Intelligent garden irrigation system

Abstract

The invention discloses an intelligent garden irrigation system. The system comprises a soil image acquisition module, an image processing module, an image analysis module, a control center and an irrigation pipe network, wherein the soil image acquisition module is used for collecting an image of garden soil, the image processing module is used for performing normalization treatment and graying treatment on the acquired soil image; the image analysis module uses a convolutional neural network algorithm to analyze characteristics of the treated soil image to judge the soil humidity, and a functional relationship model is established corresponding to the soil humidity, thereby judging the soil humidity; the control center analyzes and judges the water content of the soil through the analysis of the soil humidity, thereby achieving the control of the irrigation pipe network. The intelligent garden irrigation system has the advantages that it can be judged whether or not a garden needs tobe watered according to soil surface photos of different vegetation gardens, then irrigation decisions are made autonomously, when the garden does not need watering, watering stops intelligently, sothat water resources and human resources can be greatly reduced, the unreasonable irrigation is avoided, the installation is simple and the operation is easy.

Description

technical field [0001] The invention relates to an irrigation system, in particular to an intelligent garden irrigation system. Background technique [0002] Garden watering has always been faced with such a dilemma: manual watering is expensive, while automatic irrigation leads to water waste, under-irrigation or over-irrigation and other problems. Introducing intelligent technology into garden watering work is an effective way to solve the above dilemma. The invention automatically obtains soil images through a camera, uses deep learning technology to obtain soil moisture characteristics through soil images, and then automatically makes a decision whether the soil needs irrigation, and the decision signal is transmitted to an automatic control system, thereby realizing garden intelligent irrigation. The main technical content includes: Based on a large number of experiments, deep learning and machine vision technology are applied to image-based soil moisture classificatio...

AI Technical Summary

Problems solved by technology

[0002] Garden watering has always been faced with such a dilemma: manual watering is expensive, while automatic irrigation leads to water waste, under-irrigation or over-irrigation, etc.

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