Track Maven is a web application designed to streamline task management processes within organizations. Track Maven aims to provide a centralized platform for managing tasks, enabling efficient task assignment, monitoring, and tracking. The dashboard offers a user-friendly interface for creating, updating, and deleting tasks, as well as assigning tasks to specific teams or individuals. It also includes features for monitoring task completion status and generating reports to track team performance. The project utilizes React for the frontend interface, Node.js and Express.js for the backend server, and MongoDB as the database. The application is secured using JWT authentication, ensuring that only authorized users can access and modify task-related information. Additionally, the dashboard includes data visualization features to provide managers with insights into team productivity and task completion rates. Keywords— Task Management, Dashboard, Task Tracking, Data Visualization, JWT Authentication.
{"title":"Track Maven","authors":"Adarsh Trivedi","doi":"10.55041/ijsrem34493","DOIUrl":"https://doi.org/10.55041/ijsrem34493","url":null,"abstract":"Track Maven is a web application designed to streamline task management processes within organizations. Track Maven aims to provide a centralized platform for managing tasks, enabling efficient task assignment, monitoring, and tracking. The dashboard offers a user-friendly interface for creating, updating, and deleting tasks, as well as assigning tasks to specific teams or individuals. It also includes features for monitoring task completion status and generating reports to track team performance. The project utilizes React for the frontend interface, Node.js and Express.js for the backend server, and MongoDB as the database. The application is secured using JWT authentication, ensuring that only authorized users can access and modify task-related information. Additionally, the dashboard includes data visualization features to provide managers with insights into team productivity and task completion rates. Keywords— Task Management, Dashboard, Task Tracking, Data Visualization, JWT Authentication.","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":"141112965","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 role played by email communication in our lives nowadays has been such a tremendous one especially when it comes to fast exchange of information. Nevertheless, this convenience is marred by the omnipresent threat of email spam that not only disrupts channels of communication but also present serious security and privacy concerns. Traditional models of spam detection which are based on rules or heuristics tend to fail because they do not adapt quickly enough to the new techniques employed by spammers. In response to these challenges, this paper proposes an inventive solution to the problem—integration of blockchain technology into the process of detecting email spams.Email spam is often defined as an unwanted and usually malicious form of correspondence, thus it has continued being a notable cyber security worry. The conventional mechanisms for discovering them are prone to false positives and negatives at times. Additionally, such systems have centralized data which can be interfered with and accessed without permission. Weighing up the limitations inherent in existing methods, this research examines how blockchain may change email spam detection. Keywords— Blockchain technology, ethereum, Spam, email
{"title":"Spam Mail Detection Using Blockchai","authors":"Niraj patil","doi":"10.55041/ijsrem34520","DOIUrl":"https://doi.org/10.55041/ijsrem34520","url":null,"abstract":"The role played by email communication in our lives nowadays has been such a tremendous one especially when it comes to fast exchange of information. Nevertheless, this convenience is marred by the omnipresent threat of email spam that not only disrupts channels of communication but also present serious security and privacy concerns. Traditional models of spam detection which are based on rules or heuristics tend to fail because they do not adapt quickly enough to the new techniques employed by spammers. In response to these challenges, this paper proposes an inventive solution to the problem—integration of blockchain technology into the process of detecting email spams.Email spam is often defined as an unwanted and usually malicious form of correspondence, thus it has continued being a notable cyber security worry. The conventional mechanisms for discovering them are prone to false positives and negatives at times. Additionally, such systems have centralized data which can be interfered with and accessed without permission. Weighing up the limitations inherent in existing methods, this research examines how blockchain may change email spam detection. Keywords— Blockchain technology, ethereum, Spam, email","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":"141113090","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 report is set to give an interactive visualization and analytical presentation for Meteorological records in Finland. These Meteorological records Data of Finland is recorded by way of integrating the three current infrastructures for numerical weather prediction, observational information and satellite tv for pc image processing and this is recorded. The Meteorological data used in the study consists of near- floor atmospheric elements including wind direction, apparent temperature, cloud layer(s), ceiling peak, visibility, current weather, wind velocity, cloud cowl and precipitation amount and so on. The data consists of hourly recorded data for the past ten years of Finland from 2006-04- 01 at time 00:00:00.000 to 2016-09-09 at time 23:00:00.000. The analysis had been performed out for 2-m floor temperature. Through this analysis, all the valuable insights into the changing weather patterns and environmental conditions in Finland are analyzed and presented in an interactive visualization, providing a solid foundation for understanding and addressing the impacts of Global Warming in the region. This project main objective is to show the complete analysis of the influences of the Global Warming on the Apparent temperature & humidity in Finland over the course of 10 years from 2006 to 2016. Keywords — Data Analysis, Data Visualization, Meteorological Data, Climate Change, Global Warning, Apparent Temperature, Humidity
{"title":"DATA ANALYSIS OF METROLOGICAL DATA","authors":"Divyam Parhwal","doi":"10.55041/ijsrem34399","DOIUrl":"https://doi.org/10.55041/ijsrem34399","url":null,"abstract":"This project report is set to give an interactive visualization and analytical presentation for Meteorological records in Finland. These Meteorological records Data of Finland is recorded by way of integrating the three current infrastructures for numerical weather prediction, observational information and satellite tv for pc image processing and this is recorded. The Meteorological data used in the study consists of near- floor atmospheric elements including wind direction, apparent temperature, cloud layer(s), ceiling peak, visibility, current weather, wind velocity, cloud cowl and precipitation amount and so on. The data consists of hourly recorded data for the past ten years of Finland from 2006-04- 01 at time 00:00:00.000 to 2016-09-09 at time 23:00:00.000. The analysis had been performed out for 2-m floor temperature. Through this analysis, all the valuable insights into the changing weather patterns and environmental conditions in Finland are analyzed and presented in an interactive visualization, providing a solid foundation for understanding and addressing the impacts of Global Warming in the region. This project main objective is to show the complete analysis of the influences of the Global Warming on the Apparent temperature & humidity in Finland over the course of 10 years from 2006 to 2016. Keywords — Data Analysis, Data Visualization, Meteorological Data, Climate Change, Global Warning, Apparent Temperature, Humidity","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":"141112307","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}
A unique platform that connects people worldwide and at the same time brings truckloads of information on almost anything you can imagine. People make sites to find their lost love and end up connecting millions (heard of Orkut?), brand owners can listen to thousands of customers from around the globe without moving from their chair (seen Twitter?), NGO's run campaigns to motivate people to vote (Jagore.com) ... these are just a few examples of internet's growing reality in today's world.
{"title":"INTERNET MARKETING","authors":"Nisha Gurunath Vishe,","doi":"10.55041/ijsrem34416","DOIUrl":"https://doi.org/10.55041/ijsrem34416","url":null,"abstract":"A unique platform that connects people worldwide and at the same time brings truckloads of information on almost anything you can imagine. People make sites to find their lost love and end up connecting millions (heard of Orkut?), brand owners can listen to thousands of customers from around the globe without moving from their chair (seen Twitter?), NGO's run campaigns to motivate people to vote (Jagore.com) ... these are just a few examples of internet's growing reality in today's world.","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":"141112886","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 this research, we propose a novel approach for detecting and explaining deepfake images using deep learning techniques. Our method utilizes a combination of face detection, feature extraction, and attention visualization to provide insights into the authenticity of facial images. We employ the Multi-Task Cascaded Convolutional Neural Network (MTCNN) for accurate face detection and the InceptionResnetV1 architecture pretrained on the VGGFace2 dataset for feature extraction. The model is further enhanced with GradCAM, a gradient-based visualization technique, to highlight the regions of the input image contributing most to the classification decision. Our approach offers interpretable explanations by overlaying attention maps onto the original images, enabling users to understand the model's decision-making process. Experimental results demonstrate the effectiveness and interpretability of our method in detecting deepfake images and providing insightful explanations, contributing to the advancement of deepfake detection research. Keywords: - python, python libraries, Mtcnn, InceptionResnetV1,Gradio
{"title":"Manipulated Face Detection System Using Deep Learning","authors":"Prof. Bireshwar Ganguly","doi":"10.55041/ijsrem34458","DOIUrl":"https://doi.org/10.55041/ijsrem34458","url":null,"abstract":"In this research, we propose a novel approach for detecting and explaining deepfake images using deep learning techniques. Our method utilizes a combination of face detection, feature extraction, and attention visualization to provide insights into the authenticity of facial images. We employ the Multi-Task Cascaded Convolutional Neural Network (MTCNN) for accurate face detection and the InceptionResnetV1 architecture pretrained on the VGGFace2 dataset for feature extraction. The model is further enhanced with GradCAM, a gradient-based visualization technique, to highlight the regions of the input image contributing most to the classification decision. Our approach offers interpretable explanations by overlaying attention maps onto the original images, enabling users to understand the model's decision-making process. Experimental results demonstrate the effectiveness and interpretability of our method in detecting deepfake images and providing insightful explanations, contributing to the advancement of deepfake detection research. Keywords: - python, python libraries, Mtcnn, InceptionResnetV1,Gradio","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":"141110549","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 paper presents a novel approach to improving information accessibility for physically impaired individuals, specifically those with hearing impairments, through the development and implementation of a sign language detection system. The system leverages state-of-the-art machine learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), combined with advanced computer vision techniques to accurately recognize and interpret sign language gestures in real-time. This technology is designed to bridge the communication gap by converting recognized gestures into text or spoken language, thereby facilitating access to a wide range of digital information and communication platforms.
{"title":"ACCESSING INFORMATION FOR PHYSICALLY IMPAIRED PERSONS USING SIGN LANGUAGE DETECTION SYSTEM","authors":".Karthikeyan V.K","doi":"10.55041/ijsrem34415","DOIUrl":"https://doi.org/10.55041/ijsrem34415","url":null,"abstract":"This paper presents a novel approach to improving information accessibility for physically impaired individuals, specifically those with hearing impairments, through the development and implementation of a sign language detection system. The system leverages state-of-the-art machine learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), combined with advanced computer vision techniques to accurately recognize and interpret sign language gestures in real-time. This technology is designed to bridge the communication gap by converting recognized gestures into text or spoken language, thereby facilitating access to a wide range of digital information and communication platforms.","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":"141111243","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 Cool Guru is a brick-and-mortar establishment that has been repurposed into a fulfillment center. These distribution hubs are not accessible to the general public, allowing for ample inventory space and efficient order fulfillment. Cool Gurus offer an extensive and ever-expanding array of resources, enabling customers to purchase products online with options for same-day delivery or even within hours, as well as in-store pickup. While the concept is not novel, various companies, including Whole Foods, Walmart, Target, Bed Bath & Beyond, and numerous major clothing retailers, have employed similar strategies. However, with brick-and-mortar stores facing challenges during closures, the prevalence of Cool Gurus has surged. Our team is currently developing a Cool Guru utilizing NLP technology to analyze real-time customer feedback and sentiment, enabling us to automate product ranking and enhance customer satisfaction. Keywords: Cool Guru, brick-and-mortar, lockdown, shoppers, Bed Bath & Beyond, Natural Language Processing, Sentiment Analysis.
{"title":"CoolGuru E-Commerce Website using Sentiment Analysis Prediction","authors":"Abhishek Rajbhar","doi":"10.55041/ijsrem34320","DOIUrl":"https://doi.org/10.55041/ijsrem34320","url":null,"abstract":"The Cool Guru is a brick-and-mortar establishment that has been repurposed into a fulfillment center. These distribution hubs are not accessible to the general public, allowing for ample inventory space and efficient order fulfillment. Cool Gurus offer an extensive and ever-expanding array of resources, enabling customers to purchase products online with options for same-day delivery or even within hours, as well as in-store pickup. While the concept is not novel, various companies, including Whole Foods, Walmart, Target, Bed Bath & Beyond, and numerous major clothing retailers, have employed similar strategies. However, with brick-and-mortar stores facing challenges during closures, the prevalence of Cool Gurus has surged. Our team is currently developing a Cool Guru utilizing NLP technology to analyze real-time customer feedback and sentiment, enabling us to automate product ranking and enhance customer satisfaction. Keywords: Cool Guru, brick-and-mortar, lockdown, shoppers, Bed Bath & Beyond, Natural Language Processing, Sentiment Analysis.","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":"141108637","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}
As computing power increases, "deep fakes," or films that seem like they were created by a real person, are becoming feasible thanks to deep learning algorithms. Political instability, terrorism, revenge porn, or extortion can be the motivation for these lifelike face swapped deep fakes. This research presents a novel deep learning system that can recognize the difference between real and AI-generated films.We have developed a method that can identify deep fake replacements and reenactments automatically. We're using AI to combat AI. Our system's Res-Next Convolution neural network retrieves properties at the frame level. A recurrent neural network (RNN) trained using long short-term memory (LSTM) characteristics can distinguish between deep films and regular movies. On big, balanced, and mixed datasets, our technique is tested by Face-Forensic++ [1], Deepfake Detection Challenge [2], and Celeb-DF [3]. The quality of real-time data is enhanced by this. We prove that our technology consistently outperforms the competitors. Computer vision, Res-Next Convolution neural network, RNN, and LSTM are some of the index phrases.
{"title":"DEEPFAKE DETECTION USING LSTM & RESNEXT-50 1","authors":"M. Sm","doi":"10.55041/ijsrem34528","DOIUrl":"https://doi.org/10.55041/ijsrem34528","url":null,"abstract":"As computing power increases, \"deep fakes,\" or films that seem like they were created by a real person, are becoming feasible thanks to deep learning algorithms. Political instability, terrorism, revenge porn, or extortion can be the motivation for these lifelike face swapped deep fakes. This research presents a novel deep learning system that can recognize the difference between real and AI-generated films.We have developed a method that can identify deep fake replacements and reenactments automatically. We're using AI to combat AI. Our system's Res-Next Convolution neural network retrieves properties at the frame level. A recurrent neural network (RNN) trained using long short-term memory (LSTM) characteristics can distinguish between deep films and regular movies. On big, balanced, and mixed datasets, our technique is tested by Face-Forensic++ [1], Deepfake Detection Challenge [2], and Celeb-DF [3]. The quality of real-time data is enhanced by this. We prove that our technology consistently outperforms the competitors. Computer vision, Res-Next Convolution neural network, RNN, and LSTM are some of the index phrases.","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":"141110482","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}
Soil stabilization techniques play a crucial role in enhancing the engineering properties of soils, ensuring their suitability for various construction applications. This review paper synthesizes the findings from multiple studies on soil stabilization methods and their effectiveness in improving soil characteristics. A comprehensive comparison of different stabilization techniques, including traditional methods like cement and lime stabilization, as well as modern approaches utilizing materials such as fly ash, coal bottom ash, and ground granulated blast-furnace slag (GGBS), is presented. The review examines the impact of these techniques on soil strength, moisture content, and swelling behavior. Additionally, innovative approaches such as microbial-induced carbonate precipitation and chemical grouting with polymers are explored for their potential in soil stabilization. The paper also discusses the environmental implications and economic feasibility of various stabilization methods. Through a thorough analysis of the literature, this review aims to provide insights into the selection and application of soil stabilization techniques based on specific soil conditions and project requirements. Keywords— Soil stabilization, ground improvement, engineering properties, traditional methods, modern techniques, environmental impact, economic feasibility.
{"title":"A Brief Review on Soil Stabilization Techniques","authors":"Avinash A Rakh","doi":"10.55041/ijsrem34435","DOIUrl":"https://doi.org/10.55041/ijsrem34435","url":null,"abstract":"Soil stabilization techniques play a crucial role in enhancing the engineering properties of soils, ensuring their suitability for various construction applications. This review paper synthesizes the findings from multiple studies on soil stabilization methods and their effectiveness in improving soil characteristics. A comprehensive comparison of different stabilization techniques, including traditional methods like cement and lime stabilization, as well as modern approaches utilizing materials such as fly ash, coal bottom ash, and ground granulated blast-furnace slag (GGBS), is presented. The review examines the impact of these techniques on soil strength, moisture content, and swelling behavior. Additionally, innovative approaches such as microbial-induced carbonate precipitation and chemical grouting with polymers are explored for their potential in soil stabilization. The paper also discusses the environmental implications and economic feasibility of various stabilization methods. Through a thorough analysis of the literature, this review aims to provide insights into the selection and application of soil stabilization techniques based on specific soil conditions and project requirements. Keywords— Soil stabilization, ground improvement, engineering properties, traditional methods, modern techniques, environmental impact, economic feasibility.","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":"141109546","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 concept of a "smart home" is rapidly gaining popularity among homeowners worldwide, and it's all thanks to the integration of WiFi connectivity. Smart home automation systems driven by WiFi offer exciting new possibilities for enhancing our living spaces, from increased comfort and convenience to greater energy efficiency and sustainability. By leveraging the power of WiFi, smart home automation systems enable us to remotely monitor and manage various aspects of our homes using smartphones, tablets, or other internet-enabled devices. Plus, these systems are designed to seamlessly communicate and integrate across different manufacturers and platforms, making it easier than ever to customize your living space to suit your needs. But the benefits of smart home automation systems go beyond mere convenience. They also have the potential to significantly reduce our energy consumption, minimize waste, and contribute to a more sustainable future. At the same time, integrated sensors, cameras, and motion detectors can enhance our home security and safety, providing peace of mind and mitigating risks associated with burglary, fire, or other hazards. Ofcourse, there are some challenges and considerations to keep in mind when it comes to WiFi-enabled smart home automation systems. Privacy and data security are top concerns, and interoperability and compatibility issues must be addressed to ensure that these systems remain flexible and adaptable to the evolving needs and preferences of homeowners. Additionally, user-friendly interfaces and intuitive design principles are essential for ensuring a positive and enjoyable experience. In this research paper, we aim to explore the transformative potential of WiFi-enabled smart home automation systems and provide constructive insights into how we can overcome the challenges and considerations associated with this technology. By shedding light on the opportunities, challenges, and best practices associated with these systems, we hope to empower homeowners, policymakers, and industry stakeholders alike to make informed decisions that enhance the quality of life while safeguarding privacy, security, and sustainability.
{"title":"Smart Home Automation System Using Wi-Fi","authors":"Aditya Kumar Jha ,","doi":"10.55041/ijsrem34110","DOIUrl":"https://doi.org/10.55041/ijsrem34110","url":null,"abstract":"The concept of a \"smart home\" is rapidly gaining popularity among homeowners worldwide, and it's all thanks to the integration of WiFi connectivity. Smart home automation systems driven by WiFi offer exciting new possibilities for enhancing our living spaces, from increased comfort and convenience to greater energy efficiency and sustainability. By leveraging the power of WiFi, smart home automation systems enable us to remotely monitor and manage various aspects of our homes using smartphones, tablets, or other internet-enabled devices. Plus, these systems are designed to seamlessly communicate and integrate across different manufacturers and platforms, making it easier than ever to customize your living space to suit your needs. But the benefits of smart home automation systems go beyond mere convenience. They also have the potential to significantly reduce our energy consumption, minimize waste, and contribute to a more sustainable future. At the same time, integrated sensors, cameras, and motion detectors can enhance our home security and safety, providing peace of mind and mitigating risks associated with burglary, fire, or other hazards. Ofcourse, there are some challenges and considerations to keep in mind when it comes to WiFi-enabled smart home automation systems. Privacy and data security are top concerns, and interoperability and compatibility issues must be addressed to ensure that these systems remain flexible and adaptable to the evolving needs and preferences of homeowners. Additionally, user-friendly interfaces and intuitive design principles are essential for ensuring a positive and enjoyable experience. In this research paper, we aim to explore the transformative potential of WiFi-enabled smart home automation systems and provide constructive insights into how we can overcome the challenges and considerations associated with this technology. By shedding light on the opportunities, challenges, and best practices associated with these systems, we hope to empower homeowners, policymakers, and industry stakeholders alike to make informed decisions that enhance the quality of life while safeguarding privacy, security, and sustainability.","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":"141112775","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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