Design and Built a Prototype Kit for Fire Detection in a Peat Swamp Forest: A Preliminary Results

Abstract

Peat forest fire detectors need to be developed immediately due to the frequency of peat forest fires in Malaysia during the summer is very high. This can affect the life in the forest and the health of the surrounding population. Among them is the Ayer Hitam Muar Forest Reserve, Johor which is almost 50,000 acres in size and experiences fires every year. However, fire monitoring management methods still need to be improved in terms of speed, accuracy and systematic channeling fire alerts. Apart from location and area factors, the main challenge of the early fire detection process is the lack of manpower to monitor and notify fires. The conventional method through patrols and phone calls from farmers who see a fire is less effective because of the delay in the notification received by the authorities. Initially, the work of identifying the location of the fire and measuring the signal strength of the telco service in the Forest Reserve was done with the help of rangers from the Muar district forestry department. This article proposes a prototype for detecting peat forest fires capable of monitoring and sending early fire notifications using a smartphone. The prototype uses an ESP32 microcontroller, GSM/GPRS modem and industry-standard sensors incluing smoke, temperature, humidity and motion detectors. A total of five prototype units were developed as sensor nodes (SN) 1 to 5 with unique IDs that can send information to UTHM web servers simultaneously. Data from each SN is displayed in real-time while notifications of smoke detection and motion alerts are sent to the authorities via the Telegram application. Solar panels are used as a source of electricity supply while the authorities can access information via smartphones. This prototype was tested to see its stability and operational accuracy while the data obtained were recorded. The developed system can help the authorities detect fires at an early stage and the location of the fire can be known based on the SN information received on the smartphone screen.