LED street lamp brightness adaptive adjustment method and system
By constructing a mesh network and edge computing, combined with meta-learning algorithms, the brightness of LED streetlights is dynamically adjusted, solving the problem that static fusion strategies cannot adapt to dynamic environments, and achieving both precision and energy efficiency in brightness adjustment.
CN121728634APending Publication Date: 2026-03-24CECEP LATTICELIGHTING
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Patent Information
- Application Number
- CN202511871932.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-12
- Publication Date
- 2026-03-24
AI Technical Summary
Technical Problem
In existing LED street light brightness adaptive adjustment methods, static fusion strategies cannot adapt to dynamic environments, resulting in abnormal brightness output, energy waste, and traffic safety hazards.
Method used
By constructing a mesh network to collect multi-source data, performing dynamic scene clustering and brightness attenuation prediction, and combining edge computing and meta-learning algorithms, the system can match and adapt to scene requirements in real time, thereby achieving precise control of brightness adjustment.
Benefits of technology
It achieves precise adaptation of LED street light brightness adjustment, improves energy saving and traffic safety, and reduces operation and maintenance costs.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides an LED street lamp brightness adaptive adjustment method and system, and the method comprises the steps: collecting light intensity time sequence data in a target region, the position-speed associated data of a road surface moving target, and power supply frequency fluctuation data through a Mesh network, so as to create a corresponding fusion data set; transmitting the fusion data set to an edge computing node of the LED street lamp to perform dynamic scene clustering and divide a plurality of target use scenes, and synchronously outputting an initial brightness adjustment parameter matched with each target use scene; historical operation data of the LED street lamp is called, a corresponding brightness attenuation prediction model is constructed, and the brightness attenuation amount in the future preset time is predicted according to the current operation duration and the environment temperature data; and performing pre-compensation correction processing on the initial brightness adjustment parameter according to the brightness attenuation so as to output a corresponding target brightness control parameter, and correspondingly controlling the output luminous flux of the LED street lamp according to the target brightness control parameter. The energy-saving benefit of the street lamp can be effectively improved.
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