Unmanned aerial vehicle intelligent spraying system and method based on prescription map

Abstract

The invention discloses an unmanned aerial vehicle intelligent spraying system and method based on a prescription map. The system herein comprises an unmanned aerial vehicle flight decision system, anunmanned aerial vehicle precision operating system, an operating prescription system and an unmanned aerial vehicle engineering survey system. The unmanned aerial vehicle flight decision system is communicated with the unmanned aerial vehicle precision operating system through a ZigBee wireless sensing network; the unmanned aerial vehicle precision operating system is communicated with the operating prescription system through a 4G network; the operating prescription system is communicated with the unmanned aerial vehicle engineering survey system through the 4G network; the unmanned aerial vehicle engineering survey system is communicated with the unmanned aerial vehicle flight decision system through the ZigBee wireless sensing network. Soil fertility is judged via low-altitude remote sensing, decisions are made by artificial intelligence, an unmanned aerial vehicle is driven to provide precision operating in prescription map mode, and therefore, the technical problem that traditional operating modes have unreasonable application of fertilizers, low labor efficiency, non-uniform spraying, and poor fertilization effect is solved, and fine operating is achieved.

Description

technical field [0001] The invention belongs to the technical field of low-altitude remote sensing images, and relates to a UAV intelligent spraying system and method based on prescription maps. Background technique [0002] Low-altitude remote sensing technology can refine and quantitatively analyze the fertility of fields, and research on crops can provide evidence for precise operations; the ability of artificial intelligence makes intelligent decision-making possible. The current drone plant protection operations can be divided into two categories: manual flight control and autonomous flight control; [0003] (1) In the case of manual flight control, human factors lead to unstable flight posture of UAVs, high labor costs, high technical thresholds, and easy crashes, which is not conducive to the promotion of UAV plant protection operations; [0004] (2) In the case of autonomous flight control, it can solve the problem of labor cost and high technical threshold, but it ...

AI Technical Summary

Problems solved by technology

[0003] (1) In the case of manual flight control, human factors lead to unstable flight posture of drones, high labor costs, high technical thresholds, and easy crashes, which is not conducive to the promotion of drone plant protection operations;

[0004] (2) In the case of autonomous flight control, it can solve the problem of labor cost and high technical threshold, but it cannot solve the problem of interference from farmland wind field factors;

[0005] Whether it is in the case of manual flight control or autonomous flight control, the height, speed, and flight route are fixed during the operation process, resulting in uncontrollable distribution of fertilizer application, and precise operations cannot be performed according to field fertility and real-time environmental conditions.

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