IoT Based Smart Home-Health Monitoring System Using Dempster-Shafer Evidence Theory for Pandemic Situation

ABSTRACT

With the advancement of the Internet of Things in our smart environment, smart devices are working without human intervention. So home can be converted to intelligent home automation systems to perform its computation automatically. In a pandemic situation, the majority of people have spent their maximum time at home. So indoor air quality, insider's and outsider's health monitoring has become an important issue. As respiratory diseases are the main concern for pandemics, we have to develop an intelligent home system model to monitor healthy environmental conditions for the users. This paper proposes an energy-efficient smart system model to monitor the health and environmental condition by measuring the carbon monoxide threat level that indirectly affects other atmospheric parameters. Our system alerts when the carbon monoxide level exceeds the safe level. Remote monitoring of the home and health parameters is done in real-time with the help of the system model. For this purpose, we are adopting Dempster-Shafer evidence theory as a mathematical model to aggregate the data coming from different sensors. The sensor nodes track the home and health parameters such as room temperature, humidity, carbon monoxide level, SpO2 level, body temperature, and pulse rate. The smartphone app updates the user's real-time sensor data through the display and indirectly helps to maintain the physical distance. The proposed intelligent home-health system model is compact, cost-effective, energy-efficient for the user, and is especially useful for the quarantined covid affected people in a pandemic situation. © 2022 ACM.