GIS Street Lighting Control for Localized Roadway Illumination
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Solution Overview
Problem
Current street light management systems lack the ability to account for various geographic and usage-specific variables, such as crime rates, land use changes, and traffic patterns, leading to inconsistent lighting levels and inefficiencies in energy use and crime prevention.
Innovation Solution
A centralized street light management system that utilizes geographic information systems (GIS) to manage multiple layers such as street light infrastructure, land use, and speed limits, dynamically adjusting parameters like color temperature, brightness, and light distribution based on real-time and time-dependent data to ensure consistent service levels and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a broad brush lighting design is applied across a city based on collector/collector intersection classification, then implementation simplicity is improved, but the ability to account for local variables such as crime rates, land use changes, and sidewalks deteriorates
Solution Approach 1:
The patent divides the city into multiple geographic regions with different lighting requirements, creating segmented control zones based on land use, crime rates, and other local factors. This allows each region to have customized lighting parameters while maintaining overall system manageability through the geographic segmentation approach.
Solution Approach 2:
The patent implements local quality by allowing different lighting parameters (brightness, color temperature, distribution) to be applied to different geographic regions based on their specific characteristics. Each region can have tailored lighting settings that match its local needs, such as higher brightness in high-crime areas or different color temperatures in residential versus commercial zones.
2Adaptability or versatility
If centralized control with detailed geographic layer management is implemented, then adaptability to local conditions is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal platform that handles multiple functions: geographic layer management, real-time data integration, performance profile calculation, and dynamic lighting control. This multi-functional system reduces overall complexity by consolidating what would otherwise require separate systems for each function into a single integrated platform.
Solution Approach 2:
The patent introduces an intermediary layer (the management system with geographic information system) that mediates between raw data sources (sensors, traffic information, land use data) and the street light controls. This intermediary processes and integrates multiple data sources into unified performance profiles, simplifying the control architecture while enabling detailed local adaptability.
3Use of energy by moving object
If dynamic adjustment of lighting parameters is implemented, then energy efficiency is improved, but control system complexity increases
Solution Approach 1:
The patent implements dynamic adjustment of lighting parameters based on real-time data from sensors, traffic patterns, and environmental conditions. Lighting brightness, color temperature, and distribution are continuously adjusted to match actual needs, enabling energy efficiency improvements while the system handles complexity through automated dynamic control algorithms.
Solution Approach 2:
The patent incorporates feedback mechanisms where sensor data and performance measurements are continuously fed back to the control system. This feedback loop enables automated adjustment of lighting parameters based on actual conditions, improving energy efficiency while the feedback-driven automation reduces the need for manual intervention and simplifies operational complexity.
Data Source
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AI summary
A two-way communication Geographic Lighting Central Management System (GLCMS) to determine roadway lighting performance. Points, lines, polygons, etc. are used to define multiple geographic features overlaid on each other in a municipality relationships to dynamically establish street lighting performance including brightness, color temperature, and light distribution. The geographic data is accessible through a wide range of sources, and the geographic relationship between the data sources determines the lighting performance. Geographically represented features include, but are not limited to, lighting and associated infrastructure, pedestrian conflict, crime, roadway classifications, intersection classifications, lighting layouts, vehicular traffic volumes and road surface reflectance classifications.