SMARTLIGHT: AI-Driven Adaptive Urban Lighting Using Floating Car Data for Real-Time Energy Optimization

Proposal Abstract
Smartlight is an AI-Powered Adaptive Urban Lighting system that adjusts lighting levels in real time by analyzing traffic flow and weather conditions, enhancing energy efficiency and reducing carbon emissions. Smartlight models and predicts traffic conditions by integrating historical datasets (such as traffic patterns, weather, and accidents) with real-time data (including vehicle counts and signal states), employing advanced machine learning algorithms and feature selection techniques to optimize urban lighting levels, enhance energy efficiency, and improve safety in urban environments. Through continuous analysis of traffic flow and weather patterns, the system dynamically adjusts lighting level in compliance with EN 13201 standards.
Smartlight is an AI-powered, IoT-enabled adaptive lighting system that introduces a novel approach by eliminating the need for physical roadside sensors. Instead, the system leverages Floating Car Data (FCD) from platforms like TomTom, Yandex, and Be-Mobile, integrating this data with AI-powered predictive models to adjust lighting level in real time. This innovation significantly reduces the requirement for costly sensor infrastructure, enabling widespread adoption and large-scale deployment in urban environments. The result is a more cost-effective and efficient solution that offers enhanced scalability, reduced operational costs, and greater overall efficiency. A map-based dashboard enables remote control and real-time monitoring of individual lighting units, tracking operational status, energy consumption, and fault detection. Integrated with IoT infrastructure, system provides continuous data feedback for efficient control, optimization, and performance analysis across the lighting network.