Impact Factor
Call For Paper
Volume 12 Issue 08
August 2026
Author(s)
Abstract
Traditional Street Lighting Operates On Fixed Schedules With No Fault Detection, Causing Energy Waste, Delayed Maintenance, And Safety Risks. This Paper Proposes An IoT-Based Smart Street Light Fault Detection And Adaptive Brightness Control Framework Leveraging ESP32 Microcontrollers, LDR, ACS712 Current Sensors, Voltage Sensors, And PIR Motion Detectors. The Blynk Cloud Platform Provides Remote Monitoring Via Mobile Apps, While MQTT Enables Lightweight Device-to-cloud Communication. Threshold-based Anomaly Detection Identifies Lamp Failures, Voltage Irregularities, And Connectivity Disruptions. Results Show ~45% Energy Reduction And Fault Detection Within 15 Seconds. The Modular Architecture Supports Future AI-driven Predictive Maintenance, Solar Integration, And Smart City Interoperability.
Keywords
Paper ID
IJSARTV12I6105646
Publication Date
June 9, 2026
Research Area
Computer Applications