Synergistic integration of digital twins and zero energy buildings for climate change mitigation in sustainable smart cities: A systematic review and novel framework DOI Creative Commons

Simon Elias Bibri,

Jeffrey Huang, Osama Omar

et al.

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115484 - 115484

Published: Feb. 1, 2025

Language: Английский

Contributions of artificial intelligence and digitization in achieving clean and affordable energy DOI Creative Commons
Omojola Awogbemi, Daramy Vandi Von Kallon, K. Sunil Kumar

et al.

Intelligent Systems with Applications, Journal Year: 2024, Volume and Issue: 22, P. 200389 - 200389

Published: May 19, 2024

Concerned by the continuous decline in quality of life, poverty, environmental degradation, and escalated war conflicts, United Nations 2015 instituted 17 Sustainable Development Goals (SDGs) 169 targets. Access to clean, modern, affordable energy, also known as SDG 7, is one goals. Universal access electricity metrics for measuring a good life it fundamentally affects education, healthcare, food security, job creation, other socioeconomic indices. To achieve this goal targets, there has been increased traction research, development, actionable plans, policies, activities governments, scientific community, environmentalists, development experts, stakeholders achieving goal. This review presents various avenues which AI digitization can provide impetus 7. The global trends attaining clean electricity, cooking fuel, renewable energy efficiency, international public financial flows between 2005 2021 are reviewed while contribution towards meeting 7 highlighted. study concludes that deployment into sector will catalyze attainment 2030, provided ethical issues, regulatory concerns, manpower shortage, shortcomings effectively handled. recommends adequate infrastructural upgrades, modernization data collection, storage, analysis capabilities, improved awareness professional collaborative innovation, promotion legal issues ways advancing universal 2030. Going forward, more collaborations academic research institutions producers help produce experts professionals propel innovative digital technologies sector.

Language: Английский

Citations

13

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs DOI

Zhicheng Duan,

Tie Wei,

Pin Xie

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 252, P. 118742 - 118742

Published: April 2, 2024

Language: Английский

Citations

12

Comparative analysis of solar cells and hydrogen fuel: A mini-review DOI Creative Commons

Lina M. Shaker,

Jabbar K. Mohammed,

Ali Basem

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102507 - 102507

Published: July 4, 2024

The aim of this mini-review is to compare the effectiveness and potential solar cells hydrogen fuel technologies in clean energy generation. Key aspects such as efficiency, scalability, environmental footprint, technological maturity are examined. Solar analyzed for their ability convert sunlight into electricity efficiently widespread deployment with minimal impact. Hydrogen assessed based on efficiency production, overall footprint from production end use. review identifies significant challenges, including high costs, infrastructure needs, policy requirements, well opportunities innovation market growth. findings provide insights guide decision-making towards a sustainable future.

Language: Английский

Citations

10

Exploring the influence of linear infrastructure projects 4.0 technologies to promote sustainable development in smart cities DOI Creative Commons
Omar Sánchez, Karen Castañeda, Sofía Vidal-Méndez

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102824 - 102824

Published: Sept. 1, 2024

Language: Английский

Citations

9

Real-time gas explosion prediction at urban scale by GIS and graph neural network DOI
Jihao Shi, Junjie Li, Haoran Zhang

et al.

Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124614 - 124614

Published: Oct. 9, 2024

Language: Английский

Citations

9

AI and machine learning in climate change research: A review of predictive models and environmental impact DOI Creative Commons

Ahmad Hamdan,

Kenneth Ifeanyi Ibekwe,

Emmanuel Augustine Etukudoh

et al.

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 21(1), P. 1999 - 2008

Published: Jan. 25, 2024

The burgeoning threat of climate change has spurred an increased reliance on advanced technologies to comprehend and mitigate its far-reaching consequences. Artificial Intelligence (AI) Machine Learning (ML) have emerged as indispensable tools in research, offering unprecedented capabilities for predictive modeling assessing environmental impact. This review synthesizes the current state AI ML applications emphasizing their role understanding repercussions. Predictive models leveraging algorithms demonstrated remarkable efficacy forecasting patterns, extreme weather events, sea-level rise. These incorporate vast datasets encompassing meteorological, geospatial, oceanic information, enabling more accurate predictions future scenarios. Moreover, AI-driven excel recognizing intricate patterns non-linear relationships within data, enhancing capacity simulate complex systems. Environmental impact assessment stands a critical facet techniques are proving instrumental this regard. facilitate analysis diverse ecological parameters, including deforestation rates, biodiversity loss, carbon sequestration dynamics. By discerning nuanced immense datasets, systems contribute direct indirect consequences ecosystems. Despite these advancements, challenges persist, such need standardized data formats, model interpretability, ethical considerations. Additionally, integration findings into policy frameworks remains crucial frontier. As intersection AI, ML, research evolves, continuous interdisciplinary collaboration is essential harness full potential safeguarding our planet's future. illuminates landscape applications, providing insights efficacy, challenges, contributions advancing sustainability.

Language: Английский

Citations

8

Inclusive smart cities? Technology-driven urban development and disabilities DOI Creative Commons
Teemu Makkonen, Tommi Inkinen

Cities, Journal Year: 2024, Volume and Issue: 154, P. 105334 - 105334

Published: Aug. 2, 2024

The concept of smart cities refers to urban areas that utilize (digital) technologies enhance operations, services, and the quality life their residents. However, people have varying possibilities capabilities for using technologies. This intertwines technology-driven development with ideal inclusiveness (or lack thereof) as it seems unrealistic assume would benefit equally whole society. controversy is approached by questioning whether can really improve living conditions disadvantaged via reviewing literature ties persons disabilities. study shows, first, disabilities are rarely discussed in extant on particularly from a critical perspective. Second, underlined here, based reviewed literature, while city initiatives hold promise enhancing disabilities, they not one-size-fits-all answers tackle marginalization Rather, since technological solutions do counter fundamental barriers exclusion, still need advanced ideas establishing truly inclusive city.

Language: Английский

Citations

8

Predictive analysis-based sustainable waste management in smart cities using IoT edge computing and blockchain technology DOI

C. Anna Palagan,

S. Sebastin Antony Joe, S. A. Sahaaya Arul Mary

et al.

Computers in Industry, Journal Year: 2025, Volume and Issue: 166, P. 104234 - 104234

Published: Jan. 5, 2025

Language: Английский

Citations

1

Generative Spatial Artificial Intelligence for Sustainable Smart Cities: A Pioneering Large Flow Model for Urban Digital Twin DOI Creative Commons
Jeffrey Huang,

Simon Elias Bibri,

Paul Keel

et al.

Environmental Science and Ecotechnology, Journal Year: 2025, Volume and Issue: 24, P. 100526 - 100526

Published: Jan. 15, 2025

Language: Английский

Citations

1

Linking smart cities and SDGs through descriptive analysis of US municipalities DOI
Meng Cai, Travis Decaminada, Yingjie Li

et al.

Nature Cities, Journal Year: 2025, Volume and Issue: 2(2), P. 144 - 148

Published: Jan. 17, 2025

Language: Английский

Citations

1