Monitoring orientation of moving objects around focal points

Patroumpas, K; Sellis, T

dc.contributor.author	Patroumpas, K	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:46:14Z
dc.date.available	2014-03-01T02:46:14Z
dc.date.issued	2009	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32621
dc.subject	Access Method	en
dc.subject	Communication Cost	en
dc.subject	Focal Point	en
dc.subject	Indexation	en
dc.subject	Location Awareness	en
dc.subject	Moving Object	en
dc.subject.other	Central processors	en
dc.subject.other	Central servers	en
dc.subject.other	Communication cost	en
dc.subject.other	Focal points	en
dc.subject.other	Location-aware	en
dc.subject.other	Moving objects	en
dc.subject.other	Novel access	en
dc.subject.other	Object orientation	en
dc.subject.other	Specific sites	en
dc.subject.other	Streaming approach	en
dc.subject.other	Trajectory movements	en
dc.subject.other	Cost reduction	en
dc.subject.other	Focusing	en
dc.title	Monitoring orientation of moving objects around focal points	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-02982-0_16	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-02982-0_16	en
heal.publicationDate	2009	en
heal.abstract	We consider a setting with numerous location-aware moving objects that communicate with a central server. Assuming a set of focal points of interest, we aim at continuously monitoring object orientations and hence detect situations where many objects get closer to or move away from any such site. Towards this goal, we propose a streaming approach that delegates part of the processing to objects, which relay positional updates upon significant deviations at their course. The central processor maintains the changing distribution of current object headings around each focal point and may issue alerts once it observes many objects moving along a direction (e.g., increased northbound traffic near the stadium). To efficiently answer such navigational queries, we introduce a novel access method that indexes object headings influencing a specific site. Furthermore, we extent this scheme to examine trajectory movements around sites over the recent past. Experimental results verify that this framework is able to cope with scalable numbers of objects at reduced communication cost, while offering instant notification of important trends along diverse directions for multiple focal points. © 2009 Springer Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-02982-0_16	en
dc.identifier.volume	5644 LNCS	en
dc.identifier.spage	228	en
dc.identifier.epage	246	en