The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
NilmDB: The Non-Intrusive Load Monitor Database
Abstract
This paper presents NilmDB, a comprehensive framework designed to solve the “big data” problem of non-intrusive load monitoring and diagnostics. It provides the central component of a flexible, distributed architecture for the storage, transfer, manipulation, and analysis of time-series data. NilmDB is network-transparent and facilitates remote viewing and management of large data sets by utilizing efficient data reduction and indexing techniques.
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“The latter argument is supported by Paris, Donnal, and Leeb (2014) who assert that one of the prime barriers to the analysis of BD arises from a lack of data provenance, knowledge and discrepancies of scale inherent in data collection and processing.”
From Critical analysis of Big Data challenges and analytical methods (2017) · cites this paper as Paris, Donnal, and Leeb (2014)
Citations
Cites
Hypertext Transfer Protocol -- HTTP/1.1
Fielding, R., Gettys, J., Mogul, J., Frystyk, H., Masinter, L., Leach, P., & Berners-Lee, T. (1999) · doi:10.17487/rfc2616 · Cited by 1,218
Research works printed but not linked: 20
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Cited by
Sorted by citations
Critical analysis of Big Data challenges and analytical methods
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.001 · Cited by 2,066
“The latter argu-ment is supported by Paris, Donnal, and Leeb (2014) who assert that one of the prime barriers to the analysis of BD arises from a lack of data provenance, knowledge and discrepancies of scale inherent in data collection and processing.”
BackgroundAkter, S., Bandara, R., Hani, U., Fosso Wamba, S., Foropon, C., & Papadopoulos, T. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.01.020 · Cited by 193
Metadata
- Authors
- Paris, J., Donnal, J. S., & Leeb, S. B.
- Affiliations
- Massachusetts Institute of Technology (US)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2014-09
- Volume
- 5
- Issue
- 5
- Pages
- 2459-2467
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2037072846
- Cited by
- 48
- References
- 1
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2022: 8 · 2021: 3 · 2020: 6 · 2019: 7 · 2018: 8 · 2017: 5 · 2016: 4 · 2015: 4
- FWCI
- 2.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
- Keywords
- non-intrusive load monitoring, time series, data storage, data reduction, indexing, big data, energy diagnostics
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