Real-Time Fire Detection and Irrigation Management System Using IoT and Image Processing

Accurate prediction of water requirement is essential to effectively irrigate and conserve our water resources. On the other hand, wildfire in agricultural fields can cause enormous losses to the farmers. Therefore, this scenario clearly depicts the need for an irrigation and fire detection system. Advanced sensors can be implemented to overcome these issues. To be more explicit, soil moisture sensors can enable us to capture the moisture contents of the earth, gas sensors can detect all kinds of damaging gases, and flame sensors will help us trace nearby flames. This data collected will be gathered through an ESP-32 microcontroller and fed into a database for analysis purposes. We have also put in a picture fire detection module with a custom-trained YOLO-V8 model that works on a customized dataset based particularly on fires with an accuracy as high as 87.5%. There has also been integration of a cell phone application containing live updates directly from the said sensors along with controls for control of irrigation motors. With this holistic approach, we aim to improve irrigation use along with effective wildfire detection, all of which is achieved through this remote access to vital information and controls by users. This is indeed an innovative system that has tremendous potential for great differences in terms of effectiveness in irrigation and wildfire detection.