Most of fire incidents in waste tire recycler had happened in the non-auditing and certification period, and the main positions were steel wire separating machine and shredded tire storage area. The aim of this project was to establish auto-monitor temperature system in 2 main positions. After estimating, we selected the fixed FLIR thermal camera as the temperature measuring device and installed IoT system to transfer data to the cloud system where we carried out big data analyses. In our plant, we had established 3 thermal cameras, 2 for shredded tire storage area and 1 for steel wire separating machine. Each camera would be set up 3 or 8 detecting zones which record above 8,600 pieces of highest temperature data in the sole detecting zone. We also utilized temperature contacting detector to measure temperature regarding implementing the verification of cameras and the result showed identical value compared to cameras. The period of the big data is from 7/12 to 10/15, and we managed to establish the 5 mins predictable module through analyzing data. After that, we tried to set up the warning temperature value. Due to a lack of references regarding fire incidents in waste tire recyclers, we had set up the alarm value based on recorder highest temperature range. When the temperature exceeds alarm value and meets other deigned conditions, the cloud system will alert workers immediately. We had created alert platform on messaging app, LINE, where workers would receive warning information conveniently. Based on our research, the IoT measuring temperature system could be suit on other waste tire recyclers, but it is necessary to re-estimate the numbers and scale of devices to accord with each plant.

Waste tire treatment, Internet of things (IoT), Artificial Intelligence (AI)