An AIoT LoRaWAN Control System With Compression and Image Recovery Algorithm (CIRA) for Extreme Weather

Promoting smart city applications can facilitate sustainable development to achieve carbon neutrality and solve existing problems, such as the frequent occurrence of extreme weather events caused by climate change. However, monitoring a large area in detail is very challenging, and there is currently no cost-effective solution. This research aims to design an artificial intelligence (AI) of Things (AIoT) LoRaWAN-based low-power, extensive coverage monitoring and alarm system at a low cost. Using the LoRaWAN communication system, it can provide point-to-point communication distances of more than 1 km, forming a low-cost remote network. Additionally, low-power consumption cameras and temperature and humidity sensors monitor the environment for a long time, then use the image compression and data transmission methods developed in this research to achieve stable and low data rate transmission of images and data. On the other hand, AI image analysis algorithms are used for image monitoring and object detection to provide alarm functions. Through this research, this system successfully monitored the environmental data and images under different extreme weather conditions in Hong Kong and provided effective warnings. Based on this research, a low-cost remote monitoring network can be further formed to automatically and effectively provide environmental monitoring and alerts to local governments over a long period.