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Open AccessArticle

Illuminance Reconstruction of Road Lighting in Urban Areas for Efficient and Healthy Lighting Performance Evaluation

by Qi Yao 1,*, Hongbing Wang 1, Jim Uttley 2,3,* and Xiaobo Zhuang 4
1
College of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
2
School of Architecture, The University of Sheffield, Sheffield S10 2TN, UK
3
Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK
4
Shanghai Alpha Lighting Equipment Testing Ltd., Shanghai 201114, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2018, 8(9), 1646; https://doi.org/10.3390/app8091646
Received: 9 August 2018 / Revised: 8 September 2018 / Accepted: 11 September 2018 / Published: 13 September 2018
(This article belongs to the Special Issue Smart Lighting)
Big lighting data are required for evaluation of lighting performance and impacts on human beings, environment, and ecology for smart urban lighting. However, traditional approaches of measuring road lighting cannot achieve this aim. We propose a rule-of-thumb model approach based on some feature points to reconstruct road lighting in urban areas. We validated the reconstructed illuminance with both software simulated and real road lighting scenes, and the average error is between 6 and 19%. This precision is acceptable in practical applications. Using this approach, we reconstructed the illuminance of three real road lighting environments in a block and further estimated the mesopic luminance and melanopic illuminance performance. In the future, by virtue of Geographic Information System technology, the approach may provide big lighting data for evaluation and analysis, and help build smarter urban lighting. View Full-Text
Keywords: luminance; mesopic luminance; non-visual biological effect; equivalent melanopic lux; big data luminance; mesopic luminance; non-visual biological effect; equivalent melanopic lux; big data
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MDPI and ACS Style

Yao, Q.; Wang, H.; Uttley, J.; Zhuang, X. Illuminance Reconstruction of Road Lighting in Urban Areas for Efficient and Healthy Lighting Performance Evaluation. Appl. Sci. 2018, 8, 1646.

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