DALI illumination control system

By establishing preset and human-factor lighting parameters mapping in the DALI lighting control system and using neural network models for training, the problem that the existing rhythm lighting system cannot match user preferences is solved, achieving better user experience and lighting parameter matching.

CN119697850APending Publication Date: 2025-03-25JIANGSU YIFENG TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202411647851.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-18
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The existing rhythmic lighting system cannot effectively distinguish whether the user's lighting adjustment is occasional or habitual, which leads to the inability to stably match the user's preferences, and there are challenges in optimizing the user experience.

Method used

By establishing a mapping of preset lighting parameters and human-factor lighting parameters, training the neural network model and updating the preset lighting parameters, the system gradually learns the user's lighting habits, and the automatically output lighting parameters are increasingly in line with users' preferences.

Benefits of technology

The lighting parameters automatically output by the DALI lighting control system are consistent with the user's lighting habits, optimize the user experience, and improve the matching degree of the system and user preferences.

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Abstract

A DALI lighting control system comprises an application program controller, a DALI lamp, a rhythm sensor and a wireless input module, when the application program controller receives a control signal from the wireless input module, the application program controller controls the DALI lamp according to the control signal, so that the lighting parameter of the current environment reaches the human factor lighting parameter; and establishing mapping of the preset lighting parameters and the human factor lighting parameters as training samples, and when the number of the training samples reaches a preset threshold value, assigning the training samples to the neural network model for training so as to update the preset lighting parameters. The application program controller stores initial preset lighting parameters of the system and is internally provided with a neural network model, the neural network model is trained by establishing mapping of the preset lighting parameters and human factor lighting parameters, and the preset lighting parameters are updated. The lighting parameters automatically output by the DALI lighting control system are more and more in line with the light using habit of the user, and are in line with the preference of the user, so that the user experience is optimized.
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