Evaluation of Real-Time Object Detection Model for 3D Object Detection in Outdoor Environment

Numerous studies have been conducted on smart agriculture, which integrates information and communication technologies across the entire agricultural process. Smart agriculture incorporating various technologies enhances productivity, reduces labor requirements, and enables the production of high-quality crops. LiDAR, a technology that measures object position coordinates and distances, offers a wide field of view and high-precision measurements, and has been applied to smart agriculture in combination with other information and communication technologies. In addition, advanced artificial intelligence–based object detection techniques have been widely utilized throughout smart agriculture processes, including fruit maturity assessment and harvest time prediction. AI-based 3D object detection using LiDAR leverages these advantages to contribute to agricultural efficiency and the sustainable development of agriculture. In this study, we evaluate the performance of a 3D object detection model using point cloud data acquired by LiDAR in real agricultural environments.