Celso M. de Melo, Benjamin T. Files, Kimberly A. Pollard, P. Khooshabeh
{"title":"Social Factors in Human-Agent Teaming","authors":"Celso M. de Melo, Benjamin T. Files, Kimberly A. Pollard, P. Khooshabeh","doi":"10.1201/9781003215349-6","DOIUrl":"https://doi.org/10.1201/9781003215349-6","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"37 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74612788","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}
{"title":"Cybersecurity in Smart and Intelligent Manufacturing Systems","authors":"Abbas Moallem","doi":"10.1201/9781003215349-8","DOIUrl":"https://doi.org/10.1201/9781003215349-8","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"15 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81165183","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}
{"title":"Agent Transparency","authors":"Jessie Y. C. Chen","doi":"10.1201/9781003215349-4","DOIUrl":"https://doi.org/10.1201/9781003215349-4","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"7 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81822079","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}
{"title":"User State Assessment in Adaptive Intelligent Systems","authors":"J. Schwarz","doi":"10.1201/9781003215349-3","DOIUrl":"https://doi.org/10.1201/9781003215349-3","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"73 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86389150","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}
Mohd Anwar, Hilda Goins, Tianyang Zhang, Xiangfeng Dai
{"title":"Human Elements in Machine Learning-Based Solutions to Cybersecurity","authors":"Mohd Anwar, Hilda Goins, Tianyang Zhang, Xiangfeng Dai","doi":"10.1201/9781003215349-7","DOIUrl":"https://doi.org/10.1201/9781003215349-7","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"58 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82746598","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}
{"title":"Smart Telehealth Systems for the Aging Population","authors":"Carl Markert, J. Moon, F. Sasangohar","doi":"10.1201/9781003215349-5","DOIUrl":"https://doi.org/10.1201/9781003215349-5","url":null,"abstract":"","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"29 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75619445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.21307/IJSSIS-2021-009
Sara El Ouadaa, Slimane Bah, A. Berrado
Abstract The reader-to-tag collision problem occurs when multiple readers try to access the same tag simultaneously. The traditional collision avoidance techniques such as RTS (request to send) and CTS (clear to send) are not applicable because a reader may communicate with multiple tags simultaneously. In this paper, we introduce a collaborative communication protocol to avoid reader-to-tag collisions using TDMA and clustering approaches. The protocol targets the RFID-WSN static systems arranged in a square grid topology, which we can find in different RFID applications such as warehouse stocktaking, parking cars, agricultural fields, and libraries. In such simple topologies, the other proposed reader collision solutions for general use of RFID systems are not efficient since they cannot avoid all possible collisions, and worse of that, some of them are not even detectable, which is intolerable for stocktaking applications. Moreover, they are complicated and heavy in resources, while read throughput is limited. Our protocol presents a simple solution for simple RFID systems with better performances. To validate the proposed protocol, we presented a model using the Process Meta Language (Promela), which is executed under the simple Promela interpreter (SPIN) model checker to verify the protocol properties as deadlocks and livelocks. Also as a proof of concept, we have done a first-step performance analysis using the java runtime.
{"title":"TDMA-clustering-based approach to avoid the reader-to-tag collision problem during the stocktaking process","authors":"Sara El Ouadaa, Slimane Bah, A. Berrado","doi":"10.21307/IJSSIS-2021-009","DOIUrl":"https://doi.org/10.21307/IJSSIS-2021-009","url":null,"abstract":"Abstract The reader-to-tag collision problem occurs when multiple readers try to access the same tag simultaneously. The traditional collision avoidance techniques such as RTS (request to send) and CTS (clear to send) are not applicable because a reader may communicate with multiple tags simultaneously. In this paper, we introduce a collaborative communication protocol to avoid reader-to-tag collisions using TDMA and clustering approaches. The protocol targets the RFID-WSN static systems arranged in a square grid topology, which we can find in different RFID applications such as warehouse stocktaking, parking cars, agricultural fields, and libraries. In such simple topologies, the other proposed reader collision solutions for general use of RFID systems are not efficient since they cannot avoid all possible collisions, and worse of that, some of them are not even detectable, which is intolerable for stocktaking applications. Moreover, they are complicated and heavy in resources, while read throughput is limited. Our protocol presents a simple solution for simple RFID systems with better performances. To validate the proposed protocol, we presented a model using the Process Meta Language (Promela), which is executed under the simple Promela interpreter (SPIN) model checker to verify the protocol properties as deadlocks and livelocks. Also as a proof of concept, we have done a first-step performance analysis using the java runtime.","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"14 1","pages":"1 - 14"},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43219098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.21307/IJSSIS-2021-008
Ehsan ul haq, H. Nasir, Asif Iqbal, Muhammad Ali Qadir
Abstract Target motion analysis is a key requirement of autonomous and self-driving machines like drones and robots. However, with strict weight limits, the aerospace industry is always on the hunt for simpler and lighter sensing solutions. Continuous-wave Doppler radars are the simplest radars that can easily obtain a target’s relative velocity using the Doppler shift in the received wave. However, these radars cannot provide the target’s range. In this work, we address the problem of obtaining target’s range and velocity by incorporating Doppler frequency measurements from a simple continuous wave Doppler radar. To this end, we find out the movement patterns and maneuvers that an observer can make to converge to the target’s location. After presenting the observability requirements, we design and compare various non-linear Kalman filter-based target trackers. We experimented with different simulation scenarios to compare the tracking results with bearings-only, frequency-only, and bearings-frequency measurement sets. In our analysis, Unscented Kalman Filter with bearings-frequency measurements performed best. Experiments show that an observer can locate the target accurately within 10 cm by incorporating Doppler frequency measurements. Moreover, it also reduced the convergence time to a fraction of a second.
{"title":"Comparative study of Kalman filter-based target motion analysis by incorporating Doppler frequency measurements","authors":"Ehsan ul haq, H. Nasir, Asif Iqbal, Muhammad Ali Qadir","doi":"10.21307/IJSSIS-2021-008","DOIUrl":"https://doi.org/10.21307/IJSSIS-2021-008","url":null,"abstract":"Abstract Target motion analysis is a key requirement of autonomous and self-driving machines like drones and robots. However, with strict weight limits, the aerospace industry is always on the hunt for simpler and lighter sensing solutions. Continuous-wave Doppler radars are the simplest radars that can easily obtain a target’s relative velocity using the Doppler shift in the received wave. However, these radars cannot provide the target’s range. In this work, we address the problem of obtaining target’s range and velocity by incorporating Doppler frequency measurements from a simple continuous wave Doppler radar. To this end, we find out the movement patterns and maneuvers that an observer can make to converge to the target’s location. After presenting the observability requirements, we design and compare various non-linear Kalman filter-based target trackers. We experimented with different simulation scenarios to compare the tracking results with bearings-only, frequency-only, and bearings-frequency measurement sets. In our analysis, Unscented Kalman Filter with bearings-frequency measurements performed best. Experiments show that an observer can locate the target accurately within 10 cm by incorporating Doppler frequency measurements. Moreover, it also reduced the convergence time to a fraction of a second.","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":" ","pages":"1 - 12"},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44033362","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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