Analene Montesines Nagayo, S. Sangeetha, Mahmood Zayid K. Al Ajmi, Abdullah Yousuf M. Al Bulushi, Mohammed Said A. Al Hinaai, Loay Yahia T. Al Hamadani
{"title":"将室内环境与健康协议监控系统集成到智能机器人中,促进大学校园安全","authors":"Analene Montesines Nagayo, S. Sangeetha, Mahmood Zayid K. Al Ajmi, Abdullah Yousuf M. Al Bulushi, Mohammed Said A. Al Hinaai, Loay Yahia T. Al Hamadani","doi":"10.1109/ICEARS56392.2023.10085327","DOIUrl":null,"url":null,"abstract":"This article discusses about the design and deployment of a smart robotic system on university campuses for monitoring the indoor environment, health protocols, and sanitation. The designed VEX autonomous robotic system performed the following tasks: (a) moving around the university classrooms and scanning the body temperature of students and staff, as well as tracking environmental parameters in classrooms; (b) executing sanitation function by disinfecting objects in classrooms; and (c) performing security function by sending an alert signal to health and safety officer if a student or staff with fever enters the classroom, or if staff or student is not wearing face mask indoors. Particle Photon microcontrollers linked to sensors and actuators were used to detect and manage indoor environmental conditions as well as track individuals' body temperatures from a distance, with the data being stored in the ThingSpeak and Particle cloud platforms and displayed on smartphone apps. Transfer learning through MIT App Inventor's Personal Image Classifier was used to detect health protocol violations with 93.33% accuracy. The maximum distance traversed by the robot prototype was 38 meters, with an average time of 220 seconds and an average speed of 0.17 meters per second. The robot had an 88.89% success rate in following the black-lined course. This intelligent robotic system can limit staff and student exposure to infectious diseases and implement \"new normal\" health and safety practices on campus as post-COVID-19 precautions.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"35 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Indoor Environment and Health Protocol Monitoring and Control System Integrated into a Smart Robot to Promote Safety on University Campuses\",\"authors\":\"Analene Montesines Nagayo, S. Sangeetha, Mahmood Zayid K. Al Ajmi, Abdullah Yousuf M. Al Bulushi, Mohammed Said A. Al Hinaai, Loay Yahia T. Al Hamadani\",\"doi\":\"10.1109/ICEARS56392.2023.10085327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article discusses about the design and deployment of a smart robotic system on university campuses for monitoring the indoor environment, health protocols, and sanitation. The designed VEX autonomous robotic system performed the following tasks: (a) moving around the university classrooms and scanning the body temperature of students and staff, as well as tracking environmental parameters in classrooms; (b) executing sanitation function by disinfecting objects in classrooms; and (c) performing security function by sending an alert signal to health and safety officer if a student or staff with fever enters the classroom, or if staff or student is not wearing face mask indoors. Particle Photon microcontrollers linked to sensors and actuators were used to detect and manage indoor environmental conditions as well as track individuals' body temperatures from a distance, with the data being stored in the ThingSpeak and Particle cloud platforms and displayed on smartphone apps. Transfer learning through MIT App Inventor's Personal Image Classifier was used to detect health protocol violations with 93.33% accuracy. The maximum distance traversed by the robot prototype was 38 meters, with an average time of 220 seconds and an average speed of 0.17 meters per second. The robot had an 88.89% success rate in following the black-lined course. 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Indoor Environment and Health Protocol Monitoring and Control System Integrated into a Smart Robot to Promote Safety on University Campuses
This article discusses about the design and deployment of a smart robotic system on university campuses for monitoring the indoor environment, health protocols, and sanitation. The designed VEX autonomous robotic system performed the following tasks: (a) moving around the university classrooms and scanning the body temperature of students and staff, as well as tracking environmental parameters in classrooms; (b) executing sanitation function by disinfecting objects in classrooms; and (c) performing security function by sending an alert signal to health and safety officer if a student or staff with fever enters the classroom, or if staff or student is not wearing face mask indoors. Particle Photon microcontrollers linked to sensors and actuators were used to detect and manage indoor environmental conditions as well as track individuals' body temperatures from a distance, with the data being stored in the ThingSpeak and Particle cloud platforms and displayed on smartphone apps. Transfer learning through MIT App Inventor's Personal Image Classifier was used to detect health protocol violations with 93.33% accuracy. The maximum distance traversed by the robot prototype was 38 meters, with an average time of 220 seconds and an average speed of 0.17 meters per second. The robot had an 88.89% success rate in following the black-lined course. This intelligent robotic system can limit staff and student exposure to infectious diseases and implement "new normal" health and safety practices on campus as post-COVID-19 precautions.