Big Data Value Chain: Multiple Perspectives for the Built Environment

被引:5
|
作者
Hernandez-Moral, Gema [1 ]
Mulero-Palencia, Sofia [1 ]
Serna-Gonzalez, Victor Ivan [1 ]
Rodriguez-Alonso, Carla [1 ]
Sanz-Jimeno, Roberto [1 ]
Marinakis, Vangelis [2 ]
Dimitropoulos, Nikos [2 ]
Mylona, Zoi [3 ]
Antonucci, Daniele [4 ]
Doukas, Haris [2 ]
机构
[1] CARTIF Technol Ctr, Parque Tecnol Boecillo, Valladolid 47151, Spain
[2] Natl Tech Univ Athens, Sch Elect & Comp Engn, Decis Support Syst Lab, Athens 15780, Greece
[3] HOLISTIC IKE, Athens 15343, Greece
[4] Eurac Res, Inst Renewable Energy, I-39100 Bozen Bolzano, Italy
基金
欧盟地平线“2020”;
关键词
big data; artificial intelligence; machine learning; analytics; building stock; BUILDING ENERGY; NEURAL-NETWORKS; PREDICTION; EFFICIENCY; VERIFICATION; METHODOLOGY; CONSUMPTION;
D O I
10.3390/en14154624
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Current climate change threats and increasing CO2 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.
引用
收藏
页数:21
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