Surveillance Monitoring using ESP32-Cam Module for Fog Detection in Agriculture

Fog is a common weather phenomenon that can have a significant impact on agriculture. It can reduce visibility, making it difficult for farmers to work in their fields. It can also damage crops by reducing photosynthesis and increasing the risk of frost. This paper presents a system for monitoring fog in an agriculture field using a camera module. The system uses a machine learning algorithm to detect fog in images captured by the camera. A fog detector is a device or system designed to detect the presence of fog or reduce the impact of foggy conditions. If the fog level is too high, an alert is sent to the farmer. The system was evaluated in a field experiment. According to the Indian Meteorological Department, the average humidity level during the fog season (October to March) is around 90%. However, humidity levels can often reach 100% or higher, especially in the early morning hours. The results showed that the system was able to accurately detect fog with a high degree of sensitivity and specificity. The system also had a low false alarm rate. The results of this study demonstrate the potential of using camera modules for fog detection in agriculture. This system can help farmers to protect their crops from the harmful effects of fog