Abstract
With the wide application of LED lighting products in road lighting, there are more and more requirements for illumination measurement. Traditional road illumination measurement uses full manual method, which takes a long time, but the amount of data collected is small, which easily leads to inadequate measurement accuracy, and the full manual measurement method cannot guarantee the personal safety of the surveyors. Therefore, the development and design of an intelligent car can accurately and quickly detect the illumination of street lamp and road surface. The design of this intelligent car is based on cloud server. The hardware core is composed of Raspberry pie and Arduino. Through Arduino management and scheduling illuminance measurement module, GPS positioning module and wireless remote control module, the measured data are packaged and sent to the cloud server through Raspberry pie for data storage and analysis in real time. Finally, the data are stored and analyzed through the visual window. The test results were displayed. Compared with the traditional road lighting detection method, the illumination detection method based on intelligent car can improve the detection efficiency, increase the data accuracy and ensure the safety of the inspectors.
Supported by Science Foundation for Goldlamp Co., Ltd (2017-228195).
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References
ANSI/IESNA RP-8-00:2005 American National Standard Practice for Roadway Lighting
GB/T 5700 Lighting measurement method. Standards Press of China (2008)
Xu, J.: Design and application of vehicular road lighting detector. Light Light. 42(4), 23–25 (2018)
Kuicai, S.: Design and application of vehicle-borne road lighting detection system based on AT89S52 single chip microcomputer. Lamps Light. (2), 16–18 (2018)
Liu, B.: Design of light intensity data acquisition system based on BH1750. J. Henan Sci. Technol. (13), 27–28 2016
Wu, B., Kong, J., Wang, X.: Design and implementation of intelligent car based on Arduino and Raspberry Pi. Electron. Des. Eng. 25(15), 58–61 (2017)
Princy, S.E., Nigel, K.G.J.: Implementation of cloud server for real time data storage using Raspberry Pi. In: 2015 Online International Conference on Green Engineering and Technologies (IC-GET) (2015)
Gu, M., Jiao, Z., Wang, W., Hou, J., Jiang, W.: Design of multifunctional navigation intelligent car. Microcomput. Appl. 36(12), 33–35 (2017)
Zhang, G., Guo, W., Sun, Y.: Design of warp workshop data acquisition and monitoring system. Autom. Instrum. 33(9), 54–58, 103 (2018)
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Li, X. et al. (2019). Design and Implementation of Intelligent Car for Light Environment Detection Based on Data Analysis. In: Jin, J., Li, P., Fan, L. (eds) Green Energy and Networking. GreeNets 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 282. Springer, Cham. https://doi.org/10.1007/978-3-030-21730-3_24
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DOI: https://doi.org/10.1007/978-3-030-21730-3_24
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