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Smart Meter Load Profiling for e-Health Monitoring System
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems, Electronic and embedded systems. University of Turku (UTU), Turku, Finland.ORCID iD: 0000-0003-2357-1108
University of Turku (UTU), Turku, Finland.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems, Electronic and embedded systems. University of Turku (UTU), Turku, Finland.
2019 (English)In: 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada: IEEE, 2019, , p. 6Conference paper, Published paper (Refereed) [Artistic work]
Abstract [en]

A structural health-monitoring system needed to come out from the problem associated due to the rapidly growing population of elderly and the health care demand. The paper discussed the consumer's electricity usage data, from the smart meter, how to support the healthcare sector by load profiling the normal or abnormal energy consumption. For this work, the measured dataset is taken from 12 households and collected by the smart meter with an interval of an hour for one month. The dataset is grouped according to the features pattern, reduced by matrix-based analysis and classified with K-Means algorithm data mining clustering method. We showed how the clustering result of the Sum Square Error (SSE) has connection trend to indicate normal or abnormal behavior of electricity usage and leads to determine the assumption of the consumer's health status.

Place, publisher, year, edition, pages
Oshawa, ON, Canada: IEEE, 2019. , p. 6
Series
IEEE Catalog Number: CFP19SEJ-ART, ISSN 2575-2693
Keywords [en]
smart meter; clustering method; ehealth monitoring
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-262651DOI: 10.1109/SEGE.2019.8859936Scopus ID: 2-s2.0-85074105936ISBN: 978-1-7281-2440-7 (print)OAI: oai:DiVA.org:kth-262651DiVA, id: diva2:1361524
Conference
2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE)ON, Canada, 2019, pp. 97-102.
Note

QC 20191209

Available from: 2019-10-16 Created: 2019-10-16 Last updated: 2019-12-09Bibliographically approved

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