Aqib Ali, Baqir Nadeem Hashmi, Aliya Batool, Samreen Naeem, Sania Anam, Muhammad Munawar Ahmed
{"title":"Machine Learning Based Implementation of Home Automation Using Smart Mirror","authors":"Aqib Ali, Baqir Nadeem Hashmi, Aliya Batool, Samreen Naeem, Sania Anam, Muhammad Munawar Ahmed","doi":"10.32350/umtair.21.002","DOIUrl":null,"url":null,"abstract":"When ordered, it may be folded in half quickly and effortlessly. IoT (Internet of Things) technology drives the Smart Mirror's functionality. Standard mirror functionality is included, in addition to showing the user's social notifications, daily tasks, weather updates, breaking news, reminders, voice assistant notifications, and smartphone notifications. The Smart Mirror is connected to the Raspberry Pi-based network through Wi-Fi. A two-way mirror or an acrylic mirror sheet is used with the Raspberry-Pi mainboard to conceal the Mirror's rear end from the user. It supports modules written in any programming language. When Python is used as the primary programming language, these changes take care of the hardware and software limitations. This work discusses the creation and building of the Mirror in appropriate manner. In addition, possible uses of the Mirror are discussed. Compared to this DIY method, the cost is substantially lower, and the result is more predictable. The result produced by the support vector machine classifier are of accuracy which is 84% for detecting theft, and the confusion matrix is often diagonal, showing that this classifier can accurately labelled the data. Similarly, F1 score of 0.82% shows that there are a few false positives and false negatives, which is a favorable indicator.","PeriodicalId":198719,"journal":{"name":"UMT Artificial Intelligence Review","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"UMT Artificial Intelligence Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32350/umtair.21.002","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
When ordered, it may be folded in half quickly and effortlessly. IoT (Internet of Things) technology drives the Smart Mirror's functionality. Standard mirror functionality is included, in addition to showing the user's social notifications, daily tasks, weather updates, breaking news, reminders, voice assistant notifications, and smartphone notifications. The Smart Mirror is connected to the Raspberry Pi-based network through Wi-Fi. A two-way mirror or an acrylic mirror sheet is used with the Raspberry-Pi mainboard to conceal the Mirror's rear end from the user. It supports modules written in any programming language. When Python is used as the primary programming language, these changes take care of the hardware and software limitations. This work discusses the creation and building of the Mirror in appropriate manner. In addition, possible uses of the Mirror are discussed. Compared to this DIY method, the cost is substantially lower, and the result is more predictable. The result produced by the support vector machine classifier are of accuracy which is 84% for detecting theft, and the confusion matrix is often diagonal, showing that this classifier can accurately labelled the data. Similarly, F1 score of 0.82% shows that there are a few false positives and false negatives, which is a favorable indicator.
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