Identifying Typical Movements among Indoor Objects: Concepts and Empirical Study

Laura Radaelli, Dovydas Sabonis, Hua Lu, Christian S. Jensen

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


With the proliferation of mobile computing, positioning systems are becoming available that enable indoor location-based services. As a result, indoor tracking data is also becoming available. This paper puts focus on one use of such data, namely the identification of typical movement patterns among indoor moving objects. Specifically, the paper presents a method for the identification of movement patterns. Leveraging concepts from sequential pattern mining, the method takes into account the specifics of spatial movement and, in particular, the specifics of tracking data that captures indoor movement. For example, the paper's proposal supports spatial aggregation and utilizes the topology of indoor spaces to achieve better performance. The paper reports on empirical studies with real and synthetic data that offer insights into the functional and computational aspects of its proposal
TitelIEEE 14th International Conference on Mobile Data Management, Milan, Italy, June 3-6, 2013 : MDM 2013, Milan, Italy, June 3-6, 2013
Antal sider10
ForlagIEEE Computer Society Press
ISBN (Trykt)978-0-7685-4973-6
StatusUdgivet - 2013
Udgivet eksterntJa
Begivenhed14th IEEE International Conference on Mobile Data Management - Milano, Italien
Varighed: 3 jun. 20136 jun. 2013
Konferencens nummer: 14


Konference14th IEEE International Conference on Mobile Data Management

Citer dette