By identifying students' frontal faces from classroom photos, this research attempts to construct a general face detection and identification system that will automate the process of gathering school attendance. The main issue with conventional attendance management systems is the accuracy of the data that is gathered. Numerous automated techniques are in use, including biometric attendance. Nonetheless, the effectiveness of these methods is always impacted by scanning equipment technical issues. In order to enhance data quality and information accessibility for authorised parties, this article uses OpenCV for face recognition and principal component analysis techniques for face detection. The database that holds user data in the system was developed using SQL, while the Python programming language was utilised to create the suggested system. After testing, it was determined that the new system is safe and secures students' identities by providing an anonymous attendance environment. Keywords: (ABS) Face Detection; Attendance; Machine Learning; Database; Principal component analysis;CNN; OpenCV and Face Recognition
{"title":"Facial Recognition Attendance System","authors":"Mohammad Afzal l Nezam","doi":"10.55041/ijsrem34176","DOIUrl":"https://doi.org/10.55041/ijsrem34176","url":null,"abstract":"By identifying students' frontal faces from classroom photos, this research attempts to construct a general face detection and identification system that will automate the process of gathering school attendance. The main issue with conventional attendance management systems is the accuracy of the data that is gathered. Numerous automated techniques are in use, including biometric attendance. Nonetheless, the effectiveness of these methods is always impacted by scanning equipment technical issues. In order to enhance data quality and information accessibility for authorised parties, this article uses OpenCV for face recognition and principal component analysis techniques for face detection. The database that holds user data in the system was developed using SQL, while the Python programming language was utilised to create the suggested system. After testing, it was determined that the new system is safe and secures students' identities by providing an anonymous attendance environment. Keywords: (ABS) Face Detection; Attendance; Machine Learning; Database; Principal component analysis;CNN; OpenCV and Face Recognition","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the vast tapestry of the earth's bounty, where agriculture reigned supreme, a quest unfolded – a pursuit of sustainable practices and optimal crop selection, crucial threads in the fabric of food security and economic prosperity. For in those regions where the farmer's toil was the heartbeat of livelihood, an intricate dance between soil, environment, and crop suitability posed a formidable challenge, one that traditional knowledge and experience alone could not fully unravel. Thus, a clarion call echoed through the fertile fields, beckoning a new era of innovation – a comprehensive soil analysis and crop prediction system that would harness the power of machine learning, weaving data into a tapestry of enlightened cultivation. Like a grand symphony, this system harmonized a multifaceted approach, blending the rigorous physicochemical analysis of soil samples with the rhythmic cadence of climatic data and the echoes of historical crop yield. From the soil's pH to its nutrient composition, texture, and moisture content, each parameter was meticulously evaluated, a prelude to the orchestration that would follow.This earthly aria was then enriched by the melodious whispers of meteorological data – temperature, rainfall patterns, and humidity levels, each note tailored to the region's unique symphony.But it was the machine learning ensemble, a grand chorus of supervised and unsupervised algorithms, that truly breathed life into this composition. Trained on a comprehensive dataset of soil analysis, climatic conditions, and historical crop yield records, these algorithms learned to decipher the intricate patterns and harmonies that bind input variables to crop performance, their synthetic synapses firing in perfect synchronicity.and from this symphony emerged the system's crowning aria – a resonant recommendation of crops tailored to the specific soil and environmental conditions of each location, a harmonious blend of predicted yield potential and optimal growing conditions.
{"title":"Soil Analysis and Crop Prediction System","authors":"Vijaya Patil","doi":"10.55041/ijsrem34498","DOIUrl":"https://doi.org/10.55041/ijsrem34498","url":null,"abstract":"In the vast tapestry of the earth's bounty, where agriculture reigned supreme, a quest unfolded – a pursuit of sustainable practices and optimal crop selection, crucial threads in the fabric of food security and economic prosperity. For in those regions where the farmer's toil was the heartbeat of livelihood, an intricate dance between soil, environment, and crop suitability posed a formidable challenge, one that traditional knowledge and experience alone could not fully unravel. Thus, a clarion call echoed through the fertile fields, beckoning a new era of innovation – a comprehensive soil analysis and crop prediction system that would harness the power of machine learning, weaving data into a tapestry of enlightened cultivation. Like a grand symphony, this system harmonized a multifaceted approach, blending the rigorous physicochemical analysis of soil samples with the rhythmic cadence of climatic data and the echoes of historical crop yield. From the soil's pH to its nutrient composition, texture, and moisture content, each parameter was meticulously evaluated, a prelude to the orchestration that would follow.This earthly aria was then enriched by the melodious whispers of meteorological data – temperature, rainfall patterns, and humidity levels, each note tailored to the region's unique symphony.But it was the machine learning ensemble, a grand chorus of supervised and unsupervised algorithms, that truly breathed life into this composition. Trained on a comprehensive dataset of soil analysis, climatic conditions, and historical crop yield records, these algorithms learned to decipher the intricate patterns and harmonies that bind input variables to crop performance, their synthetic synapses firing in perfect synchronicity.and from this symphony emerged the system's crowning aria – a resonant recommendation of crops tailored to the specific soil and environmental conditions of each location, a harmonious blend of predicted yield potential and optimal growing conditions.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141110090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Microfinance institutions (MFIs) act as indispensable financial intermediaries, providing small loans and services to individuals excluded from mainstream banking due to socio-economic constraints. Their significance lies in empowering marginalized communities, promoting financial inclusion, and fostering opportunities for income generation and entrepreneurship. Notably, microfinance contributes significantly to poverty alleviation and gender equality, particularly in empowering women, who often constitute a substantial portion of its beneficiaries. However, the effectiveness of microfinance in India faces multifaceted challenges. This paper addresses hurdles such as exorbitant interest rates, insufficient infrastructure, and the urgent need for effective regulation to prevent the exploitation of vulnerable borrowers Overall, this paper will find out the indispensable role of microfinance in India's economic development while acknowledging the challenges hindering its full potential. Unravelling these dynamics provides policymakers, practitioners, and stakeholders with a comprehensive understanding of microfinance in the Indian context, crucial for formulating informed strategies that foster sustained growth and ensure its continued positive impact on economic development. The insights gleaned from this study are vital for shaping the trajectory of microfinance in India.
{"title":"Role of Micro Finance in uplifting Indian Economy: An Analysis","authors":"Anwita Singh","doi":"10.55041/ijsrem34395","DOIUrl":"https://doi.org/10.55041/ijsrem34395","url":null,"abstract":"Microfinance institutions (MFIs) act as indispensable financial intermediaries, providing small loans and services to individuals excluded from mainstream banking due to socio-economic constraints. Their significance lies in empowering marginalized communities, promoting financial inclusion, and fostering opportunities for income generation and entrepreneurship. Notably, microfinance contributes significantly to poverty alleviation and gender equality, particularly in empowering women, who often constitute a substantial portion of its beneficiaries. However, the effectiveness of microfinance in India faces multifaceted challenges. This paper addresses hurdles such as exorbitant interest rates, insufficient infrastructure, and the urgent need for effective regulation to prevent the exploitation of vulnerable borrowers Overall, this paper will find out the indispensable role of microfinance in India's economic development while acknowledging the challenges hindering its full potential. Unravelling these dynamics provides policymakers, practitioners, and stakeholders with a comprehensive understanding of microfinance in the Indian context, crucial for formulating informed strategies that foster sustained growth and ensure its continued positive impact on economic development. The insights gleaned from this study are vital for shaping the trajectory of microfinance in India.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141113156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cryptography, while essential for data security, faces challenges such as interception during transmission, potentially exposing information to unauthorized parties. To combat this, game-based cryptography techniques have emerged, offering innovative solutions to safeguard sensitive data. This project focuses on developing security models inspired by popular games like Sudoku puzzles. These models aim to enhance data security while engaging users through interactive gameplay. As encryption gains increasing significance amidst rising data breaches and cyber threats, traditional methods often lack user engagement and accessibility. The proposed game-based encryption approach seeks to address these shortcomings by providing a more intuitive and interactive means of securing data across various complexity levels. By integrating puzzle elements into the encryption process, the project aims to bridge the gap between encryption experts and general users, making data security more understandable and engaging for everyone. Keywords : Cryptography, Encryption, Information, Games
{"title":"Intelligent System to Secure the Information based on Innovative Games","authors":"Pooja B","doi":"10.55041/ijsrem33862","DOIUrl":"https://doi.org/10.55041/ijsrem33862","url":null,"abstract":"Cryptography, while essential for data security, faces challenges such as interception during transmission, potentially exposing information to unauthorized parties. To combat this, game-based cryptography techniques have emerged, offering innovative solutions to safeguard sensitive data. This project focuses on developing security models inspired by popular games like Sudoku puzzles. These models aim to enhance data security while engaging users through interactive gameplay. As encryption gains increasing significance amidst rising data breaches and cyber threats, traditional methods often lack user engagement and accessibility. The proposed game-based encryption approach seeks to address these shortcomings by providing a more intuitive and interactive means of securing data across various complexity levels. By integrating puzzle elements into the encryption process, the project aims to bridge the gap between encryption experts and general users, making data security more understandable and engaging for everyone. Keywords : Cryptography, Encryption, Information, Games","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141110518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This project aims to develop a system called E-Pilots that uses machine learning algorithms to predict hard landings during the approach phase of commercial flights.The system will analyze flight data to precede hard landings.The goal is to provide pilots with real-time warnings and guidance to prevent accidents and improve safety.The research methodology includes the collection and analysis of flight data, the development and testing of machine learning algorithms, and the integration of the E-Pilots system with existing flight systems.The findings of this project are expected to contribute to the improvement of aviation safety and reduce the occurrence of hard landings. The implications of this research may also extend to other areas of aviation safety and flight automation.
{"title":"Epilots : A System to Predict Hard Landing During the Approach Phase of Commercial Flights","authors":".Mamatha, M","doi":"10.55041/ijsrem34534","DOIUrl":"https://doi.org/10.55041/ijsrem34534","url":null,"abstract":"This project aims to develop a system called E-Pilots that uses machine learning algorithms to predict hard landings during the approach phase of commercial flights.The system will analyze flight data to precede hard landings.The goal is to provide pilots with real-time warnings and guidance to prevent accidents and improve safety.The research methodology includes the collection and analysis of flight data, the development and testing of machine learning algorithms, and the integration of the E-Pilots system with existing flight systems.The findings of this project are expected to contribute to the improvement of aviation safety and reduce the occurrence of hard landings. The implications of this research may also extend to other areas of aviation safety and flight automation.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study explores the use of nitrogen (N2) injection to rejuvenate inactive wells and enhance reservoir productivity. We analyze the mechanism of N2 injection and its effectiveness in stimulating production from dormant wells through case studies and field applications. Our findings highlight the cost-effectiveness and environmental benefits of N2 kickoff in extending the life of mature reservoirs and maximizing hydrocarbon recovery. By examining operational conditions such as gas injection rate and pressure, we identify optimal conditions using Wellflo® simulations. Key factors like water cut, reservoir pressure, gas oil ratio, and productivity index (J) are considered to predict production outcomes. A new metric, the Optimum Economic Factor (OEF), assesses the efficiency of each operation based on production rate, operation length, and nitrogen usage. Our decision matrix, incorporating all examined factors, reveals trends: higher gas injection rates are needed for wells with higher water cut, lower gas oil ratio, lower productivity index, and lower reservoir pressure. We also studied the effects of wellhead pressure, well depth, and coiled tubing size, finding increased frictional pressure gradients with larger coiled tubing. Optimizing nitrogen unloading operations can significantly reduce costs, particularly by paying for coiled tubing packages on an hourly basis instead of daily rates. Our decision matrix facilitates planning and execution, optimizing nitrogen usage and reducing manpower requirements. Overall, our study demonstrates that proper optimization can make nitrogen unloading economically viable in mature oil fields.
{"title":"Revitalizing Reservoirs Nitrogen Kick-off Techniques for Reactivating Inactive Wells","authors":"Srimannarayana, Vv","doi":"10.55041/ijsrem34476","DOIUrl":"https://doi.org/10.55041/ijsrem34476","url":null,"abstract":"This study explores the use of nitrogen (N2) injection to rejuvenate inactive wells and enhance reservoir productivity. We analyze the mechanism of N2 injection and its effectiveness in stimulating production from dormant wells through case studies and field applications. Our findings highlight the cost-effectiveness and environmental benefits of N2 kickoff in extending the life of mature reservoirs and maximizing hydrocarbon recovery. By examining operational conditions such as gas injection rate and pressure, we identify optimal conditions using Wellflo® simulations. Key factors like water cut, reservoir pressure, gas oil ratio, and productivity index (J) are considered to predict production outcomes. A new metric, the Optimum Economic Factor (OEF), assesses the efficiency of each operation based on production rate, operation length, and nitrogen usage. Our decision matrix, incorporating all examined factors, reveals trends: higher gas injection rates are needed for wells with higher water cut, lower gas oil ratio, lower productivity index, and lower reservoir pressure. We also studied the effects of wellhead pressure, well depth, and coiled tubing size, finding increased frictional pressure gradients with larger coiled tubing. Optimizing nitrogen unloading operations can significantly reduce costs, particularly by paying for coiled tubing packages on an hourly basis instead of daily rates. Our decision matrix facilitates planning and execution, optimizing nitrogen usage and reducing manpower requirements. Overall, our study demonstrates that proper optimization can make nitrogen unloading economically viable in mature oil fields.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Profiler introduces a cutting-edge approach to efficiently manage and track Data Structures and Algorithms (DSA) in software development projects. In the realm of modern software engineering, where complexity is ubiquitous and scalability is critical, effective management of DSAs is essential for ensuring the robustness, maintainability, and performance of software systems. DSA Profiler seamlessly integrates into the development lifecycle, offering developers a centralized platform to meticulously document, organize, and monitor the implementation of various data structures and algorithms within their codebase. Its intuitive interfaces and powerful functionalities facilitate the process of incorporating, modifying, and optimizing DSAs. By providing detailed insights and analytics, DSA Profiler empowers developers to make informed decisions about the most appropriate data structures and algorithms for their specific needs, ultimately streamlining the development process and significantly enhancing code quality. One of the standout features of DSA Profiler is its ability to benchmark data structures and algorithms, allowing developers to evaluate their performance under different conditions. This benchmarking capability ensures that developers can identify and address performance bottlenecks early in the development cycle. Furthermore, This collaborative environment helps maintain consistency and adherence to standards across projects, which is particularly beneficial in large-scale and distributed development environments. Keywords - data structure benchmarking, data structure optimization, algorithm performance tracking, software scalability, development lifecycle integration, codebase management, performance analytics, collaborative development tools, real-time optimization recommendations.
{"title":"Data Structure Profiler Using MERN Technology","authors":"Rahul Sharma","doi":"10.55041/ijsrem34507","DOIUrl":"https://doi.org/10.55041/ijsrem34507","url":null,"abstract":"Profiler introduces a cutting-edge approach to efficiently manage and track Data Structures and Algorithms (DSA) in software development projects. In the realm of modern software engineering, where complexity is ubiquitous and scalability is critical, effective management of DSAs is essential for ensuring the robustness, maintainability, and performance of software systems. DSA Profiler seamlessly integrates into the development lifecycle, offering developers a centralized platform to meticulously document, organize, and monitor the implementation of various data structures and algorithms within their codebase. Its intuitive interfaces and powerful functionalities facilitate the process of incorporating, modifying, and optimizing DSAs. By providing detailed insights and analytics, DSA Profiler empowers developers to make informed decisions about the most appropriate data structures and algorithms for their specific needs, ultimately streamlining the development process and significantly enhancing code quality. One of the standout features of DSA Profiler is its ability to benchmark data structures and algorithms, allowing developers to evaluate their performance under different conditions. This benchmarking capability ensures that developers can identify and address performance bottlenecks early in the development cycle. Furthermore, This collaborative environment helps maintain consistency and adherence to standards across projects, which is particularly beneficial in large-scale and distributed development environments. Keywords - data structure benchmarking, data structure optimization, algorithm performance tracking, software scalability, development lifecycle integration, codebase management, performance analytics, collaborative development tools, real-time optimization recommendations.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141113117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research paper delves into the pivotal role of perspective management in shaping effective marketing strategies. In today's dynamic business environment, where consumer behaviors and preferences constantly evolve, understanding and influencing perspectives is essential for sustainable market success. This study adopts a comprehensive approach to analyze the interplay between perspective management and marketing strategy, drawing insights from various disciplines such as psychology, sociology, and marketing. Key aspects explored include the influence of cognitive biases, cultural differences, and social norms on consumer perspectives, as well as strategies for effectively managing and leveraging these perspectives to drive brand engagement, loyalty, and market penetration. Through a combination of theoretical frameworks, empirical evidence, and case studies, this paper offers valuable insights for marketers seeking to enhance their understanding of consumer perspectives and optimize their marketing strategies accordingly. Key Words: Perspective management, Marketing strategy, Consumer behavior, Cognitive biases, Cultural differences, Brand engagement.
{"title":"Leveraging Perspective Management in Marketing Strategy: A Comprehensive Analysis","authors":"Nikhil Dattatray Avhad","doi":"10.55041/ijsrem34171","DOIUrl":"https://doi.org/10.55041/ijsrem34171","url":null,"abstract":"This research paper delves into the pivotal role of perspective management in shaping effective marketing strategies. In today's dynamic business environment, where consumer behaviors and preferences constantly evolve, understanding and influencing perspectives is essential for sustainable market success. This study adopts a comprehensive approach to analyze the interplay between perspective management and marketing strategy, drawing insights from various disciplines such as psychology, sociology, and marketing. Key aspects explored include the influence of cognitive biases, cultural differences, and social norms on consumer perspectives, as well as strategies for effectively managing and leveraging these perspectives to drive brand engagement, loyalty, and market penetration. Through a combination of theoretical frameworks, empirical evidence, and case studies, this paper offers valuable insights for marketers seeking to enhance their understanding of consumer perspectives and optimize their marketing strategies accordingly. Key Words: Perspective management, Marketing strategy, Consumer behavior, Cognitive biases, Cultural differences, Brand engagement.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141111841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The project concept of An autonomous fire safety mechanism for EVs is an inventive way of considering a less cost-effective design and a more convenient application for e-vehicle safety. Day by day, the number of fatalities in electric vehicles increases. In this project, our main aim is to reduce the number of accidents with electric vehicles by making a smart fire safety system for electric vehicles. With the rapid adoption of electric vehicles (EVs), ensuring their safety, particularly concerning fire hazards, has become paramount. This abstract presents a conceptual framework for a sophisticated fire safety system tailored specifically for EVs. The proposed system integrates advanced technologies such as battery monitoring systems (BMS), temperature and smoke sensors, machine learning algorithms, active fire suppression mechanisms, emergency shutdown features, remote monitoring capabilities, user alerts, and compliance with safety standards. By combining these elements into a cohesive system, EV manufacturers can significantly mitigate the risks associated with fires in electric vehicles, enhancing overall safety for drivers, passengers, and emergency responders. With this technique, the fire extinguisher automatically puts out the fire when it detects flames or smoke coming from the vehicle's fire zones. Numerous factors can cause an electric vehicle to catch fire. The lithium-ion battery is the primary cause of flames in electric vehicles used within them. Installing an autonomous fire extinguishing system with Internet of Things (IoT) technology can reduce potential financial loss from a fire while also raising vehicle and human safety standards. Additionally, as soon as an accident is discovered, the nearby authorities or emergency services are notified, allowing them to get to you sooner. KEYWORDS:- Accident prevention, emergency alert, controller, fire incident, IOT technology, etc.
{"title":"Design & Development of Smart Fire Safety System For e-Vehicles Using IOT","authors":"Sandip Patorkar","doi":"10.55041/ijsrem34484","DOIUrl":"https://doi.org/10.55041/ijsrem34484","url":null,"abstract":"The project concept of An autonomous fire safety mechanism for EVs is an inventive way of considering a less cost-effective design and a more convenient application for e-vehicle safety. Day by day, the number of fatalities in electric vehicles increases. In this project, our main aim is to reduce the number of accidents with electric vehicles by making a smart fire safety system for electric vehicles. With the rapid adoption of electric vehicles (EVs), ensuring their safety, particularly concerning fire hazards, has become paramount. This abstract presents a conceptual framework for a sophisticated fire safety system tailored specifically for EVs. The proposed system integrates advanced technologies such as battery monitoring systems (BMS), temperature and smoke sensors, machine learning algorithms, active fire suppression mechanisms, emergency shutdown features, remote monitoring capabilities, user alerts, and compliance with safety standards. By combining these elements into a cohesive system, EV manufacturers can significantly mitigate the risks associated with fires in electric vehicles, enhancing overall safety for drivers, passengers, and emergency responders. With this technique, the fire extinguisher automatically puts out the fire when it detects flames or smoke coming from the vehicle's fire zones. Numerous factors can cause an electric vehicle to catch fire. The lithium-ion battery is the primary cause of flames in electric vehicles used within them. Installing an autonomous fire extinguishing system with Internet of Things (IoT) technology can reduce potential financial loss from a fire while also raising vehicle and human safety standards. Additionally, as soon as an accident is discovered, the nearby authorities or emergency services are notified, allowing them to get to you sooner. KEYWORDS:- Accident prevention, emergency alert, controller, fire incident, IOT technology, etc.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141110915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The entire set of interconnected devices as well as the technology enabling communication between the devices and the cloud. This article presents an innovative Internet of Things (IOT)based autonomous location monitoring system that is made possible by Positioning, Navigation, and Timing (PNT) services. The system allows for real-time tracking and surveillance of objects or persons by combining Internet of Things sensors and communication modules with PNT technologies like GPS, Galileo, or GLONASS. The technology uses advanced machine learning techniques and algorithms to automatically identify and evaluate anomalies in the monitored area. It then swiftly reports these findings to the relevant authorities.PNT services are seamlessly linked to ensure accurate and reliable location, even in challenging Environment. In addition to being adaptable, scalable, and compatible with existing infrastructure, the Technology has a wide range of applications, including border security, asset protection, and perimeter monitoring. This work advances the possibilities of autonomous surveillance systems. In depth features provided by the research include mobile number identification (subject to legal and regulatory constraints), real-time location visualization, and centralized vehicle data management for enhanced fleet management, security, and operational effectiveness The development of sophisticated solutions that make use of precision navigation and timing (PNT) and the internet of things (IOT) has been spurred by the growing need for effective location based surveillance systems. Edge computing units, a central control unit and a monitoring and control user interface are important parts of the system. Data is processed locally with edge computing, which lowers latency and improves response times. to create a self-contained location monitoring system using precise PNT services and IOT technology. Keywords: IOT, Real-Time Tracking, Vehicle Management, Python Flask, Mobile Number Tracking, Data Fetching
{"title":"IOT based Autonomous Location Surveillance System Using PNT Services","authors":"M. S","doi":"10.55041/ijsrem34248","DOIUrl":"https://doi.org/10.55041/ijsrem34248","url":null,"abstract":"The entire set of interconnected devices as well as the technology enabling communication between the devices and the cloud. This article presents an innovative Internet of Things (IOT)based autonomous location monitoring system that is made possible by Positioning, Navigation, and Timing (PNT) services. The system allows for real-time tracking and surveillance of objects or persons by combining Internet of Things sensors and communication modules with PNT technologies like GPS, Galileo, or GLONASS. The technology uses advanced machine learning techniques and algorithms to automatically identify and evaluate anomalies in the monitored area. It then swiftly reports these findings to the relevant authorities.PNT services are seamlessly linked to ensure accurate and reliable location, even in challenging Environment. In addition to being adaptable, scalable, and compatible with existing infrastructure, the Technology has a wide range of applications, including border security, asset protection, and perimeter monitoring. This work advances the possibilities of autonomous surveillance systems. In depth features provided by the research include mobile number identification (subject to legal and regulatory constraints), real-time location visualization, and centralized vehicle data management for enhanced fleet management, security, and operational effectiveness The development of sophisticated solutions that make use of precision navigation and timing (PNT) and the internet of things (IOT) has been spurred by the growing need for effective location based surveillance systems. Edge computing units, a central control unit and a monitoring and control user interface are important parts of the system. Data is processed locally with edge computing, which lowers latency and improves response times. to create a self-contained location monitoring system using precise PNT services and IOT technology. Keywords: IOT, Real-Time Tracking, Vehicle Management, Python Flask, Mobile Number Tracking, Data Fetching","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141111688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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