A municipal authority aiming to optimize street lighting based on traffic and environmental conditions for cost and energy efficiency.
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To reduce the power consumption of streetlights by dynamically adjusting their intensity based on the actual traffic presence and conditions on the street.
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- Developed an IoT-based solution that gathers real-time data from parking sensors, CCTV video feeds, and business application data.
- Utilized data science to generate descriptive and prescriptive analytics, providing insights to adjust lighting intensity. This was based on real-time data from light sensors, motion detectors, and live weather conditions.
Parking sensors, CCTV systems, Business application interfaces, Light sensors, Motion detectors, Data analytics tools.
- Enabled the system to identify and predict traffic volumes on streets, allowing for appropriate lighting adjustments.
- Automated dimming and brightening of streetlights based on pre-established triggers and conditions.
- Achieved a significant reduction in power consumption, with savings exceeding 15%.
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