The Hybrid Smoke–Temperature Sensing for Adaptive Ventilation Control and Motor Protection in Biomass-Fired SME Kitchens

Abstract

Biomass-fired cooking activities in small and medium-sized food enterprises (SMEs) generate smoke and excessive heat that can affect worker comfort, indoor air quality, and production efficiency. Conventional exhaust fan systems are commonly operated manually or at a fixed speed, which may result in delayed smoke removal and unnecessary electrical energy consumption. This study develops an Internet of Things (IoT)-based adaptive dual-speed exhaust fan control and motor protection system using an MQ-2 smoke sensor, DS18B20 temperature sensor, ESP32 microcontroller, and PZEM-004T electrical monitoring module. The proposed control strategy combines smoke-based activation during ignition and high-emission conditions with temperature-based ventilation retention during the cooling stage. The system also incorporates overload and overcurrent protection to improve motor operational safety. Experimental testing showed that the MQ-2 sensor activated the exhaust fan with an average response time of 0.6 s, while the transition from Speed 1 to Speed 2 required approximately 0.8 s when smoke concentration exceeded 1000 ppm. The DS18B20 achieved a temperature measurement accuracy of 97.97% compared with a thermocouple reference. The automatic dual-speed mode produced an average power demand of approximately 25.27 W, compared with 32.07 W for manual operation, corresponding to an average reduction of approximately 21.2%. The motor protection system detected abnormal current conditions and automatically disconnected the exhaust fan during sustained overcurrent conditions. The proposed system integrates adaptive environmental control, energy monitoring, and motor protection into a single IoT-based ventilation platform for biomass-fired SME kitchens.