FUZZY LOGIC AND IOT INTEGRATION FOR SMART STREET LIGHTING SYSTEMS

Zulfikar Putra

Open Access

FUZZY LOGIC AND IOT INTEGRATION FOR SMART STREET LIGHTING SYSTEMS

pdf

Zulfikar Putra ¹ ,

⁴ Department of Electrical Engineering, Universitas Pendidikan Indonesia, Indonesia

Abstract

This paper explores the development and implementation of smart street lighting systems through the integration of Internet of Things (IoT) technology and fuzzy logic control. As urbanization accelerates, the demand for efficient and adaptive street lighting solutions becomes increasingly crucial for enhancing energy efficiency, reducing operational costs, and improving public safety. Traditional street lighting systems often operate without real-time adaptability, leading to energy wastage and suboptimal performance. By leveraging IoT sensors and networks, this research enables real-time data acquisition and communication between street lights and a central control system. Fuzzy logic algorithms are employed to process the data, allowing for dynamic adjustment of lighting intensity based on environmental conditions, traffic flow, and pedestrian activity. The integration of fuzzy logic provides a robust mechanism to handle the uncertainties and variabilities inherent in urban environments. Our prototype system demonstrates significant improvements in energy efficiency, with adaptive lighting adjustments reducing power consumption by up to 40% compared to conventional systems. Moreover, the enhanced responsiveness of the lighting system contributes to increased safety and comfort for urban residents. The findings underscore the potential of IoT and fuzzy logic integration in creating intelligent, sustainable, and user-centric urban infrastructure.

Keywords

Smart Street Lighting, Internet of Things (IoT), Fuzzy Logic

References

📄 H. Ahmad, K. Naseer, M. Asif, and M. F. Alam, “Smart Street light system powered by footsteps,” Proc. - 2019 7th Int. Conf. Green Hum. Inf. Technol. ICGHIT 2019, pp. 122–124, 2019,

📄 D. K. Srivatsa, B. Preethi, R. Parinitha, G. Sumana, and A. Kumar, “Smart street lights,” Proc. - 2013 Texas Instruments India Educ. Conf. TIIEC 2013, pp. 103–106, 2013,

📄 S. G. Varghese, C. P. Kurian, V. I. George, A. John, V. Nayak, and A. Upadhyay, “Comparative study of zigBee topologies for IoT-based lighting automation,” IET Wirel. Sens. Syst., vol. 9, no. 4, pp. 201–207, 2019,

📄 A.Farahat, A. Florea, J. L. M. Lastra, C. Brañas, and F. J. A. Sánchez, “Energy Efficiency Considerations for LED-Based Lighting of Multipurpose Outdoor Environments,” IEEE J. Emerg. Sel. Top. Power Electron., vol. 3, no. 3, pp. 599–608, 2015,

📄 A.Abdullah, S. H. Yusoff, S. A. Zaini, N. S. Midi, and S. Y. Mohamad, “Smart Street Light Using Intensity Controller,” Proc. 2018 7th Int. Conf. Comput. Commun. Eng. ICCCE 2018, pp. 361–365, 2018,

📄 S. Kumar, A. Deshpande, S. S. Ho, J. S. Ku, and S. E. Sarma, “Urban Street Lighting Infrastructure Monitoring Using a Mobile Sensor Platform,” IEEE Sens. J., vol. 16, no. 12, pp. 4981–4994, 2016,

📄 F. Leccese, “Remote-control system of high efficiency and intelligent street lighting using a zig bee network of devices and sensors,” IEEE Trans. Power Deliv., vol. 28, no. 1, pp. 21–28, 2013,

📄 M. Eriyadi, A. G. Abdullah, S. B. Mulia, and H. Hasbullah, “Street lighting efficiency with particle swarm optimization algorithm following Indonesian standard,” J. Phys. Conf. Ser., vol. 1402, no. 4, 2019,

📄 F. Kamaruddin, N. N. Nik Abd Malik, N. A. Murad, N. M. Abdul Latiff, S. K. S. Yusof, and S. A. Hamzah, “IoTbased intelligent irrigation management and monitoring system using Arduino,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 17, no. 5, p. 2378, 2019,

📄 G. Shahzad, H. Yang, A. W. Ahmad, and C. Lee, “Energy-Efficient Intelligent Street Lighting System Using Traffic-Adaptive Control,” IEEE Sens. J., vol. 16, no. 13, 2016,

📄 M. Caroline Viola Stella Mary, G. Prince Devaraj, T. Anto Theepak, D. Joseph Pushparaj, and J. Monica Esther, “Intelligent energy efficient street light controlling system based on IoT for smart city,” Proc. Int. Conf. Smart Syst. Inven. Technol. ICSSIT 2018, no. Icssit, pp. 551–554, 2018,

📄 R. R. Mohamed, M. A. Mohamed, A. Ahmad, and M. A. H. Abd Halim, “Provisioning of street lighting based on ambience intensity for smart city,” Indones. J. Electr. Eng. Comput. Sci., vol. 12, no. 3, pp. 1401–1406, 2018,

📄 R. B. Caldo et al., “Design and development of fuzzy logic controlled dimming lighting system using Arduino microcontroller,” 8th Int. Conf. Humanoid, Nanotechnology, Inf. Technol. Commun. Control. Environ. Manag. HNICEM 2015, no. December, pp. 0–5, 2016,

📄 D. Hartanti, R. N. Aziza, and P. C. Siswipraptini, “Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 17, no. 1, pp. 320–327, 2019,

📄 K. Choeychuen, “Fuzzy membership function optimization for smart LED lamp using particle swarm optimization,” 2018 Int. Work. Adv. Image Technol. IWAIT 2018, pp. 1–4, 2018,

How to Cite

Zulfikar Putra. (2024). FUZZY LOGIC AND IOT INTEGRATION FOR SMART STREET LIGHTING SYSTEMS. Global Multidisciplinary Journal, 3(08), 1-6. https://www.grpublishing.org/journals/index.php/gmj/article/view/110

Download Citation

Most read articles by the same author(s)

<< < 5 6 7 8 9 10 11 12 13 14 > >>

Global Multidisciplinary Journal

FUZZY LOGIC AND IOT INTEGRATION FOR SMART STREET LIGHTING SYSTEMS

Abstract

Keywords

References

How to Cite

Most read articles by the same author(s)

Similar Articles