Classification of Street Lighting Conditions for a Community-Centric System
Yasufumi Takama*, Xiaotong Xu*, Chi-Chih Yu*, Yu-Sheng Chen*, and Lieu-Hen Chen**
*Graduate School of System Design, Tokyo Metropolitan University
6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
**College of Science and Technology, National Chi Nan University
#1 University Road, Puli, Nantao, Taiwan
This paper proposes a method for classifying street lighting conditions after dark in order to share the collected data with the local community. Such information is important for the safety and security of residents, and can be used to discuss about anti-crime activities and nighttime route recommendations. However, it is difficult to ascertain the actual street lighting conditions because of insufficient street-lamp data and the effects of obstacles and other light sources. In order to tackle this problem, we propose a social approach by which local residents collaboratively collect street lighting conditions using their smartphones. The technology behind this approach is a classifier that places the street lighting conditions into one of three levels. It is based on three attributes that are calculated from the illuminance data collected by the smartphones. The results of experiments on 164 actual streets show a maximum classification accuracy of 88.4%. We also discuss performance differences between smartphones and the effect of walking speed during data collection, both of which are important factors affecting the classification accuracy.
-  Metropolitan Police Department in Japan, “Protect yourself from sexual crimes,” http://www.keishicho.metro.tokyo.jp/kurashi/higai/koramu2/koramu8.html (in Japanese) [Accessed October 23, 2016].
-  T. Kurashima, T. Iwata, G. Irie, and K. Fujimura, “Travel Route Recommendation Using Geotags in Photo Sharing Sites,” CIKM’10, pp. 579-587, 2010.
-  X. Lu, C. Wang, J. Yang, Y. Pang, and L. Zhang, “Photo2Trip: Generating Travel Routes from Geo-Tagged Photos for Trip Planning,” ACM Multimedia2010, pp. 143-152, 2010.
-  T. Okumura, W. Sasaki, and Y. Takama, “Proposal of Walking Navigation System with Implicit Control of Consumed Calorie,” JSAI SIG-AM, pp. 1-6, 2013 (in Japanese).
-  W. Sasaki and Y. Takama, “Walking Route Recommender System Considering SAW Criteria,” TAAI2013, pp. 246-251, 2013.
-  C. Yu, T. Okumura, Y. Ho, L. Chen, E. Sato-Shimokawara, T. Yamaguchi, and Y. Takama, “Proposal of Community-based Walking Trail Sharing Service,” JSAI2012 Int. Organized Session, 3M2IOS-3b-7, 2012.
-  Y. Matsuda and I. Arai, “Comprehensive Gathering System for Streetlamps Brightness Utilizing Collective Smartphone Light Sensor Data,” IPSJ J., Vol.55, No.2, pp. 750-760, 2014 (in Japanese).
-  Y. Takama, X. Xu, C. Yu, and Y. Chen, “Toward Social Approach of Classifying Road Lighting Situation for Community-centric System,” TAAI2015, pp. 53-57, 2015.
-  Y. Akasaka, K. Yamagishi, M. Ishitsuka, Y. Haga, and M. Miura, “The detection point of the problem based on Horizontal Illuminance, Resident’s Subjective Assessment, Resident’s Awareness Questionnaire: Supports of Streetlights Illuminance Improvement Activity Based on the Residents’ Initiatives in the 2 Area with the Problem of the Darkness of Street at Night,” Summaries of technical papers of Annual Meeting Architectural Institute of Japan, D-1, pp. 1103-1104, 2011 (in Japanese).
-  K. Ikegami, T. Hayashi, and Y. Ohsawa, “Creative Communication and Action Process in Utilization of Data,” IEICE Technical Report, Vol.114, No.343, AI2014-33, pp. 45-50, 2014 (in Japanese).
-  L. Chang, Y. Ohsawa, and Y. Suda, “Valuation of Data through Use-Scenarios in Innovators’ Marketplace on Data Jackets,” ICDM Workshops, pp. 694-701, 2013.
-  Y. Ohsawa, J. Hendler, and O. Lassila, “Innovators’ marketplace: Using games to activate and train innovators,” Springer-Verlag, 2012.
-  X. Xu, W. Sasaki, C. Yu, and Y. Takama, “Proposal of Collecting Lighting Situation of Roads at Night for Recommendation of Safety Walking Route Using Smartphone,” SII2014, pp. 414-418, 2014.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.