The main focus of this research is to develop a real-time forest fire monitoring system using an Unmanned Aerial Vehicle (UAV). The UAV is equipped with sensors, a mini processor (Raspberry Pi) and Ardu Pilot Mega (APM) for the flight controller. This system used five sensors. The first is a temperature sensor that served to measure the temperature in the monitored forest area. The others sensors are embedded in the APM. There are a barometer, Global Positioning Sensor (GPS), inertial measurement unit (IMU) and compass sensor. GPS and compass are used in the navigation system. The barometer measured the air pressure that is used as a reference to maintain the height of the UAV. The IMU consists of accelerometer and gyroscope sensors that are used to estimate the vehicle position. The temperature data from the sensor and the data from GPS are processed by the Raspberry Pi 3, which serves as a mini processor. The results of the data processing are sent to the server to be accessible online and real-time on the website. The data transmission used the Transmission Control Protocol (TCP) system. The experimental setup was carried out in an area of 40 meters × 40 meters with 10 hotspots. The diameter of the hotspots is 0.4 meters with a height of 0.5 meters. The UAV is flown at a constant speed of 5 m/s at an altitude of 20 meters above the ground. The flight path is set by using a mission planner so the UAV can fly autonomously. The experimental results show that the system could detect seven hotspots in the first trial and nine hotspots in the second trial. This happened because there is some data loss in the transmission process. Other results indicate that the coordinates of hotspots detected by the UAV have a deviation error of approximately 1 meter from the actual fire point coordinates. This is still within the standard GPS accuracy as this system uses GPS with a range accuracy of 2.5 meters.
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