Farmland disaster supervision method and system based on Internet-of-things

Abstract

The invention discloses a farmland disaster supervision method and a system based on Internet-of-things, and the method comprises the steps: carrying out the network division of a farmland supervisionregion, and establishing a supervision region grid layout network; marking the grid units belonging to the same farmland area as the same network group; placing a detection extension set in each network group, and placing a detection device in each grid unit; connecting each detection extension set to the farmland supervision network management host in a distributed manner; obtaining a predictionresult through the farmland disaster prediction neural network model; and sending the prediction result to the corresponding management extension set for disaster processing by the management host. By remotely monitoring the farmland disaster state in real time, the farmland disaster state can be intelligently and effectively supervised, the detection accuracy and the detection efficiency can beimproved, the supervision efficiency is improved, and safe and reliable operation of the farmland is ensured; overall and local distributed management is carried out on the farmland, and the method issuitable for large-scale centralized management of farmland disasters.

Description

technical field [0001] The invention belongs to the technical field of farmland disaster supervision, and in particular relates to a method and system for farmland disaster supervision based on the Internet of Things. Background technique [0002] Farmland disasters are a huge problem affecting agricultural production. Disasters will reduce crop yields and bring huge losses to agricultural production. With the scale of farmland planting, the manual monitoring mode of large-scale farmland has lagged behind. [0003] At present, technologies such as satellite remote sensing are usually used to monitor farmland disasters, but there are shortcomings such as long shooting period, low spatial resolution, and vulnerability to weather, and the monitoring information has time discontinuity; high-definition fixed-point camera technology has real-time, high resolution, etc. characteristics, but the monitoring range is extremely limited, the spatial information is discontinuous; the co...

AI Technical Summary

Problems solved by technology

[0002] Farmland disasters are a huge problem that affects agricultural production. Disasters will reduce crop yields and bring huge losses to agricultural production.

With the scale of farmland planting, the manual monitoring mode of large-scale farmland has lagged behind

[0003] At present, technologies such as satellite remote sensing are usually used to monitor farmland disasters, but there are shortcomings such as long shooting period, low spatial resolution, and vulnerability to weather, and the monitoring information has time discontinuity; high-definition fixed-point camera technology has real-time, high resolution, etc. characteristics, but the monitoring range is extremely limited, the spatial information is discontinuous; the cost is high and the reliability is low

It is impossible to grasp the state of farmland disasters from both overall and partial aspects at the same time, and it is impossible to detect the disaster state in time, which greatly reduces the efficiency of supervision and brings huge economic and social benefits

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