受賞

2015年11月

Best paper award

MELT2015:5th International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments co-located with 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2015)
  • MELT2015:5th International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments co-located with 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2015)

タイトル
Estimate a User’s Location Using Smartphone’s Barometer on a Subway
受賞区分
国際学会・会議・シンポジウム等の賞
受賞国・地域
アメリカ合衆国

Knowing the location of a train is necessary to develop a useful service for train passengers. However, popular localization methods such as GPS and Wi-Fi are not accurate especially on a subway. As an alternative method, estimation of motion state and stop station by using sensors on a smartphone is being studied for subway passengers. This paper proposes a localization method that uses only a barometer on a smartphone. We estimate motion state from the change of elevation, and also estimate latest stop station by the similarity of a series of elevations recorded when the train stopped and actual elevations of stations. By estimation of the motion state and the latest stop station, development of various context-aware services for subway passengers becomes possible. Through experiments in four lines of subway in Tokyo, we demonstrated that the accuracy of estimation of the motion state is 86%, and estimation of the stop station is 58%.