Video Imager Lighting Control via Spatial Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing photo-sensors have limited functionality as they operate based on the total amount of light in their field of view, making it inefficient for areas not directly receiving light and requiring multiple sensors for multiple task-areas, increasing cost and complexity.
Innovation Solution
A video-based system that uses a video imager to determine light levels in a space through an image stream, allowing for independent estimation of global and local illumination levels and controlling light sources accordingly, enabling holistic lighting control across different areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple photo-sensors are used to independently control lighting of multiple task-areas, then lighting control precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent divides the scene into multiple areas of interest (AOIs) within a single image, allowing one photo-sensor to measure lighting conditions in different spatial regions independently. The image is segmented into multiple AOIs, and lighting estimates are calculated for each AOI separately, enabling fine-grained lighting control without requiring multiple physical sensors.
Solution Approach 2:
The patent transitions from spatial distribution of sensors to spatial distribution of measurement regions within a single sensor's field of view. Instead of placing multiple sensors at different locations, the system creates multiple virtual measurement zones across the image plane, adding a dimensional transformation that reduces hardware complexity while maintaining control precision.
2Device complexity
If a single photo-sensor is used with large field of view, then device complexity is reduced, but measurement precision for specific task-areas deteriorates
Solution Approach 1:
The patent segments the field of view into multiple areas of interest, allowing a single photo-sensor to extract lighting information from different spatial regions. By dividing the image into multiple AOIs, the system maintains the ability to measure local illumination conditions with precision while using only one physical sensor.
Solution Approach 2:
The single photo-sensor is designed to perform multiple functions simultaneously - it can measure lighting conditions across the entire field of view and also extract specific local illumination data from different AOIs. This multi-functionality allows one sensor to replace what would traditionally require multiple sensors for comprehensive lighting monitoring.
3Measurement precision
If photo-sensors are placed in areas not directly receiving light, then measurement precision for task-areas is improved, but use of energy increases
Solution Approach 1:
The patent uses reflected light from surfaces as an intermediary to indirectly measure lighting conditions in task-areas. Instead of placing sensors directly in dark task-areas where they would consume energy without effective measurement capability, the system uses reflective surfaces to bring light information back to the sensor, enabling precise measurement while keeping the sensor positioned in lighter areas with lower energy consumption.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and cost-effective control of lighting by allowing a single sensor to measure and adjust light levels in multiple areas, optimizing energy usage and user satisfaction by utilizing both natural and artificial lighting.
Implementation Method 1
A video-based system that uses a video imager to determine light levels in a space through image streams
Data Source
AI summary
A video imager may be used to measure the natural and/or artificial light levels in a space. The lighting estimates may be passed to a controller via a communication network. The lighting estimates may be in the form of actual radiance values, brightness, or other forms. The controller may determine if and which areas of the space require more light or if and which areas of the space have more light than required. Based on the lighting estimates, the controller may issue commands to turn on/off or dim/brighten the light from various ones or combinations of light sources in or around the space via actuators. The controller may also directly interface with the light sources.