Hua Lu – Finding Frequently Visited Indoor POIs Using Symbolic Indoor Tracking Data
Indoor tracking data is being amassed due to the deployment of indoor positioning technologies. Analyzing such data discloses useful insights that are otherwise hard to obtain. For example, by studying tracking data from an airport, we can identify the shops and restaurants that are most popular among passengers. This talk will present two types of queries that find frequently visited Points of Interest (POIs) from symbolic indoor tracking data. The snapshot query finds those POIs that were most frequently visited at a given time point, whereas the interval query finds such POIs for a given time interval. A symbolic indoor tracking system deploys a limited number of proximity detection devices, like RFID readers, at preselected locations, covering only part of the host indoor space. Consequently, symbolic tracking data is inherently uncertain and only enables the discrete capture of the trajectories of indoor moving objects in terms of coarse regions. The talk will cover uncertainty analyses of the data in relation to the two kinds of queries. The outcomes of the analyses are used to design processing algorithms for both query types. The experimental evaluation on the algorithms will also be discussed in the talk.
Hua Lu is an associate professor in the Department of Computer Science, Aalborg University, Denmark. He received the BSc and MSc degrees from Peking University, China, and the PhD degree in computer science from National University of Singapore. His research interests include database and data management, geographic information systems, and mobile computing. Recently, he has been working on indoor data management, skyline queries, complex spatial queries, and social data management. He has served as PC co chair or vice chair for ISA 2011, MUE 2011 and MDM 2012, demo chair for SSDBM 2014, and PhD forum cochair for MDM 2016. He has served on the program committees for conferences and workshops including ICDE, CIKM, ACM SIGSPATIAL, SSTD, MDM, PAKDD, APWeb, WAIM, and MobiDE. He is a senior member of the IEEE.