{"title":"A context-aware system for personalized and accessible pedestrian paths","authors":"S. Mirri, Catia Prandi, P. Salomoni","doi":"10.1109/HPCSim.2014.6903776","DOIUrl":null,"url":null,"abstract":"This work presents mPASS (mobile Pervasive Accessibility Social Sensing), a social and ubiquitous context aware system to provide users with personalized and accessible pedestrian paths and maps. In order to collect a complete data set, our system gathers information from different sources: sensing, crowdsourcing and data produced by local authors and disability organizations. Gathered information are tailored to user's needs and preferences on the basis of his/her context, defined by his/her location, his/her profile and quality of data about the personalized path. To support the effectiveness of our approach, we have developed a prototype, which is described in this paper, together with some results of the context-based adaptation.","PeriodicalId":6469,"journal":{"name":"2014 International Conference on High Performance Computing & Simulation (HPCS)","volume":"51 1","pages":"833-840"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSim.2014.6903776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
Abstract
This work presents mPASS (mobile Pervasive Accessibility Social Sensing), a social and ubiquitous context aware system to provide users with personalized and accessible pedestrian paths and maps. In order to collect a complete data set, our system gathers information from different sources: sensing, crowdsourcing and data produced by local authors and disability organizations. Gathered information are tailored to user's needs and preferences on the basis of his/her context, defined by his/her location, his/her profile and quality of data about the personalized path. To support the effectiveness of our approach, we have developed a prototype, which is described in this paper, together with some results of the context-based adaptation.