RFID-based solution for galleries and museums visit modelling using Markov model, BBN's and MAP decisions

Authors:
Petar Solic;Nikola Rozic;Josko Radic
Affiliations:
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Department of Communication and Information Technologies, University of Split, Rudjera Boskovica b.b. 21000 Split, ...;Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Department of Communication and Information Technologies, University of Split, Rudjera Boskovica b.b. 21000 Split, ...;Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Department of Communication and Information Technologies, University of Split, Rudjera Boskovica b.b. 21000 Split, ...
Venue:
International Journal of Intelligent Information and Database Systems
Year:
2010

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Abstract

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 behaviour in a gallery room. The built model can be used in planning of exhibitions, in modelling of visitor's preferences, and/or in generation of predictions related with exhibition lasting, expected sales and pricing. Presented system performance improvements are realised through Bayesian belief network (BBN) and maximum a posterior probability (MAP) decision approximation algorithm.