K. S. Babulal, A. Das, Pushpendra Kumar, D. Rajput, Afroj Alam, Ahmed J. Obaid
As the corona virus can mutate and due to other scientific factor associated to it, experts believe that COVID-19 will remain with us for decades. Therefore, one has to keep social distancing measures. Accepting the pandemic situation, the paper presents a mechanism for detecting violations of social distancing using deep learning to estimate the distance between individuals to diminish the influence of COVID-19. The focus of this paper is to understand the effect of social distancing on the spread of COVID-19 by using YOLOv3 and Faster-RCNN and proposes IFRCNN (improved faster region – convolution neural network). The proposed method IFRCNN is checked on a live streaming video of pedestrians walking on the street. This paper keeps the live updates of the recorded video along with social distancing violation records on a location, so how many people in a location are maintaining social distancing. Updates will be stored in a cloud-based storage system and any organization or firm can get live updates of that location in their digital devices.
{"title":"Real-Time Surveillance System for Detection of Social Distancing","authors":"K. S. Babulal, A. Das, Pushpendra Kumar, D. Rajput, Afroj Alam, Ahmed J. Obaid","doi":"10.4018/ijehmc.309930","DOIUrl":"https://doi.org/10.4018/ijehmc.309930","url":null,"abstract":"As the corona virus can mutate and due to other scientific factor associated to it, experts believe that COVID-19 will remain with us for decades. Therefore, one has to keep social distancing measures. Accepting the pandemic situation, the paper presents a mechanism for detecting violations of social distancing using deep learning to estimate the distance between individuals to diminish the influence of COVID-19. The focus of this paper is to understand the effect of social distancing on the spread of COVID-19 by using YOLOv3 and Faster-RCNN and proposes IFRCNN (improved faster region – convolution neural network). The proposed method IFRCNN is checked on a live streaming video of pedestrians walking on the street. This paper keeps the live updates of the recorded video along with social distancing violation records on a location, so how many people in a location are maintaining social distancing. Updates will be stored in a cloud-based storage system and any organization or firm can get live updates of that location in their digital devices.","PeriodicalId":43154,"journal":{"name":"International Journal of E-Health and Medical Communications","volume":"7 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87042499","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 : 2019-04-01DOI: 10.4018/ijehmc.2019040104
R. Selvanambi, Jaisankar N.
Quality analysis of the treatment of cancer has been an objective of e-health services for quite some time. The objective is to predict the stage of breast cancer by using diverse input parameters. Breast cancer is one of the main causes of death in women when compared to other tumors. The classification of breast cancer information can be profitable to anticipate diseases or track the hereditary of tumors. For classification, an artificial neural network (ANN) structure was carried out. In the structure, nine training algorithms are used and the proposed is the Levenberg-Marquardt algorithm. For optimizing the hidden layer and neuron, three optimization techniques are used. In the result, the best approval execution is anticipated and the diverse execution evaluation estimation for three optimization algorithms is researched. The correlation execution diagram for an accuracy of 95%, a sensitivity of 98%, and a specificity of 89% of a social spider optimization (SSO) algorithm are shown.
{"title":"Healthcare","authors":"R. Selvanambi, Jaisankar N.","doi":"10.4018/ijehmc.2019040104","DOIUrl":"https://doi.org/10.4018/ijehmc.2019040104","url":null,"abstract":"Quality analysis of the treatment of cancer has been an objective of e-health services for quite some time. The objective is to predict the stage of breast cancer by using diverse input parameters. Breast cancer is one of the main causes of death in women when compared to other tumors. The classification of breast cancer information can be profitable to anticipate diseases or track the hereditary of tumors. For classification, an artificial neural network (ANN) structure was carried out. In the structure, nine training algorithms are used and the proposed is the Levenberg-Marquardt algorithm. For optimizing the hidden layer and neuron, three optimization techniques are used. In the result, the best approval execution is anticipated and the diverse execution evaluation estimation for three optimization algorithms is researched. The correlation execution diagram for an accuracy of 95%, a sensitivity of 98%, and a specificity of 89% of a social spider optimization (SSO) algorithm are shown.","PeriodicalId":43154,"journal":{"name":"International Journal of E-Health and Medical Communications","volume":"264 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73225472","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 : 2018-07-01DOI: 10.4018/ijehmc.2018070105
Jegan R., Nimi W.S.
This article describes how physiological signal monitoring plays an important role in identifying the health condition of heart. In recent years, online monitoring and processing of biomedical signals play a major role in accurate clinical diagnosis. Therefore, there is a requirement for the developing of online monitoring systems that will be helpful for physicians to avoid mistakes. This article focuses on the method for real time acquisition of an ECG and PPG signal and it's processing and monitoring for tele-health applications. This article also presents the real time peak detection of ECG and PPG for vital parameters measurement. The implementation and design of the proposed wireless monitoring system can be done using a graphical programming environment that utilizes less power and a minimized area with reasonable speed. The advantages of the proposed work are very simple, low cost, easy integration with programming environment and continuous monitoring of physiological signals.
{"title":"Sensor Based Smart Real Time Monitoring of Patients Conditions Using Wireless Protocol","authors":"Jegan R., Nimi W.S.","doi":"10.4018/ijehmc.2018070105","DOIUrl":"https://doi.org/10.4018/ijehmc.2018070105","url":null,"abstract":"This article describes how physiological signal monitoring plays an important role in identifying the health condition of heart. In recent years, online monitoring and processing of biomedical signals play a major role in accurate clinical diagnosis. Therefore, there is a requirement for the developing of online monitoring systems that will be helpful for physicians to avoid mistakes. This article focuses on the method for real time acquisition of an ECG and PPG signal and it's processing and monitoring for tele-health applications. This article also presents the real time peak detection of ECG and PPG for vital parameters measurement. The implementation and design of the proposed wireless monitoring system can be done using a graphical programming environment that utilizes less power and a minimized area with reasonable speed. The advantages of the proposed work are very simple, low cost, easy integration with programming environment and continuous monitoring of physiological signals.","PeriodicalId":43154,"journal":{"name":"International Journal of E-Health and Medical Communications","volume":"39 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75556123","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 : 1900-01-01DOI: 10.4018/ijehmc.2021030105
Hitender Vats, R. S. Tomar
One knows that smart transport is also an integrated part of healthcare technologies. To minimize the pollution for benefiting the healthcare, the traffic throughput on roundabout intersection has to be increased which will reduce wasted time and will also enhance passenger comfort. This paper presents a new approach by use of cooperative vehicular control utilizing VANET without compromising the safety of vehicles. This intersection side unit (ISU)-based system use lane change mechanism. The modular use of lane with lane change in newly designed protocol CARA (collision avoidance at roundabout algorithm) will greatly enhance the capacity utilization of roundabout. A new simulator ‘RoundSim' was also developed exclusively for simulation in roundabout. A new MAC protocol RMAC (roundabout MAC) is also designed which will suit the roundabout management utilizing lane change to minimize sudden jerk to passengers, thus enhancing healthcare of people. This RMAC utilizes message set with different prioritization scheme which results in better utilization of allotted frequency spectrum.
众所周知，智能交通也是医疗技术的一个组成部分。为了最大限度地减少污染，有利于健康，必须增加交叉路口的交通吞吐量，这样可以减少浪费的时间，也可以提高乘客的舒适度。本文提出了在不影响车辆安全的前提下，利用VANET进行车辆协同控制的新方法。该系统基于交叉口侧单元(ISU)，采用变道机制。新设计的环形交叉口避撞算法CARA (collision avoidance at roundabout algorithm)将带变道的车道模块化使用，大大提高了环形交叉口的容量利用率。一个新的模拟器' RoundSim'也开发了专门模拟在回旋。设计了一种新的环形交叉口控制协议RMAC (roundabout MAC)，该协议将适应环形交叉口的管理，利用变道来减少乘客的突然颠簸，从而提高人们的健康水平。该RMAC利用具有不同优先级方案的消息集，从而更好地利用分配的频谱。
{"title":"RMAC","authors":"Hitender Vats, R. S. Tomar","doi":"10.4018/ijehmc.2021030105","DOIUrl":"https://doi.org/10.4018/ijehmc.2021030105","url":null,"abstract":"One knows that smart transport is also an integrated part of healthcare technologies. To minimize the pollution for benefiting the healthcare, the traffic throughput on roundabout intersection has to be increased which will reduce wasted time and will also enhance passenger comfort. This paper presents a new approach by use of cooperative vehicular control utilizing VANET without compromising the safety of vehicles. This intersection side unit (ISU)-based system use lane change mechanism. The modular use of lane with lane change in newly designed protocol CARA (collision avoidance at roundabout algorithm) will greatly enhance the capacity utilization of roundabout. A new simulator ‘RoundSim' was also developed exclusively for simulation in roundabout. A new MAC protocol RMAC (roundabout MAC) is also designed which will suit the roundabout management utilizing lane change to minimize sudden jerk to passengers, thus enhancing healthcare of people. This RMAC utilizes message set with different prioritization scheme which results in better utilization of allotted frequency spectrum.","PeriodicalId":43154,"journal":{"name":"International Journal of E-Health and Medical Communications","volume":"90 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74963166","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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