Pub Date : 2021-01-08DOI: 10.1108/IJPCC-08-2019-0065
A. Shinde, S. Nalbalwar, A. Nandgaonkar
Purpose In today’s digital world, real-time health monitoring is becoming a most important challenge in the field of medical research. Body signals such as electrocardiogram (ECG), electromyogram and electroencephalogram (EEG) are produced in human body. This continuous monitoring generates huge count of data and thus an efficient method is required to shrink the size of the obtained large data. Compressed sensing (CS) is one of the techniques used to compress the data size. This technique is most used in certain applications, where the size of data is huge or the data acquisition process is too expensive to gather data from vast count of samples at Nyquist rate. This paper aims to propose Lion Mutated Crow search Algorithm (LM-CSA), to improve the performance of the LMCSA model. Design/methodology/approach A new CS algorithm is exploited in this paper, where the compression process undergoes three stages: designing of stable measurement matrix, signal compression and signal reconstruction. Here, the compression process falls under certain working principle, and is as follows: signal transformation, computation of Θ and normalization. As the main contribution, the theta value evaluation is proceeded by a new “Enhanced bi-orthogonal wavelet filter.” The enhancement is given under the scaling coefficients, where they are optimally tuned for processing the compression. However, the way of tuning seems to be the great crisis, and hence this work seeks the strategy of meta-heuristic algorithms. Moreover, a new hybrid algorithm is introduced that solves the above mentioned optimization inconsistency. The proposed algorithm is named as “Lion Mutated Crow search Algorithm (LM-CSA),” which is the hybridization of crow search algorithm (CSA) and lion algorithm (LA) to enhance the performance of the LM-CSA model. Findings Finally, the proposed LM-CSA model is compared over the traditional models in terms of certain error measures such as mean error percentage (MEP), symmetric mean absolute percentage error (SMAPE), mean absolute scaled error, mean absolute error (MAE), root mean square error, L1-norm and L2-normand infinity-norm. For ECG analysis, under bior 3.1, LM-CSA is 56.6, 62.5 and 81.5% better than bi-orthogonal wavelet in terms of MEP, SMAPE and MAE, respectively. Under bior 3.7 for ECG analysis, LM-CSA is 0.15% better than genetic algorithm (GA), 0.10% superior to particle search optimization (PSO), 0.22% superior to firefly (FF), 0.22% superior to CSA and 0.14% superior to LA, respectively, in terms of L1-norm. Further, for EEG analysis, LM-CSA is 86.9 and 91.2% better than the traditional bi-orthogonal wavelet under bior 3.1. Under bior 3.3, LM-CSA is 91.7 and 73.12% better than the bi-orthogonal wavelet in terms of MAE and MEP, respectively. Under bior 3.5 for EEG, L1-norm of LM-CSA is 0.64% superior to GA, 0.43% superior to PSO, 0.62% superior to FF, 0.84% superior to CSA and 0.60% better than LA, respectively. Originality/value This pap
{"title":"Impact of optimal scaling coefficients in bi-orthogonal wavelet filters on compressed sensing","authors":"A. Shinde, S. Nalbalwar, A. Nandgaonkar","doi":"10.1108/IJPCC-08-2019-0065","DOIUrl":"https://doi.org/10.1108/IJPCC-08-2019-0065","url":null,"abstract":"\u0000Purpose\u0000In today’s digital world, real-time health monitoring is becoming a most important challenge in the field of medical research. Body signals such as electrocardiogram (ECG), electromyogram and electroencephalogram (EEG) are produced in human body. This continuous monitoring generates huge count of data and thus an efficient method is required to shrink the size of the obtained large data. Compressed sensing (CS) is one of the techniques used to compress the data size. This technique is most used in certain applications, where the size of data is huge or the data acquisition process is too expensive to gather data from vast count of samples at Nyquist rate. This paper aims to propose Lion Mutated Crow search Algorithm (LM-CSA), to improve the performance of the LMCSA model.\u0000\u0000\u0000Design/methodology/approach\u0000A new CS algorithm is exploited in this paper, where the compression process undergoes three stages: designing of stable measurement matrix, signal compression and signal reconstruction. Here, the compression process falls under certain working principle, and is as follows: signal transformation, computation of Θ and normalization. As the main contribution, the theta value evaluation is proceeded by a new “Enhanced bi-orthogonal wavelet filter.” The enhancement is given under the scaling coefficients, where they are optimally tuned for processing the compression. However, the way of tuning seems to be the great crisis, and hence this work seeks the strategy of meta-heuristic algorithms. Moreover, a new hybrid algorithm is introduced that solves the above mentioned optimization inconsistency. The proposed algorithm is named as “Lion Mutated Crow search Algorithm (LM-CSA),” which is the hybridization of crow search algorithm (CSA) and lion algorithm (LA) to enhance the performance of the LM-CSA model.\u0000\u0000\u0000Findings\u0000Finally, the proposed LM-CSA model is compared over the traditional models in terms of certain error measures such as mean error percentage (MEP), symmetric mean absolute percentage error (SMAPE), mean absolute scaled error, mean absolute error (MAE), root mean square error, L1-norm and L2-normand infinity-norm. For ECG analysis, under bior 3.1, LM-CSA is 56.6, 62.5 and 81.5% better than bi-orthogonal wavelet in terms of MEP, SMAPE and MAE, respectively. Under bior 3.7 for ECG analysis, LM-CSA is 0.15% better than genetic algorithm (GA), 0.10% superior to particle search optimization (PSO), 0.22% superior to firefly (FF), 0.22% superior to CSA and 0.14% superior to LA, respectively, in terms of L1-norm. Further, for EEG analysis, LM-CSA is 86.9 and 91.2% better than the traditional bi-orthogonal wavelet under bior 3.1. Under bior 3.3, LM-CSA is 91.7 and 73.12% better than the bi-orthogonal wavelet in terms of MAE and MEP, respectively. Under bior 3.5 for EEG, L1-norm of LM-CSA is 0.64% superior to GA, 0.43% superior to PSO, 0.62% superior to FF, 0.84% superior to CSA and 0.60% better than LA, respectively.\u0000\u0000\u0000Originality/value\u0000This pap","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121882945","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 : 2020-12-31DOI: 10.1108/ijpcc-09-2020-0137
Archana Kollu, Sucharita V.
Purpose Data centres evolve constantly in size, complexity and power consumption. Energy-efficient scheduling in a cloud data centre is a critical and challenging research problem. It becomes essential to minimize the overall operational costs as well as environmental impact and to guarantee the service-level agreements for the services provided by the cloud data centres. Resource scheduling in cloud data centres is NP-hard and often requires substantial computational resources. Design/methodology/approach To overcome these problems, the authors propose a novel model that leads to nominal operational cost and energy consumption in cloud data centres. The authors propose an effective approach, parallel hybrid Jaya algorithm, that performs parallel processing of Jaya algorithm and genetic algorithm using multi-threading and shared memory for interchanging the information to enhance convergence premature rate and global exploration. Findings Experimental results reveal that the proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms. Originality/value Experimental results reveals that our proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms.
{"title":"Energy efficiency in cloud data centres using parallel hybrid Jaya algorithm","authors":"Archana Kollu, Sucharita V.","doi":"10.1108/ijpcc-09-2020-0137","DOIUrl":"https://doi.org/10.1108/ijpcc-09-2020-0137","url":null,"abstract":"\u0000Purpose\u0000Data centres evolve constantly in size, complexity and power consumption. Energy-efficient scheduling in a cloud data centre is a critical and challenging research problem. It becomes essential to minimize the overall operational costs as well as environmental impact and to guarantee the service-level agreements for the services provided by the cloud data centres. Resource scheduling in cloud data centres is NP-hard and often requires substantial computational resources.\u0000\u0000\u0000Design/methodology/approach\u0000To overcome these problems, the authors propose a novel model that leads to nominal operational cost and energy consumption in cloud data centres. The authors propose an effective approach, parallel hybrid Jaya algorithm, that performs parallel processing of Jaya algorithm and genetic algorithm using multi-threading and shared memory for interchanging the information to enhance convergence premature rate and global exploration.\u0000\u0000\u0000Findings\u0000Experimental results reveal that the proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms.\u0000\u0000\u0000Originality/value\u0000Experimental results reveals that our proposed approach reduces the power consumption in cloud data centres up to 38% and premature convergence rate up to 60% compared to other algorithms.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133601428","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 : 2020-12-28DOI: 10.1108/ijpcc-09-2020-0136
Francis H. Shajin, P. Rajesh
Purpose This study aims to evaluate the direct trust value for each node and calculate the trust value of all nodes satisfying the condition and update the trust value and value each trust update interval for a secure and efficient communication between sender and destination node. Hence, a Trusted Secure Geographic Routing Protocol (TSGRP) has been proposed for detecting attackers (presence of the hacker), considering the trust value for a node produced by combining the location trusted information and the direct trusted information. Design/methodology/approach Amelioration in the research studies related to mobile ad hoc networks (MANETs) and wireless sensor networks has shown greater concern in the presence of malicious nodes, due to which the delivery percentage in any given network can degrade to a larger extent, and hence make the network less reliable and more vulnerable to security. Findings TSGRP has outperformed the conventional protocols for detecting attacks in MANET. TSGRP is establishing a trust-based secure communication between the sender and destination node. The evaluated direct trust value is used after the transmission of route-request and route-reply packets, to evaluate the direct trust value of each node and a secure path is established between the sender and the destination node. The effectiveness of the proposed TSGRP is evaluated through NS-2 simulation. Originality/value The simulation results show the delay of the proposed method is 92% less than PRISM approach and the overhead of the proposed TSGRP approach is 61% less than PRISM approach.
{"title":"Trusted Secure Geographic Routing Protocol: outsider attack detection in mobile ad hoc networks by adopting trusted secure geographic routing protocol","authors":"Francis H. Shajin, P. Rajesh","doi":"10.1108/ijpcc-09-2020-0136","DOIUrl":"https://doi.org/10.1108/ijpcc-09-2020-0136","url":null,"abstract":"\u0000Purpose\u0000This study aims to evaluate the direct trust value for each node and calculate the trust value of all nodes satisfying the condition and update the trust value and value each trust update interval for a secure and efficient communication between sender and destination node. Hence, a Trusted Secure Geographic Routing Protocol (TSGRP) has been proposed for detecting attackers (presence of the hacker), considering the trust value for a node produced by combining the location trusted information and the direct trusted information.\u0000\u0000\u0000Design/methodology/approach\u0000Amelioration in the research studies related to mobile ad hoc networks (MANETs) and wireless sensor networks has shown greater concern in the presence of malicious nodes, due to which the delivery percentage in any given network can degrade to a larger extent, and hence make the network less reliable and more vulnerable to security.\u0000\u0000\u0000Findings\u0000TSGRP has outperformed the conventional protocols for detecting attacks in MANET. TSGRP is establishing a trust-based secure communication between the sender and destination node. The evaluated direct trust value is used after the transmission of route-request and route-reply packets, to evaluate the direct trust value of each node and a secure path is established between the sender and the destination node. The effectiveness of the proposed TSGRP is evaluated through NS-2 simulation.\u0000\u0000\u0000Originality/value\u0000The simulation results show the delay of the proposed method is 92% less than PRISM approach and the overhead of the proposed TSGRP approach is 61% less than PRISM approach.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133690113","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 : 2020-12-14DOI: 10.1108/ijpcc-07-2020-0079
P. Aylapogu, Madhusudan Donga, D. Venkatachari, B. Ramadevi
Purpose The suggested antenna has a switched mechanism among the successive elements of the radiating patch. The purpose of this paper is to develop high gain and less interference at higher frequencies. Design/methodology/approach The design geometry of the suggested high gain switched beam Yagi-Uda antennas. The constructed antenna has been developed with Rogers Substrate, relative permittivity (εr) of 4.4, tangent of loss 0.0009 and with height of 1.6 mm. The proposed antenna has an input impedance of 50, and it is connected to input feed line with 2 mm. Findings In forthcoming life, the antennas play key role in all the wireless devices, because these devices perform with high gain and high efficacy. Originality/value The pivotal principle of this paper is to accomplish the gain as high, high directivity and interference is low at higher frequencies. Therefore, it is more applicable to 5G mobile communications and millimeter wave communications.
{"title":"High gain switched beam Yagi-Uda antenna for millimeter wave communications","authors":"P. Aylapogu, Madhusudan Donga, D. Venkatachari, B. Ramadevi","doi":"10.1108/ijpcc-07-2020-0079","DOIUrl":"https://doi.org/10.1108/ijpcc-07-2020-0079","url":null,"abstract":"\u0000Purpose\u0000The suggested antenna has a switched mechanism among the successive elements of the radiating patch. The purpose of this paper is to develop high gain and less interference at higher frequencies.\u0000\u0000\u0000Design/methodology/approach\u0000The design geometry of the suggested high gain switched beam Yagi-Uda antennas. The constructed antenna has been developed with Rogers Substrate, relative permittivity (εr) of 4.4, tangent of loss 0.0009 and with height of 1.6 mm. The proposed antenna has an input impedance of 50, and it is connected to input feed line with 2 mm.\u0000\u0000\u0000Findings\u0000In forthcoming life, the antennas play key role in all the wireless devices, because these devices perform with high gain and high efficacy.\u0000\u0000\u0000Originality/value\u0000The pivotal principle of this paper is to accomplish the gain as high, high directivity and interference is low at higher frequencies. Therefore, it is more applicable to 5G mobile communications and millimeter wave communications.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132903535","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 : 2020-12-03DOI: 10.1108/ijpcc-08-2020-0106
N. Renuka, M. SatyaSairam
Purpose The tremendous growth of wireless applications and the demand for high data rate, the spectrum utilization improvement has been the most crucial challenges for wireless communication. Adapting cognitive radio with orthogonal frequency division multiplexing or offset quadrature amplitude modulation (OFDM/OQAM) improves the spectrum and energy efficiencies. Design/methodology/approach Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from secondary user (SUs) to primary user (PUs) and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high peak to average power ratio (PAPR) phenomenon is a common issue in the majority of the multicarrier modulation systems and thus OFDM/OQAM is no exception in this case. Findings Therefore, this paper aims to examine the effect of integrating the Walsh–Hadamard Transform (WHT) on the power spectral density and investigates the problem of PAPR in the WHT/OQAM system. Originality/value Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from SUs to PUs and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high PAPR phenomenon is a common issue in the majority of the multicarrier modulation systems thus OFDM/OQAM is no exception in this case.
{"title":"PAPR reduction using OQAM for spectrum sensing","authors":"N. Renuka, M. SatyaSairam","doi":"10.1108/ijpcc-08-2020-0106","DOIUrl":"https://doi.org/10.1108/ijpcc-08-2020-0106","url":null,"abstract":"\u0000Purpose\u0000The tremendous growth of wireless applications and the demand for high data rate, the spectrum utilization improvement has been the most crucial challenges for wireless communication. Adapting cognitive radio with orthogonal frequency division multiplexing or offset quadrature amplitude modulation (OFDM/OQAM) improves the spectrum and energy efficiencies.\u0000\u0000\u0000Design/methodology/approach\u0000Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from secondary user (SUs) to primary user (PUs) and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high peak to average power ratio (PAPR) phenomenon is a common issue in the majority of the multicarrier modulation systems and thus OFDM/OQAM is no exception in this case.\u0000\u0000\u0000Findings\u0000Therefore, this paper aims to examine the effect of integrating the Walsh–Hadamard Transform (WHT) on the power spectral density and investigates the problem of PAPR in the WHT/OQAM system.\u0000\u0000\u0000Originality/value\u0000Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from SUs to PUs and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high PAPR phenomenon is a common issue in the majority of the multicarrier modulation systems thus OFDM/OQAM is no exception in this case.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129497086","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 : 2020-11-30DOI: 10.1108/ijpcc-10-2020-0169
R. Babu, A. Balaji, K. KavinKumar, Dr Sudhanshu Maurya, N. SaravanaKumarM.
Purpose The purpose of the study is to highlight the potential of the sensor based smartphone in assessing the covid-19 cases. Coronavirus disease 2019 (COVID-19) is a noxious pandemic affecting the respiratory system of the human and leading to the severe acute respiratory syndrome, sometimes causing death. COVID-19 is a highly transmittable disease that spreads from an infected person to others. In this regard, a smart device is required to monitor the COVID-19 infected patients by which widespread pandemic can be reduced. Design/methodology/approach In this paper, an electrochemical sensor-enabled smartphone has been developed to assess the COVID-19 infected patients. The data-enabled smartphone uses the Internet of Things (IoT) to share the details with the other devices. The electrochemical sensor enables the smartphone to evaluate the ribonucleic acid (RNA) of COVID-19 without the nucleic acid and feeds the data into the data server by using a smartphone. Findings The obtained result identifies the infected person by using the portable electrochemical sensor-enabled smartphone, and the data is feed into the data server using the IoT. Whenever an infected person moves outside the restricted zone, the data server gives information to the concerned department. Originality/value The developed electrochemical sensor-enabled smartphone gives an accuracy of 81% in assessing the COVID-19 cases. Thus, through the developed approach, a COVID-19 infected person can be identified and the spread can be minimized.
{"title":"Smartphone-based electrochemical sensor for assessing COVID-19 infected patients","authors":"R. Babu, A. Balaji, K. KavinKumar, Dr Sudhanshu Maurya, N. SaravanaKumarM.","doi":"10.1108/ijpcc-10-2020-0169","DOIUrl":"https://doi.org/10.1108/ijpcc-10-2020-0169","url":null,"abstract":"\u0000Purpose\u0000The purpose of the study is to highlight the potential of the sensor based smartphone in assessing the covid-19 cases. Coronavirus disease 2019 (COVID-19) is a noxious pandemic affecting the respiratory system of the human and leading to the severe acute respiratory syndrome, sometimes causing death. COVID-19 is a highly transmittable disease that spreads from an infected person to others. In this regard, a smart device is required to monitor the COVID-19 infected patients by which widespread pandemic can be reduced.\u0000\u0000\u0000Design/methodology/approach\u0000In this paper, an electrochemical sensor-enabled smartphone has been developed to assess the COVID-19 infected patients. The data-enabled smartphone uses the Internet of Things (IoT) to share the details with the other devices. The electrochemical sensor enables the smartphone to evaluate the ribonucleic acid (RNA) of COVID-19 without the nucleic acid and feeds the data into the data server by using a smartphone.\u0000\u0000\u0000Findings\u0000The obtained result identifies the infected person by using the portable electrochemical sensor-enabled smartphone, and the data is feed into the data server using the IoT. Whenever an infected person moves outside the restricted zone, the data server gives information to the concerned department.\u0000\u0000\u0000Originality/value\u0000The developed electrochemical sensor-enabled smartphone gives an accuracy of 81% in assessing the COVID-19 cases. Thus, through the developed approach, a COVID-19 infected person can be identified and the spread can be minimized.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115853351","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 : 2020-11-30DOI: 10.1108/ijpcc-04-2020-0030
D. Chandramohan, A. Dumka, V. Dhilipkumar, L. Jayakumar
Purpose This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more. Design/methodology/approach The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand. Findings The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities. Originality/value There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.
{"title":"Data dissemination for green-VANETs communication: an opportunistic optimization approach","authors":"D. Chandramohan, A. Dumka, V. Dhilipkumar, L. Jayakumar","doi":"10.1108/ijpcc-04-2020-0030","DOIUrl":"https://doi.org/10.1108/ijpcc-04-2020-0030","url":null,"abstract":"\u0000Purpose\u0000This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more.\u0000\u0000\u0000Design/methodology/approach\u0000The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand.\u0000\u0000\u0000Findings\u0000The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities.\u0000\u0000\u0000Originality/value\u0000There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125912933","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 : 2020-11-30DOI: 10.1108/ijpcc-09-2020-0146
R. Karthickraja, R. Kumar, S. Kirubakaran, L. JeganAntonyMarcilin, R. Manikandan
Purpose The purpose of the research work is to focus on the deployment of wearable sensors in addressing symptom Analysis in the Internet of Things (IoT) environment to reduce human interaction in this epidemic circumstances. Design/methodology/approach COVID-19 pandemic has distracted the world into an unaccustomed situation in the recent past. The pandemic has pulled us toward data harnessing and focused on the digital framework to monitor the COVID-19 cases seriously, as there is an urge to detect the disease, wearable sensors aided in predicting the incidence of COVID-19. This COVID-19 has initiated many technologies like cloud computing, edge computing, IoT devices, artificial intelligence. The deployment of sensor devices has tremendously increased. Similarly, IoT applications have witnessed many innovations in addressing the COVID-19 crisis. State-of-the-art focuses on IoT factors and symptom features deploying wearable sensors for predicting the COVID-19 cases. The working model incorporates wearable devices, clinical therapy, monitoring the symptom, testing suspected cases and elements of IoT. The present research sermonizes on symptom analysis and risk factors that influence the coronavirus by acknowledging the respiration rate and oxygen saturation (SpO2). Experiments were proposed to carry out with chi-Square distribution with independent measures t-Test. Findings IoT devices today play a vital role in analyzing COVID-19 cases effectively. The research work incorporates wearable sensors, human interpretation and Web server, statistical analysis with IoT factors, data management and clinical therapy. The research is initiated with data collection from wearable sensors, data retrieval from the cloud server, pre-processing and categorizing based on age and gender information. IoT devices contribute to tracking and monitoring the patients for prerequisites. The suspected cases are tested based on symptom factors such as temperature, oxygen level (SPO2), respiratory rate variation and continuous investigation, and these demographic factors are taken for analyzed based on the gender and age factors of the collected data with the IoT factors thus presenting a cutting edge construction design in clinical trials. Originality/value The contemporary study comprehends 238 data through wearable sensors and transmitted through an IoT gateway to the cloud server. Few data are considered as outliers and discarded for analysis. Only 208 data are contemplated for statistical examination. These filtered data are proclaimed using chi-square distribution with t-test measure correlating the IoT factors. The research also interprets the demographic features that induce IoT factors using alpha and beta parameters showing the equal variance with the degree of freedom (df = 206).
{"title":"COVID-19 prediction and symptom analysis using wearable sensors and IoT","authors":"R. Karthickraja, R. Kumar, S. Kirubakaran, L. JeganAntonyMarcilin, R. Manikandan","doi":"10.1108/ijpcc-09-2020-0146","DOIUrl":"https://doi.org/10.1108/ijpcc-09-2020-0146","url":null,"abstract":"\u0000Purpose\u0000The purpose of the research work is to focus on the deployment of wearable sensors in addressing symptom Analysis in the Internet of Things (IoT) environment to reduce human interaction in this epidemic circumstances.\u0000\u0000\u0000Design/methodology/approach\u0000COVID-19 pandemic has distracted the world into an unaccustomed situation in the recent past. The pandemic has pulled us toward data harnessing and focused on the digital framework to monitor the COVID-19 cases seriously, as there is an urge to detect the disease, wearable sensors aided in predicting the incidence of COVID-19. This COVID-19 has initiated many technologies like cloud computing, edge computing, IoT devices, artificial intelligence. The deployment of sensor devices has tremendously increased. Similarly, IoT applications have witnessed many innovations in addressing the COVID-19 crisis. State-of-the-art focuses on IoT factors and symptom features deploying wearable sensors for predicting the COVID-19 cases. The working model incorporates wearable devices, clinical therapy, monitoring the symptom, testing suspected cases and elements of IoT. The present research sermonizes on symptom analysis and risk factors that influence the coronavirus by acknowledging the respiration rate and oxygen saturation (SpO2). Experiments were proposed to carry out with chi-Square distribution with independent measures t-Test.\u0000\u0000\u0000Findings\u0000IoT devices today play a vital role in analyzing COVID-19 cases effectively. The research work incorporates wearable sensors, human interpretation and Web server, statistical analysis with IoT factors, data management and clinical therapy. The research is initiated with data collection from wearable sensors, data retrieval from the cloud server, pre-processing and categorizing based on age and gender information. IoT devices contribute to tracking and monitoring the patients for prerequisites. The suspected cases are tested based on symptom factors such as temperature, oxygen level (SPO2), respiratory rate variation and continuous investigation, and these demographic factors are taken for analyzed based on the gender and age factors of the collected data with the IoT factors thus presenting a cutting edge construction design in clinical trials.\u0000\u0000\u0000Originality/value\u0000The contemporary study comprehends 238 data through wearable sensors and transmitted through an IoT gateway to the cloud server. Few data are considered as outliers and discarded for analysis. Only 208 data are contemplated for statistical examination. These filtered data are proclaimed using chi-square distribution with t-test measure correlating the IoT factors. The research also interprets the demographic features that induce IoT factors using alpha and beta parameters showing the equal variance with the degree of freedom (df = 206).\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122630673","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 : 2020-11-20DOI: 10.1108/ijpcc-10-2020-0176
Hoang-Long Cao, Huynh Nguyen, Trong Hieu Luu, H. Vu, Diep Pham, Van Thi Ngoc Vu, Hoang Hai Le, Duy Xuan Bach Nguyen, T. T. Truong, Hoang D. Nguyen, Chi-Ngon Nguyen
Purpose COVID-19 hits every country’s health-care system and economy. There is a trend toward using automation technology in response to the COVID-19 crisis not only in developed countries but also in those with lower levels of technology development. However, current studies mainly focus on the world level, and only a few ones report deployments at the country level. The purpose of this paper is to investigate the use of automation solutions in Vietnam with locally available materials mainly in the first wave from January to July 2020. Design/methodology/approach The authors collected COVID-related automation solutions during the first wave of COVID-19 in Vietnam from January to July 2020 through a search process. The analysis and insights of a panel consisting of various disciplines (i.e. academia, health care, government, entrepreneur and media) aim at providing a clear picture of how and to what extent these solutions have been deployed. Findings The authors found seven groups of solutions from low to high research and development (R&D) levels deployed across the country with various funding sources. Low R&D solutions were widely spread owing to simplicity and affordability. High R&D solutions were mainly deployed in big cities. Most of the solutions were deployed during the first phases when international supply chains were limited with a significant contribution of the media. Higher R&D solutions have opportunities to be deployed in the reopening phase. However, challenges can be listed as limited interdisciplinary research teams, market demand, the local supporting industry, end-user validation and social-ethical issues. Originality/value To the authors’ best knowledge, this is the first study analyzing the use of automation technology in response to COVID-19 in Vietnam and also in a country in Southeast Asia. Lessons learned from these current deployments are useful for future emerging infectious diseases. The reality of Vietnam’s automation solutions in response to COVID-19 might be a reference for other developing countries with similar social-economic circumstances and contributes to the global picture of how different countries adopt technology to combat COVID-19.
{"title":"Localized automation solutions in response to the first wave of COVID-19: a story from Vietnam","authors":"Hoang-Long Cao, Huynh Nguyen, Trong Hieu Luu, H. Vu, Diep Pham, Van Thi Ngoc Vu, Hoang Hai Le, Duy Xuan Bach Nguyen, T. T. Truong, Hoang D. Nguyen, Chi-Ngon Nguyen","doi":"10.1108/ijpcc-10-2020-0176","DOIUrl":"https://doi.org/10.1108/ijpcc-10-2020-0176","url":null,"abstract":"\u0000Purpose\u0000COVID-19 hits every country’s health-care system and economy. There is a trend toward using automation technology in response to the COVID-19 crisis not only in developed countries but also in those with lower levels of technology development. However, current studies mainly focus on the world level, and only a few ones report deployments at the country level. The purpose of this paper is to investigate the use of automation solutions in Vietnam with locally available materials mainly in the first wave from January to July 2020.\u0000\u0000\u0000Design/methodology/approach\u0000The authors collected COVID-related automation solutions during the first wave of COVID-19 in Vietnam from January to July 2020 through a search process. The analysis and insights of a panel consisting of various disciplines (i.e. academia, health care, government, entrepreneur and media) aim at providing a clear picture of how and to what extent these solutions have been deployed.\u0000\u0000\u0000Findings\u0000The authors found seven groups of solutions from low to high research and development (R&D) levels deployed across the country with various funding sources. Low R&D solutions were widely spread owing to simplicity and affordability. High R&D solutions were mainly deployed in big cities. Most of the solutions were deployed during the first phases when international supply chains were limited with a significant contribution of the media. Higher R&D solutions have opportunities to be deployed in the reopening phase. However, challenges can be listed as limited interdisciplinary research teams, market demand, the local supporting industry, end-user validation and social-ethical issues.\u0000\u0000\u0000Originality/value\u0000To the authors’ best knowledge, this is the first study analyzing the use of automation technology in response to COVID-19 in Vietnam and also in a country in Southeast Asia. Lessons learned from these current deployments are useful for future emerging infectious diseases. The reality of Vietnam’s automation solutions in response to COVID-19 might be a reference for other developing countries with similar social-economic circumstances and contributes to the global picture of how different countries adopt technology to combat COVID-19.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114718758","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 : 2020-11-13DOI: 10.1108/ijpcc-08-2020-0115
Sitharthan Ramachandran, S. Dhanabalan, Rajesh Mehta, M. Karthikeyan, I. Raglend, J. Edward, R. RajaSingh, R. Kumar
Purpose Corona Virus Disease 2019 (COVID-19) is a deadly virus named after severe acute respiratory syndrome coronavirus 2; it affects the respiratory system of the human and sometimes leads to death. The COVID-19 mainly attacks the person with previous lung diseases; the major cause of lung diseases is the exposure to nitrogen dioxide (NO2) for a longer duration. NO2 is a gaseous air pollutant caused as an outcome of the vehicles, industrial smoke and other combustion processes. Exposure of NO2 for long-term leads to the risk of respiratory and cardiovascular diseases and sometimes leads to fatality. This paper aims to analyze the NO2 level impact in India during pre- and post-COVID-19 lockdown. The study also examines the relationship between the fatality rate of humans because of exposure to NO2 and COVID-19. Design/methodology/approach Spatial analysis has been conducted in India based on the mortality rate caused by the COVID-19 using the data obtained through Internet of Medical things. Meanwhile, the mortality rate because of the exposure of NO2 has been conducted in India to analyze the relationship. Further, NO2 level assessment is carried out using Copernicus Sentinel-5P satellite data. Moreover, aerosol optical depth analysis has been carried out based on NASA’s Earth Observing System data. Findings The results indicate that NO2 level has dropped 20-year low because of the COVID-19 lockdown. The results also determine that the mortality rate because of long-time exposure to NO2 is higher than COVID-19 and the mortality rate because of COVID-19 may be a circumlocutory effect owing to the inhalation of NO2. Originality/value Using the proposed approach, the COVID-19 spread can be identified by knowing the air pollution in major cities. The research also identifies that COVID-19 may have an effect because of the inhalation of NO2, which can severe the COVID-19 in the human body.
{"title":"Assessing nitrogen dioxide (NO2) impact on health pre- and post-COVID-19 pandemic using IoT in India","authors":"Sitharthan Ramachandran, S. Dhanabalan, Rajesh Mehta, M. Karthikeyan, I. Raglend, J. Edward, R. RajaSingh, R. Kumar","doi":"10.1108/ijpcc-08-2020-0115","DOIUrl":"https://doi.org/10.1108/ijpcc-08-2020-0115","url":null,"abstract":"Purpose Corona Virus Disease 2019 (COVID-19) is a deadly virus named after severe acute respiratory syndrome coronavirus 2; it affects the respiratory system of the human and sometimes leads to death. The COVID-19 mainly attacks the person with previous lung diseases; the major cause of lung diseases is the exposure to nitrogen dioxide (NO2) for a longer duration. NO2 is a gaseous air pollutant caused as an outcome of the vehicles, industrial smoke and other combustion processes. Exposure of NO2 for long-term leads to the risk of respiratory and cardiovascular diseases and sometimes leads to fatality. This paper aims to analyze the NO2 level impact in India during pre- and post-COVID-19 lockdown. The study also examines the relationship between the fatality rate of humans because of exposure to NO2 and COVID-19. Design/methodology/approach Spatial analysis has been conducted in India based on the mortality rate caused by the COVID-19 using the data obtained through Internet of Medical things. Meanwhile, the mortality rate because of the exposure of NO2 has been conducted in India to analyze the relationship. Further, NO2 level assessment is carried out using Copernicus Sentinel-5P satellite data. Moreover, aerosol optical depth analysis has been carried out based on NASA’s Earth Observing System data. Findings The results indicate that NO2 level has dropped 20-year low because of the COVID-19 lockdown. The results also determine that the mortality rate because of long-time exposure to NO2 is higher than COVID-19 and the mortality rate because of COVID-19 may be a circumlocutory effect owing to the inhalation of NO2. Originality/value Using the proposed approach, the COVID-19 spread can be identified by knowing the air pollution in major cities. The research also identifies that COVID-19 may have an effect because of the inhalation of NO2, which can severe the COVID-19 in the human body.","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130333398","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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