Next Location Prediction Within a Smart Office Building
نویسندگان
چکیده
We investigate the feasibility of in-door next location prediction using sequences of previously visited locations and compare the efficiency of several prediction methods. The scenario concerns employees in an office building visiting offices in a regular fashion over some period of time. We model the scenario by different prediction techniques like Neural networks, Bayesian networks, State and Markov predictors. We use exactly the same evaluation set-up and benchmarks to compare the different methods. The publicly available Augsburg Indoor Location Tracking Benchmarks are applied as predictor loads.
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