Pub Date : 2022-08-05DOI: 10.1108/ijpcc-07-2020-0085
Jitender Tanwar, S. Sharma, M. Mittal
Purpose Drones are used in several purposes including examining areas, mapping surroundings and rescue mission operations. During these tasks, they could encounter compound surroundings having multiple obstacles, acute edges and deadlocks. The purpose of this paper is to propose an obstacle dodging technique required to move the drones autonomously and generate the obstacle's map of an unknown place dynamically. Design/methodology/approach Therefore, an obstacle dodging technique is essentially required to move autonomously. The automaton of drones requires complicated vision sensors and a high computing force. During this research, a methodology that uses two basic ultrasonic-oriented proximity sensors placed at the center of the drone and applies neural control using synaptic plasticity for dynamic obstacle avoidance is proposed. The two-neuron intermittent system has been established by neural control. The synaptic plasticity is used to find turning angles from different viewpoints with immediate remembrance, so it helps in decision-making for a drone. Hence, the automaton will be able to travel around and modify its angle of turning for escaping objects during the route in unknown surroundings with narrow junctions and dead ends. Furthermore, wherever an obstacle is detected during the route, the coordinate information is communicated using RESTful Web service to an android app and an obstacle map is generated according to the information sent by the drone. In this research, the drone is successfully designed and automated and an obstacle map using the V-REP simulation environment is generated. Findings Simulation results show that the drone effectively moves and turns around the obstacles and the experiment of using web services with the drone is also successful in generating the obstacle's map dynamically. Originality/value The obstacle map generated by autonomous drone is useful in many applications such as examining fields, mapping surroundings and rescue mission operations.
{"title":"Designing obstacle's map of an unknown place using autonomous drone navigation and web services","authors":"Jitender Tanwar, S. Sharma, M. Mittal","doi":"10.1108/ijpcc-07-2020-0085","DOIUrl":"https://doi.org/10.1108/ijpcc-07-2020-0085","url":null,"abstract":"\u0000Purpose\u0000Drones are used in several purposes including examining areas, mapping surroundings and rescue mission operations. During these tasks, they could encounter compound surroundings having multiple obstacles, acute edges and deadlocks. The purpose of this paper is to propose an obstacle dodging technique required to move the drones autonomously and generate the obstacle's map of an unknown place dynamically.\u0000\u0000\u0000Design/methodology/approach\u0000Therefore, an obstacle dodging technique is essentially required to move autonomously. The automaton of drones requires complicated vision sensors and a high computing force. During this research, a methodology that uses two basic ultrasonic-oriented proximity sensors placed at the center of the drone and applies neural control using synaptic plasticity for dynamic obstacle avoidance is proposed. The two-neuron intermittent system has been established by neural control. The synaptic plasticity is used to find turning angles from different viewpoints with immediate remembrance, so it helps in decision-making for a drone. Hence, the automaton will be able to travel around and modify its angle of turning for escaping objects during the route in unknown surroundings with narrow junctions and dead ends. Furthermore, wherever an obstacle is detected during the route, the coordinate information is communicated using RESTful Web service to an android app and an obstacle map is generated according to the information sent by the drone. In this research, the drone is successfully designed and automated and an obstacle map using the V-REP simulation environment is generated.\u0000\u0000\u0000Findings\u0000Simulation results show that the drone effectively moves and turns around the obstacles and the experiment of using web services with the drone is also successful in generating the obstacle's map dynamically.\u0000\u0000\u0000Originality/value\u0000The obstacle map generated by autonomous drone is useful in many applications such as examining fields, mapping surroundings and rescue mission operations.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121631206","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 : 2022-07-14DOI: 10.1108/ijpcc-05-2021-0111
N. A., Sajimon Abraham
Purpose A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of their trace such as stay points, revisit locations and meeting points is important. More trained staffs and tools are required under the traditional system of contact tracing. At the time of the spiralling patient count, the time-bound tracing of primary and secondary contacts may not be possible, and there are chances of human errors as well. In this context, the purpose of this paper is to propose an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. Design/methodology/approach Pandemic situations push the world into existential crises. In this context, this paper proposes an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. By exploring the daily mobility and activities of the general public, the system identifies multiple levels of contacts with respect to an infected person and extracts semantic information by considering vital factors that can induce virus spread. It grades different geographic locations according to a measure called weightage of participation so that vulnerable locations can be easily identified. This paper gives directions on the advantages of using spatio-temporal aggregate queries for extracting general characteristics of social mobility. The system also facilitates room for the generation of various information by combing through the medical reports of the patients. Findings It is identified that context of movement is important; hence, the existing SemTraClus algorithm is modified by accounting for four important factors such as stay point, contact presence, stay time of primary contacts and waypoint severity. The priority level can be reconfigured according to the interest of authority. This approach reduces the overwhelming task of contact tracing. Different functionalities provided by the system are also explained. As the real data set is not available, experiments are conducted with similar data and results are shown for different types of journeys in different geographical locations. The proposed method efficiently handles computational movement and activity analysis by incorporating various relevant semantics of trajectories. The incorporation of cluster-ba
{"title":"Contact tracing and mobility pattern detection during pandemics - a trajectory cluster based approach","authors":"N. A., Sajimon Abraham","doi":"10.1108/ijpcc-05-2021-0111","DOIUrl":"https://doi.org/10.1108/ijpcc-05-2021-0111","url":null,"abstract":"\u0000Purpose\u0000A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of their trace such as stay points, revisit locations and meeting points is important. More trained staffs and tools are required under the traditional system of contact tracing. At the time of the spiralling patient count, the time-bound tracing of primary and secondary contacts may not be possible, and there are chances of human errors as well. In this context, the purpose of this paper is to propose an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations.\u0000\u0000\u0000Design/methodology/approach\u0000Pandemic situations push the world into existential crises. In this context, this paper proposes an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. By exploring the daily mobility and activities of the general public, the system identifies multiple levels of contacts with respect to an infected person and extracts semantic information by considering vital factors that can induce virus spread. It grades different geographic locations according to a measure called weightage of participation so that vulnerable locations can be easily identified. This paper gives directions on the advantages of using spatio-temporal aggregate queries for extracting general characteristics of social mobility. The system also facilitates room for the generation of various information by combing through the medical reports of the patients.\u0000\u0000\u0000Findings\u0000It is identified that context of movement is important; hence, the existing SemTraClus algorithm is modified by accounting for four important factors such as stay point, contact presence, stay time of primary contacts and waypoint severity. The priority level can be reconfigured according to the interest of authority. This approach reduces the overwhelming task of contact tracing. Different functionalities provided by the system are also explained. As the real data set is not available, experiments are conducted with similar data and results are shown for different types of journeys in different geographical locations. The proposed method efficiently handles computational movement and activity analysis by incorporating various relevant semantics of trajectories. The incorporation of cluster-ba","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126945831","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 : 2022-06-28DOI: 10.1108/ijpcc-10-2021-0269
Linus Wilson
Purpose This study aims to analyze whether average video watch time or click-through rates (CTR) on YouTube videos are more closely associated with high numbers of views per subscriber using linear regressions. Design/methodology/approach In 2018, YouTube began releasing CTR data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. To the best of the author’s knowledge, this is the first academic study looking at that CTR data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube? Findings The author analyzed new video releases on YouTube. This paper finds almost no or limited evidence that higher percent audience retention or total average watch time per view, respectively, are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views. Originality/value The author knows no other study that tests the relative importance of CTR or watch time per view in predicting views for new videos on YouTube.
{"title":"The relative importance of click-through rates (CTR) versus watch time for YouTube views","authors":"Linus Wilson","doi":"10.1108/ijpcc-10-2021-0269","DOIUrl":"https://doi.org/10.1108/ijpcc-10-2021-0269","url":null,"abstract":"\u0000Purpose\u0000This study aims to analyze whether average video watch time or click-through rates (CTR) on YouTube videos are more closely associated with high numbers of views per subscriber using linear regressions.\u0000\u0000\u0000Design/methodology/approach\u0000In 2018, YouTube began releasing CTR data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. To the best of the author’s knowledge, this is the first academic study looking at that CTR data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube?\u0000\u0000\u0000Findings\u0000The author analyzed new video releases on YouTube. This paper finds almost no or limited evidence that higher percent audience retention or total average watch time per view, respectively, are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views.\u0000\u0000\u0000Originality/value\u0000The author knows no other study that tests the relative importance of CTR or watch time per view in predicting views for new videos on YouTube.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128843344","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 : 2022-06-23DOI: 10.1108/ijpcc-07-2022-315
Rajakumar Chellappan, Chow Chee Onn, D. Pelusi
{"title":"Guest editorial: Hyperscale computing for edge of things and pervasive intelligence","authors":"Rajakumar Chellappan, Chow Chee Onn, D. Pelusi","doi":"10.1108/ijpcc-07-2022-315","DOIUrl":"https://doi.org/10.1108/ijpcc-07-2022-315","url":null,"abstract":"","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132642076","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 : 2022-05-27DOI: 10.1108/ijpcc-12-2021-0307
Devid Jegerson, M. Hussain
Purpose This study aims to identify the acceptance factors in the UAE for the digital mobile payment market, introduces a new hierarchical framework based on the continuation intention factors and prioritises the importance of the acceptance criteria and sub-criteria. Design/methodology/approach The measurement of acceptance factors in payment systems is a complex and unstructured topic involving many criteria and sub-criteria, which requires breaking the problem down into several components organised in a hierarchical multi-level form. The analytic hierarchy process (AHP) methodology manages the complexity of multi-criteria decision-making processes based on a new set of criteria connected to the adoption and continuance intention factors. Findings The AHP framework developed a ranking of 18 sustainability sub-factors based on evaluations by experienced payment professionals. Research limitations/implications The future directions of the research would be to investigate the impact of dynamic capabilities on the resilience of retail service networks, especially during COVID-19, where supply and demand are highly indeterminate. Practical implications Through successive stages of data collection, measurement analysis and refinement, the contribution of this research is a reliable and valid framework that can be used to conceptualise and prioritise sustainability strategies in payment management. Originality/value Given the lowest mobile payment products penetration rates of the UAE and the scarcity of literature on this topic, this study aims to contribute to the knowledge by including UTAUT, the IS success model and the impact of COVID-19 as adoption and continuance intention factor in the digital mobile payment case in the UAE.
{"title":"A framework for measuring the adoption factors in digital mobile payments in the COVID-19 era","authors":"Devid Jegerson, M. Hussain","doi":"10.1108/ijpcc-12-2021-0307","DOIUrl":"https://doi.org/10.1108/ijpcc-12-2021-0307","url":null,"abstract":"\u0000Purpose\u0000This study aims to identify the acceptance factors in the UAE for the digital mobile payment market, introduces a new hierarchical framework based on the continuation intention factors and prioritises the importance of the acceptance criteria and sub-criteria.\u0000\u0000\u0000Design/methodology/approach\u0000The measurement of acceptance factors in payment systems is a complex and unstructured topic involving many criteria and sub-criteria, which requires breaking the problem down into several components organised in a hierarchical multi-level form. The analytic hierarchy process (AHP) methodology manages the complexity of multi-criteria decision-making processes based on a new set of criteria connected to the adoption and continuance intention factors.\u0000\u0000\u0000Findings\u0000The AHP framework developed a ranking of 18 sustainability sub-factors based on evaluations by experienced payment professionals.\u0000\u0000\u0000Research limitations/implications\u0000The future directions of the research would be to investigate the impact of dynamic capabilities on the resilience of retail service networks, especially during COVID-19, where supply and demand are highly indeterminate.\u0000\u0000\u0000Practical implications\u0000Through successive stages of data collection, measurement analysis and refinement, the contribution of this research is a reliable and valid framework that can be used to conceptualise and prioritise sustainability strategies in payment management.\u0000\u0000\u0000Originality/value\u0000Given the lowest mobile payment products penetration rates of the UAE and the scarcity of literature on this topic, this study aims to contribute to the knowledge by including UTAUT, the IS success model and the impact of COVID-19 as adoption and continuance intention factor in the digital mobile payment case in the UAE.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125767307","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 : 2022-04-28DOI: 10.1108/ijpcc-02-2022-0053
K. Nagarajaiah, Supriya Maganahalli Chandramouli, Lokesh Malavalli Ramakrishna
Purpose Coronavirus disease 2019 is one of the novel diseases formed by a dreadful virus called Severe Acute Respiratory Syndrome Coronavirus 2. Various countries are affected by this viral disease, and many countries declare a lockdown with several rules and conditions. To prevent this rapid viral transmission, various researchers have introduced different mobile applications. This paper aims to study issues like viral transmission, mortality rates, vaccination rates, etc. and also provides suitable solutions based on the statistical analysis with the assistance of the Six-Sigma Define-Measure-Analyse-Improve-Control (DMAIC) concept. Design/methodology/approach Statistical analysis is done for different countries, and the required solutions are provided by using the DMAIC procedure. This application has the ability to represent the current risk status of the user and notify them to secure themselves. Findings The proposed work suggests the Aarogya Setu application to prevent large viral transmission by affording many preventive measures. This application also issues the current risk status of each individual user. Hence, it gives improved results in avoiding high viral transmission. Originality/value The proposed six-sigma DMAIC concept also affords the control measures to prevent viral transmission. Hence, the suggested application has the highest chance of avoiding the rapid viral transmission.
{"title":"Six sigma DMAIC approach based mobile application for statistical analysis of COVID-19 data","authors":"K. Nagarajaiah, Supriya Maganahalli Chandramouli, Lokesh Malavalli Ramakrishna","doi":"10.1108/ijpcc-02-2022-0053","DOIUrl":"https://doi.org/10.1108/ijpcc-02-2022-0053","url":null,"abstract":"\u0000Purpose\u0000Coronavirus disease 2019 is one of the novel diseases formed by a dreadful virus called Severe Acute Respiratory Syndrome Coronavirus 2. Various countries are affected by this viral disease, and many countries declare a lockdown with several rules and conditions. To prevent this rapid viral transmission, various researchers have introduced different mobile applications. This paper aims to study issues like viral transmission, mortality rates, vaccination rates, etc. and also provides suitable solutions based on the statistical analysis with the assistance of the Six-Sigma Define-Measure-Analyse-Improve-Control (DMAIC) concept.\u0000\u0000\u0000Design/methodology/approach\u0000Statistical analysis is done for different countries, and the required solutions are provided by using the DMAIC procedure. This application has the ability to represent the current risk status of the user and notify them to secure themselves.\u0000\u0000\u0000Findings\u0000The proposed work suggests the Aarogya Setu application to prevent large viral transmission by affording many preventive measures. This application also issues the current risk status of each individual user. Hence, it gives improved results in avoiding high viral transmission.\u0000\u0000\u0000Originality/value\u0000The proposed six-sigma DMAIC concept also affords the control measures to prevent viral transmission. Hence, the suggested application has the highest chance of avoiding the rapid viral transmission.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130266327","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 : 2022-03-21DOI: 10.1108/ijpcc-05-2021-0122
S. Datta, Utkarsh Utkarsh
Purpose The behaviour of audience, consuming video entertainment, has changed intensely over the years. Lately, the consumers have increasingly preferred to watch video programs, through video-on-demand services through over-the-top medium. The service is novel and the consumer’s perception of the service quality is not well explored. As extant literature considers service quality as the construct to determine the sustained growth of a service, the present study has attempted to explore the dimensions to measure service quality of video-on-demand services. Design/methodology/approach The authors conducted qualitative, semi-structured interviews and focus group discussions amongst the user of the video-on-demand service. The qualitative data was content analysed to furnish thematic dimensions. Findings The study reveals thematic attributes perceived as dimensions to measure service quality of video-on-demand services. Research limitations/implications Considering the exploratory nature of the study, the themes proposed might seem nascent. Hence, it was the authors’ discretion to stop expanding the respondent sample to avoid data saturation. A quantitative establishment of the service quality dimensions was beyond the scope of the current research and would follow in a different study. Originality/value The objective of the study is to qualitatively explore service quality dimensions of video-on-demand services. In pursuit of that, the current study explored the consumers’ excerpts, content analysed the data and furnished several themes perceived as service quality dimensions in this context. Such a detailed approach is uncommon in this context.
{"title":"A qualitative study proposing service quality dimensions for video-on-demand services through over-the-top medium","authors":"S. Datta, Utkarsh Utkarsh","doi":"10.1108/ijpcc-05-2021-0122","DOIUrl":"https://doi.org/10.1108/ijpcc-05-2021-0122","url":null,"abstract":"\u0000Purpose\u0000The behaviour of audience, consuming video entertainment, has changed intensely over the years. Lately, the consumers have increasingly preferred to watch video programs, through video-on-demand services through over-the-top medium. The service is novel and the consumer’s perception of the service quality is not well explored. As extant literature considers service quality as the construct to determine the sustained growth of a service, the present study has attempted to explore the dimensions to measure service quality of video-on-demand services.\u0000\u0000\u0000Design/methodology/approach\u0000The authors conducted qualitative, semi-structured interviews and focus group discussions amongst the user of the video-on-demand service. The qualitative data was content analysed to furnish thematic dimensions.\u0000\u0000\u0000Findings\u0000The study reveals thematic attributes perceived as dimensions to measure service quality of video-on-demand services.\u0000\u0000\u0000Research limitations/implications\u0000Considering the exploratory nature of the study, the themes proposed might seem nascent. Hence, it was the authors’ discretion to stop expanding the respondent sample to avoid data saturation. A quantitative establishment of the service quality dimensions was beyond the scope of the current research and would follow in a different study.\u0000\u0000\u0000Originality/value\u0000The objective of the study is to qualitatively explore service quality dimensions of video-on-demand services. In pursuit of that, the current study explored the consumers’ excerpts, content analysed the data and furnished several themes perceived as service quality dimensions in this context. Such a detailed approach is uncommon in this context.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128976917","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 : 2022-03-10DOI: 10.1108/ijpcc-12-2021-0314
J. Boga, D. V
Purpose For achieving the profitable human activity recognition (HAR) method, this paper solves the HAR problem under wireless body area network (WBAN) using a developed ensemble learning approach. The purpose of this study is,to solve the HAR problem under WBAN using a developed ensemble learning approach for achieving the profitable HAR method. There are three data sets used for this HAR in WBAN, namely, human activity recognition using smartphones, wireless sensor data mining and Kaggle. The proposed model undergoes four phases, namely, “pre-processing, feature extraction, feature selection and classification.” Here, the data can be preprocessed by artifacts removal and median filtering techniques. Then, the features are extracted by techniques such as “t-Distributed Stochastic Neighbor Embedding”, “Short-time Fourier transform” and statistical approaches. The weighted optimal feature selection is considered as the next step for selecting the important features based on computing the data variance of each class. This new feature selection is achieved by the hybrid coyote Jaya optimization (HCJO). Finally, the meta-heuristic-based ensemble learning approach is used as a new recognition approach with three classifiers, namely, “support vector machine (SVM), deep neural network (DNN) and fuzzy classifiers.” Experimental analysis is performed. Design/methodology/approach The proposed HCJO algorithm was developed for optimizing the membership function of fuzzy, iteration limit of SVM and hidden neuron count of DNN for getting superior classified outcomes and to enhance the performance of ensemble classification. Findings The accuracy for enhanced HAR model was pretty high in comparison to conventional models, i.e. higher than 6.66% to fuzzy, 4.34% to DNN, 4.34% to SVM, 7.86% to ensemble and 6.66% to Improved Sealion optimization algorithm-Attention Pyramid-Convolutional Neural Network-AP-CNN, respectively. Originality/value The suggested HAR model with WBAN using HCJO algorithm is accurate and improves the effectiveness of the recognition.
{"title":"Human activity recognition in WBAN using ensemble model","authors":"J. Boga, D. V","doi":"10.1108/ijpcc-12-2021-0314","DOIUrl":"https://doi.org/10.1108/ijpcc-12-2021-0314","url":null,"abstract":"\u0000Purpose\u0000For achieving the profitable human activity recognition (HAR) method, this paper solves the HAR problem under wireless body area network (WBAN) using a developed ensemble learning approach. The purpose of this study is,to solve the HAR problem under WBAN using a developed ensemble learning approach for achieving the profitable HAR method. There are three data sets used for this HAR in WBAN, namely, human activity recognition using smartphones, wireless sensor data mining and Kaggle. The proposed model undergoes four phases, namely, “pre-processing, feature extraction, feature selection and classification.” Here, the data can be preprocessed by artifacts removal and median filtering techniques. Then, the features are extracted by techniques such as “t-Distributed Stochastic Neighbor Embedding”, “Short-time Fourier transform” and statistical approaches. The weighted optimal feature selection is considered as the next step for selecting the important features based on computing the data variance of each class. This new feature selection is achieved by the hybrid coyote Jaya optimization (HCJO). Finally, the meta-heuristic-based ensemble learning approach is used as a new recognition approach with three classifiers, namely, “support vector machine (SVM), deep neural network (DNN) and fuzzy classifiers.” Experimental analysis is performed.\u0000\u0000\u0000Design/methodology/approach\u0000The proposed HCJO algorithm was developed for optimizing the membership function of fuzzy, iteration limit of SVM and hidden neuron count of DNN for getting superior classified outcomes and to enhance the performance of ensemble classification.\u0000\u0000\u0000Findings\u0000The accuracy for enhanced HAR model was pretty high in comparison to conventional models, i.e. higher than 6.66% to fuzzy, 4.34% to DNN, 4.34% to SVM, 7.86% to ensemble and 6.66% to Improved Sealion optimization algorithm-Attention Pyramid-Convolutional Neural Network-AP-CNN, respectively.\u0000\u0000\u0000Originality/value\u0000The suggested HAR model with WBAN using HCJO algorithm is accurate and improves the effectiveness of the recognition.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554476","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 : 2022-02-15DOI: 10.1108/ijpcc-02-2021-0038
Minakshi Sharma, Rajneesh Kumar, Anurag Jain
Purpose During high demand for the virtualized resources in cloud environment, efficient task scheduling achieves the desired performance criteria by balancing the load in the system. Design/methodology/approach It is a task scheduling approach used for load balancing in cloud environment. Task scheduling in such an environment is used for the task execution on a suitable resource by considering some parameters and constraints to achieve performance. Findings The presented mechanism is an extension of the previous proposed work quality of service (QoS)-enabled join minimum loaded queue (JMLQ) (Sharma et al., 2019c). The proposed approach has been tested in the CloudSim simulator, and the results show that the proposed approach achieves better results in comparison to QoS-enabled JMLQ and its other variants in the cloud environment. Originality/value 90%
{"title":"A distributed quality of service-enabled load balancing approach for cloud environment","authors":"Minakshi Sharma, Rajneesh Kumar, Anurag Jain","doi":"10.1108/ijpcc-02-2021-0038","DOIUrl":"https://doi.org/10.1108/ijpcc-02-2021-0038","url":null,"abstract":"\u0000Purpose\u0000During high demand for the virtualized resources in cloud environment, efficient task scheduling achieves the desired performance criteria by balancing the load in the system.\u0000\u0000\u0000Design/methodology/approach\u0000It is a task scheduling approach used for load balancing in cloud environment. Task scheduling in such an environment is used for the task execution on a suitable resource by considering some parameters and constraints to achieve performance.\u0000\u0000\u0000Findings\u0000The presented mechanism is an extension of the previous proposed work quality of service (QoS)-enabled join minimum loaded queue (JMLQ) (Sharma et al., 2019c). The proposed approach has been tested in the CloudSim simulator, and the results show that the proposed approach achieves better results in comparison to QoS-enabled JMLQ and its other variants in the cloud environment.\u0000\u0000\u0000Originality/value\u000090%\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128656382","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 : 2022-02-14DOI: 10.1108/ijpcc-10-2021-0275
Syama R., M. C.
Purpose This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways incorporating current and historical information and contextual features. The interactions among the vehicles are modelled using long-short-term memory (LSTM). Design/methodology/approach Predicting the surrounding vehicles' behaviour is crucial in any Advanced Driver Assistance Systems (ADAS). To make a decision, any prediction models available in the literature consider the present and previous observations of the surrounding vehicles. These existing models failed to consider the contextual features such as traffic density that also affect the behaviour of the vehicles. To forecast the appropriate driving behaviour, a better context-aware learning method should be able to consider a distinct goal for each situation is more significant. Considering this, a deep learning-based model is proposed to predict the lane changing behaviours using past and current information of the vehicle and contextual features. The interactions among vehicles are modeled using an LSTM encoder-decoder. The different lane-changing behaviours of the vehicles are predicted and validated with the benchmarked data set NGSIM and the open data set Level 5. Findings The lane change behaviour prediction in ADAS is gaining popularity as it is crucial for safe travel in a mixed driving environment. This paper shows the prediction of maneuvers with a prediction window of 5 s using NGSIM and Level 5 data sets. The proposed method gives a prediction accuracy of 97% on average for all lane-change maneuvers for both the data sets. Originality/value This research presents a strategy for predicting autonomous vehicle behaviour based on contextual features. The paper focuses on deep learning techniques to assist the ADAS.
{"title":"Context-aware behaviour prediction for autonomous driving: a deep learning approach","authors":"Syama R., M. C.","doi":"10.1108/ijpcc-10-2021-0275","DOIUrl":"https://doi.org/10.1108/ijpcc-10-2021-0275","url":null,"abstract":"\u0000Purpose\u0000This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways incorporating current and historical information and contextual features. The interactions among the vehicles are modelled using long-short-term memory (LSTM).\u0000\u0000\u0000Design/methodology/approach\u0000Predicting the surrounding vehicles' behaviour is crucial in any Advanced Driver Assistance Systems (ADAS). To make a decision, any prediction models available in the literature consider the present and previous observations of the surrounding vehicles. These existing models failed to consider the contextual features such as traffic density that also affect the behaviour of the vehicles. To forecast the appropriate driving behaviour, a better context-aware learning method should be able to consider a distinct goal for each situation is more significant. Considering this, a deep learning-based model is proposed to predict the lane changing behaviours using past and current information of the vehicle and contextual features. The interactions among vehicles are modeled using an LSTM encoder-decoder. The different lane-changing behaviours of the vehicles are predicted and validated with the benchmarked data set NGSIM and the open data set Level 5.\u0000\u0000\u0000Findings\u0000The lane change behaviour prediction in ADAS is gaining popularity as it is crucial for safe travel in a mixed driving environment. This paper shows the prediction of maneuvers with a prediction window of 5 s using NGSIM and Level 5 data sets. The proposed method gives a prediction accuracy of 97% on average for all lane-change maneuvers for both the data sets.\u0000\u0000\u0000Originality/value\u0000This research presents a strategy for predicting autonomous vehicle behaviour based on contextual features. The paper focuses on deep learning techniques to assist the ADAS.\u0000","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132047224","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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