S. Bhatlawande, S. Shilaskar, Tejal Gadad, S. Ghulaxe, Rachana Gaikwad
{"title":"Smart Home Security Monitoring System based on Face Recognition and Android Application","authors":"S. Bhatlawande, S. Shilaskar, Tejal Gadad, S. Ghulaxe, Rachana Gaikwad","doi":"10.1109/IDCIoT56793.2023.10053558","DOIUrl":null,"url":null,"abstract":"Facial recognition is important concept when it comes to identification and security. The traditional ways of securing homes like the use of locks and keys are inefficient. Developing a security system using artificial intelligence (AI) that will monitor the surroundings and act in case of emergencies is vital. This paper proposes a smart home security monitoring system that can make decisions based on facial recognition technology. It is implemented using Mediapipe for face detection and FaceNet model for facial feature extraction. The proposed face recognition model is 80.55% accurate. An android application is developed which allows user to interact with the system even from remote distances. A door opening mechanism is implemented with the help of ESP8266. With the aid of the feedback from the reed switch, an alarm sounds when someone tries to break into the residence. The developed system provides a whole new security approach by discarding the need for traditional methods of security. The accuracy of the system is 80.55%.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"54 1","pages":"222-227"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"物联网技术","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/IDCIoT56793.2023.10053558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Facial recognition is important concept when it comes to identification and security. The traditional ways of securing homes like the use of locks and keys are inefficient. Developing a security system using artificial intelligence (AI) that will monitor the surroundings and act in case of emergencies is vital. This paper proposes a smart home security monitoring system that can make decisions based on facial recognition technology. It is implemented using Mediapipe for face detection and FaceNet model for facial feature extraction. The proposed face recognition model is 80.55% accurate. An android application is developed which allows user to interact with the system even from remote distances. A door opening mechanism is implemented with the help of ESP8266. With the aid of the feedback from the reed switch, an alarm sounds when someone tries to break into the residence. The developed system provides a whole new security approach by discarding the need for traditional methods of security. The accuracy of the system is 80.55%.