A MODEL OF AN AUTONOMOUS SMART LIGHTING SYSTEM USING SENSORS
DOI:
https://doi.org/10.37943/12UICC8045Keywords:
street lights, automation, smart technologies, optimization, modeling, data collection and processing algorithms.Abstract
Traditional street lighting systems receive data about daylight levels and adjust lighting. However, in such conditions, energy consumption increases since the sensors of such systems receive data on only one indicator which is daylight. Therefore, a suitable automated intelligent lighting system model is needed. Intelligent lighting systems can adjust the brightness of the light not only based on natural data, but also based on the movement of vehicles and people. This paper describes the development, implementation, and testing of a smart lighting system model to increase energy efficiency and high reliability. This system is controlled by a micro-controller programmed to control the lighting and receive data from sensors for processing with good efficiency. Distributed sensors record environmental conditions such as daylight and traffic. Photo-resistors change resistance in daylight to light up the streets at night. The HC-SR501 infrared motion sensor detects objects emitting infrared radiation (heat) in the controlled motion zone and sends a signal to the micro-controller. The intelligent lighting system uses LED's, which consume less energy and achieve high efficiency. Calculations show that the efficiency of using these lamps is almost 70%, compared to what is used in conventional street lighting systems.
References
de Melo, M.F., Vizzotto, W.D., Quintana, P.J., Kirsten, A.L., Dalla Costa, M.A., & Garcia, J. (2015). Bidirectional grid-tie flyback converter applied to distributed power generation and street lighting integrated system. IEEE Transactions on Industry Applications, 51(6), 4709-4717. https://doi.
org/10.1109/TIA.2015.2451115
Cheng, B., Chen, Z., Yu, B., Li, Q., Wang, C., Li, B., ... & Wu, J. (2020). Automated extraction of street lights from JL1-3B nighttime light data and assessment of their solar energy potential. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 675-684. https://doi.org/10.1109/JSTARS.2020.2971266
Jin, H., Jin, S., Chen, L., Cen, S., & Yuan, K. (2015). Research on the lighting performance of LED street lights with different color temperatures. IEEE Photonics Journal, 7(6), 1-9. https://doi.org/10.1109/
JPHOT.2015.2497578
Zhunussova, M., Jaeger, M., & Adair, D. (2015, November). Environmental impact of developing large buildings close to residential environments. In 2015 International Conference on Sustainable Mobility Applications, Renewables and Technology (SMART) (pp. 1-8). IEEE. https://doi.org/10.1109/SMART.2015.7399257
Saymbetov, A.K., Nurgaliyev, M.K., Nalibayev, Y.D., Kuttybay, N.B., Svanbayev, Y.A., Dosymbetova, G.B.,... & Gaziz, K.A. (2018, August). Intelligent energy efficient wireless communacation system for street lighting. In 2018 International conference on computing and network communications (CoCoNet)(pp. 18-22). IEEE. https://doi.org/10.1109/CoCoNet.2018.8476893
Tukymbekov, D., Saymbetov, A., Nurgaliyev, M., Kuttybay, N., Nalibayev, Y., & Dosymbetova, G. (2019, September). Intelligent energy efficient street lighting system with predictive energy consumption. In 2019 International conference on smart energy systems and technologies (SEST) (pp. 1-5). IEEE.
https://doi.org/10.1109/SEST.2019.8849023
Sun, C.C., Lee, X.H., Moreno, I., Lee, C.H., Yu, Y.W., Yang, T.H., & Chung, T.Y. (2017). Design of LED street lighting adapted for free-form roads. IEEE Photonics Journal, 9(1), 1-13. https://doi.org/10.1109/JPHOT.2017.2657742
Kostrub, D., & Ostradicky, P. (2019, November). A qualitative methodology framework of investigation of learning and teaching based on the USE of augmented reality. In 2019 17th International Conference on Emerging eLearning Technologies and Applications (ICETA) (pp. 425-440). IEEE. https://doi.org/10.1109/ICETA48886.2019.9040150
Knobel, C. (2013, May). Social network analysis as an augmentation of qualitative research. In 2013 International Conference on Collaboration Technologies and Systems (CTS) (pp. 84-85). IEEE. https://doi.org/10.1109/CTS.2013.6567209
Ma, W., Qu, D., Xiong, Z., & Wu, W. (2016, August). A Quantitative Assessment Method of Image Matching Methods Based on Cumulative Prospect Theory. In 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) (Vol. 2, pp. 359-362). IEEE. https://doi.org/10.1109/IHMSC.2016.108
DiVita, J., & Morris, R. L. (2013, February). Quantitative methods for ranking critical events. In 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA) (pp. 118-121). IEEE. https://doi.org/10.1109/CogSIMA.2013.6523833
Jiang, Y., Xie, W., & Zhuang, B. (2017, May). The civil-military integration development of equipment construction based on SWOT quantitative method. In 2017 29th Chinese Control And Decision Conference (CCDC) (pp. 4439-4443). IEEE. https://doi.org/10.1109/CCDC.2017.7979280
Vaghela, M., Shah, H., Jayswal, H., Patel, H. (2017). Arduino Based Auto Street Light Intensity Controller, Inverti Rapid, 1-4.
Mustafa, E.G. (2020). A novel strategy for transformation of conventional road lighting to smart road lighting, Light & Engineering, 28, 97–105.
Kasenda, S., Kantohe, D., Langie, M., & Waroh, A. (2018, October). Light Intensity Control Prototype Design Using Arduino Uno. In 2018 International Conference on Applied Science and Technology (iCAST) (pp. 563-566). IEEE. https://doi.org/10.1109/iCAST1.2018.8751501
Makni, W., Hadj, N. B., Samet, H., & Neji, R. (2016, December). Design simulation and realization of solar battery charge controller using Arduino Uno. In 2016 17th International Conference on Sciences
and Techniques of Automatic Control and Computer Engineering (STA) (pp. 635-639). IEEE. https://doi.org/10.1109/STA.2016.7952093
Kaur, A., Saini, S.S., Singh, L., Sharma, A., & Sidhu, E. (2016, October). Efficient Arduino UNO driven smart highway/bridge/tunnel lighting system employing rochelle piezoelectric sensor. In 2016 International Conference on Control, Computing, Communication and Materials (ICCCCM) (pp. 1-4). IEEE. https://doi.org/10.1109/ICCCCM.2016.7918247
Sulayman, I.I. A., Almalki, S.H., Soliman, M.S., & Dwairi, M.O. (2017, May). Designing and implementation of home automation system based on remote sensing technique with Arduino Uno microcontroller. In 2017 9th IEEE-GCC Conference and Exhibition (GCCCE) (pp. 1-9). IEEE. https://doi.org/10.1109/IEEEGCC.2017.8447984
Amestica, O.E., Melin, P.E., Duran-Faundez, C.R., & Lagos, G.R. (2019, November). An experimental comparison of Arduino IDE compatible platforms for digital control and data acquisition applications. In 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) (pp. 1-6). IEEE. https://doi.org/10.1109/CHILECON47746.2019.8986865
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