engleski

RFID-based solution for Galleries and Museums Visit modeling using Markov Model, BBN’s and MAP decisions

RFID technologies are becoming increasingly popular and widely used in many applications. Tags can be used for environment and habit monitoring, healthcare applications, home automation and pedestrian or vehicle traffic control. This paper describes the method of building a robust N-state Markov model that describes visitor’s behavior in a gallery room. The built model can be used in planning of exhibitions, in modeling of visitor’s preferences, and/or in generation of predictions related with exhibition lasting, expected sales and pricing. Presented system performance improvements are realized through Bayesian Belief Network (BBN) and MAP (Maximum A posteriori Probability) decision approximation algorithm.

Algorithm describing visitor’s behavior; Markov model of visitors; RFID based applications; Visitors tracking; Bayesian Network; MAP decision making.

nije evidentirano