Keywords
golden apple snail
pest detection
precision agriculture
YOLOv8
How to Cite
Abstract
Golden apple snails represent a critical threat that drastically diminishes rice crop productivity. This study aims to develop an Internet of Things (IoT)-based smart farming system for the early detection of golden apple snail infestations in paddy fields. The system employs an external Logitech camera integrated with the YOLOv8 object detection model, supported by DHT22, soil moisture, and LDR sensors to monitor microclimate variables in real time. Applying the Research and Development (R&D) framework, field testing was conducted over three consecutive days in the rice fields of Dolok Masihul. System evaluation involved direct field observation, functional black-box assessments, and user perception surveys using the Technology Acceptance Model (TAM). The results demonstrate that the system successfully identifies golden apple snails accurately across varying ambient lighting conditions and attains an overall user acceptance rate of 90.63%.
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