A traffic-aware street lighting scheme for Smart Cities using autonomous networked sensors. (July 2015) - Lau, Sei Ping; Merrett, Geoff V.; Weddell, Alex S.; White, Neil M.
Graphical abstract: Highlights: TALiSMaN detects road users and sets streetlight brightness appropriately. A utility model is detailed to quantify the usefulness of street lighting. Street lighting schemes are evaluated with StreetlightSim. TALiSMaN offers comparable usefulness as conventional lighting schemes. TALiSMaN consumes 2–55% of the energy of conventional/state-of-the-art schemes. Abstract: Street lighting is a ubiquitous utility, but sustaining its operation presents a heavy financial and environmental burden. Many schemes have been proposed which selectively dim lights to improve energy efficiency, but little consideration has been given to the usefulness of the resultant street lighting system. This paper proposes a real-time adaptive lighting scheme, which detects the presence of vehicles and pedestrians and dynamically adjusts their brightness to the optimal level. This improves the energy efficiency of street lighting and its usefulness; a streetlight utility model is presented to evaluate this. The proposed scheme is simulated using an environment modelling a road network, its users, and a networked communication system – and considers a real streetlight topology from a residential area. The proposed scheme achieves similar or improved utility to existing schemes, while consuming as little as 1–2% of the energy required by conventional and state-of-the-art techniques.