Domestic fire is a fatal disaster threat that requires a responsive and reliable early detection system to minimize material losses. This research focuses on the design of the F-GUARD fire early warning system which uses a decision-level sensor fusion approach based on the NodeMCU ESP8266 microcontroller. This system integrates the MLX90614 contactless temperature sensor for precision thermal radiation detection, the MQ-2 smoke sensor, and the Infrared Flame Sensor to detect the presence of fire directly. The novelty of this research lies in the implementation of a single exponential smoothing algorithm to dampen noise in temperature data and a hold time mechanism for 15 seconds on the smoke sensor to eliminate chattering and false alarms. Environmental data is processed in real-time and visualized on an OLED screen, with buzzer actuator management based on non-blocking execution. The system transmits telemetry data to a cloud database every 5 seconds and sends instant emergency notifications via Telegram Bot. The main contribution of this research is the integration of the single exponential smoothing algorithm and hold time mechanism which successfully increased fire detection accuracy to 95% and reduced false alarms by up to 80% compared to conventional systems. Test results show that this multi-sensor integration with digital filtering logic is able to detect fire with an accuracy level of 95% and the average system response speed from detection to notification delivery is recorded at 2.5 seconds. Thus, F-GUARD is proven effective in providing more reliable, stable, and adaptive fire mitigation management for modern household environment protection needs.
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