Pub Date : 2023-04-29DOI: 10.5121/ijitcs.2023.13201
R. P, C. S, Pavithra H, P. K, Nehal Chakravarthy M D, Shivaraj B Karegera
A rapid growth in the population and economic growth has resulted in an increasing number of vehicles on road every year. Traffic congestion is a big problem in every metropolitan city. To reach their destination faster and to avoid traffic, some people are violating traffic rules and regulations. Violation of traffic rules puts everyone in danger. Maintaining traffic rules manually has become difficult over the time due to the rapid increase in the population. This alarming situation has be taken care of at the earliest. To overcome this, we need a real-time violation detection system to help maintain the traffic rules. The approach is to detect traffic violations in real-time using edge computing, which reduces the time to detect. Different machine learning models and algorithms were applied to detect traffic violations like traveling without a helmet, line crossing, parking violation detection, violating the one-way rule etc. The model implemented gave an accuracy of around 85%, due to memory constraints of the edge device in this case NVIDIA Jetson Nano, as the fps is quite low.
{"title":"APPLICATION OF VARIOUS DEEP LEARNING MODELS FOR AUTOMATIC TRAFFIC VIOLATION DETECTION USING EDGE COMPUTING","authors":"R. P, C. S, Pavithra H, P. K, Nehal Chakravarthy M D, Shivaraj B Karegera","doi":"10.5121/ijitcs.2023.13201","DOIUrl":"https://doi.org/10.5121/ijitcs.2023.13201","url":null,"abstract":"A rapid growth in the population and economic growth has resulted in an increasing number of vehicles on road every year. Traffic congestion is a big problem in every metropolitan city. To reach their destination faster and to avoid traffic, some people are violating traffic rules and regulations. Violation of traffic rules puts everyone in danger. Maintaining traffic rules manually has become difficult over the time due to the rapid increase in the population. This alarming situation has be taken care of at the earliest. To overcome this, we need a real-time violation detection system to help maintain the traffic rules. The approach is to detect traffic violations in real-time using edge computing, which reduces the time to detect. Different machine learning models and algorithms were applied to detect traffic violations like traveling without a helmet, line crossing, parking violation detection, violating the one-way rule etc. The model implemented gave an accuracy of around 85%, due to memory constraints of the edge device in this case NVIDIA Jetson Nano, as the fps is quite low.","PeriodicalId":418938,"journal":{"name":"International Journal of Information Technology Convergence and Services","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130317307","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 : 2022-02-28DOI: 10.5121/ijitcs.2022.12101
Mohamed El Merroun
The decline of environmental sustainability is undoubtedly one of the biggest problems if not the most severe one that threatens our planet. In the last decade, to overcome this global issue, industries were regulated, events and conferences were organized, objectives have been made, but the high cost of green practices, the fierce competition among firms, and the massive increase rate of production made all these efforts insufficient, in the other hand, the fourth industrial revolution could potentially provide suitable solutions to achieve high environmental sustainability. The present research contributes to the environmental sustainability literature by studying the vision that companies in Europe have on Industry 4.0 and the main objectives that they want to achieve from this transformation. Furthermore, relying on a statistical study, the research identifies the differences between large companies and SMEs in Europe when it comes to the incorporation of environmental sustainability objectives within their Industry 4.0 strategies
{"title":"Industry 4.0 as an Opportunity to Achieve Environmental Sustainability: The Difference between SMES and Large Companies","authors":"Mohamed El Merroun","doi":"10.5121/ijitcs.2022.12101","DOIUrl":"https://doi.org/10.5121/ijitcs.2022.12101","url":null,"abstract":"The decline of environmental sustainability is undoubtedly one of the biggest problems if not the most severe one that threatens our planet. In the last decade, to overcome this global issue, industries were regulated, events and conferences were organized, objectives have been made, but the high cost of green practices, the fierce competition among firms, and the massive increase rate of production made all these efforts insufficient, in the other hand, the fourth industrial revolution could potentially provide suitable solutions to achieve high environmental sustainability. The present research contributes to the environmental sustainability literature by studying the vision that companies in Europe have on Industry 4.0 and the main objectives that they want to achieve from this transformation. Furthermore, relying on a statistical study, the research identifies the differences between large companies and SMEs in Europe when it comes to the incorporation of environmental sustainability objectives within their Industry 4.0 strategies","PeriodicalId":418938,"journal":{"name":"International Journal of Information Technology Convergence and Services","volume":"330 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115969086","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 : 2021-12-31DOI: 10.5121/ijitcs.2021.11601
Seyedeh Samaneh Seyedi, Abolfazl Darroudi
Autism is an advanced neurological disease that affect communication and social behaviors, including attention -one of the fundamental skills to learn about the world around us. Autistic people have difficulty moving their attention from one point to another fluently. Due to the high prevalence of autism and its increasing progression, and the need to address common disorders in patients, this study aimed to implement and simulate a computational model for attention deficit disorder in autistic patients using MATLAB. This computational model has three components: context-sensitive reinforcement learning, contextual processing, and automation that can teach a shift-shift task automatically. At first, the model functions like normal people, but its performance gets closer to autistic people after changing a single parameter. This study demonstrates that even a simple computational model can be used for normal and abnormal developmental cases using a neural network reinforcement learning approach and provide valuable insights into autism.
{"title":"Simulating Attention Disorder in Autistic Patients based on a Computational Model with Neural Networks Reinforcement Learning Approach","authors":"Seyedeh Samaneh Seyedi, Abolfazl Darroudi","doi":"10.5121/ijitcs.2021.11601","DOIUrl":"https://doi.org/10.5121/ijitcs.2021.11601","url":null,"abstract":"Autism is an advanced neurological disease that affect communication and social behaviors, including attention -one of the fundamental skills to learn about the world around us. Autistic people have difficulty moving their attention from one point to another fluently. Due to the high prevalence of autism and its increasing progression, and the need to address common disorders in patients, this study aimed to implement and simulate a computational model for attention deficit disorder in autistic patients using MATLAB. This computational model has three components: context-sensitive reinforcement learning, contextual processing, and automation that can teach a shift-shift task automatically. At first, the model functions like normal people, but its performance gets closer to autistic people after changing a single parameter. This study demonstrates that even a simple computational model can be used for normal and abnormal developmental cases using a neural network reinforcement learning approach and provide valuable insights into autism.","PeriodicalId":418938,"journal":{"name":"International Journal of Information Technology Convergence and Services","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114838695","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 : 2019-02-28DOI: 10.5121/IJITCS.2019.9101
P. Owoche, Franklin Wabwoba, A. N. Wechuli
Information Technology (IT) infrastructure and related research communities can help tackle environmental challenges in developing countries through environmentally sustainable models of economic development. The paper sought to examine the status of current and emerging environmentally friendly technologies, equipment and applications in supporting programs that play a role in addressing environment degradation in Kenya. It also sought to underscore the role of IT in environmentally sustainable consumption. The paper examines what constitutes environment degradation and explores the negative effects of IT infrastructure on the environment. The consequences of E-waste on environment are discussed followed by green IT as part of the solution to environment degradation as a result of adoption of IT. The papers also discuss the available IT infrastructure that can be used to combat the challenges of environment degradation. The paper ends with possible IT infrastructure measures that can be used to mitigate environment degradation.
{"title":"GLOBAL INFORMATION TECHNOLOGY INFRASTRUCTURE IN ADDRESSING THE PROBLEM OF ENVIRONMENTAL DEGRADATION IN KENYA","authors":"P. Owoche, Franklin Wabwoba, A. N. Wechuli","doi":"10.5121/IJITCS.2019.9101","DOIUrl":"https://doi.org/10.5121/IJITCS.2019.9101","url":null,"abstract":"Information Technology (IT) infrastructure and related research communities can help tackle environmental challenges in developing countries through environmentally sustainable models of economic development. The paper sought to examine the status of current and emerging environmentally friendly technologies, equipment and applications in supporting programs that play a role in addressing environment degradation in Kenya. It also sought to underscore the role of IT in environmentally sustainable consumption. The paper examines what constitutes environment degradation and explores the negative effects of IT infrastructure on the environment. The consequences of E-waste on environment are discussed followed by green IT as part of the solution to environment degradation as a result of adoption of IT. The papers also discuss the available IT infrastructure that can be used to combat the challenges of environment degradation. The paper ends with possible IT infrastructure measures that can be used to mitigate environment degradation.","PeriodicalId":418938,"journal":{"name":"International Journal of Information Technology Convergence and Services","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121399202","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 : 2018-08-30DOI: 10.5121/ijitcs.2018.8401
Jackelou Sulapas Mapa
Android smart phone is one of the fast growing mobile phones and because of these it the one of the most preferred target of malware developer. Malware apps can penetrate the device and gain privileges in which it can perform malicious activities such reading user contact, misusing of private information such as sending SMS and can harm user by exploiting the users private data which is stored in the device. The study is about implementation of detecting untrusted on android applications, which would be the basis of all future development regarding malware detection. The smartphone users worldwide are not aware of the permissions as the basis of all malicious activities that could possibly operate in an android system and may steal personal and private information. Android operating system is an open system in which users are allowed to install application from any unsafe sites. However permission mechanism of and android system is not enough to guarantee the invulnerability of the application that can harm the user. In this paper, the permission scoring-based analysis that will scrutinized the installed permission and allows user to increase the efficiency of Android permission to inform user about the risk of the installed Android application, in this paper, the framework that would classify the level of sensitivity of the permission access by the application. The framework uses a formula that will calculate the sensitivity level of the permission and determine if the installed application is untrusted or not. Our result show that, in a collection of 26 untrusted application, the framework is able to correct and determine the application's behavior consistently and efficiently.
{"title":"Android Untrusted Detection with Permission Based Scoring Analysis","authors":"Jackelou Sulapas Mapa","doi":"10.5121/ijitcs.2018.8401","DOIUrl":"https://doi.org/10.5121/ijitcs.2018.8401","url":null,"abstract":"Android smart phone is one of the fast growing mobile phones and because of these it the one of the most preferred target of malware developer. Malware apps can penetrate the device and gain privileges in which it can perform malicious activities such reading user contact, misusing of private information such as sending SMS and can harm user by exploiting the users private data which is stored in the device. The study is about implementation of detecting untrusted on android applications, which would be the basis of all future development regarding malware detection. The smartphone users worldwide are not aware of the permissions as the basis of all malicious activities that could possibly operate in an android system and may steal personal and private information. Android operating system is an open system in which users are allowed to install application from any unsafe sites. However permission mechanism of and android system is not enough to guarantee the invulnerability of the application that can harm the user. In this paper, the permission scoring-based analysis that will scrutinized the installed permission and allows user to increase the efficiency of Android permission to inform user about the risk of the installed Android application, in this paper, the framework that would classify the level of sensitivity of the permission access by the application. The framework uses a formula that will calculate the sensitivity level of the permission and determine if the installed application is untrusted or not. Our result show that, in a collection of 26 untrusted application, the framework is able to correct and determine the application's behavior consistently and efficiently.","PeriodicalId":418938,"journal":{"name":"International Journal of Information Technology Convergence and Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126822956","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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