000			03441nam a22005175i 4500
001			978-1-4614-4927-0
003			DE-He213
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007			cr nn 008mamaa
008			121116s2013 xxu| s |||| 0|eng d
020			_a9781461449270 _9978-1-4614-4927-0
024	7		_a10.1007/978-1-4614-4927-0 _2doi
050		4	_aT385
050		4	_aTA1637-1638
050		4	_aTK7882.P3
072		7	_aUYQV _2bicssc
072		7	_aCOM016000 _2bisacsh
082	0	4	_a006.6 _223
100	1		_aBestehorn, Markus. _eauthor.
245	1	0	_aQuerying Moving Objects Detected by Sensor Networks _h[electronic resource] / _cby Markus Bestehorn.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aXII, 71 p. 29 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Computer Science, _x2191-5768
505	0		_aIntroduction -- Applications for MOSD -- Background -- Generic Model of a Sensor Network -- Point Set Topology for Sensor Networks -- Deriving Predicate Results -- Spatio-Temporal Developments -- Spatio-Temporal Query Processing in SN -- Evaluation.
520			_aDeclarative query interfaces to Sensor Networks (SN) have become a commodity. These interfaces allow access to SN deployed for collecting data using relational queries. However, SN are not confined to data collection, but may track object movement, e.g., wildlife observation or traffic monitoring. While rational approaches are well suited for data collection, research on Moving Object Databases (MOD) has shown that relational operators are unsuitable to express information needs on object movement, i.e., spatio-temporal queries. Querying Moving Objects Detected by Sensor Networks studies declarative access to SN that track moving objects. The properties of SN present a straightforward application of MOD, e.g., node failures, limited detection ranges and accuracy which vary over time etc. Furthermore, point sets used to model MOD-entities like regions assume the availability of very accurate knowledge regarding the spatial extend of these entities, assuming such knowledge is unrealistic for most SN. This book is the first that defines a complete set of spatio-temporal operators for SN while taking into account their properties. Based on these operators, we systematically investigate how to derive query results from object detections by SN. Finally, process spatio-temporal queries are shown in SN efficiently, i.e., reducing the communication between nodes. The evaluation shows that the measures reduce communication by 45%-89%.
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aComputer graphics.
650		0	_aElectrical engineering.
650	1	4	_aComputer Science.
650	2	4	_aComputer Imaging, Vision, Pattern Recognition and Graphics.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aCommunications Engineering, Networks.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461449263
830		0	_aSpringerBriefs in Computer Science, _x2191-5768
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-4927-0
912			_aZDB-2-SCS
942			_cEBK
999			_c57659 _d57659