Landscaping maintenance monitoring and early warning method and system

By combining perception, image recognition, and decision-making intelligence, automated and precise maintenance of landscaping has been achieved, solving the problems of lag and resource waste in traditional manual inspections, and improving the ability to promote healthy plant growth and control pests and diseases.

CN121121968APending Publication Date: 2025-12-12佛山市高明区城市管理公用事业服务中心
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Patent Information

Application Number
CN202511271577.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-08
Publication Date
2025-12-12

AI Technical Summary

Technical Problem

Traditional landscaping maintenance relies on manual inspections, lacks accurate insight into the actual needs of plants, has a low level of intelligence, makes it difficult to make scientific and systematic maintenance decisions, and results in delayed detection of pests and diseases, leading to high costs and poor results.

Method used

The system uses a perception module to collect image and video data, combined with soil and weather sensors. The image recognition module performs feature extraction and semantic understanding, and the decision-making agent is simulated in a digital twin to generate optimized decision instructions, which drive the execution module to perform irrigation and fertilization operations.

Benefits of technology

It enables real-time monitoring of plant physiological status and early identification of pests and diseases, reduces human resource consumption, reduces resource waste, improves irrigation precision and pest and disease control efficiency, and reduces costs.

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Abstract

The invention discloses a landscaping maintenance monitoring and early warning method and system, and relates to the technical field of garden irrigation, the system comprises a sensing module, an execution module and a communication module, the sensing module is used for collecting image and video data, the execution module is used for executing irrigation and fertilization operation, and the communication module is used for data interaction inside and outside the early warning system. The early warning system further comprises an image recognition module and a decision intelligent agent, the sensing module comprises image acquisition equipment and video acquisition equipment which are arranged on a fixed monitoring point and a mobile platform, and the sensing module is used for acquiring visual data of a plant growth state; the system has the advantages that plant physiological status and pest and disease damage signs are automatically analyzed through the image recognition module, simulation deduction is performed by fusing multi-source environmental data in the digital twinborn body through the decision agent, and optimized decision instructions such as scientific water and fertilizer ratio, irrigation scheduling and pest and disease damage intervention strategies can be generated.
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