An algorithmic approach for analysis of animal movement with granular computing in relation with data mining

The paper aims to bring together researchers and domain experts involved in developing and utilizing methods for knowledge extraction from massive amounts of data from moving objects. Technologies for object tracking are low cost and increasingly reliable in terms of coverage and accuracy; hence mov...

Full description

Saved in:
Bibliographic Details
Published in2014 International Conference on Contemporary Computing and Informatics (IC3I) pp. 224 - 229
Main Authors Rawat, Neelam, Sodhi, J. S., Tyagi, Rajesh K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2014
Subjects
Online AccessGet full text

Cover

Loading…
Abstract The paper aims to bring together researchers and domain experts involved in developing and utilizing methods for knowledge extraction from massive amounts of data from moving objects. Technologies for object tracking are low cost and increasingly reliable in terms of coverage and accuracy; hence movement records are nowadays generated in huge volumes on a routine basis, using diverse technologies such as radio frequency mapping, Global Navigation Satellite Systems, video sequences and Doppler radar. The computational analysis of movement data has seen a successful first decade with progress made in capturing, preprocessing, storing, indexing and querying movement data, combined with promising results in visualizing movement and detecting movement patterns. In many application fields, such as animal monitoring, transportation, or epidemiology, the need for analyzing large sets of trajectories is evident and crucial; however, only very rudimentary automated analysis tools are available and more advanced analyses are carried out manually. Thus the analysis part has been neglected and in comparison with the image processing part it is technologically far behind in the development. A reason for this is a lack of theoretical and practical solutions for many crucial fundamental problems.
AbstractList The paper aims to bring together researchers and domain experts involved in developing and utilizing methods for knowledge extraction from massive amounts of data from moving objects. Technologies for object tracking are low cost and increasingly reliable in terms of coverage and accuracy; hence movement records are nowadays generated in huge volumes on a routine basis, using diverse technologies such as radio frequency mapping, Global Navigation Satellite Systems, video sequences and Doppler radar. The computational analysis of movement data has seen a successful first decade with progress made in capturing, preprocessing, storing, indexing and querying movement data, combined with promising results in visualizing movement and detecting movement patterns. In many application fields, such as animal monitoring, transportation, or epidemiology, the need for analyzing large sets of trajectories is evident and crucial; however, only very rudimentary automated analysis tools are available and more advanced analyses are carried out manually. Thus the analysis part has been neglected and in comparison with the image processing part it is technologically far behind in the development. A reason for this is a lack of theoretical and practical solutions for many crucial fundamental problems.
Author Rawat, Neelam
Sodhi, J. S.
Tyagi, Rajesh K.
Author_xml – sequence: 1
  givenname: Neelam
  surname: Rawat
  fullname: Rawat, Neelam
  organization: KIET, Ghaziabad, India
– sequence: 2
  givenname: J. S.
  surname: Sodhi
  fullname: Sodhi, J. S.
  organization: Amity Univ., Noida, India
– sequence: 3
  givenname: Rajesh K.
  surname: Tyagi
  fullname: Tyagi, Rajesh K.
  organization: MVN Univ., Faridabad, India
BookMark eNotUEtqwzAUVKFdtGkOULrRBew-2bJkLYPpxxDIpl2HZ0tyBLJkZKclt68hWc3AfBjmidyHGAwhLwxyxkC9tU3Z5gUwnktgqpLyjmyVrBmXSglRqOqR-F2g6IeY3HIaXU9xmlLE_kRtTBQD-svsZhrtyt2Ino7x14wmLPRvDdAhYTh7TLSP43ReXBioCzQZj4uL4erRuCAdXVjFZ_Jg0c9me8MN-fl4_26-sv3hs212-8wxAUtWlrbi0IGRkkkNYG0JvVHcWC5F0WtVSNWD1aLDQmit6g6AWym6ql6dTJQb8nrtdcaY45TW5elyvH1Q_gMgPVdQ
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/IC3I.2014.7019577
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library Online
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library Online
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9781479966295
1479966290
EndPage 229
ExternalDocumentID 7019577
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i160t-33f540b0e7717d00ff30ce94ef4762cd9279c0fd6ba26dd98b004f76b58f30163
IEDL.DBID RIE
IngestDate Thu Jun 29 18:37:48 EDT 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i160t-33f540b0e7717d00ff30ce94ef4762cd9279c0fd6ba26dd98b004f76b58f30163
PageCount 6
ParticipantIDs ieee_primary_7019577
PublicationCentury 2000
PublicationDate 2014-Nov.
PublicationDateYYYYMMDD 2014-11-01
PublicationDate_xml – month: 11
  year: 2014
  text: 2014-Nov.
PublicationDecade 2010
PublicationTitle 2014 International Conference on Contemporary Computing and Informatics (IC3I)
PublicationTitleAbbrev IC3I
PublicationYear 2014
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.592627
Snippet The paper aims to bring together researchers and domain experts involved in developing and utilizing methods for knowledge extraction from massive amounts of...
SourceID ieee
SourceType Publisher
StartPage 224
SubjectTerms Algorithm design and analysis
Animals
Data mining
Heuristic algorithms
Indexes
Informatics
Movement analysis - Moving Objects
Moving Point
Moving Region
Spatio-temporal Data
Time-domain analysis
Title An algorithmic approach for analysis of animal movement with granular computing in relation with data mining
URI https://ieeexplore.ieee.org/document/7019577
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV09T8MwELXaTkyAWsS3PDCS1GmcOB5RRdUiFTFQqVvlzxLRJKhKF349ZyctAjGwWdHJiWw57-787h1Cd64wIIbIIzBEiQBOog0ETUSgAIwjRUUUWZfQnz-n0wV9WibLDro_1MIYYzz5zIRu6O_ydaV2LlU2dNLhCWNd1GWcN7Va7UVlRPhwNo5njqtFw9buR8MUjxeTYzTfv6mhibyHu1qG6vOXCON_P-UEDb4r8_DLAXNOUceUfbR5KLHYrCuI89-KXOG9TjgGhxSLVnUEVxbGeSE2uKi8SHiNXRIWrwGtHBcVK9_gAabFeYm3LUmusXE8Ulz4XhIDtJg8vo6nQdtFIcijlNRBHFvwyiQxDCI3TYi1MVGGU2Mp_AiV5iPGFbE6lWKUas0zd5AtS2WSgSW4a2eoV1alOUfYaE25VFJpALU0E2LEFCeWc5txKVl0gfpupVYfjVDGql2ky78fX6Ejt1tNYd816tXbnbkBhK_lrd_aL--vqoQ
link.rule.ids 310,311,783,787,792,793,799,27937,55086
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT8JAEJ4gHvSkBoxv9-DRli197tEQDSgQD5BwI_tEIm0NKRd_vbNtwWg8eNs0k22zm-03M_vNNwB3tjDAx8jD0VRyB0-icXgQckciGHsy4J5nbEJ_NI760-B5Fs4acL-rhdFal-Qz7dpheZevcrmxqbKOlQ4P43gP9tGvTqKqWqu-qvQo6wx6_sCytQK3tvzRMqVEjKcjGG3fVRFF3t1NIVz5-UuG8b8fcwzt79o88rpDnRNo6KwFq4eM8NUix0j_LV1KslUKJ-iSEl7rjpDc4HiZ8hVJ81ImvCA2DUsWiFeWjUpk2eIBpyXLjKxrmlxlY5mkJC27SbRh-vQ46fWduo-Cs_QiWji-b9AvE1THGLspSo3xqdQs0CbAX6FUrBszSY2KBO9GSrHEHmUTRyJM0BIdtlNoZnmmz4BopQImpJAKYS1KOO_GklHDmEmYELF3Di27UvOPSipjXi_Sxd-Pb-GgPxkN58PB-OUSDu3OVWV-V9As1ht9jXhfiJtym78AA1-tzw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2014+International+Conference+on+Contemporary+Computing+and+Informatics+%28IC3I%29&rft.atitle=An+algorithmic+approach+for+analysis+of+animal+movement+with+granular+computing+in+relation+with+data+mining&rft.au=Rawat%2C+Neelam&rft.au=Sodhi%2C+J.+S.&rft.au=Tyagi%2C+Rajesh+K.&rft.date=2014-11-01&rft.pub=IEEE&rft.spage=224&rft.epage=229&rft_id=info:doi/10.1109%2FIC3I.2014.7019577&rft.externalDocID=7019577