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

Abstract

An IoT (Internet of Things) system for monitoring campus environmental parameters was successfully developed in this study. Various sensors were adopted in the front of IoT system for sensing air pollutants. The architecture of LongRange (LoRa) 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 transmission communication protocol. In addition, this monitoring system uses the Petri net software tool to build a correct IoT platform based on the fundamental working processes, and to demonstrate the feasibility of the IoT system through simulation-based verification. Finally, the experimental results have shown that the IoT system for monitoring the campus environmental parameters 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.