Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Growing an organic indoor location system
Proceedings of the 8th international conference on Mobile systems, applications, and services
Accurate, low-energy trajectory mapping for mobile devices
Proceedings of the 8th USENIX conference on Networked systems design and implementation
MAQS: a personalized mobile sensing system for indoor air quality monitoring
Proceedings of the 13th international conference on Ubiquitous computing
Locating in fingerprint space: wireless indoor localization with little human intervention
Proceedings of the 18th annual international conference on Mobile computing and networking
A reliable and accurate indoor localization method using phone inertial sensors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
ARIEL: automatic wi-fi based room fingerprinting for indoor localization
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
CrowdInside: automatic construction of indoor floorplans
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Hi-index | 0.00 |
People spend approximately 70% of their time indoors. Understanding the indoor environments is therefore important for a wide range of emerging mobile personal and social applications. Knowledge of indoor floorplans is often required by these applications. However, indoor floorplans are either unavailable or obtaining them requires slow, tedious, and error-prone manual labor. This paper describes an automatic indoor floorplan construction system. Leveraging Wi-Fi fingerprints and user motion information, this system automatically constructs floorplan via three key steps: (1) room adjacency graph construction to determine which rooms are adjacent; (2) hallway layout learning to estimate room sizes and order rooms along each hallway, and (3) force directed dilation to adjust room sizes and optimize the overall floorplan accuracy. Deployment study in three buildings with 189 rooms demonstrates high floorplan accuracy. The system has been implemented as a mobile middleware, which allows emerging mobile applications to generate, leverage, and share indoor floorplans.