{"title":"AIoT-based Audio Recognition System for Smart Home Applications","authors":"Bo-Wei Chen, Yun-Syuan Jhang, Hao-Ting Pai, Szu-Hong Wang, M. Sheu, Tzu-Hsuing Chen","doi":"10.1109/ICCE-TW52618.2021.9603103","DOIUrl":null,"url":null,"abstract":"In this paper, we design an audio recognition system to detect events of lighters sound, which names Audio Recognition System (ARS). ARS is composed of AIOT device (i.e. Raspberry Pi), deep-learning-based analytics, and real-time alarming advisory (e.g. Line Notify). We conduct experiments with 8,000 observations. The result shows ARS achieves 97% accuracy in a quiet place and 94% accuracy in a noisy environment.","PeriodicalId":141850,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-TW52618.2021.9603103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we design an audio recognition system to detect events of lighters sound, which names Audio Recognition System (ARS). ARS is composed of AIOT device (i.e. Raspberry Pi), deep-learning-based analytics, and real-time alarming advisory (e.g. Line Notify). We conduct experiments with 8,000 observations. The result shows ARS achieves 97% accuracy in a quiet place and 94% accuracy in a noisy environment.