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

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.