{"title":"Future Directions for Indoor Information Systems: A Panel Discussion","authors":"D. Zeinalipour-Yazti","doi":"10.1109/MDM.2018.00013","DOIUrl":null,"url":null,"abstract":"Geographic Information Systems (GIS) have enabled a vast range of applications in outdoor spaces, but these systems are bound to accurate localization technologies that are not available inside buildings where people carry 90% of their activities. Additionally, GIS don't address the unique characteristics of complex indoor environments off-the-shelf. At the same time, we witness the uptake of a new class of Indoor Information Systems (IIS), which store indoor spatial models along with sensor signals (e.g., wireless, light and magnetic) used to localize users. Such IIS might be considered as specialized GIS applications that are tailored to the unique challenges pertinent to indoor spaces, namely new indoor data management operators, new indexes, new data privacy schemes, built-in data-driven localization algorithms, models to crowdsource IIS data and these might even use NoSQL architectures. This panel will explore how the academia and industry are tackling the future challenges that rise in the scope of IIS. It will also identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management and mobile data mining communities should contribute to.","PeriodicalId":205319,"journal":{"name":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDM.2018.00013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Geographic Information Systems (GIS) have enabled a vast range of applications in outdoor spaces, but these systems are bound to accurate localization technologies that are not available inside buildings where people carry 90% of their activities. Additionally, GIS don't address the unique characteristics of complex indoor environments off-the-shelf. At the same time, we witness the uptake of a new class of Indoor Information Systems (IIS), which store indoor spatial models along with sensor signals (e.g., wireless, light and magnetic) used to localize users. Such IIS might be considered as specialized GIS applications that are tailored to the unique challenges pertinent to indoor spaces, namely new indoor data management operators, new indexes, new data privacy schemes, built-in data-driven localization algorithms, models to crowdsource IIS data and these might even use NoSQL architectures. This panel will explore how the academia and industry are tackling the future challenges that rise in the scope of IIS. It will also identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management and mobile data mining communities should contribute to.