| Title |
Development of VLC-based Smart Streetlight System |
| Authors |
이소연(Soyeon Lee) ; 이강선(Kangsun Lee) ; 최예원(Yewon Choi) ; 심규성(Kyusung Shim) ; 안병구(Beongku An) |
| DOI |
https://doi.org/10.5573/ieie.2025.62.6.38 |
| Keywords |
AI; Deep neural network; Internet-of-Things; Visible light communication |
| Abstract |
In this paper, we propose a novel visible light communication (VLC)-based smart streetlight system. The main contributions of this paper can be summarized as follows. First, the developed system can measure the surrounding environment and decide whether the streetlight should be turned on or off. It can send these results to other streetlights via LED and provide the current status of the streetlight and surrounding environment to users and administrators through a web page. Second, various Internet-of-Things (IoT) sensors are used to sense the surrounding environment and store the collected data in a database. Third, a deep neural network, one of the artificial intelligence (AI) techniques, is employed to decide whether the streetlight should be turned on or off. Fourth, the proposed system can transmit decisions to other streetlights via VLC. Fifith, users and administrators can monitor the status of streetlights and the surrounding environment via a web page. Finally, numerical results confirm that the proposed VLC-based smart streetlight system works successfully. |