IoT Street Lighting System with Real-Time Fog and Light Intensity Sensing and Cloud-Enabled Data Monitoring for Smart Cities

Today’s urbanization has led us to the need of conservation of energy. One of the routine applications is city street lighting system for road safety. This paper proposes a low budget environment friendly street light controller that activates lighting automated to darkness and fog presence. The system uses ESP32 microcontroller interface with LDR to measure light intensity and DHT22 sensor to monitor temperature and humidity. The algorithm for fog detection used a threshold of humidity exceeding 90% and temperature lowering to 20°C. Data from multiple sensors are processed at real time, which is controlling a LED to simulate the status of street light on/off. Parallel to this a code is transmitting environment readings, activation status to a Google Sheet via Wi-Fi (serverless webhook for real time cloud logging). A series of test cases are collected for accuracy and responsiveness of the system. Comparative analysis demonstrates advantages of this system over traditional one. The proposed system is cost effective, scalable, easy to deploy. Future enhancement includes solar power integration, predictive analysis using machine learning, user friendly dashboards. This work gives a feasible effective solution for adaptive urban or rural area street lighting