IoT for COVID-19 Indoor Spread Prevention: Cough Detection, Air Quality Control and Contact Tracing
Nenad Petrović, Đorđe Kocić · 2021
Since the beginning of 2020, COVID-19 pandemic has influenced a variety of aspects related to our everyday activities. From entertainment and education to healthcare and transportation, most of the existing processes and routines have been reshaped in order to comply with safety guidelines regarding the COVID-19, either indoors or outdoors. In this paper, it is explored how cost-effective IoT devices in synergy with state-of-the-art embedded machine learning and blockchain can be adopted with aim to reduce the spread of this coronavirus indoors. The focus is on two main aspects: contact tracing and air quality control. As outcome of this research, prototypes are developed and presented, leveraging RFID for person identification, blockchain for contact tracing records, smartphone apps for notifications and deep learning-based cough detection executed on affordable IoT devices.