Development and Verification of an IoT-enabled Air Quality Monitoring System Based on Petri Nets

Abstract

An internet of things (IoT) system for monitoring environmental parameters on campus has been successfully developed in this study. Various sensors are adopted in front of the IoT system for detecting air pollutants. The architecture of LongRange in Class C uses low-power and long-distance transmission technologies, which has been set up on the large campus so that the terminal equipment can reach a balance between downlink latency and battery life, making it the best communication protocol. In addition, this monitoring system uses the Petri net software tool to build a correct IoT platform based on the fundamental design process and to demonstrate the feasibility of the IoT system through simulation-based verification. Finally, the experimental results indicate that the IoT system for monitoring the environmental parameters on campus achieves the goal of an acceptable data transmission success rate of more than 95%. Thus, it can facilitate the air quality trends for policy making as well as the hazardous prediction and prevention.