Big Data Value Chain: Multiple Perspectives for the Built Environment

Gema Hernández-Moral, Sofía Mulero-Palencia, Víctor Iván Serna-González, Carla Rodríguez-Alonso, Roberto Sanz-Jimeno, Vangelis Marinakis, Nikos Dimitropoulos, Zoi Mylona, Daniele Antonucci and Haris Doukas
Additional contact information
Gema Hernández-Moral: CARTIF Technology Centre, Parque Tecnológico de Boecillo, Boecillo, 47151 Valladolid, Spain
Sofía Mulero-Palencia: CARTIF Technology Centre, Parque Tecnológico de Boecillo, Boecillo, 47151 Valladolid, Spain
Víctor Iván Serna-González: CARTIF Technology Centre, Parque Tecnológico de Boecillo, Boecillo, 47151 Valladolid, Spain
Carla Rodríguez-Alonso: CARTIF Technology Centre, Parque Tecnológico de Boecillo, Boecillo, 47151 Valladolid, Spain
Roberto Sanz-Jimeno: CARTIF Technology Centre, Parque Tecnológico de Boecillo, Boecillo, 47151 Valladolid, Spain
Vangelis Marinakis: Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Nikos Dimitropoulos: Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Zoi Mylona: HOLISTIC IKE, 15343 Athens, Greece
Daniele Antonucci: Institute for Renewable Energy, Eurac Research, 39100 Bozen/Bolzano, Italy
Haris Doukas: Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Athens, Greece

Energies, 2021, vol. 14, issue 15, 1-21

Abstract: Current climate change threats and increasing CO 2 emissions, especially from the building stock, represent a context where action is required. It is necessary to provide efficient manners to manage energy demand in buildings and contribute to a decarbonised future. By combining new technologies, such as artificial intelligence, Internet of things, blockchain, and the exploitation of big data towards solving real life problems, the way could be paved towards smart and energy-aware buildings. In this context, the aim of this paper is to present a critical review and an in-detail definition of the big data value chain for the built environment in Europe, covering multiple needs and perspectives: “policy”, “technology” and “business”, in order to explore the main challenges and opportunities in this area.

Keywords: big data; artificial intelligence; machine learning; analytics; building stock (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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