Energy efficient data mining scheme for high dimensional data

Moh'D Alwadi, Girija CHETTY

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)
2 Downloads (Pure)

Abstract

In this paper, we propose energy efficient big data mining scheme for forest cover type and gas drift classification. Efficient machine learning and data mining techniques provide unprecedented opportunity to monitor and characterize physical environments, such as forest cover type, using low cost wireless sensor networks. The experimental validation on two different sensor network datasets, forest cover type and gas sensor array drift dataset from publicly available UCI machine learning repository. Coupled with an appropriate feature selection, the complete scheme leads towards an energy efficient protocol for intelligent monitoring of large physical environments instrumented with wireless sensor networks.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Information and Communications Technologies
EditorsPhilip Samual
Place of PublicationIndia
PublisherElsevier
Pages483-490
Number of pages8
Volume46
DOIs
Publication statusPublished - 2015
EventInternational Conference on Information and Communication Technologies: ICICT 2015 - Kochi, Kochi, India
Duration: 3 Dec 20145 Dec 2014

Publication series

NameProcedia Computer Science
PublisherElsevier
Volume46
ISSN (Print)1877-0509

Conference

ConferenceInternational Conference on Information and Communication Technologies
CountryIndia
CityKochi
Period3/12/145/12/14

Fingerprint

Data mining
Learning systems
Wireless sensor networks
Sensor arrays
Chemical sensors
Sensor networks
Feature extraction
Network protocols
Monitoring
Gases
Costs
Big data

Cite this

Alwadi, MD., & CHETTY, G. (2015). Energy efficient data mining scheme for high dimensional data. In P. Samual (Ed.), Proceedings of the International Conference on Information and Communications Technologies (Vol. 46, pp. 483-490). (Procedia Computer Science; Vol. 46). India: Elsevier. https://doi.org/10.1016/j.procs.2015.02.047
Alwadi, Moh'D ; CHETTY, Girija. / Energy efficient data mining scheme for high dimensional data. Proceedings of the International Conference on Information and Communications Technologies. editor / Philip Samual. Vol. 46 India : Elsevier, 2015. pp. 483-490 (Procedia Computer Science).
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Alwadi, MD & CHETTY, G 2015, Energy efficient data mining scheme for high dimensional data. in P Samual (ed.), Proceedings of the International Conference on Information and Communications Technologies. vol. 46, Procedia Computer Science, vol. 46, Elsevier, India, pp. 483-490, International Conference on Information and Communication Technologies, Kochi, India, 3/12/14. https://doi.org/10.1016/j.procs.2015.02.047

Energy efficient data mining scheme for high dimensional data. / Alwadi, Moh'D; CHETTY, Girija.

Proceedings of the International Conference on Information and Communications Technologies. ed. / Philip Samual. Vol. 46 India : Elsevier, 2015. p. 483-490 (Procedia Computer Science; Vol. 46).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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AU - CHETTY, Girija

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AB - In this paper, we propose energy efficient big data mining scheme for forest cover type and gas drift classification. Efficient machine learning and data mining techniques provide unprecedented opportunity to monitor and characterize physical environments, such as forest cover type, using low cost wireless sensor networks. The experimental validation on two different sensor network datasets, forest cover type and gas sensor array drift dataset from publicly available UCI machine learning repository. Coupled with an appropriate feature selection, the complete scheme leads towards an energy efficient protocol for intelligent monitoring of large physical environments instrumented with wireless sensor networks.

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KW - data mining

KW - wireless sensor networks

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Alwadi MD, CHETTY G. Energy efficient data mining scheme for high dimensional data. In Samual P, editor, Proceedings of the International Conference on Information and Communications Technologies. Vol. 46. India: Elsevier. 2015. p. 483-490. (Procedia Computer Science). https://doi.org/10.1016/j.procs.2015.02.047