Bartholomew Idoko, John Bush Idoko, Yusuf Zubair Mahmud Kazaure, Yahanasu Mohammed Ibrahim, Fatai A. Akinsola, Adereti Rasak Raji
{"title":"IoT Based Motion Detector Using Raspberry Pi Gadgetry","authors":"Bartholomew Idoko, John Bush Idoko, Yusuf Zubair Mahmud Kazaure, Yahanasu Mohammed Ibrahim, Fatai A. Akinsola, Adereti Rasak Raji","doi":"10.1109/ITED56637.2022.10051334","DOIUrl":null,"url":null,"abstract":"In this paper, we designed a sophisticated security system that monitors a particular region (home or office) or a distinguished substance, evaluating occurrences within the scene. The system is implemented using gadgetry such as raspberry pi 2 model B, HC-SR501 sensor, Pi camera, mobile phone and a machine learning based python source code integrating the operations of these gadgets with those of SMS and image service clients (Nexmo and IMGUR) respectively. The unified function of these gadgets and services is basically to capture detected image within the scene and send it to a registered mobile phone in form of text message. The accuracy and response time of the proposed integrated system are very high and very low respectively.","PeriodicalId":246041,"journal":{"name":"2022 5th Information Technology for Education and Development (ITED)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th Information Technology for Education and Development (ITED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITED56637.2022.10051334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we designed a sophisticated security system that monitors a particular region (home or office) or a distinguished substance, evaluating occurrences within the scene. The system is implemented using gadgetry such as raspberry pi 2 model B, HC-SR501 sensor, Pi camera, mobile phone and a machine learning based python source code integrating the operations of these gadgets with those of SMS and image service clients (Nexmo and IMGUR) respectively. The unified function of these gadgets and services is basically to capture detected image within the scene and send it to a registered mobile phone in form of text message. The accuracy and response time of the proposed integrated system are very high and very low respectively.