{"title":"Context-Aware Computing: A Guide for the Pervasive Computing Community","authors":"G. K. Mostéfaoui, J. Pasquier-Rocha, P. Brézillon","doi":"10.1109/ICPS.2004.14","DOIUrl":null,"url":null,"abstract":"There is a high interest on context-aware computing expressed by the pervasive computing community, which considers context as a key to design more adaptive applications. Due to this interest, a huge amount of contributions have been made in the field as we can notice from the increasing amount of publications on context and context-aware computing. However, the user interested in integrating context in its specific application will rapidly find himself in a jungle of various tools and techniques. This paper aims at structuring this information by providing a survey on the main context-aware categorization, acquisition and modeling techniques. \"Main\" refers to the most promising techniques in terms of their genericity in a way that they can be used in various application domains. This work tends to provide a guide for the pervasive computing community in order to select the best technique to use in a specific application or -more interesting- to justify the development of a new one.","PeriodicalId":222266,"journal":{"name":"The IEEE/ACS International Conference on Pervasive Services","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"96","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The IEEE/ACS International Conference on Pervasive Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS.2004.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 96
Abstract
There is a high interest on context-aware computing expressed by the pervasive computing community, which considers context as a key to design more adaptive applications. Due to this interest, a huge amount of contributions have been made in the field as we can notice from the increasing amount of publications on context and context-aware computing. However, the user interested in integrating context in its specific application will rapidly find himself in a jungle of various tools and techniques. This paper aims at structuring this information by providing a survey on the main context-aware categorization, acquisition and modeling techniques. "Main" refers to the most promising techniques in terms of their genericity in a way that they can be used in various application domains. This work tends to provide a guide for the pervasive computing community in order to select the best technique to use in a specific application or -more interesting- to justify the development of a new one.