Abstract

WiFi-based indoor localization has emerged as perhaps the most promising approach to indoor localization because it holds the possibility of pretty good localization at a low cost, by leveraging the near-ubiquitous coverage of WiFi in indoor spaces of interest such as office buildings and malls. However, widespread deployment has been stymied by the need for significant calibration effort.

In this talk, I will trace through our research at MSR , moving towards the goal of zero-effort indoor localization. I will start with the Radar system, which pioneered the idea of piggybacking on an existing RF-based wireless LAN to perform indoor localization. Radar introduced two approaches to indoor localization: (a) RF fingerprinting through empirical measurements made at known locations, and (b) RF computation using mathematical modeling. While these techniques offer good localization accuracy and there has been much follow-on work on further improving accuracy, making empirical measurements in a new environment is expensive and customizing the mathematical model to such an environment is challenging. To overcome these difficulties, we advocate a crowdsourcing-based approach, wherein smartphones carried by users in normal course are used to make measurements and construct models, without any explicit effort on the part of users. The key is to use the radios and sensors on these smartphones, such as WiFi, GPS , accelerometer, and compass, in unison to (i) track users and thereby enable empirical measurement of training data, using a system called Zee, and (ii) construct an RF model with patchy information, using a system called EZ.

[EZ is joint work with Krishna Chintalapudi and Anand Iyer, and Zee with Krishna, Anshul Rai, and Riju Sen.]

Bio:Venkat Padmanabhan is a Principal Researcher and Research Manager at Microsoft Research India in Bangalore, where he founded and now leads the Mobility, Networks, and Systems group. Venkat was previously with Microsoft Research Redmond for almost 9 years. His research interests are broadly in networked and mobile systems, and his current/recent work is/has been on indoor localization, efficient mobile communication, network diagnostics, and green computing. He is serving as program co-chair for ACM Sigcomm 2012, and has served as an affiliate faculty member at the University of Washington, where he has taught and served on student thesis committees. Venkat holds a B.Tech. from IIT Delhi and an M.S. and a Ph.D. from UC Berkeley, all in Computer Science. He is a Fellow of the IEEE and a Distinguished Scientist of the ACM . He can be reached on the web athttp://research.microsoft.com/~padmanab/.