Pub Date : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216343
Samira Yeasmin, A. Baig
Industrial Internet of Things (IIoT) is one of the most trending topics in the present world. It has numerous benefits and its potentiality is unfolding gradually. The implementation of IIoT in mission and safety-critical systems has shown its significance. Since it deals with important and sensitive information, an extensive study is required to address the susceptibility of it towards security issues. Therefore, there have been many proposals to use certificateless signature scheme, machine learning approaches, public key encryption as well as blockchain to improve the security of IIoT. It is important to note that blockchain is playing a significant role in the IIoT technology where the important characteristics of blockchain, immutability, decentralization, tamper-proof, have made a profound impact on the security vulnerabilities of IIoT. Taking this into account, this paper proposes a permissioned blockchain for IIoT that addresses and guarantees to ensure and improve the security vulnerabilities and susceptibility of IIoT towards cyber threats. The permissioned blockchain enabled IIoT ensures a secure medium for device communication, data sharing, and access control. This paper also discusses the security issues of IIoT and presents a comprehensive analysis of some of the proposed blockchain based solutions to improve IIoT security challenges. It addresses the benefits of a permissioned blockchain enabled IIoT over a public blockchain as well as presents a future direction for the upcoming integration of blockchain with IIoT and other industries.
{"title":"Permissioned Blockchain-based Security for IIoT","authors":"Samira Yeasmin, A. Baig","doi":"10.1109/IEMTRONICS51293.2020.9216343","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216343","url":null,"abstract":"Industrial Internet of Things (IIoT) is one of the most trending topics in the present world. It has numerous benefits and its potentiality is unfolding gradually. The implementation of IIoT in mission and safety-critical systems has shown its significance. Since it deals with important and sensitive information, an extensive study is required to address the susceptibility of it towards security issues. Therefore, there have been many proposals to use certificateless signature scheme, machine learning approaches, public key encryption as well as blockchain to improve the security of IIoT. It is important to note that blockchain is playing a significant role in the IIoT technology where the important characteristics of blockchain, immutability, decentralization, tamper-proof, have made a profound impact on the security vulnerabilities of IIoT. Taking this into account, this paper proposes a permissioned blockchain for IIoT that addresses and guarantees to ensure and improve the security vulnerabilities and susceptibility of IIoT towards cyber threats. The permissioned blockchain enabled IIoT ensures a secure medium for device communication, data sharing, and access control. This paper also discusses the security issues of IIoT and presents a comprehensive analysis of some of the proposed blockchain based solutions to improve IIoT security challenges. It addresses the benefits of a permissioned blockchain enabled IIoT over a public blockchain as well as presents a future direction for the upcoming integration of blockchain with IIoT and other industries.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124610187","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216384
A. Kyung, S. Whitney
The economy suffered a major loss when COVID-19 hit due to business shutdowns. Repercussions from economic downfall due to closed businesses from social distance policies has made many small businesses lose operation mechanisms and see a decrease in profit and sales. Many people lost their jobs due to businesses losses a record 22 million employees have filed for unemployment. In this paper, how the COVID-19 epidemic has changed people’s behaviors and changed the way people shop. As more people are shopping online to avoid at risk situations at busy stores, small businesses are seeing losses in sales and customers. Also we studied when they rely on small profits margins, how the small businesses have suffered the worst losses, seeing a decrease in business sales and a lower revenue margin. This research shows how social distance policy has especially affected businesses vulnerable to COVID-19 risks. This often includes businesses that have large groups of people in close quarters or highly susceptible relationships that increase the risks of spreading the illness, such as restaurants or retail stores. Government help has been recommended especially for small businesses and workers who are most vulnerable to economic losses.
{"title":"A Study on The Financial and Entrepreneurial Risks of Small Business Owners Amidst COVID-19","authors":"A. Kyung, S. Whitney","doi":"10.1109/IEMTRONICS51293.2020.9216384","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216384","url":null,"abstract":"The economy suffered a major loss when COVID-19 hit due to business shutdowns. Repercussions from economic downfall due to closed businesses from social distance policies has made many small businesses lose operation mechanisms and see a decrease in profit and sales. Many people lost their jobs due to businesses losses a record 22 million employees have filed for unemployment. In this paper, how the COVID-19 epidemic has changed people’s behaviors and changed the way people shop. As more people are shopping online to avoid at risk situations at busy stores, small businesses are seeing losses in sales and customers. Also we studied when they rely on small profits margins, how the small businesses have suffered the worst losses, seeing a decrease in business sales and a lower revenue margin. This research shows how social distance policy has especially affected businesses vulnerable to COVID-19 risks. This often includes businesses that have large groups of people in close quarters or highly susceptible relationships that increase the risks of spreading the illness, such as restaurants or retail stores. Government help has been recommended especially for small businesses and workers who are most vulnerable to economic losses.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115530614","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216347
Niko Anthony Simon, Cheol-Hong Min
Row detection in agricultural applications has commonly used Hough transform techniques and traditional signal processing based approaches relating to machine vision. There are various learning based methods available that are capable of producing similar results in terms of detection. In this paper, a neural network based algorithm is developed, and we compare the Hough transform and a machine learning implementation with the proposed approach to determine which would be the most appropriate in a real-time application given a variety of factors including computational performance, accuracy, and environmental variability. Compared to the learning based approaches which rely on training data, Hough transform based detection relies on a variety of processes, including binarization and denoising, which are not required to be explicitly implemented in the machine learning or neural network models. Additionally, to add another layer of diversity to the three possible solutions examined is the consideration for color input data. The Hough transform method and the neural network model implemented both require color input data while the machine learning model relies on texture features instead of color to make its classification predictions. Compared to the traditional image understanding techniques, autonomous vehicles face challenges due to similarities in color and texture between the crops and their surroundings. Therefore, the algorithm is developed to overcome such challenges. Preliminary results show that the neural network model developed was found to offer the most versatility compared to traditional methods and the highest accuracy on the order of 97% for this application across several different input conditions.
{"title":"Neural Network Based Corn Field Furrow Detection for Autonomous Navigation in Agriculture Vehicles","authors":"Niko Anthony Simon, Cheol-Hong Min","doi":"10.1109/IEMTRONICS51293.2020.9216347","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216347","url":null,"abstract":"Row detection in agricultural applications has commonly used Hough transform techniques and traditional signal processing based approaches relating to machine vision. There are various learning based methods available that are capable of producing similar results in terms of detection. In this paper, a neural network based algorithm is developed, and we compare the Hough transform and a machine learning implementation with the proposed approach to determine which would be the most appropriate in a real-time application given a variety of factors including computational performance, accuracy, and environmental variability. Compared to the learning based approaches which rely on training data, Hough transform based detection relies on a variety of processes, including binarization and denoising, which are not required to be explicitly implemented in the machine learning or neural network models. Additionally, to add another layer of diversity to the three possible solutions examined is the consideration for color input data. The Hough transform method and the neural network model implemented both require color input data while the machine learning model relies on texture features instead of color to make its classification predictions. Compared to the traditional image understanding techniques, autonomous vehicles face challenges due to similarities in color and texture between the crops and their surroundings. Therefore, the algorithm is developed to overcome such challenges. Preliminary results show that the neural network model developed was found to offer the most versatility compared to traditional methods and the highest accuracy on the order of 97% for this application across several different input conditions.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124931967","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216363
Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, M. Jeon
Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.
{"title":"Multiple Objects Tracking using Radar for Autonomous Driving","authors":"Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, M. Jeon","doi":"10.1109/IEMTRONICS51293.2020.9216363","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216363","url":null,"abstract":"Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121130260","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216367
R. Gayen, Payel Midya, Sutanu Ghosh, K. Patra, M. Gangopadhyay
In this paper, the simple design of a "U" slot substrate-integrated waveguide (SIW)-based single substrate self-diplexing antenna is proposed. Two longitudinal slots (similar length) and one transverse slot are designated for "U" slot representation respectively, which radiate at two separate resonant frequencies, being imprinted on the top surface of the antenna. Two different microstrip feed lines are used to feed the SIW antenna. A high degree of isolation is achieved between the two ports.
{"title":"Design of a ‘U’ Slot Substrate-Integrated Waveguide Cavity-Backed Self-Diplexing Antenna","authors":"R. Gayen, Payel Midya, Sutanu Ghosh, K. Patra, M. Gangopadhyay","doi":"10.1109/IEMTRONICS51293.2020.9216367","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216367","url":null,"abstract":"In this paper, the simple design of a \"U\" slot substrate-integrated waveguide (SIW)-based single substrate self-diplexing antenna is proposed. Two longitudinal slots (similar length) and one transverse slot are designated for \"U\" slot representation respectively, which radiate at two separate resonant frequencies, being imprinted on the top surface of the antenna. Two different microstrip feed lines are used to feed the SIW antenna. A high degree of isolation is achieved between the two ports.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121422180","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216447
E. Aloufi, Raed Alharthi, M. Zohdy, Dareen Alsulami, Ibrahim Alrashdi, Richard Olawoyin
Spatial crowdsourcing is a form of location-based crowdsourcing. With the spread use of mobile phones and smart devices that can share location, spatial crowdsourcing gained a lot of attention, especially in ride-hailing services. This paper evaluates the performance of a proposed spatial crowdsourcing task assignment approach to increase the task assignment rate while preserving the location privacy of the crowd workers. The overall experiments on real-world data sets show that the proposed approach results in the maximal total number of assigned tasks without significant disclosure of crowd workers' locations.
{"title":"An Efficient Approach for Task Assignment in Spatial Crowdsourcing","authors":"E. Aloufi, Raed Alharthi, M. Zohdy, Dareen Alsulami, Ibrahim Alrashdi, Richard Olawoyin","doi":"10.1109/IEMTRONICS51293.2020.9216447","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216447","url":null,"abstract":"Spatial crowdsourcing is a form of location-based crowdsourcing. With the spread use of mobile phones and smart devices that can share location, spatial crowdsourcing gained a lot of attention, especially in ride-hailing services. This paper evaluates the performance of a proposed spatial crowdsourcing task assignment approach to increase the task assignment rate while preserving the location privacy of the crowd workers. The overall experiments on real-world data sets show that the proposed approach results in the maximal total number of assigned tasks without significant disclosure of crowd workers' locations.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125789498","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216457
Teena Gakhar, A. Hazra
In this work we have proposed p-TiO2-GO nanocomposite field effect transistor based ethanol sensor. p-type TiO2 nanoparticles was prepared by sol-gel method and mixed with 2 wt% aquas solution of graphene oxide (GO) and sonicated for 30 min. The nanocomposite was prepared in combination of 5 vol% p-TiO2 nanoparticles with 95 vol% GO. The morphological and structural characterizations of developed nancomposite were carried out with field emission scanning electron microscopy (FESEM) and Raman spectroscopy techniques, respectively. The p-TiO2-GO field effect transistor (FET) sensor showed a response magnitude of 6% in terminal structure when VGS=0 and 41% as in three terminal structure when VGS=0.65 V in the exposure of 100 ppm ethanol at 100°C. The p-TiO2-GO FET showed maximum ~7 times amplification in sensitivity due to application of positive gate voltage.
{"title":"TiO2-GO Field Effect Transistors for Amplified Ethanol Sensing","authors":"Teena Gakhar, A. Hazra","doi":"10.1109/IEMTRONICS51293.2020.9216457","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216457","url":null,"abstract":"In this work we have proposed p-TiO2-GO nanocomposite field effect transistor based ethanol sensor. p-type TiO2 nanoparticles was prepared by sol-gel method and mixed with 2 wt% aquas solution of graphene oxide (GO) and sonicated for 30 min. The nanocomposite was prepared in combination of 5 vol% p-TiO2 nanoparticles with 95 vol% GO. The morphological and structural characterizations of developed nancomposite were carried out with field emission scanning electron microscopy (FESEM) and Raman spectroscopy techniques, respectively. The p-TiO2-GO field effect transistor (FET) sensor showed a response magnitude of 6% in terminal structure when VGS=0 and 41% as in three terminal structure when VGS=0.65 V in the exposure of 100 ppm ethanol at 100°C. The p-TiO2-GO FET showed maximum ~7 times amplification in sensitivity due to application of positive gate voltage.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134124272","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216386
Mohammad Marufur Rahman, Md. Motaleb Hossen Manik, Md. Milon Islam, Saifuddin Mahmud, Jong-Hoon Kim
COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the world. The impact of COVID-19 has been fallen on almost all sectors of development. The healthcare system is going through a crisis. Many precautionary measures have been taken to reduce the spread of this disease where wearing a mask is one of them. In this paper, we propose a system that restrict the growth of COVID-19 by finding out people who are not wearing any facial mask in a smart city network where all the public places are monitored with Closed-Circuit Television (CCTV) cameras. While a person without a mask is detected, the corresponding authority is informed through the city network. A deep learning architecture is trained on a dataset that consists of images of people with and without masks collected from various sources. The trained architecture achieved 98.7% accuracy on distinguishing people with and without a facial mask for previously unseen test data. It is hoped that our study would be a useful tool to reduce the spread of this communicable disease for many countries in the world.
{"title":"An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network","authors":"Mohammad Marufur Rahman, Md. Motaleb Hossen Manik, Md. Milon Islam, Saifuddin Mahmud, Jong-Hoon Kim","doi":"10.1109/IEMTRONICS51293.2020.9216386","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216386","url":null,"abstract":"COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the world. The impact of COVID-19 has been fallen on almost all sectors of development. The healthcare system is going through a crisis. Many precautionary measures have been taken to reduce the spread of this disease where wearing a mask is one of them. In this paper, we propose a system that restrict the growth of COVID-19 by finding out people who are not wearing any facial mask in a smart city network where all the public places are monitored with Closed-Circuit Television (CCTV) cameras. While a person without a mask is detected, the corresponding authority is informed through the city network. A deep learning architecture is trained on a dataset that consists of images of people with and without masks collected from various sources. The trained architecture achieved 98.7% accuracy on distinguishing people with and without a facial mask for previously unseen test data. It is hoped that our study would be a useful tool to reduce the spread of this communicable disease for many countries in the world.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"2020 35","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132678560","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216375
Tri Vien Tran, H. Takahashi, T. Narabayashi, H. Kikura
The concept "Internet of Things" has been applied in many fields to reduce human efforts by using automatic things. It also provides opportunities to develop remote laboratories or distance researches/studies. The main objective of this article is to conduct the telemetry experiment on the measurement of the flow behavior in the pool scrubbing of a Filtered Containment Venting System (FCVS). The Internet of Things (IoT) has been applied to monitor and control the experimental performance and the measurement system. An IoT network that consists of various sensors, web-cameras, IoT appliances, and PCs was established. Thus, the laboratory's experimental works can be implemented from home. It is valuable for the current situation of social distancing due to the Covid-19 pandemic.
{"title":"An Application of IoT for Conduct of Laboratory Experiment from Home","authors":"Tri Vien Tran, H. Takahashi, T. Narabayashi, H. Kikura","doi":"10.1109/IEMTRONICS51293.2020.9216375","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216375","url":null,"abstract":"The concept \"Internet of Things\" has been applied in many fields to reduce human efforts by using automatic things. It also provides opportunities to develop remote laboratories or distance researches/studies. The main objective of this article is to conduct the telemetry experiment on the measurement of the flow behavior in the pool scrubbing of a Filtered Containment Venting System (FCVS). The Internet of Things (IoT) has been applied to monitor and control the experimental performance and the measurement system. An IoT network that consists of various sensors, web-cameras, IoT appliances, and PCs was established. Thus, the laboratory's experimental works can be implemented from home. It is valuable for the current situation of social distancing due to the Covid-19 pandemic.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124307766","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 : 2020-09-01DOI: 10.1109/IEMTRONICS51293.2020.9216352
Shuvankar Roy, M. Pal, Sonali Bhattacharyya, Srirup Lahiri
In this paper, we have represented implementation of an informative online platform-Covid-19 Predictor which is capable of disseminating accurate prediction of confirmed, deceased and affected Covid-19 cases in India on the basis of the data available in a reliable online repository. The work characterizes proper utilization of advanced technologies for web scrapping, model prediction, implementation of web application framework and cloud hosting.
{"title":"Implementation of an Informative Website – \"Covid19 Predictor\", Highlighting COVID-19 Pandemic Situation in India","authors":"Shuvankar Roy, M. Pal, Sonali Bhattacharyya, Srirup Lahiri","doi":"10.1109/IEMTRONICS51293.2020.9216352","DOIUrl":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216352","url":null,"abstract":"In this paper, we have represented implementation of an informative online platform-Covid-19 Predictor which is capable of disseminating accurate prediction of confirmed, deceased and affected Covid-19 cases in India on the basis of the data available in a reliable online repository. The work characterizes proper utilization of advanced technologies for web scrapping, model prediction, implementation of web application framework and cloud hosting.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124362867","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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