Lighting Design Platform With Digital Fixture Models and Aesthetic Filters
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Solution Overview
Problem
Current lighting design workflows are inefficient due to a fragmented market with limited and inaccurate information about lighting products, leading to suboptimal results and underutilization of intelligent lighting features in installations.
Innovation Solution
A platform that utilizes automated search engines, data structures, and machine learning to coordinate the design, acquisition, installation, and operation of lighting installations, including near-field illumination characterization and pattern matching systems, to optimize lighting effects and leverage intelligent lighting fixtures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If designers use physical samples and manual evaluation processes, then they can assess lighting fixtures in person, but the design process takes days or weeks and produces suboptimal results
Solution Approach 1:
The system creates digital twins and virtual models of physical lighting fixtures, allowing designers to evaluate lighting products in a virtual environment without needing physical samples. This copying approach enables instant access to accurate lighting data and visualizations, eliminating the time-consuming process of traveling to sample closets while maintaining evaluation accuracy through photorealistic rendering and simulated lighting conditions.
Solution Approach 2:
The system pre-computes and stores comprehensive lighting data, including photometric information, 3D models, and performance characteristics, before the design process begins. This preliminary preparation of lighting product information allows designers to immediately access and compare fixtures without manual evaluation, dramatically reducing design timeline while ensuring accurate product selection through pre-validated data.
2Adaptability or versatility
If the lighting market remains fragmented with multiple suppliers, then designers have access to various product options, but information about lighting products is unavailable, limited, or inaccurate
Solution Approach 1:
The system merges data from multiple lighting suppliers and manufacturers into a unified digital platform, consolidating fragmented product information into a single accessible repository. This integration maintains the versatility of having multiple product options from different suppliers while eliminating information gaps through centralized data collection, standardization, and verification processes that ensure complete and accurate product specifications.
Solution Approach 2:
The system creates a universal data structure and communication protocol that works across different lighting product types and manufacturers, enabling a single platform to handle diverse lighting fixtures from multiple suppliers. This universal approach ensures consistent information availability for all products while maintaining the ability to select from a wide range of lighting solutions, effectively bridging the fragmented market through standardized multi-functional access.
3Extent of automation
If lighting fixtures are configured as IoT devices with network connectivity, then they can be controlled remotely and operate autonomously, but most lighting installations do little to take advantage of this increased intelligence
Solution Approach 1:
The system implements feedback loops that connect IoT lighting fixtures to the design and operations platform, enabling real-time monitoring of lighting performance, energy consumption, and operational status. This feedback mechanism allows the system to automatically adjust lighting parameters, optimize energy usage, and provide actionable insights, thereby unlocking the full potential of intelligent fixtures while maintaining ease of operation through automated control and user-friendly interfaces.
Solution Approach 2:
The system enables lighting fixtures to autonomously perform functions such as self-diagnosis, performance optimization, and predictive maintenance without requiring manual intervention. Through embedded sensors and AI algorithms, the fixtures automatically monitor their own status, adjust operating parameters for optimal performance, and alert operators only when intervention is needed, thereby maximizing the value of intelligent features while simplifying operations for end users.
Data Source
AI summary
A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.