mlsanityData to 14 Oct 2026

A semantic web approach to uplift decentralized household energy data

arXiv 2208.10265 ↗First posted 18 Aug 2022cs.AI cs.IR cs.LGcited by 1

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Abstract (arXiv)

In a decentralized household energy system comprised of various devices such as home appliances, electric vehicles, and solar panels, end-users are able to dig deeper into the system's details and further achieve energy sustainability if they are presented with data on the electric energy consumption and production at the granularity of the device. However, many databases in this field are siloed from other domains, including solely information pertaining to energy. This may result in the loss of information (e.g. weather) on each device's energy use. Meanwhile, a large number of these datasets have been extensively used in computational modeling techniques such as machine learning models. While such computational approaches achieve great accuracy and performance by concentrating only on a local view of datasets, model reliability cannot be guaranteed since such models are very vulnerable to data input fluctuations when information omission is taken into account. This article tackles the data isolation issue in the field of smart energy systems by examining Semantic Web methods on top of a household energy system. We offer an ontology-based approach for managing decentralized data at the device-level resolution in a system. As a consequence, the scope of the data associated with each device may easily be expanded in an interoperable manner throughout the Web, and additional information, such as weather, can be obtained from the Web, provided that the data is organized according to W3C standards.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 61 references that are in the map. First posted on arXiv 18 Aug 2022.

Builds on

10 of 61 references.

References · 10

  1. 2018SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuatorscited by 27
  2. 2019Estimating Solar Irradiance Using Sky Imagerscited by 4
  3. 2021Validating Clustering Frameworks for Electric Load Demand Profilescited by 4
  4. 2016Estimation of solar irradiance using ground-based whole sky imagerscited by 3
  5. 2021A Clustering Framework for Residential Electric Demand Profilescited by 3
  6. 2021Ontology Modeling for Decentralized Household Energy Systemscited by 3
  7. 2019Interlinking Heterogeneous Data for Smart Energy Systemscited by 2
  8. 2021An Ontology Model for Climatic Data Analysiscited by 2
  9. 2021Automated Climate Analyses Using Knowledge Graphcited by 2
  10. 2021An Interoperable Open Data Portal for Climate Analysiscited by 1

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Citing papers per year: 2023: 1.

1 paper.