VOLUME 12, ISSUE 11, NOVEMBER 2024

Abstract: In this paper a machine learning technique-based method is presented for identifying faults in a microgrid. The machine learning method considered is multilayer neural network. The microgrid model includes renewable energy sources such as solar photovoltaic and wind generator. Both normal and fault situations for the microgrid are simulated when operating in grid-connected and islanded modes. The fault conditions include various faults experienced on a power distribution line. The fault currents and voltages are used for training a neural network with Levenberg-Marquardt method. The trained neural network is effective in identifying and classifying faults using trained and untrained data for both grid-connected and islanded modes of operation.

Keywords: Machine Learning, Microgrid, Neural Network, Protective Relaying, Fault Detection.

Abstract: This research thesis addresses the growing need for adaptive dynamic interior walls in modern home- schooling design to accommodate the dynamic nature of contemporary lifestyles and enhance living environments. By integrating insights from interior design, architecture, psychology, and engineering, this multidisciplinary study investigates the efficacy of dynamic walls in meeting the evolving needs of inhabitants. The paper begins with a comprehensive literature review, exploring historical precedents, theoretical frameworks, and practical applications relevant to adaptive interior design. Drawing from influential scholars such as Christopher Alexander and Sarah Williams Gold Hagen, the review highlights the psychological, physiological, and sociocultural dimensions of spatial design, emphasizing the pivotal role of adaptability in promoting human well-being and satisfaction in built environments. Building on this theoretical foundation, the study delves into the design development process of dynamic walls, elucidating the intricate interplay between form, function, and technology. Through a detailed exploration of material selection, structural considerations, and responsive design principles, the research illuminates the complexities inherent in creating adaptive architectural elements. Inspirations from innovative projects like the MIT Media Lab's City Home and Ori Systems robotic furniture showcase the transformative potential of dynamic walls in optimizing spatial utilization and enhancing user experience. Furthermore, the study delves into empirical findings derived from surveys, experiments, and user feedback. The collection of robust data and analysis of both quantitative metrics and qualitative responses demonstrate the profound influence of adaptive design solutions on aspects such as spatial flexibility, usability, and overall satisfaction. Concrete evidence of measurable benefits, such as space optimization and improved user experience, is complemented by nuanced perspectives from qualitative feedback, shedding light on user interactions. The versatility and scalability of dynamic walls are underscored through the inclusion of real-world case studies across diverse settings. These case studies provide tangible proof of concept, showcasing successful implementations in commercial spaces, educational environments, This research paper offers a compelling argument for the transformative potential of dynamic walls as an effective design solution. By synthesizing theoretical insights, design principles, and empirical evidence, it contributes to the discourse on adaptive interior design and provides practical guidance for architects, designers, and stakeholders seeking to enhance spatial functionality and user experience.

Keywords: Adaptive design; Dynamic walls; Home Schooling; Spatial flexibility; User experience.

Abstract: Smart construction management harnesses artificial intelligence (AI) to address inefficiencies and challenges in modern construction projects, enhancing scheduling, resource allocation, and decision-making processes. By leveraging AI technologies such as machine learning (ML), natural language processing (NLP), and computer vision, construction managers can optimize workflows, monitor progress in real-time, and predict potential issues before they occur.
This research explores how AI-driven tools transform key aspects of construction management, from improving safety and quality control to reducing costs and delays. Case studies highlight the practical applications of AI, including predictive maintenance, dynamic task adjustments, and automated inspections, demonstrating significant improvements in project outcomes. Despite its benefits, the adoption of AI in construction faces challenges such as data integration, high implementation costs, and the need for specialized skills. The paper discusses potential solutions to these challenges and outlines future opportunities for AI in smart construction management.

Keywords: Artificial Intelligence, Smart Construction Management, Machine Learning, Natural Language Processing, Computer Vision, Predictive Analytics, Resource Allocation, Real-Time Monitoring, Safety Management, Construction Optimization.

Abstract: This paper presents an energy-efficient lighting system that integrates Light Emitting Diodes (LEDs) with motion (PIR) and ambient light sensors (LDR). The system optimizes energy consumption by controlling the lights based on occupancy and ambient light conditions. The use of LEDs ensures low power consumption, while the sensors help reduce unnecessary energy usage. The system, managed by a microcontroller, adjusts the LED brightness or turns the lights off when no movement is detected or when ambient light is sufficient. The proposed system is designed to offer energy savings without compromising lighting requirements.

Keywords: Energy efficiency, LED lighting, PIR sensor, LDR sensor, smart lighting, microcontroller, energy savings, automated control, ambient light, occupancy detection.

Abstract: The E-Career Mitra is a comprehensive platform designed to streamline the various activities involved in managing campus placements and training. This system addresses the challenges faced by educational institutions in organizing placement drives, tracking student eligibility, and coordinating with companies. By automating and digitizing the entire process, the system enhances efficiency, reduces manual errors, and provides real-time updates to all stakeholders involved. The system features modules for student registration, resume submission, job application tracking, company registration. Additionally, it offers administrative tools for managing eligibility criteria, generating reports, and communicating with students. The System also has the Training Module where TPO can post the training or study materials. The E-Career Mitra ensures seamless coordination between students, placement officers, ultimately improving the overall placement experience.

Keywords: Training, Artificial Intelligence, Placement, Web Development.

Abstract: The manufacturing sector plays an essential role in satisfying society's needs and provides a catalyst for the country's progress. In the manufacturing and machining industry, there are new technologies. In the metal forming industry, the single point incremental forming is new technology. In SPIF single point tool is used to form the material without the use of an external die. Heat-assisted incremental forming is an advancement in single-point incremental forming, which enhances the formability of the material. In this experimental work, titanium material is formed by a heat- assisted single-point incremental process with the hemispherical tool at a different temperature, feed rate, step size, and lubricant on the vertical machining centre. The effect of these parameters on formability and surface roughness of material is analysed Using Taguchi design. ANOVA is used to assess which parameter substantially impacts the surface roughness of the material and assess the difference between statistical and mathematical experiment data for confirmation using regression analysis

Keywords: Hot incremental sheet forming, lubricant, coil heating system, formability, spring back, surface roughness, sheet thinning.

Abstract: The aim of this research is making the protection system for the three-phase induction motor. Providing the protection system to the induction motor is very importance in industrial or commercial application as well as domestic application. In industry lots of operation like production, mixing, conveyor belts are not hampered owing to failure of any motor. The basic idea for the developing a project is to providing safety to industrial motor, lifts, pumps and giving alerts of which types of faults is produce to the operator or maintenance department. In this project we develop the three- phase induction Motor protection system which are over voltage, over current, under voltage, earth fault protection and over temperature with using micro controller. In additional also introduce the GSM alerts for which kind of faults are Produce at the Operation of motor.

Keywords: Three phase induction motor, Current, Voltage variation, Arduino.