Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150981
K. Kumar, Rikendra
The requirement for producing food is rising as the world's population rises. The decline of the workforce in rural areas and the rise in production costs are other issues the food industry is currently dealing with. The Internet of Things (IoT) could be used in "smart farming," a concept in farm management that aims to address the current issues in food production. This emerging paradigm aims to connect various intelligent physical elements in order to modernise various domains. Numerous IoT-based frameworks have been developed to manage and track agricultural lands automatically and with the least amount of human involvement. Based on statistical and quantitative methods, the current agricultural system can be revolutionised more effectively. In a green field, one can also encounter irrigation, plant diseases, different crop stages, and drone activation from IoT. The discussion of how IoT uses sensors for a variety of purposes. The main objective of this research is to create cutting-edge IoT tools and concepts for modern agricultural practises. Systematic evaluation provides information on current and future trends in the agricultural sector..
{"title":"Recent advancements of Internet of Things in Precision Agriculture: A Review","authors":"K. Kumar, Rikendra","doi":"10.1109/ICDT57929.2023.10150981","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150981","url":null,"abstract":"The requirement for producing food is rising as the world's population rises. The decline of the workforce in rural areas and the rise in production costs are other issues the food industry is currently dealing with. The Internet of Things (IoT) could be used in \"smart farming,\" a concept in farm management that aims to address the current issues in food production. This emerging paradigm aims to connect various intelligent physical elements in order to modernise various domains. Numerous IoT-based frameworks have been developed to manage and track agricultural lands automatically and with the least amount of human involvement. Based on statistical and quantitative methods, the current agricultural system can be revolutionised more effectively. In a green field, one can also encounter irrigation, plant diseases, different crop stages, and drone activation from IoT. The discussion of how IoT uses sensors for a variety of purposes. The main objective of this research is to create cutting-edge IoT tools and concepts for modern agricultural practises. Systematic evaluation provides information on current and future trends in the agricultural sector..","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127313326","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151182
K. C, B. Devi, L. Maguluri, Mahaveer Singh Naruka
The classification of real time images from the fast data capturing devices in Internet of Things (IoT) environment is a critical task. It requires suitable processing and development of a model for increased accuracy in classifying the objects in real-time. Therefore, the necessity in improving the accuracy of classifying the instances is needed post performing the modelling, building and development of a model. In this paper, a three-dimensional (3D) Convolutional Neural Network (CNN) is developed to increase the process of classification for the objects in the real-time environment. The objects needed to train the classifier is supplied and the model is built in python environment. The results show an increased classification accuracy in detecting multi-objectives than the state-of-art models.
{"title":"3D-CNN Architecture to Improve the Classification Accuracy of the Real-Time Images from IOT Devices","authors":"K. C, B. Devi, L. Maguluri, Mahaveer Singh Naruka","doi":"10.1109/ICDT57929.2023.10151182","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151182","url":null,"abstract":"The classification of real time images from the fast data capturing devices in Internet of Things (IoT) environment is a critical task. It requires suitable processing and development of a model for increased accuracy in classifying the objects in real-time. Therefore, the necessity in improving the accuracy of classifying the instances is needed post performing the modelling, building and development of a model. In this paper, a three-dimensional (3D) Convolutional Neural Network (CNN) is developed to increase the process of classification for the objects in the real-time environment. The objects needed to train the classifier is supplied and the model is built in python environment. The results show an increased classification accuracy in detecting multi-objectives than the state-of-art models.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129610286","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150475
Kapil Yadav, Nipun Bansal
Clickbait is a type of providing false content, intended to attract a variety of users and get engagement and monetary benefits. It makes users curious to click the link and follow the content in various formats like audio, video, text, and images. Clickbait detection is a critical and difficult task. Many researchers have proposed various techniques using deep learning techniques and machine learning techniques like Logistic Regres- sion, Linear Support Vector Machine, Adaboost, Multilayer Per- ceptron, Random Forest, Convolution Neural Networks(CNN), and Recurrent Convolutional Neural Networks (RCNN). To give a clear overview of the efficient algorithms, we went through some existing studies from 2016–2022, which proposed various clickbait detection methods. This review gives an exhaustive study of existing methods and also suggests some recommendations for further enhancements to be done by combining the various deep learning techniques and machine learning techniques.
{"title":"A Comparative Study on Clickbait Detection using Machine Learning Based Methods","authors":"Kapil Yadav, Nipun Bansal","doi":"10.1109/ICDT57929.2023.10150475","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150475","url":null,"abstract":"Clickbait is a type of providing false content, intended to attract a variety of users and get engagement and monetary benefits. It makes users curious to click the link and follow the content in various formats like audio, video, text, and images. Clickbait detection is a critical and difficult task. Many researchers have proposed various techniques using deep learning techniques and machine learning techniques like Logistic Regres- sion, Linear Support Vector Machine, Adaboost, Multilayer Per- ceptron, Random Forest, Convolution Neural Networks(CNN), and Recurrent Convolutional Neural Networks (RCNN). To give a clear overview of the efficient algorithms, we went through some existing studies from 2016–2022, which proposed various clickbait detection methods. This review gives an exhaustive study of existing methods and also suggests some recommendations for further enhancements to be done by combining the various deep learning techniques and machine learning techniques.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126250219","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150639
Juhi Singh, Kritika Jaiswal, Minal Singh, Muskan Sama, Swasti Singhal
Market segmentation is an approach whose aim is to identify and outline the market segments on which an organization can target for its marketing plans. Market Segmentation is used not only for selling a commodity and various services but also plays a crucial role in meeting the customer’s needs because without customers there is no business. So satisfying a customer’s need is really important and hence the need for market segmentation. The general objective of this research service is to analyze various factors which influence the student’s admission process in various private institutions. Various factors like teaching staff, quality of education, and facilities play an important role in influencing students while selecting a college or university. But as Technology is increasing, we can say digital advertisement also plays an important role in luring a student to select a particular college/university through various online platforms such as websites, emails, etc., and just like that several factors need consideration. So the main aim of this research is to analyze all the factors and their broad segments which can be used by various higher education managers to develop strategies and customize their plans for making their businesses more profitable. A student survey allows students to share their issues, needs, and desires, giving feedback on how a teacher can change his or her instruction to help them perform better in class. By implementing certain measures, it is possible to enhance student engagement and motivation, resulting in better academic outcomes and higher levels of student achievement.
{"title":"Market segmentation using ML","authors":"Juhi Singh, Kritika Jaiswal, Minal Singh, Muskan Sama, Swasti Singhal","doi":"10.1109/ICDT57929.2023.10150639","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150639","url":null,"abstract":"Market segmentation is an approach whose aim is to identify and outline the market segments on which an organization can target for its marketing plans. Market Segmentation is used not only for selling a commodity and various services but also plays a crucial role in meeting the customer’s needs because without customers there is no business. So satisfying a customer’s need is really important and hence the need for market segmentation. The general objective of this research service is to analyze various factors which influence the student’s admission process in various private institutions. Various factors like teaching staff, quality of education, and facilities play an important role in influencing students while selecting a college or university. But as Technology is increasing, we can say digital advertisement also plays an important role in luring a student to select a particular college/university through various online platforms such as websites, emails, etc., and just like that several factors need consideration. So the main aim of this research is to analyze all the factors and their broad segments which can be used by various higher education managers to develop strategies and customize their plans for making their businesses more profitable. A student survey allows students to share their issues, needs, and desires, giving feedback on how a teacher can change his or her instruction to help them perform better in class. By implementing certain measures, it is possible to enhance student engagement and motivation, resulting in better academic outcomes and higher levels of student achievement.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122646657","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151445
Sparsh Singh, Vidit Kumar, Zaid K. Ahmed, Kajol Mittal
Recent years have seen a substantial increase in study on air pollution as a result of its negative ramifications It is also acknowledged as one in the current atmosphere. one of the main risk elements. Accurate air quality assessment is the first stage in the implementation of air pollution control systems, which helps in the growth of developed nations' economies and societies. the two methodical Accurate air quality predictions are essential for emissions control, public health, and wellbeing. The metropolis of India, Delhi, has been the most polluted metropolis in the world for the past two years. In this study, the results have been compared using SARIMAX, Prophet, and LSTM are three distinct machine learning algorithms that were tested against one another. The same quantity of parameter calibration was applied to all the models, and SARIMAX seems to be more reliable out of the three.
{"title":"Delhi Air Pollution Prediction: A Comparative Analysis using Time Series Forecasting","authors":"Sparsh Singh, Vidit Kumar, Zaid K. Ahmed, Kajol Mittal","doi":"10.1109/ICDT57929.2023.10151445","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151445","url":null,"abstract":"Recent years have seen a substantial increase in study on air pollution as a result of its negative ramifications It is also acknowledged as one in the current atmosphere. one of the main risk elements. Accurate air quality assessment is the first stage in the implementation of air pollution control systems, which helps in the growth of developed nations' economies and societies. the two methodical Accurate air quality predictions are essential for emissions control, public health, and wellbeing. The metropolis of India, Delhi, has been the most polluted metropolis in the world for the past two years. In this study, the results have been compared using SARIMAX, Prophet, and LSTM are three distinct machine learning algorithms that were tested against one another. The same quantity of parameter calibration was applied to all the models, and SARIMAX seems to be more reliable out of the three.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024708","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151418
Ramakrishna M M, Nageswara Rao Atyam, Nikhil Chaurasia, L. Senthamil, Mohd Asif Shah, V. L. Raja
There are many vehicle exchanges around the world are using the manual transmission and automatic transmission are the most popular. At this time, many popular manufacturers have started using the robot version in their new products. The gearbox of the robot is, in fact, mechanical; it has an additional automatic clutch and gear shift. Accordingly, the operation of the transmission is not completely dependent on the driver, as in other options, but on the electronic control unit. For the proper functioning of the transmission the driver needs to correctly transmit only the incoming information. In this paper an automation innovation was proposed to control the vehicle gear shifting functions by using the machine learning based on the robotic operation model. An automaton or robot, after some time, must first learn the device of a new invention. The automatic gearbox received a friction type clutch. It is a disk set or a built-in separate mechanism. The most reliable and durable design can be called the double clutch design.
{"title":"An Automation Innovation of Gearbox Vehicle Control by Using Machine Learning Based Robotic Operation","authors":"Ramakrishna M M, Nageswara Rao Atyam, Nikhil Chaurasia, L. Senthamil, Mohd Asif Shah, V. L. Raja","doi":"10.1109/ICDT57929.2023.10151418","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151418","url":null,"abstract":"There are many vehicle exchanges around the world are using the manual transmission and automatic transmission are the most popular. At this time, many popular manufacturers have started using the robot version in their new products. The gearbox of the robot is, in fact, mechanical; it has an additional automatic clutch and gear shift. Accordingly, the operation of the transmission is not completely dependent on the driver, as in other options, but on the electronic control unit. For the proper functioning of the transmission the driver needs to correctly transmit only the incoming information. In this paper an automation innovation was proposed to control the vehicle gear shifting functions by using the machine learning based on the robotic operation model. An automaton or robot, after some time, must first learn the device of a new invention. The automatic gearbox received a friction type clutch. It is a disk set or a built-in separate mechanism. The most reliable and durable design can be called the double clutch design.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130837327","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150606
Muhamad Hariz Muhamad Adnan, Siti Fatimah Mohamed, Nurul Fazilah Ahmad, Nurul Naqibah Binti Annual, Satria Abadi, N. M. Husain
This study presents an artificial intelligence-powered online platform that can help aspiring digital entrepreneurs improve their digital skills, organise their finances, and recognise their multiple intelligences. The platform uses an artificial intelligence-based algorithm, namely double auction for optimization, to provide aspiring digital entrepreneurs with a one-stop shop for learning and development. The research was conducted using the following methodology: Literature review, requirements elicitation, platform design and development, user testing, evaluation, and refinement. The results of the evaluation show that the platform has the potential to strengthen the environment for digital entrepreneurship.
{"title":"AI Meets Entrepreneurship: A Framework of Web Platform for Enhancing Skills, Streamlining Finance and Identifying Multiple Intelligence","authors":"Muhamad Hariz Muhamad Adnan, Siti Fatimah Mohamed, Nurul Fazilah Ahmad, Nurul Naqibah Binti Annual, Satria Abadi, N. M. Husain","doi":"10.1109/ICDT57929.2023.10150606","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150606","url":null,"abstract":"This study presents an artificial intelligence-powered online platform that can help aspiring digital entrepreneurs improve their digital skills, organise their finances, and recognise their multiple intelligences. The platform uses an artificial intelligence-based algorithm, namely double auction for optimization, to provide aspiring digital entrepreneurs with a one-stop shop for learning and development. The research was conducted using the following methodology: Literature review, requirements elicitation, platform design and development, user testing, evaluation, and refinement. The results of the evaluation show that the platform has the potential to strengthen the environment for digital entrepreneurship.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131207219","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151367
Isha Gupta, Manasvi Jain, P. Johri
Through technological changes, data science and artificial intelligence are altering the world. One of the most significant uses of machine learning is the classification of people based on their personality features. We can see many applications of machine learning in our daily lives. Each individual on the world has a distinct personality type. Targeting particular demographics has made it possible to make marketing campaigns more effective. This is made possible by the availability of high-dimensional data. Such personality-based promotions are quite effective at raising brand awareness and enhancing the appeal of goods and services. Using the Big Five personality traits, we created a system for predicting personality. Every day, a large number of students take competitive exams with a strong personality component. These tests' primary goal is to evaluate the student's talents and personality. Writing the personality test and assessing the subject's personality are made easier by this initiative. The person can view their personality type and make improvements to their personality depending on the results of the personality classification. In our paper, we tried to combine phrase frequency algorithm to determine a person's talent and personality prediction utilizing ML algorithms like KNN, CNN, and Logistic regression to predict a person's personality. From this model or system, users can quickly determine his personality and level of technical proficiency.
{"title":"Smart-Hire Personality Prediction Using ML","authors":"Isha Gupta, Manasvi Jain, P. Johri","doi":"10.1109/ICDT57929.2023.10151367","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151367","url":null,"abstract":"Through technological changes, data science and artificial intelligence are altering the world. One of the most significant uses of machine learning is the classification of people based on their personality features. We can see many applications of machine learning in our daily lives. Each individual on the world has a distinct personality type. Targeting particular demographics has made it possible to make marketing campaigns more effective. This is made possible by the availability of high-dimensional data. Such personality-based promotions are quite effective at raising brand awareness and enhancing the appeal of goods and services. Using the Big Five personality traits, we created a system for predicting personality. Every day, a large number of students take competitive exams with a strong personality component. These tests' primary goal is to evaluate the student's talents and personality. Writing the personality test and assessing the subject's personality are made easier by this initiative. The person can view their personality type and make improvements to their personality depending on the results of the personality classification. In our paper, we tried to combine phrase frequency algorithm to determine a person's talent and personality prediction utilizing ML algorithms like KNN, CNN, and Logistic regression to predict a person's personality. From this model or system, users can quickly determine his personality and level of technical proficiency.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127497076","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151184
K. Kaswan, Jagjit Singh Dhatterwal, Naresh Kumar, Shashank Awasthi, S. Chauhan
scientific research will increasingly rely on AI and the cloud in the future; our suggested solution will allow us to use these technologies to solve a number of problems (CC). We have outlined the different issues that may be addressed via the combined efforts of cloud computing and AI and discussed how to implement such an approach. One of the most powerful exploration techniques is, for example, using cloud-based artificial intelligence algorithms to increase productivity. Drive to create apps, manufactured in the cloud, beyond the fundamental automation pro, requires the ability to predict scenarios and make continuous decisions online. In this paper, we describe a programming language for intelligent computing that will enable machines to reason and make choices for themselves, in real time.
{"title":"Real-Time Decision-Making Techniques using Artificial Intelligence and Cloud Computing","authors":"K. Kaswan, Jagjit Singh Dhatterwal, Naresh Kumar, Shashank Awasthi, S. Chauhan","doi":"10.1109/ICDT57929.2023.10151184","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151184","url":null,"abstract":"scientific research will increasingly rely on AI and the cloud in the future; our suggested solution will allow us to use these technologies to solve a number of problems (CC). We have outlined the different issues that may be addressed via the combined efforts of cloud computing and AI and discussed how to implement such an approach. One of the most powerful exploration techniques is, for example, using cloud-based artificial intelligence algorithms to increase productivity. Drive to create apps, manufactured in the cloud, beyond the fundamental automation pro, requires the ability to predict scenarios and make continuous decisions online. In this paper, we describe a programming language for intelligent computing that will enable machines to reason and make choices for themselves, in real time.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126625438","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}
Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151217
K. Kumar, P. C. Vashist, Atharva Sharma, Kavya Sharma, Achintya Kaushal Jha
The paper proposes a real-time attendance capturing system that uses a two-step authentication process and is based on the user’s location using GPS. The proposed system is implemented as an Android mobile application that communicates with the real-time location of the user and allows the user to mark attendance using the in- built camera of the smartphone. Once the attendance is marked, the application updates the database with the time stamp of the provisional attendance to keep a record of the time difference between provisional and final attendance. The proposed system does not require any auxiliary equipment except for a smartphone, which reduces the computation time and cost of placing redundant equipment. The two-step authentication process involves both location-based service and facial recognition to avoid proxy attendances.
{"title":"A Real-Time Attendance Capturing System Using 2-Step Authentication","authors":"K. Kumar, P. C. Vashist, Atharva Sharma, Kavya Sharma, Achintya Kaushal Jha","doi":"10.1109/ICDT57929.2023.10151217","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151217","url":null,"abstract":"The paper proposes a real-time attendance capturing system that uses a two-step authentication process and is based on the user’s location using GPS. The proposed system is implemented as an Android mobile application that communicates with the real-time location of the user and allows the user to mark attendance using the in- built camera of the smartphone. Once the attendance is marked, the application updates the database with the time stamp of the provisional attendance to keep a record of the time difference between provisional and final attendance. The proposed system does not require any auxiliary equipment except for a smartphone, which reduces the computation time and cost of placing redundant equipment. The two-step authentication process involves both location-based service and facial recognition to avoid proxy attendances.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121747651","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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