Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51528
Title: Smart Meter Data Analysis
Contributor(s): Aljamea, Moudhi M (author); Brankovic, Ljiljana  (author)orcid ; Gao, Jia (author); Iliopoulos, Costas S (author); Samiruzzaman, M (author)
Publication Date: 2016-03-22
DOI: 10.1145/2896387.2896407
Handle Link: https://hdl.handle.net/1959.11/51528
Abstract: 

Providing a global understanding of privacy is crucial, because everything is connected. Nowadays companies are providing their customers with more services that will give them more access to their data and daily activity; electricity companies are marketing the new smart meters as a new service with great benefit to reduce the electricity usage by monitoring the electricity reading in real time. Although the users might benefit from this extra service, it will compromise the privacy of the users by having constant access to the readings. Since the smart meters will provide the users with real electricity readings, they will be able to decide and identify which devices are consuming energy in that specific moment and how much it will cost. This kind of information can be exploited by numerous types of people. Unauthorized use of this information is an invasion of privacy and may lead to much more severe consequences. This paper will propose an algorithm approach for the comparison and analysis of Smart Meter data readings, considering the time and temperature factors at each second to identify the use patterns at each house by identifying the appliances activities at each second in time complexity O(log(m)).

Publication Type: Conference Publication
Conference Details: ICC 2016: International Conference on Internet of things and Cloud Computing, Cambridge, United Kingdom, 22nd - 23rd March, 2016
Source of Publication: ICC '16: Proceedings of the International Conference on Internet of things and Cloud Computing, p. 1-6
Publisher: Association for Computing Machinery (ACM)
Place of Publication: New York, United States of America
Fields of Research (FoR) 2020: 460402 Data and information privacy
Socio-Economic Objective (SEO) 2020: 220405 Cybersecurity
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
WorldCat record: http://www.worldcat.org/oclc/959722060
Appears in Collections:Conference Publication
School of Science and Technology

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