Adaptive Lighting Controller Using Historical and Real-Time Traffic Data
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Solution Overview
Problem
Existing lighting systems for roads and buildings face a challenge in balancing energy conservation with the need for constant lighting that makes drivers and pedestrians feel secure, as providing full lighting at all times contradicts energy-saving goals.
Innovation Solution
A controller system that adjusts lighting based on historical and current traffic information, providing increased lighting during historically busy times even if not busy on the current day, and during busy times on the current day even if not historically busy, using a combination of historical and current traffic data to determine illumination levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If constant/full lighting is provided at all times, then safety and security comfort for drivers and pedestrians is improved, but energy consumption increases
Solution Approach 1:
The lighting system dynamically adjusts illumination levels based on real-time traffic sensor data and historical patterns. The controller continuously monitors traffic conditions and modifies lighting output accordingly, transitioning from static constant lighting to dynamic adaptive lighting that matches actual safety needs while reducing energy consumption during low-traffic periods.
Solution Approach 2:
The system changes the illumination parameter (lighting intensity) based on traffic conditions. During high-traffic periods, full lighting is provided to ensure safety; during low-traffic periods, lighting is reduced to conserve energy. This parameter adjustment is controlled by comparing real-time sensor data with historical traffic patterns to determine appropriate lighting levels.
2Use of energy by moving object
If lighting is reduced to conserve energy, then energy consumption decreases, but safety and security comfort for drivers and pedestrians deteriorates
Solution Approach 1:
The system implements a feedback loop where traffic sensors continuously monitor actual traffic conditions and provide data to the controller. The controller compares real-time traffic data with historical patterns and adjusts lighting levels accordingly. This feedback mechanism ensures that lighting is reduced only when traffic conditions genuinely warrant lower illumination, maintaining safety while conserving energy.
Solution Approach 2:
The system uses historical traffic data to predict future traffic conditions and pre-adjusts lighting levels accordingly. By analyzing historical patterns, the system can anticipate high-traffic periods and ensure full lighting is provided in advance, while also preparing for low-traffic periods by reducing lighting proactively, thus maintaining safety without excessive energy consumption.
3Use of energy by moving object
If lighting is controlled based only on historical traffic statistics, then energy conservation is improved, but responsiveness to current day traffic conditions deteriorates
Solution Approach 1:
The system merges historical traffic data with real-time sensor data to make lighting decisions. The controller combines information from both historical patterns and current traffic conditions, using the historical data to establish baseline expectations and the real-time sensor data to detect deviations from those patterns. This combination enables both energy conservation through historical analysis and responsiveness to current conditions through real-time sensing.
Solution Approach 2:
The lighting control system performs multiple functions: it analyzes historical traffic patterns for energy optimization, monitors real-time traffic conditions for safety responsiveness, and synthesizes both data sources to make comprehensive lighting decisions. This multi-functionality allows the system to simultaneously achieve energy conservation and adaptability to current conditions.
4Adaptability or versatility
If lighting is controlled based only on current day traffic information, then responsiveness to current traffic is improved, but energy conservation effectiveness deteriorates
Solution Approach 1:
The system uses historical traffic data to establish baseline patterns and predict future traffic conditions in advance. By analyzing historical trends, the controller can anticipate high- and low-traffic periods and pre-adjust lighting levels accordingly, rather than merely reacting to current conditions. This preliminary action based on historical data enables proactive energy conservation while maintaining responsiveness to actual traffic needs.
Data Source
AI summary
In an aspect, a controller is configured to: receive traffic information; determine a characterization based at least in part on a portion of the traffic information that is associated with traffic from days prior to a current day; determine whether the characterization that is based at least in part on the portion of the traffic information associated with traffic from days prior to the current day satisfies a criteria; provide on the current day, an output based at least in part thereon; determine a characterization based at least in part on a portion of the traffic information that is associated with traffic from the current day; determine whether the characterization that is based at least in part on the portion of the traffic information associated with traffic from the current day satisfies a criteria; and provide on the current day, an output based at least in part thereon.