IOT-BASED FOREST FIRE DETECTION AND EARLY WARNING SYSTEM (FO-FEWS) USING ARDUINO UNO AND GSM

• Main Author: ERNIEZA, MUSA
• Format: Final Year Project Report
• Language: English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://ir.unimas.my/id/eprint/40065/3/Ernieza%20Musa%20ft.pdf; http://ir.unimas.my/id/eprint/40065/
• Institution: Universiti Malaysia Sarawak

This project presents the design of a forest fire detection and early warning system using the Arduino UNO and GSM technologies. With its primary goal to develop an IoT-based device system, this project can monitor the forest conditions and send alerts messages or alarms remotely when a fire breaks out in the forest region where the system is installed. Although forest fires are considered a common occurrence in Malaysia every year during the dry season, its high series of incidents alarming the authorities and forest rangers because Malaysia is one of the richest countries in biodiversity. Forest fires are an inescapable problem, especially in inland forestry, and this IoT-based Fo-FEWS can help limit the likelihood of fires spreading extensively. The MQ-2 Smoke Detector sensor and the DHT11 Temperature & Humidity sensor sense any possibility of forest fire by analyzing the changes in the surrounding air, including the LPG, CO, and smoke levels, as well as humidity and temperature. The Arduino UNO acts as the central control unit for this system, will receive the reading from the sensors, and is interfaced with the GSM that notifies the end-user via SMS when the forest is on high alert for fire conditions. In addition, this system is developed using Proteus 8 Professional and Arduino IDE software to design the circuit diagram and coding, respectively, which is free and easy to use. The benefit of this system is that it reduces reaction time and potential damage to the fire location, along with assisting users in obtaining an exact status of the fire location in real-time. Not only that, but this device is compact, portable, and easy to implement, specifically in inland forests.