A farm unmanned automatic field patrol method

Abstract

The invention discloses a farm unmanned automatic field patrol method which comprises the following steps: farm basic surveying and mapping: using surveying and mapping equipment for measuring the terrain of a farmland to be patrolled, and building a terrain model of the farmland through a computer; determining farmland plot boundary information, determining the position of an unmanned aerial vehicle hangar, installing and debugging the unmanned aerial vehicle hangar, installing the unmanned aerial vehicle hangar at the pre-selected position selected in the step 3, and then debugging the unmanned aerial vehicle in the unmanned aerial vehicle hangar; setting a field patrol strategy, and setting the field patrol time and route according to the environmental conditions of the farmland; carrying an agricultural condition load into agricultural condition remote sensing acquisition data, and collecting farmland data through the agricultural condition load carried on the unmanned aerial vehicle; uploading the data to a computer terminal; and carrying out primary and secondary analysis or display on the agricultural condition data. Compared with the prior art, the technical scheme of the invention has the advantages of high efficiency, unmanned operation, completeness, losslessness and accuracy.

Description

technical field [0001] The present application relates to a field inspection method, in particular to an automatic field inspection method for unmanned farms. Background technique [0002] Traditional farms obtain agricultural information mainly through manual regular field inspections, while modern farms rely on the deployment of a large number of ground sensor networks or unmanned vehicle field inspection solutions. The cost of manual field inspection is high, and human energy is limited, and the completeness, accuracy, and stability of the collected data are low. For large-scale crops, it is impossible to pay attention to every location. If local diseases, insect pests, and weeds invade , can not be found in time, causing diseases, insect pests, and weeds to spread in a large area, affecting the crop growth and final yield of the entire farm, thereby affecting the income of the farm. [0003] The ground sensor network faces difficulties such as high deployment costs, dif...

AI Technical Summary

Problems solved by technology

The cost of manual field inspection is high, and human energy is limited, and the completeness, accuracy, and stability of the collected data are low. For large-scale crops, it is impossible to pay attention to every location. If local diseases, insect pests, and weeds invade , can not be found in time, causing diseases, insect pests, and weeds to spread in a large area, affecting the crop growth and final yield of the entire farm, thereby affecting the income of the farm

[0003] The ground sensor network faces difficulties such as high deployment costs, difficult operation and maintenance, and high-density deployment affecting land cultivation; unmanned vehicles require higher farmland pre-planning costs, and unmanned vehicles cannot go deep into the farmland. Complete agricultural data

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