Published on March 2020 | Artificial Intelligence, IoT, Embedded Systems, Cloud Computing

Real Time Adaptive Street Lighting System

With the aim to optimize the cost and performance of hardware and software integration, this paper discusses and inculcates the outcomes of various experiments that were conducted with different hardware and software technologies available commercially. This Smart Street light is designed with an aim of both performance and cost optimization, and includes a built-in weather station, forest fire/general fire notification and has the ability to continuously send data to the server for Analytics and Data Acquisition, as well as to the Mobile Application server. The data through the Mobile Application server can be fetched directly onto an app with good performance and the data being sent onto the Analytics and Data Acquisition server can be used for analysis and further research. Also, this project is sensitive to day and night and optimizes energy when there is no motion or when the ambient light is higher than a particular threshold determined experimentally. This paper opens the need for a better IoT based Street Light project with additional features and improved performance.