Cotton canopy intelligent monitoring system and method

By setting up multiple surveying scales in cotton fields and combining image acquisition with cloud recognition, the problems of high labor intensity and low accuracy in cotton plant height measurement in existing technologies have been solved. This has enabled automated and stable measurement of cotton plant height and efficient data fusion, supporting cotton field management decisions.

CN122408882APending Publication Date: 2026-07-17XINJIANG AGRI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XINJIANG AGRI UNIV
Filing Date
2026-05-11
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing agricultural monitoring systems suffer from high labor intensity, low measurement frequency, poor data continuity and low accuracy in crop height measurement, lack of stable and reliable scale references, difficulty in adapting to complex farmland environments, weak system integrity, and difficulty in efficiently integrating environmental data and image data.

Method used

A cotton canopy intelligent monitoring system was designed, including a main control development board, an environmental data acquisition module, an image acquisition module, and a communication module. By setting multiple mapping scales and combining image acquisition with cloud recognition, a mapping relationship between pixels and actual dimensions is established to realize the automated calculation of cotton plant height.

Benefits of technology

It has achieved automated and stable measurement of cotton plant height, reduced human error, improved measurement accuracy and system integrity, and can efficiently integrate environmental and image data in complex environments to support cotton field management decisions.

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Abstract

本发明涉及智慧农业技术领域,公开了一种棉花冠层智能监测系统及方法,其技术要点为:该系统包括主控开发板、环境数据采集模块、图像采集模块、通信模块以及云端数据平台;所述环境数据采集模块用于采集土壤墒情、空气温度和空气湿度等环境参数,所述图像采集模块用于采集包含棉花冠层及测绘标尺的棉田图像;所述主控开发板对采集数据进行处理并通过通信模块上传至云端平台。云端服务器基于图像识别模型对测绘标尺及刻度进行分割识别,建立像素与实际长度之间的映射关系,并结合棉花冠层基准线位置计算棉花株高,进一步通过多路测绘标尺融合获得群体株高估测结果。同时,将株高结果与环境数据进行关联存储,实现棉花生长状态的远程监测与分析。
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