Wireless sensor network for distributed event detection based on machine learning

Proceedings - 2014 IEEE International Conference on Internet of Things, iThings 2014, 2014 IEEE International Conference on Green Computing and Communications, GreenCom 2014 and 2014 IEEE International Conference on Cyber-Physical-Social Computing, CPS 2014

Volumn , Issue , 2014, Pages 540-545

  Rashid, Sidra ^a   Akram, Usman ^a   Qaisar, Saad ^a   Khan, Shoab Ahmed ^a   Felemban, Emad ^b  

^a NATIONAL UNIVERSITY OF SCIENCES AND TECHNOLOGY   (Pakistan)

^b University KSA   (Saudi Arabia)

Author keywords

Gaussian Mixture Model (GMM); K nearest neighbor (KNN); Negative pressure wave (NPW); Support Vector Machine (SVM); Wireless sensor network (WSN)

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONDITION MONITORING; CRIME; DATA HANDLING; DATA MINING; EQUIPMENT TESTING; HEALTH RISKS; IMAGE RETRIEVAL; LEARNING ALGORITHMS; LEARNING SYSTEMS; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; PATTERN RECOGNITION; PETROLEUM TRANSPORTATION; PIPELINES; SENSOR NODES; SUPPORT VECTOR MACHINES; VECTOR SPACES;

COLLABORATIVE APPROACH; COMMUNICATION OVERHEADS; DISTRIBUTED EVENT DETECTIONS; DISTRIBUTED WIRELESS SENSOR NETWORKS; ENVIRONMENTAL AND HEALTH RISKS; GAUSSIAN MIXTURE MODEL; K NEAREST NEIGHBOR (KNN); NEGATIVE PRESSURE WAVES;

WIRELESS SENSOR NETWORKS;

EID: 84988268711     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iThings.2014.93     Document Type: Conference Paper

References (12)

1. C. Antelope (2010), Valley Community College Vantage Technology Con-sulting Group, Data networking system wired vs. wireless report
2. A. Yang, S. Iyengar, S. S. Sastry, R. Bajcsy, P. Kuryloski, and R. Jafari., Distributed segmentationand classification of human actions using a wearable motion sensor network, In Proc. of IEEE Conf. on Computer Vision and Pattern Recognition Workshops (CVPRW 08), Anchorage, AK, USA, June 2008
3. M. Li, Y. Liu, and L. Chen, Non-threshold based event detection for 3d environment monitoring in sensor networks, In Proc. of 27th Intl. Conf. on Distributed Computing Systems (ICDCS 07), Toronto, Canada, June 2007
4. F. Martincic and L. Schwiebert, Distributed event detection in sensor networks, In Proc. of Intl. Conf. on Systems and Networks Communications (ICSNC 06), Tahiti, French Polynesia, Oct 2006
5. Valizadeh and S. B. andSalahshoor, Leak detection in transportation pipelines using feature extraction and knn classification, Pipelines: pp. 580-589, Oct 2009
6. www. libelium. com/development/waspmote.
7. Y. Sang, J. Zhang, and X. Lu, Signal processing based on wavelet transform in pipeline leakage detection and location, Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA 2006)
8. S. rashid, S. qaisar, H. saeed, and E. felemban, Performance analysis of leak detection algorithm in long range pipeline networks using transform analysis, IEEE conference on system, process and control 2013
9. J. C. Pesquet, H. Krim, and H. Carfantan, Time-invariant orthonormal wavelet representations, IEEE Trans. Signal Process., vol. 44, no. 8, pp. 19641970, Aug. 1996
10. L. Litwin, Fir and iir digital filters, IEEE Potentials. 0278-6648, 2000, 2831
11. H. Peng, F. Long, and C. Ding, Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy, IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1226-1238, Aug. 2005
12. www. libelium. com.