Automatic Fire Detection and Positioning System for Outdoor Lac Cultivation

This research explores the use of Kalman and Mahalanobis techniques to develop a fire detection system tailored for outdoor lac cultivation. The system leverages data from environmental sensors measuring temperature, humidity, and PM2.5 levels to identify wildfire anomalies. While the study includes a comparison between Mahalanobis and traditional Euclidean distance methods, its primary goal is to evaluate which approach provides more accurate fire alerts. The findings indicate that Mahalanobis distance significantly enhances the detection of complex anomalies, offering a more reliable and effective solution for timely fire warnings. This ensures that the system adapts well to varying environmental conditions and improves risk mitigation for farmers.