A traffic-aware street lighting scheme for smart cities using autonomous networked sensors
- Submitting institution
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University of Southampton
- Unit of assessment
- 12 - Engineering
- Output identifier
- 20804537
- Type
- D - Journal article
- DOI
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10.1016/j.compeleceng.2015.06.011
- Title of journal
- Computers & Electrical Engineering
- Article number
- -
- First page
- 192
- Volume
- 45
- Issue
- -
- ISSN
- 0045-7906
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Addressed problem of high electricity consumption from street lighting, by dynamically adjusting light levels in response to presence of vehicles and pedestrians. Adoption could save up to 99% of energy for lights in low-traffic areas. Underpinned fruitful and longstanding collaboration with Mayflower Complete Lighting Control (division of SSE with 150k connected streetlights in Hampshire and over 400k worldwide) which subsequently partnered in £1.4m EPSRC Platform grant EP/P010164/1, with £14k in-kind contributions and steering board member (Muhammad Ali muhammad.ali@mayflowercontrol.com). Research from this paper won gold medal at UNIMAS InTex16 Innovation Technology Expo. StreetlightSim simulator is available open-source with over 380 downloads.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -