{"title":"Evaluating Feasibility of Image-Based Cognitive APIs for Home Context Sensing","authors":"Sinan Chen, S. Saiki, Masahide Nakamura","doi":"10.1109/CSPIS.2018.8642772","DOIUrl":null,"url":null,"abstract":"Cognitive API is API of emerging AI-based cloud services, which extracts various contextual information from non-numerical multimedia data including image and audio. Our interest is to apply image-based cognitive APIs to implement smart and affordable context sensing services in a smart home. However, since the existing APIs are trained for general-purpose image recognition, they may not be of practical use in specific configuration of smart homes. In this paper, we therefore propose a method that evaluates the feasibility of cognitive APIs for the home context sensing. In the proposed method, we exploit document similarity measures to see how well tags extracted from given images characterize the original contexts. Using the proposed method, we evaluate practical APIs of Microsoft Azure, IBM Watson, and Google Cloud for recognizing 11 different contexts in our smart home.","PeriodicalId":251356,"journal":{"name":"2018 International Conference on Signal Processing and Information Security (ICSPIS)","volume":"37 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Signal Processing and Information Security (ICSPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPIS.2018.8642772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Cognitive API is API of emerging AI-based cloud services, which extracts various contextual information from non-numerical multimedia data including image and audio. Our interest is to apply image-based cognitive APIs to implement smart and affordable context sensing services in a smart home. However, since the existing APIs are trained for general-purpose image recognition, they may not be of practical use in specific configuration of smart homes. In this paper, we therefore propose a method that evaluates the feasibility of cognitive APIs for the home context sensing. In the proposed method, we exploit document similarity measures to see how well tags extracted from given images characterize the original contexts. Using the proposed method, we evaluate practical APIs of Microsoft Azure, IBM Watson, and Google Cloud for recognizing 11 different contexts in our smart home.
认知API是一种新兴的基于人工智能的云服务API，它可以从包括图像和音频在内的非数字多媒体数据中提取各种上下文信息。我们的兴趣是应用基于图像的认知api，在智能家居中实现智能和负担得起的上下文感知服务。然而，由于现有的api是针对通用图像识别进行训练的，因此它们可能无法在智能家居的特定配置中实际使用。因此，在本文中，我们提出了一种评估家庭环境感知认知api可行性的方法。在提出的方法中，我们利用文档相似度度量来查看从给定图像中提取的标签如何很好地表征原始上下文。使用提出的方法，我们评估了Microsoft Azure, IBM Watson和谷歌Cloud的实用api，以识别我们智能家居中的11种不同环境。
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