Lau, Sei Ping, Weddell, Alex S., White, Neil M. and Merrett, Geoff V.
Poster Abstract: Solar-Powered Adaptive Street Lighting Evaluated with Real Traffic and Sunlight Data
At 13th ACM Conference on Embedded Networked Sensor Systems (SenSys 2015), Korea, Republic of.
01 - 04 Nov 2015.
Street lighting is an important resource; it has been shown to reduce crime, improve road safety, and increase economic activity. These benefits, however, come with a cost: an annual emission of 64 million tonnes of CO2. Solar-powered street lighting is attractive for its use of renewable energy and its ease of installation (particularly in off-grid applications), but sizing and control is a non-trivial task. This paper describes TALiSMaN-Green, a traffic-aware street lighting scheme which takes account of road users as well as the available energy to dynamically adjust lighting levels. Simulations using real traffic and sunlight data illustrate that solar-powered streetlights can be managed to deliver consistent usefulness throughout the night.
Actions (login required)