TY - GEN
T1 - Utilizing IoT to Design Innovations Based on Human Behavior in The Education Sector within COVID-19 Pandemic
AU - Muqtadiroh, Feby Artwodini
AU - Purwitasari, Diana
AU - Yuniarno, Eko Mulyanto
AU - Nugroho, Supeno Mardi Susiki
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2023 American Institute of Physics Inc.. All rights reserved.
PY - 2023/12/7
Y1 - 2023/12/7
N2 - Various technological innovations and applications have been developed to ward off the threat of the Corona Virus. In this research, an integration system consisting of the Covid-19 prediction model and a design of Internet of Things (IoT) based on human tracking is proposed to come up with better solutions to deal with the current COVID-19 pandemic and when a sudden outbreak shot in the future. This technology will certainly drive the people's behavior changes due to the new normal era. During this COVID-19 pandemic, it is very important to have a monitoring system for everyone's movement to suppress the spread of the corona virus, especially in the education sector that we believe to have a fairly dense concentration with the surrounding environment. The framework is an integration monitoring system based on a remote access-based IoT and a wearable sensor system that can trigger an alert to detect COVID-19 early. This will become a community guard system when schools are declared ready to reopen based on experiments and prediction using the SEIR model approach. First, the performance of SEIR model to predict 100 days ahead to the Covid-19 fluctuation showed good since the RLMSE value is 1.2%. After having the information of Covid-19 spread in each region indicating the right time to reopen school, then the IoT will be implemented to trace the movement of stakeholder in school both indoor and outdoor settings. For indoor settings, ultra-wideband (UWB) localization is picked out to trace motion without being disturbed without depending on the capacity of the battery, various kind of hardware in mobile phone, and other disturbances such as the wall and non-exact position while using a regular Bluetooth. This technology applies UWB tags to send signals to other smart devices nearby and anchors will receive the signals to calculate user's position, then trigger action in the app. In outdoor settings, the design will apply google fence API in which an application is put into the mobile phone to track a local time, location to latitude and longitude, place, and activity. It appears that the research is not only presenting the information related to the prediction of the spread of the corona virus, but also IoT-based design solutions that will capture the symptoms of the spread caused by the movement of each stakeholder in the school. In consequence the spread of the corona virus in the school can be avoided.
AB - Various technological innovations and applications have been developed to ward off the threat of the Corona Virus. In this research, an integration system consisting of the Covid-19 prediction model and a design of Internet of Things (IoT) based on human tracking is proposed to come up with better solutions to deal with the current COVID-19 pandemic and when a sudden outbreak shot in the future. This technology will certainly drive the people's behavior changes due to the new normal era. During this COVID-19 pandemic, it is very important to have a monitoring system for everyone's movement to suppress the spread of the corona virus, especially in the education sector that we believe to have a fairly dense concentration with the surrounding environment. The framework is an integration monitoring system based on a remote access-based IoT and a wearable sensor system that can trigger an alert to detect COVID-19 early. This will become a community guard system when schools are declared ready to reopen based on experiments and prediction using the SEIR model approach. First, the performance of SEIR model to predict 100 days ahead to the Covid-19 fluctuation showed good since the RLMSE value is 1.2%. After having the information of Covid-19 spread in each region indicating the right time to reopen school, then the IoT will be implemented to trace the movement of stakeholder in school both indoor and outdoor settings. For indoor settings, ultra-wideband (UWB) localization is picked out to trace motion without being disturbed without depending on the capacity of the battery, various kind of hardware in mobile phone, and other disturbances such as the wall and non-exact position while using a regular Bluetooth. This technology applies UWB tags to send signals to other smart devices nearby and anchors will receive the signals to calculate user's position, then trigger action in the app. In outdoor settings, the design will apply google fence API in which an application is put into the mobile phone to track a local time, location to latitude and longitude, place, and activity. It appears that the research is not only presenting the information related to the prediction of the spread of the corona virus, but also IoT-based design solutions that will capture the symptoms of the spread caused by the movement of each stakeholder in the school. In consequence the spread of the corona virus in the school can be avoided.
KW - Covid-19
KW - Human Behavior
KW - IoT
KW - Monitoring System
KW - Prediction Model
KW - SEIR
KW - School Reopen
KW - System Integration
UR - http://www.scopus.com/inward/record.url?scp=85180396491&partnerID=8YFLogxK
U2 - 10.1063/5.0128032
DO - 10.1063/5.0128032
M3 - Conference contribution
AN - SCOPUS:85180396491
T3 - AIP Conference Proceedings
BT - AIP Conference Proceedings
A2 - Tjahjono, Benny
A2 - Teng, Soh Sie
A2 - Liang, A. Ruggeri Toni
A2 - Gopal, Lenin
A2 - Hugeng, Hugeng
A2 - Chuang, Channing
A2 - Soemardi, Tresna Priyana
PB - American Institute of Physics Inc.
T2 - 4th Tarumanagara International Conference of the Applications of Technology and Engineering, TICATE 2021
Y2 - 5 August 2021 through 6 August 2021
ER -