Smart System to Prevent Forest Fire based on Internet of Things

Abstract

Forest fires that have occurred in Indonesia recently caused enormous impacts and losses for human life and other living things. The problem of forest fires can cause smog, exposure to disease and human death. One of the causes of forest fires is inadequate early warning, and it is difficult for firefighters to reach hotspots. This paper aims to offer a prototype of an early warning system for forest fire monitoring and control. In this research, we have proposed an automated monitoring system that can monitor fire, humidity, and gas in real-time by using Internet of Things (IoT) and Blynk Cloud network. Several sensors are installed such as the DHT-22 sensor to control temperature and humidity, the LM393 fire sensor to detect fire, and the MQ-2 gas sensor to detect levels of liquefied petroleum gas (LPG) in forest areas. A water pump is also installed to spray water automatically when the temperature is >40 ^oC. The system resulted an early warning by turning on the "BUZZER ON" and "WARNING" lights, if the gas level is > 35% or the temperature,is >40 ^oC. In the simulation, the system can provide information and the location of hotspots by google maps and messages on smartphones, such as "temperature >40 ^oC detected, the hot temperature detected in A-SECTOR forest area". In the second test, the system can detect gas in the A-SECTOR forest area with a level of 35%.