IoT-Based Tracing and Communication Platform for Disease Control

Abstract

Coronavirus disease 2019 (COVID-19) is highly contagious and has swept the globe. Countries worldwide is in urgent need of efficient technological solutions to control the transmission of COVID-19 disease. The objective of this project is to develop an artificial intelligence-driven contact tracing platform and communication to come up with an integrated solution to block the transmission chain of the disease. Three elements are included in this platform, which are behavioral recognition system, mobile application and smart wristband. Mobile application developed through Android Studio SDK, has multiple functions, which are Quick Response (QR) code scanner for location tracking, close contact identification, COVID-19 cases update, district color alert system and exposure notification. Behavioral recognition system developed on Raspberry Pi v4 and Faster Region Based Convolutional Neural Network Version 2 (RCNN_v2) and Single Shot Multibox Detection MobileNet Version 2 (SSD MobileNet_v2) are adopted as machine learning algorithm can carry out close-proximity detection, people counting, and face mask detection. Smart wristband built with Arduino MKR GSM1400 microcontroller and various sensors are developed through Arduino Integrated Development Environment (IDE) to keep track on the location and vital signs of the quarantined people and is designed with an emergency button to allow the quarantined people to get help immediately if they are not feeling well. The data obtained from the three elements is uploaded to a centralized database, Firestore associating with accurate timestamp and location. This system integrated with various preventive measure and control measure can mitigate and manage COVID-19 pandemic effectively and efficiently.