Demonstration abstract: Crowdsourced indoor localization and navigation with Anyplace

Lambros Petrou, George Larkou, Christos Laoudias, Demetrios Zeinalipour-Yazti, Christos G. Panayiotou
2014 IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks  
In this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from
more » ... t WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data.
doi:10.1109/ipsn.2014.6846788 fatcat:sxccvbe2zngx7is3nbfqv6lnim