Incrementally mining usage correlations among appliances in smart homes

Proceedings - 2015 18th International Conference on Network-Based Information Systems, NBiS 2015

Volumn , Issue , 2015, Pages 273-279

  Chen, Yi Cheng ^a   Hung, Hsiu Chieh ^a   Chiang, Bing Yang ^a   Peng, Sheng Yuan ^a   Chen, Peng Jun ^a  

^a TAMKANG UNIVERSITY   (Taiwan)

Author keywords

Correlation pattern; Incremental mining; Sequential pattern; Smart home; Usage representation

Indexed keywords

DOMESTIC APPLIANCES; INFORMATION SYSTEMS; INTELLIGENT BUILDINGS;

CORRELATION PATTERNS; INCREMENTAL MINING; SEQUENTIAL PATTERNS; SMART HOMES; USAGE REPRESENTATION;

AUTOMATION;

EID: 84964933198     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NBiS.2015.43     Document Type: Conference Paper

References (20)

1. J. Allen, Maintaining Knowledge about Temporal Intervals. Communications of ACM, vol.26, issue 11, pp.832-843, 1983.
2. O. Aritoni, V. Negru. A Methodology for Household Appliances Behavior Recognition in AmI Systems Integration. 7th International Conference on Automatic and Autonomous Systems (ICAS'11), pp. 175-178, 2011.
3. F. Chen, J. Dai, B. Wang, S. Sahu. Naphade, M., Lu, C.T. Activity Analysis Based on Low Sample Rate Smart Meters. 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pp. 240-248, 2011.
4. Y. Chen, J. Jiang, W. Peng, S. Lee. An Efficient Algorithm for Mining Time Interval-based Patterns in Large Databases. Proceedings of 19th ACM International Conference on Information and Knowledge Management (CIKM'10), pp. 49-58, 2010.
5. Y. Chen, W. Peng, W. Lee. A Novel System for Extracting Useful Correlation in Smart Home Environmen. The Sixth International Workshop on Domain Driven Data Mining (DDDM'13), pp. 357-364, 2013.
6. Y. Chen, C. Chen, W. Peng, W. Lee. Mining Correlation Patterns among Appliances in Smart Home Environment. 18th Pacific-Asia Conference in Knowledge Discovery and Data Mining, Advances in Knowledge Discovery and Data Mining (PAKDD'14), pp. 222-233, 2014.
7. Y. Chen, Y. Ko, W. Peng, W. Lee. Mining Appliance Usage Patterns in a Smart Home Environment. 17th Pacific-Asia Conference in Knowledge Discovery and Data Mining, Advances in Knowledge Discovery and Data Mining (PAKDD'13), pp. 99-110, 2013.
8. L. Farinaccio, R. Zmeureanu. Using a Pattern Recognition Approach to Disaggregate the Total Electricity Consumption in a House into the Major End-uses. Energy and Buildings, vol. 30, no. 3, pp. 245-259, 1999.
9. H. Goncalves, A. Ocneanu, M. Bergés. Unsupervised Disaggregation of Appliances Using Aggregated Consumption Data. The 1st KDD workshop on Data Mining Applications in Sustainability (SustKDD'11), 2011.
10. M. Ito, R. Uda, S. Ichimura, K. Tago, T. Hoshi, Y. Matsushita. A Method of Appliance Detection Based on Features of Power Waveform. The 4th IEEE Symposium on Applications and the Internet (SAINT'04), pp. 291-294, 2004.
11. V. Jakkula, D. Cook. Using Temporal Relations in Smart Environment Data for Activity Prediction. Proceedings of the 24th International Conference on Machine Learning (ICML'07), pp. 1-4, 2007.
12. V. Jakkula, D. Cook, A. Crandall. Temporal Pattern Discovery for Anomaly Detection in a Smart Home. Proceedings of the 3rd IET Conference on Intelligent Environments (IE'07), pp. 339-345, 2007.
13. T. Kato, H. Cho, D. Lee, T. Toyomura, T. Yamazaki. Appliance recognition from electric current signals for information-energy integrated network in home environments. Ambient Assistive Health and Wellness Management in the Heart of the City, vol. 5597, pp. 150-157, 2009.
14. H. Kim, M. Marwah, M. Arlitt, G. Lyon, J. Han, J. Unsupervised disaggregation of low frequency power measurements. 11th SIAM International Conference on Data Mining (SDM'11), pp. 747-758, 2011.
15. J. Kolter, M. Johnson. REDD: A Public Dataset for Energy Disaggregation Research. The 1st KDD workshop on Data Mining Applications in Sustainability (SustKDD'11), 2011.
16. G. Lin, S. Lee, J. Hsu, W. Jih. Applying power meters for appliance recognition on the electric panel. The 5th IEEE Conference on Industrial Electronics and Applications (ISIEA'10), pp. 2254-2259, 2010.
17. H. Matthews, L. Soibelman, M. Berges, E. Goldman. Automatically disaggregating the total electrical load in residential buildings: a profile of the required solution. Intelligent Computing in Engineering, pp. 381-389, 2008.
18. J. Pei, J. Han, B. Mortazavi-Asl, H. Pito, Q. Chen, U. Dayal, M. Hsu. PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth. Proceedings of 17th International Conference on Data Engineering (ICDE'01), pp. 215-224, 2001.
19. A. Prudenzi. A Neuron Nets Based Procedure for Identifying Domestic Appliances Pattern-of-use from Energy Recordings at Meter Panel. IEEE Power Engineering Society Winter Meeting, vol. 2, pp.491-496, 2002.
20. K. Suzuki, S. Inagaki, T. Suzuki, H. Nakamura, K. Ito. Nonintrusive appliance load monitoring based on integer programming. International Conference on Instrumentation, Control and Information Technology (SICE'08), pp. 2742-2747, 2008.