An Exploration of Location Error Estimation

Dave Dearman, Alex Varshavsky, Eyal de Lara, Khai Truong

9th International Conference on Ubiquitous Computing (Ubicomp), Innsbruck, Austria, September 2007



Many existing localization systems generate location predictions, but fail to report how accurate the predictions are. This paper explores the e ect of revealing the error of location predictions to the end-user in a location nding eld study. We report ndings obtained under four di erent error visualization conditions and show signi cant bene t in revealing the error of location predictions to the user in location nding tasks. We report the observed in uences of error on participants' strategies for location nding. Additionally, given the observed bene t of a dynamic estimate of error, we design practical algorithms for estimating the error of a location prediction. Analysis of the algorithms shows a median estimation inaccuracy of up to 50m from the predicted location's true error.