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Smart city article details
| Title | Integrating Lora Technology For Smart Streetlight Systems: Enhancing Fault Detection And Adaptive Illumination |
|---|---|
| ID_Doc | 32031 |
| Authors | Saranya S.S.; Chokamela Kali Prasada Mani M.; Tammana M.S.S.A. |
| Year | 2025 |
| Published | 2nd International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2025 |
| DOI | http://dx.doi.org/10.1109/RMKMATE64874.2025.11042823 |
| Abstract | As the urban infrastructures are continuously updated, energy saving and public safety rely heavily on having a highly efficient and fault-resilient street lighting system. This paper proposes a fault detection and monitoring system for smart street lighting based on LoRa, which includes adaptive illumination depending on weather conditions and real-time web-based control. The system suggested uses a LoRaWAN (Long Range Wide Area Network) to obtain a smart solution for detecting faults and automating the response over long distances with very low power consumption. The streetlights have been equipped with a mechanism that can respond to specific climatic conditions like weather, ambient light, and real-time power consumption in order to adjust the illumination automatically. By determining these environmental conditions, the system suggests raised illuminations for good visibility during foggy and rainy weather, as well as overcast conditions yet is energy-efficient. The web-based dashboard allows for remote monitoring, fault notifications, and manual intervention, making possible preventive maintenance and intelligent power distribution.This study has proven to be very beneficial for the system as it helps in minimizing the cost associated maintenance, optimizes electric utilization, and improves public safety through autonomic defect recognition and adaptive brightness modifications. Its application will enable enhancement with respect to building a sustainable infrastructure for smart cities that encourage the development of energy-efficient and self-tuning street lighting networks. © 2025 IEEE. |
| Author Keywords | Adaptive Illumination; Energy Efficiency; Fault Detection; IoT; Long-Range Communication; LoRaWAN; Low-Power Networking; Power Optimization; Predictive Maintenance; Real-Time Monitoring; Smart City Infrastructure; Smart Street Lighting; Streetlight Automation; Sustainable Urban Development; Weather-Based Lighting Control; Web-Based Dashboard; Wireless Sensor Networks (WSN) |
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