{"title":"Development of Street Lighting System with Object Detection","authors":"Juvy Amor M. Galindo, M. V. Caya","doi":"10.1109/HNICEM.2018.8666410","DOIUrl":null,"url":null,"abstract":"Streetlight that emits too much light or shines when and where it’s not needed is wasteful. Wasting energy has huge economic and environmental consequences. Automated street light management system is needed to resolve this problem. This study aims to develop an energy management methodology applied in the streetlights of a school campus. The study is a street lighting that has the dimming capability to minimize the cost of energy consumption. The LED light will illuminate when an object is detected. Raspberry Pi and Pi camera module were used to control the dimming of the LED lights. Furthermore, it has the capability of detecting objects like people walking in the streets. The object detection was made possible in identifying human from other objects using computer vision technique. Dimming capability of streetlight has proven that it can minimize power consumption of electricity.","PeriodicalId":426103,"journal":{"name":"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM.2018.8666410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Streetlight that emits too much light or shines when and where it’s not needed is wasteful. Wasting energy has huge economic and environmental consequences. Automated street light management system is needed to resolve this problem. This study aims to develop an energy management methodology applied in the streetlights of a school campus. The study is a street lighting that has the dimming capability to minimize the cost of energy consumption. The LED light will illuminate when an object is detected. Raspberry Pi and Pi camera module were used to control the dimming of the LED lights. Furthermore, it has the capability of detecting objects like people walking in the streets. The object detection was made possible in identifying human from other objects using computer vision technique. Dimming capability of streetlight has proven that it can minimize power consumption of electricity.