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.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
EditorsBenny Tjahjono, Soh Sie Teng, A. Ruggeri Toni Liang, Lenin Gopal, Hugeng Hugeng, Channing Chuang, Tresna Priyana Soemardi
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735446984
Publication statusPublished - 7 Dec 2023
Event4th Tarumanagara International Conference of the Applications of Technology and Engineering, TICATE 2021 - Virtual, Online, Indonesia
Duration: 5 Aug 20216 Aug 2021

Publication series

NameAIP Conference Proceedings
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616


Conference4th Tarumanagara International Conference of the Applications of Technology and Engineering, TICATE 2021
CityVirtual, Online


  • Covid-19
  • Human Behavior
  • IoT
  • Monitoring System
  • Prediction Model
  • SEIR
  • School Reopen
  • System Integration


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