Fire and gas hazards pose significant risks to human safety, property, and industrial operations. In this project, we aim to develop an advanced Fire and Gas Detection System utilizing Arduino microcontroller technology integrated with IR sensors and MQ-135 gas sensors. The system detects hazardous conditions such as fire and gas leaks and alerts users through visual (LED) and audible (buzzer) signals. Real-time sensor data is displayed via a serial monitor, providing continuous updates and efficient debugging. By employing both hardware and software approaches, the system achieves high detection accuracy while minimizing false alarms. This project introduces adaptable and scalable modular architecture, enabling the integration of additional sensors and supporting future enhancements, such as mobile app integration and smart home compatibility. The hybrid approach of combining precise sensor readings with machine learning-based dynamic threshold adjustments enhances the system's effectiveness, offering a robust platform for ensuring safety across residential, industrial, and environmental applications.

Keywords: Fire Detection, Arduino, Infrared Senor, Gas Sensor, Internet-of-Things (IoT),