency alerting system based on LoRa (Long Range) Radio Communication which works completely independent of cellular network and Internet. In each village, the node consists of a microcontroller board (Arduino Uno) interfaced to Semtech SX1278 (Ra-02) LoRa module working at 433MHz frequency. There are dedicated push buttons available in each node through which any person can trigger medical or police emergency. Accordingly the node will send a small identifying packet containing the village ID and kind of assistance required. The Hospital and Police Station Nodes are in constant receiving mode and keep showing alerts on 16×2 LCD display while sounding a buzzer and activating LEDs. As soon as an alert gets acknowledged, a confirmatory packet will be sent back to originating village through a status LED. Moreover, each node also features a light circuit for a street light controlled by LDR, which works independent of the alerting system, thereby demonstrating another example of how the same powersaving platform could be used. A prototype, consisting of two village nodes, a hospital node, and a police station node, has been developed and tested in real-world conditions; reliable communication was achieved up to 1 km distance in the open field, with each node consuming around 0.6 W of energy.
Keywords: LoRa, SX1278, Arduino Uno, Emergency Communication, Rural Connectivity, Tribal Areas, Wireless Sensor Network, Disaster Management, LDR Sensor, Internet of Things.
Keywords: LoRa, SX1278, Arduino Uno, Emergency Communication, Rural Connectivity, Tribal Areas, Wireless Sensor Network, Disaster Management, LDR Sensor, Internet of Things.
Abstract
A novel system for comparing viscosity of two liquids via flow time delays and providing indications about liquid quality, using photo-interrupter sensors and implemented with FPGAs and VHDL
Dr Evangelos I. Dimitriadis, Leonidas Dimitriadis
DOI: 10.17148/IJIREEICE.2026.14707
Abstract: A novel system which uses FPGAs and VHDL for comparing viscosity of two liquids, with the first one be- ing the standard liquid and the second being the tested one, is presented here. The system monitors flow delay times of both liquids using two corresponding photo-interrupter sensors. If the opaque liquid goes through sensor slot, sensor transits to HIGH state with simultaneous time value storing. Our system is programed to calculate and display in FPGA board’s seven-segment displays, the signed time values difference of the two liquids, thus indicating whether standard or tested liquid reaches corresponding photo-interrupter sensor first and also what is the magnitude of viscosity differ- ence of the two liquids. A set of output LEDs is also programed to light up, in order to present the level of the above time difference depended viscosity variance of the two liquids. Our algorithm works fine also with transparent liquids as long as liquid flow tubes are sufficiently thick (several millimeters), in order to prevent infrared radiation passing through the liquid. Our system is cheap to manufacture, easy to use and able to process simultaneously, due to FPGA use, a large number of tested liquids in industrial environments, allowing it to produce valid information for liquid samples by combining it with IoT and AI systems.
Keywords: Viscosity, photo-interrupter sensors, liquid flow, FPGA, VHDL, LEDs.
Keywords: Viscosity, photo-interrupter sensors, liquid flow, FPGA, VHDL, LEDs.
Abstract
AI-Powered Robotics for Intelligent Industrial
Mr.P.U.Palkar, Pratik Rameshwar Dahale, Kaustubh Shivajirao Deshpande
DOI: 10.17148/IJIREEICE.2026.14708
Abstract: The adaptability of robotic systems in dynamic industrial settings has been limited by predefined programs and fixed control logic. Intelligent robotic systems that are capable of perception, learning, and autonomous decision- making have been made possible by recent advancements in artificial intelligence (AI). This paper presents a framework for intelligent industrial automation based on robotics powered by AI. The proposed system integrates real-time sensor data, machine learning algorithms, and robotic control systems to achieve adaptive behavior, fault awareness, and improved operational efficiency. To optimize robotic actions, AI-based decision models look at sensory inputs like vision, force, and positional data. The framework enhances productivity, flexibility, and safety, making it suitable for smart manufacturing and Industry 4.0 applications.
Keywords: AI-powered robotics, intelligent automation, predictive maintenance, and Industry 4.0
Keywords: AI-powered robotics, intelligent automation, predictive maintenance, and Industry 4.0
Abstract
Detection of Peak Peripheral Blood Flow
Sabiha G. Shaikh, Uttam R. Bagal
DOI: 10.17148/IJIREEICE.2026.14709
Abstract: Electrical impedance measurement of a body segment is performed by applying a low-amplitude, high frequency constant current through one pair of electrodes, while the resulting voltage is recorded using a separate pair of sensing electrodes. The measured voltage varies with the volume of blood present in the measured region. The negative first derivative of the impedance waveform is a peripheral blood flow (PBF) signal. Distinct fiducial points in the PBF waveform correspond to specific phases of the cardiac cycle, utilized to derive cardiovascular parameters and assess beat- to-beat variations. This study investigates automated detection of peaks in the PBF signal using three methods based on custom logic, implemented on PBF signals from subjects with normal health, hypertension, lung cancer, and coronary artery disease. Signals were recorded from 6 subjects of each type, yielding 24 recordings of 8,996 cycles. Method M3 achieved sensitivity 99.57%, precision 99.71%, F1-score 99.64%, and detection error 0.72%, outperforming all other methods.
Keywords: Electrical impedance, Fiducial points, Peripheral blood flow (PBF), Wavelet methods.
Keywords: Electrical impedance, Fiducial points, Peripheral blood flow (PBF), Wavelet methods.
Abstract
Lathe CNC Machine Tool Evaluation by Exploring Grey Set based Full Multiplicative Form Approach
Ms. Varsha Kailas Ladke* & Dr. Hulas Raj A. Tonday
DOI: 10.17148/IJIREEICE.2026.14710
Abstract: Computer Numerical Control (CNC) machine tools play a vital role in modern advanced manufacturing environments, where precision, efficiency, and reliability are critical. Evaluating CNC machines involves multiple conflicting criteria, making the decision-making process complex, particularly under conditions of uncertainty and incomplete information. Conventional evaluation techniques often lack the capability to effectively address such ambiguity. To overcome these limitations, this study proposes a comprehensive evaluation and benchmarking model for lathe CNC machine tools based on grey system theory. The proposed framework is structured using a SLS and focuses exclusively on key performance criteria and relevant metrics to ensure practical applicability. Grey set theory is incorporated into the model to manage uncertainty, vagueness, and incomplete data inherent in real-world decision environments. Furthermore, a grey-based crisp Full Multiplicative Form (FMF) approach is applied to rank and benchmark the alternative CNC lathe machines. The results demonstrate the effectiveness and robustness of the proposed approach in identifying the most suitable CNC machine tool among multiple alternatives. The study concludes by highlighting the practical implications and reliability of the model for decision-makers in advanced manufacturing systems.
Keywords: CNC Machine Tools, Grey Set Theory, Benchmarking, MCDM, Manufacturing Systems, Full Multiplicative Form Approach, MCDM
Keywords: CNC Machine Tools, Grey Set Theory, Benchmarking, MCDM, Manufacturing Systems, Full Multiplicative Form Approach, MCDM
Abstract
Machine Learning Based Retail Profit Prediction for Business Decision Support – A Comparative Model Analysis
Purnithaa B R, Maneeswar K G, Dr. Roselin A
DOI: 10.17148/IJIREEICE.2026.14711
Abstract: Retail organizations generate large volumes of transactional data, making accurate profit estimation essential for effective business decision-making. This study proposes a machine learning-based framework for predicting order- level retail profit using the SuperStore Orders dataset containing 51,290 records and 21 attributes. Three regression models—Linear Regression, Decision Tree Regressor, and Random Forest Regressor—were developed and evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²). Experimental results demonstrate that the Random Forest Regressor achieved the highest predictive performance with an R² score of 0.7095, outperforming the other models by effectively capturing complex non-linear relationships among retail transaction features. The findings indicate that Random Forest is a reliable approach for retail profit prediction and can serve as a valuable predictive component in Business Decision Support Systems.
Keywords: Machine Learning, Random Forest, Retail Profit Prediction, Business Decision Support System, Regression Analysis
Keywords: Machine Learning, Random Forest, Retail Profit Prediction, Business Decision Support System, Regression Analysis