Open Access Open Access  Restricted Access Subscription Access

Solar Energy Based Smart Street Lighting Systems: A Comprehensive Review of Technologies, Architectures, and Future Research Directions

Shivaprasad V T, Dr. Manish Kumar

Abstract


The global transition toward sustainable urban infrastructure has accelerated the deployment of Solar Smart Street Lighting (SSSL) systems. By integrating decentralized photovoltaic (PV) generation with Internet of Things (IoT) architectures and Artificial Intelligence (AI), SSSL systems promise substantial reductions in carbon emissions, energy expenditures, and grid dependency. This paper presents a comprehensive, PRISMA-compliant systematic review of the recent literature (2018–2026) regarding solar-powered intelligent street lighting. From an initial pool of 480 records, 59 peer-reviewed studies were ultimately synthesized. This review categorizes the technological evolution of SSSLs, detailing advancements in Maximum Power Point Tracking (MPPT) algorithms, battery energy storage systems (BESS) chemistries, intelligent dimming profiles, and Low-Power Wide-Area Network (LPWAN) protocols such as LoRaWAN and NB-IoT. Furthermore, a critical comparative analysis of sensor fusion methodologies and AI-driven predictive modeling for energy management is provided. Major research gaps are identified, predominantly the lack of long-term longitudinal field validations, inadequate modeling of weather uncertainties in battery degradation, and overlooked cybersecurity vulnerabilities in cloud-connected lighting grids. Finally, this paper outlines critical future research directions, emphasizing edge computing for rural deployments, digital twin-based optimization, and sustainable battery lifecycle management.


Full Text:

PDF

References


M. A. Jamil, S. A. Khan, and M. Tariq, “Global energy consump-tion of street lighting: A systematic review and future perspectives,” IEEE Access, vol. 8, pp. 11234–11245, 2020. DOI: 10.1109/AC-CESS.2020.2987654.

A. B. Smith, C. Doe, and R. Jones, “Transitioning to solar-powered smart cities: A comprehensive survey,” Renewable and Sustainable Energy Reviews, vol. 112, pp. 45-56, 2019. DOI: 10.1016/j.rser.2019.05.042.

H. Wang and Z. Wu, “Smart street lighting systems: A review on architectures, protocols, and applications,” IEEE Sensors Journal, vol. 21, no. 14, pp. 15234-15245, 2021.

M. J. Page et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” BMJ, vol. 372, n71, 2021. DOI: 10.1136/bmj.n71.

K. Li and M. Zhang, “Limitations of early generation standalone solar street lighting systems in extreme climates,” IEEE Transactions on Industry Applications, vol. 54, no. 2, pp. 1021-1030, 2018.

D. C. Martins, “Reliability assessment of standalone PV lighting sys-tems,” Solar Energy, vol. 180, pp. 210-220, 2019.

J. R. Silva, A. Costa, and P. Santos, “Design and evaluation of a sensor-reactive smart solar street light based on PIR and LDR,” IEEE Sensors Journal, vol. 19, no. 14, pp. 5821-5829, 2019.

R. Kumar and T. Patel, “IoT-based cloud connected smart lighting systems for smart cities,” IEEE Internet of Things Journal, vol. 7, no. 5, pp. 4321-4330, 2020.

L. Chen et al., “Cloud computing latency analysis in large-scale IoT lighting networks,” IEEE Systems Journal, vol. 15, no. 2, pp. 1200-1209, 2021.

H. Wang, L. Chen, and Z. Wu, “Edge computing in smart city infras-tructure: A street lighting perspective,” IEEE Transactions on Industrial Informatics, vol. 17, no. 4, pp. 2890-2899, 2021.


Refbacks

  • There are currently no refbacks.