A Novel Smart System with Jetson Nano for Remote Insect Monitoring

Insect monitoring is vital for agricultural management and environmental conservation, but traditional methods are labor-intensive and time-consuming. This paper introduces a novel smart system utilizing NVIDIA's Jetson Nano technology combined with object detection models for remote insect monitoring. The system automates the processes of detection, identification, and monitoring, thereby significantly improving the efficiency and accuracy of insect population assessments. The implementation of the YOLOv7 model on a dataset containing 10 insect species achieved a mAP@0.5 accuracy of 77.2%. This enables farmers to take timely and appropriate measures to prevent pests and diseases, reducing production costs and protecting the environment.