Title: Indoor Next Location Prediction with Wi-Fi

Year of Publication: March - 2014
Page Numbers: 107-113
Authors: Boon-Khai Ang, Daniel Dahlmeier, Ziheng Lin, Jian Huang, Mun-Lie Seeto, Hendy Shi
Conference Name: The Fourth International Conference on Digital Information Processing and Communications (ICDIPC2014)
- Malaysia


Indoor Location Intelligence is a novel application that relates indoor localization technology to business data to allow for better decision making for retail businesses. In this context, Wi-Fi technology has a big potential for localization of customers who move through the store. With this information, retailers are able to analyze shopper movement behavior when formalizing their business strategies. This paper evaluates the accuracy of next location prediction based on a Markov-chain model for forecasting the next location of a customer in a shop based on the last n locations he has visited. We report experiments on a real data set and achieve prediction accuracies of up to 37% for n=1 and 49% for n=2.