AI-Powered Digital Twins and Internet of Things for Smart Cities and Sustainable Building Environment

被引：15

作者：

Alnaser, Aljawharah A. ^{[1
]}

Maxi, Mina ^{[2
]}

Elmousalami, Haytham ^{[3
,4
]}

机构：

[1] King Saud Univ, Dept Architecture & Bldg Sci, Coll Architecture & Planning, Riyadh 11574, Saudi Arabia

[2] Norwegian Univ Sci & Technol NTNU, Ind Ecol Energy & Proc Engn, N-7034 Trondheim, Norway

[3] Univ Melbourne, Fac Engn & IT, Infrastructure Dept, Parkville, Vic 3010, Australia

[4] Gen Petr Co GPC, Projects Sect Head & PMP, Cairo 743, Egypt

来源：

APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 24期

关键词：

smart cities; artificial intelligence; digital twins; building environment; sustainability; Internet of Things; ARTIFICIAL-INTELLIGENCE;

D O I：

10.3390/app142412056

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

This systematic literature review explores the intersection of AI-driven digital twins and IoT in creating a sustainable building environment. A comprehensive analysis of 125 papers focuses on four major themes. First, digital twins are examined in construction, facility management, and their role in fostering sustainability and smart cities. The integration of IoT and AI with digital twins and energy optimization for zero-energy buildings is discussed. Second, the application of AI and automation in manufacturing, particularly in Industry 4.0 and cyber-physical systems, is evaluated. Third, emerging technologies in urban development, including blockchain, cybersecurity, and EEG-driven systems for sustainable buildings, are highlighted. The study underscores the role of data-driven approaches in flood resilience and urban digital ecosystems. This review contributes to sustainability by identifying how digital technologies and AI can optimize energy use and enhance resilience in both urban and industrial contexts.

引用

页数：28

共 101 条

[41] The Hitchhiker's Guide to Fused Twins: A Review of Access to Digital Twins In Situ in Smart Cities [J].

Grubel, Jascha ;

Thrash, Tyler ;

Aguilar, Leonel ;

Gath-Morad, Michal ;

Chatain, Julia ;

Sumner, Robert W. ;

Holscher, Christoph ;

Schinazi, Victor R. .

REMOTE SENSING, 2022, 14 (13)

[42]

Hammam A., 2020, Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach, P297

[43]

Hemanth Kumar S., 2024, Advances in Human Resources Management and Organizational Development, P169, DOI [10.4018/979-8-3693-3238-2.ch008, DOI 10.4018/979-8-3693-3238-2.CH008]

[44] AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives [J].