Definition
UAV plant protection uses multirotor or fixed-wing drones for spraying, foliar fertilizer, and seeding. It is a precision agriculture method. GPS or BeiDou, remote sensing, and image recognition support variable-rate spraying, obstacle avoidance, and a record of the flight path. The work takes less labor and less pesticide. The job record can go into agricultural product traceability and organic certification.
Core Concepts and Technical Features
Positioning uses GPS or BeiDou RTK at centimeter level, so the aircraft can follow the terrain and vary the spray. Remote sensing and recognition use remote sensing and image recognition to find pest and disease areas and spray only there. Variable-rate spraying changes the volume from a prescription map so less pesticide is wasted. Job records store the path, the dose, and the area, and upload them to the cloud platform. With soil moisture, pH, and EC, the timing of the flight can be chosen more carefully.
Use Cases
It is used for pest and disease control in rice, wheat, corn, and cotton; for spraying in three dimensions on tall crops such as orchards and tea; for foliar fertilizer in integrated water and fertilizer; and for sowing seed or a biocontrol agent. The job record supports agricultural product traceability, organic certification, and green certification. With smart agricultural machinery and precision agriculture, the loop is remote-sensing monitoring, a prescription map, then the drone or the machine.
Technical architecture and data flow
The system is the aircraft and the spray gear, flight control and positioning, remote sensing and image recognition, a ground station, and a cloud platform. Path, dose, and area go up over 4G or WiFi and connect to agricultural product traceability and the farm system. With machine learning and AI, pests and disease can be identified and a prescription map produced. SimtoLink can support this with a cloud platform, APIs, and data integration.
Implementation Guidance
Introducing drones for crop protection requires: selecting the drone model and operational capabilities, deploying remote sensing or image recognition capabilities, integrating with cloud platforms and traceability systems, and training pilots and operational standards. When selecting, focus on: endurance and payload, positioning accuracy, integration with agricultural product traceability and organic certification API , and the completeness of operational data. Combined with precision agriculture and soil moisture , the timing of crop protection and pesticide use strategies can be optimized.