This paper presents a method for detecting active gas stoves with coil burners using a Raspberry Pi and Pi Camera, focusing exclusively on the signal and image processing components. The system captures images at 30-second intervals to monitor stove activity. Our approach involves processing these images to identify the thermal characteristics of active coils. Although the broader goal was to develop a complete alert system for kitchen safety, this work details only the image processing techniques and their effectiveness in detecting active stoves. The results demonstrate that the proposed method successfully identifies active coils, providing a foundation for future integration of an alert mechanism.