<![CDATA[Fire incidents are among the most destructive disasters, often resulting in significant material losses and casualties. Therefore, an effective, accurate, and real-time fire detection system is essential to enhance building safety. This study presents the design and simulation of an Internet of Things (IoT)-based early fire detection system using an ESP32 microcontroller integrated with MQ-2, DHT22, and LDR sensors. The system is developed and tested using the Wokwi simulation platform and connected to the Blynk application for real-time remote monitoring via a smartphone. The MQ-2 sensor is used to detect smoke or flammable gas concentration, the DHT22 sensor monitors temperature and humidity, while the LDR sensor detects light intensity changes representing flame presence. The system operates based on predefined threshold values, where a hazardous condition is triggered when MQ-2 readings exceed 300 ppm, temperature reaches or exceeds 50°C, or LDR values fall below 100. Simulation results show that the system is capable of accurately identifying normal and fire conditions using multi-sensor data fusion. When a fire condition is detected, the system automatically activates a buzzer, relay, LED indicators, and sends real-time notifications to the user’s smartphone. The proposed system demonstrates potential as a low-cost and reliable solution for early fire detection in residential environments.]]>
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