The LD50 and LD90 of the pesticides for litchi stink bugs are obtained, which are used as the basis for the amount of UAV. We differentiated the image training samples into egg, nymph, and adult. The drone is used as the vehicle to carry the camera to collect the litchi stink bug image on the treetop, and the image is returned to the cloud for real-time pest identification. The information on the recognition of the image is transfer to the APP of the mobile phone form the server-side. The APP will calculate it based on the information and integrate the result into Google Maps to visualize the occurrence location and severity of the pest. The UAV designed by our team has a pressure knob, which can control the pump. Each waypoint can be controlled at different level heights, and its relative height, absolute height and other related information can be monitored in real time, and the flight hovering time of a specific waypoint can also be controlled.

This technology integrates agricultural, engineering and other academic research units, integrates real-time image recognition, environmental sensing and other Internet of Things functions and establishes a UAV identification litchi stink bug occurrence system, introduces intelligent path planning, improves the efficiency of unmanned vehicle prevention and control, and achieves precise medication. Prevention target.

This technology uses the UAV to identify the location and hazard degree of the litchi stink bug. Quantification of the hazard situation and the visualization of the distribution location are used as a reference for the effective prevention and operation of the prevention of the litchi stink bug. Using UAV with ceramics hollow cone nozzles carried appropriate pesticide dose, to establish a set of prevention strategies for litchi stink bug that can effectively control the litchi stink bug and achieve the goal of precise pesticide application. The strategies can be the standard of control litchi stink bugs on slop field for pesticide spraying service technicians, improve the overall control efficiency, also solve the problem of unmanned management of orchard.