AI Headlamp Control for Activity-Based Beam Adjustment
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Solution Overview
Problem
Traditional headlamps require manual user settings for light geometry and brightness, which is time-consuming and unintuitive, and fails to adapt to individual user preferences or activity-specific lighting needs.
Innovation Solution
A headlamp equipped with an AI unit that automatically classifies user activities using sensors and adjusts light beam geometry and brightness based on activity recognition, allowing for intuitive and user-specific control without manual pre-settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual user settings are used for light geometry and brightness, then the headlamp can be controlled, but the operation becomes time-consuming and unintuitive
Solution Approach 1:
The headlamp system performs self-service by automatically detecting user activities through sensors and autonomously adjusting lighting parameters without requiring manual user configuration. The system serves itself by classifying activities and controlling light geometry and brightness based on detected activity patterns.
Solution Approach 2:
The system implements feedback by continuously monitoring sensor data related to user activities and using this information to automatically adjust lighting parameters. The feedback loop enables the system to adapt lighting conditions based on real-time activity detection and classification results.
2Adaptability or versatility
If manual pre-settings are required for each activity, then specific lighting modes can be configured, but the process becomes complex and requires multiple iterations
Solution Approach 1:
The system automatically adapts to different activities by detecting and classifying user behaviors through sensors, eliminating the need for manual pre-configuration of lighting modes for each activity type. The self-service mechanism handles activity recognition and lighting adjustment autonomously.
Solution Approach 2:
The system performs preliminary classification of user activities and pre-adjusts lighting parameters based on detected activity patterns before the user needs to manually configure settings. This preliminary action enables the system to be ready with appropriate lighting configurations automatically.
3Adaptability or versatility
If traditional manual control is used, then the headlamp structure remains simple, but it cannot automatically adapt to user preferences or activity-specific needs
Solution Approach 1:
The control unit is designed with multi-functionality, serving both as an activity classifier that processes sensor data and as a lighting controller that adjusts light parameters. This universal component handles multiple tasks automatically, enabling adaptation to different activities without requiring separate manual control mechanisms.
Solution Approach 2:
The patent replaces manual mechanical adjustment mechanisms with an automated electronic control system that uses sensor data and classification algorithms to adjust lighting parameters. This substitution eliminates the need for physical user interaction while enabling sophisticated activity-based adaptation.
Data Source
AI summary
A portable lamp 100, preferably a headlamp 100, which is adapted to be worn or carried by a user, comprising: at least one light source 114, an AI unit 120, wherein the AI unit 120 comprises an activity classification unit 122 and a control unit 124, wherein said activity classification unit 122 is able to automatically classify an activity which the user is currently carrying out without any manual setting by the user, wherein said control unit 124 is adapted to control the beam of said at least one light source 114 at least based on the classified activity of the user.