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Article

AI and Data Democratisation for Intelligent Energy Management

School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece
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Academic Editor: Anastasios Dounis
Energies 2021, 14(14), 4341; https://doi.org/10.3390/en14144341
Received: 20 June 2021 / Revised: 11 July 2021 / Accepted: 15 July 2021 / Published: 19 July 2021
(This article belongs to the Special Issue Big Data Applications for Intelligent Energy Management in Buildings)
Despite the large number of technology-intensive organisations, their corporate know-how and underlying workforce skill are not mature enough for a successful rollout of Artificial Intelligence (AI) services in the near-term. However, things have started to change, owing to the increased adoption of data democratisation processes, and the capability offered by emerging technologies for data sharing while respecting privacy, protection, and security, as well as appropriate learning-based modelling capabilities for non-expert end-users. This is particularly evident in the energy sector. In this context, the aim of this paper is to analyse AI and data democratisation, in order to explore the strengths and challenges in terms of data access problems and data sharing, algorithmic bias, AI transparency, privacy and other regulatory constraints for AI-based decisions, as well as novel applications in different domains, giving particular emphasis on the energy sector. A data democratisation framework for intelligent energy management is presented. In doing so, it highlights the need for the democratisation of data and analytics in the energy sector, toward making data available for the right people at the right time, allowing them to make the right decisions, and eventually facilitating the adoption of decentralised, decarbonised, and democratised energy business models. View Full-Text
Keywords: artificial intelligence; data democratisation; energy data spaces; interoperability; data sharing; energy management; decarbonisation; decision support artificial intelligence; data democratisation; energy data spaces; interoperability; data sharing; energy management; decarbonisation; decision support
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MDPI and ACS Style

Marinakis, V.; Koutsellis, T.; Nikas, A.; Doukas, H. AI and Data Democratisation for Intelligent Energy Management. Energies 2021, 14, 4341. https://doi.org/10.3390/en14144341

AMA Style

Marinakis V, Koutsellis T, Nikas A, Doukas H. AI and Data Democratisation for Intelligent Energy Management. Energies. 2021; 14(14):4341. https://doi.org/10.3390/en14144341

Chicago/Turabian Style

Marinakis, Vangelis, Themistoklis Koutsellis, Alexandros Nikas, and Haris Doukas. 2021. "AI and Data Democratisation for Intelligent Energy Management" Energies 14, no. 14: 4341. https://doi.org/10.3390/en14144341

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