JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v9i5.12392ArticleDesign and Application of a Drone-Based AI Inspection System for Longan Pests and Diseaseshttps://artdesignp.com/journal/JERA/9/5/10.26689/jera.v9i5.12392ZhengLiang,WangHao2025952025-10-21Aiming at the problem that longan trees in Guangdong Province have long been affected by pests and diseases, and to address issues such as low efficiency, high cost, and limited coverage in longan pest and disease inspection, this paper designs a drone-based AI inspection system for longan pests and diseases. The system uses drones as a platform to collect images of longan orchards, which are transmitted in real time via 4G/5G networks. Meanwhile, it integrates an AI algorithm model for AI early warning and prescription suggestions. In practical applications, the system can quickly locate the areas where pests and diseases occur, identify longan pests and diseases, and provide fruit farmers with a basis for timely prevention and control. It significantly enhances the timeliness and accuracy of longan pest and disease control, and offers strong technical support for the precise management of the longan industry.

Lan ZB, 2022, Research on Monitoring and Control Technologies for Crop Pests and Diseases. Horticulture & Seedlings, 42(12): 92–94.

Huang KQ, 2021, Damage Symptoms and Control Methods of Major Pests and Diseases of Litchi. Modern Horticulture, 44(22): 40–41.

Zhang Y, et al., 2022, Deep Learning Based Real-Time Crop Disease Detection Using UAV Imagery. Computers and Electronics in Agriculture, 2022: 107310.

He Y, Zhang Z, Li J, et al., 2023, Improved AlexNet-Based Citrus Canker Detection Using UAV Images. Computers and Electronics in Agriculture, 208: 107723.

FAO, 2021, Integrated Pest Management in Tropical Fruit Crops, United Nations, Rome.

Redmon J, Farhadi A, 2018, YOLOv3: An Incremental Improvement. arXiv. https://doi.org/10.48550/arXiv.1804.02767

Ren SQ, et al., 2023, Deep Learning-based Pest Detection in Precision Agriculture. Computers and Electronics in Agriculture, 205: 107399.

Chen X, et al., 2023, UAV-Based High-Resolution Image Analysis for Banana Disease Detection. Precision Agriculture, 24(2): 305–325.

Liu X, Wang Y, et al., 2024, A Novel Deep Learning Framework for Apple Pest Detection Using Drone Imagery. Computers and Electronics in Agriculture, 212: 107956.

Zhang H, Li M, et al., 2022, Multispectral Drone Imagery for Early Detection of Potato Late Blight. Remote Sensing, 14(18): 4486.

Li Y, et al., 2023, A Comparative Study of Deep Learning Algorithms for Pest Identification in Orchard Environments. Biosystems Engineering, 227: 237–248.

Wang J, et al., 2024, A Machine Learning Approach to Predict Longan Yield Based on Environmental Factors and Pest Incidence. Agricultural Systems, 204: 103675.

Zhu J, 2020, High-Yield Cultivation Techniques and Pest Control of Longan in Hainan. Farmer’s Staff, (12): 80.

Huang J, 2024, Green Prevention and Control Strategies for Diseases and Pests in Longan Planting. Agricultural Industrialization, (10): 34–36 + 47.

Lin S, 2023, Longan Cultivation Management and Pest Control Techniques. Hebei Fruit Tree, (01): 51–53.