Real-time caterpillar detection and tracking in Jujube orchard with YOLO NAS and SORT

Sumesh Nair, Guo Fong Hong, Chia Wei Hsu, Yvonne Yuling Hu, Shean Jen Chen*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Caterpillars pose a significant threat to agriculture, devouring crop foliage and evading traditional pest control methods like sticky or pheromone traps. While chemical pesticides are effective, concerns arise over crop residues. This study aims to address these challenges by tracking and estimating caterpillar positions in orchards in real-time, leveraging the Intel Realsense D405 RGB-D camera. Training data comprises 2,000 images from a jujube orchard, capturing diverse conditions such as exposure, occlusion, and wind. Real-time inference yields promising results, even recognizing the smallest 2-cm caterpillar at 21x12 pixels from a distance of 35 cm. The transition from YOLOv7 to YOLO NAS and from DeepSORT to SORT enhances detection by 30%, surpassing 95% accuracy. This innovative approach not only offers improved pest detection but also holds promise for integration with various technologies. From employing robot arms for targeted caterpillar removal to implementing laser pest targeting, this breakthrough contributes significantly to sustainable agriculture. By addressing the critical need for effective and environmentally friendly pest control practices, it helps ensure the long-term viability of agricultural systems.

原文English
主出版物標題Optics, Photonics, and Digital Technologies for Imaging Applications VIII
編輯Peter Schelkens, Tomasz Kozacki
發行者SPIE
ISBN(電子)9781510673144
DOIs
出版狀態Published - 2024
事件Optics, Photonics, and Digital Technologies for Imaging Applications VIII 2024 - Strasbourg, 法國
持續時間: 9 4月 202411 4月 2024

出版系列

名字Proceedings of SPIE - The International Society for Optical Engineering
12998
ISSN(列印)0277-786X
ISSN(電子)1996-756X

Conference

ConferenceOptics, Photonics, and Digital Technologies for Imaging Applications VIII 2024
國家/地區法國
城市Strasbourg
期間9/04/2411/04/24

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