A Prototype System for Detecting Land Snails in Experimental Vegetable Plot Using YOLOv10-X Deep Learning Model

This paper presents a prototype system for detecting land snails in an experimental vegetable plot using YOLOv10-X Deep learning model. In this proposed system, (Internet of Things) devices were used in conjunction with computer vision techniques and YOLOv10-X Deep Learning model. Users can view the results of land snail detection in real time, view land snail detection reports via mobile application, and receive land snail detection notifications via the LINE application. The land snail species used in this study were the African giant snail and the Siamese snail. From random testing of the detection accuracy in 100 video image frames, it was found that the proposed system gave an accuracy of 74.15% for detecting African giant snails, 64.08% for Siamese snails, and mean average precision (mAP) of both classes was 97.31%.