Energy-Efficient Smart Street Lighting with Fault Detection and Real-Time Monitoring

The essential aspect for developing sustainable urban infrastructure includes effective energy management in street lighting systems. Street lighting systems require automaticstanding models with advanced energy efficiency alongside costefficient elements and systems for fault detection and energy reporting coupled with surveillance functions. System integration features sensors together with objects detection elements and real-time monitoring technology which dynamically adjusts lighting activities. Security increases through camera-based surveillance which enables remote video monitoring and adaptive lighting enables better human traffic visibility and avoids unnecessary energy usage by adapting to movements from animals. The system operates through a combination of solar power elements that charge lithium-ion cells for optimum utilization. A smart grid interface enables the system to provide live energy monitoring while enabling predictive equipment maintenance and adaptive lighting protocols to decrease operational disruptions. Energy reports are developed from continuously monitored and recorded voltage, current and power data which enables businesses to reach maximum operational effectiveness. The fault detection system can immediately identify broken streetlights while enhancing maintenance operations. IoT technology alongside machine learning and data analytics boosts fault identification and predictive services and energy monitoring so operators gain more reliable and affordable operation. The deployment of intelligent features leads to substantial energy-saving reductions along with improved city security levels. The paper reviews current strategic frameworks and technical approaches before establishing basic requirements for upcoming urban illumination systems. Technology applications contribute to constructing smart cities because they deliver better infrastructure while reducing power usage and increasing town safety.