International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Street lighting is an essential component of modern urban infrastructure, ensuring road safety, pedestrian security, and improved public visibility during nighttime conditions. However, traditional street lighting systems operate using fixed schedules or constant brightness levels, regardless of environmental changes or traffic density. This results in excessive power consumption, higher electricity costs, and inefficient resource utilization. In developing regions, where energy management is critical, the need for intelligent and automated lighting systems has become increasingly important.This paper presents the design and implementation of a cost-effective Internet of Things (IoT)-based smart street lighting system aimed at enhancing energy efficiency and automation. The proposed system integrates environmental sensors, including a Light Dependent Resistor (LDR) for ambient light detection and an infrared (IR) sensor for vehicle or motion detection. A temperature sensor is also incorporated for environmental monitoring. These sensors are interfaced with a WiFi-enabled microcontroller that collects real-time data and transmits it to a centralized server for processing and storage.The system operates dynamically by analyzing ambient light intensity to determine day and night conditions. During daylight hours, the street lights remain switched off to conserve energy. At nighttime, the system adjusts brightness levels based on detected vehicle movement. When traffic density is low, the lights operate at reduced intensity, whereas brightness increases when movement is detected to ensure road safety. All sensor readings and lighting status information are stored in a MySQL database for monitoring, data analysis, and performance evaluation.Experimental observations demonstrate that the proposed IoT-based lighting system significantly reduces unnecessary energy consumption while maintaining adequate illumination standards. The system is scalable, affordable, and suitable for smart city applications. By minimizing human intervention and enabling real-time monitoring, the proposed solution contributes to sustainable urban energy management and improved infrastructure efficiency.

Keywords: Internet of Things (IoT), Smart Street Lighting, Energy Efficiency, Motion Detection, Ambient Light Sensor, Wireless Communication, Smart City.

Downloads: | DOI: 10.17148/IJARCCE.2026.15223