Nano Uno-ML-IoT Based Smart Street Light System with Centralized Monitoring and Control
Keywords:
Internet of Things (IoT), Machine Learning (ML).Abstract
Streetlights are essential components of urban infrastructure that serve as modernity emblems and improve cities' evening aesthetic appeal. They are essential to maintaining both pedestrian and vehicle traffic safety and visibility. However, optimising energy use has become a top priority in light of the worldwide power constraint. Governments throughout the world have responded to this urgent problem by implementing Smart City programs, which use cutting-edge technology to encourage efficiency and sustainability in urban systems. This paper examined a challenge related to the creation of a smart street lighting system as part of this endeavour. This system efficiently monitors and controls streetlights by utilising state-of-the-art technology such as the Machine Learning, Internet of Things (IoT) and the GSM Communications. A CCMS, which regulates energy use and automates light operations, is incorporated into the suggested system. In order to enable precise on-and-off switching based on environmental circumstances, LDRs are employed to monitor ambient light levels. The solution greatly reduces energy consumption by integrating GSM and IoT frameworks to provide real-time streetlight performance monitoring and management. Because of this, this project not only saves electricity but also supports the larger goals of Smart City initiatives to promote sustainable urban growth. In particular, this project tackles suggestions made at the Tirupur event, demonstrating how cutting-edge technologies can be used practically to address pressing issues.
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