Energy Strategy Reviews, Год журнала: 2025, Номер 59, С. 101743 - 101743
Опубликована: Апрель 23, 2025
Язык: Английский
Sustainable Development, Год журнала: 2024, Номер unknown
Опубликована: Июль 24, 2024
Abstract Future tools for supporting collaborations between technology and sustainable development include artificial intelligence (AI) applications in Urbanization roles. This article highlights the various of AI advancing urbanization. From urban planning to disaster management, is revolutionizing way cities are designed managed. By leveraging data analytics, machine learning, predictive modeling, helping city officials make informed decisions, optimize resource usage, improve quality life residents. Despite immense potential development, there still challenges limitations overcome. We show some most significant problems related these issues. These issues privacy, algorithm bias, ethical considerations. Continued research innovation needed address ensure that used responsibly effectively shaping cities. As a result, has power transform environments create more sustainable, resilient communities. harnessing capabilities AI, can become efficient, environmentally‐friendly, prepared future. It essential policymakers, planners, developers work together harness full urbanization better future all. Proactively addressing unlock combating building
Язык: Английский
Процитировано
22
Research in International Business and Finance, Год журнала: 2024, Номер 73, С. 102531 - 102531
Опубликована: Авг. 22, 2024
Язык: Английский
Процитировано
20
International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105197 - 105197
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1
Discover Sustainability, Год журнала: 2025, Номер 6(1)
Опубликована: Янв. 16, 2025
This study presents a detailed literature review on financing for renewable and sustainable energy through bibliometric analysis scientific mapping, utilizing the Scopus database from 2000 to 2023. Using network techniques, it identifies eight main clusters, each focusing different aspects of their geographic technical contexts. The highlights most frequently cited articles, notable authors, key institutions, affiliations, journals in finance. A random effects model meta-analysis was also conducted assess overall effect size research stream. Findings indicate that finance has expanded since exhibits considerable diversity. pinpoints five major themes suitable discussion exploration new questions: (i) role Fintech finance, (ii) regulatory framework governing (iii) economic feasibility emerging markets, (iv) influence private public development, (v) relationship between development goals. insights this aim inspire equip readers as they embark inquiries into connections investment, policy, behavioral sciences. Following identifying gaps, paper outlines potential future directions. It serves thorough resource current trends investments recommends viable topics, thus benefiting researchers, professionals, policymakers alike.
Язык: Английский
Процитировано
1
Energy Economics, Год журнала: 2025, Номер unknown, С. 108231 - 108231
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1
Renewable Energy, Год журнала: 2025, Номер unknown, С. 122598 - 122598
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1
Energy, Год журнала: 2025, Номер unknown, С. 135077 - 135077
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1
Economic Change and Restructuring, Год журнала: 2024, Номер 57(5)
Опубликована: Сен. 4, 2024
Язык: Английский
Процитировано
7
Sustainable Development, Год журнала: 2024, Номер unknown
Опубликована: Окт. 6, 2024
Abstract Artificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on efforts of reducing carbon emissions more efficiently effectively, this study tries focus AI integration with capture technology. The urgency tackling climate change means we need advanced capture, is an area where can make a huge impact in how these technologies operated managed. It will minimize manufacturing improve both resource efficiency as well our planet's footprint by turning waste into something value again. could be leveraged analyze data sets from plants, searching for optimal system settings efficient ways identifying patterns available information at larger scale than currently possible. In addition, incorporated sensors monitoring mechanisms supply chain identify any operational failure reception itself allowing timely action protect those areas. also helps generative design materials, which allows researchers explore new types carbon‐absorbing material, including metal–organic frameworks polymeric materials that industrial CO 2 , such moisture. it increases accuracy reservoir simulations controls injection systems storage or enhanced oil recovery. Through applying algorithms geology, production performance real‐time would like facilitate optimization processes while assuring maximum efficiency. integrates renewable‐based employed AI‐driven smart grid methods.
Язык: Английский
Процитировано
7
Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122458 - 122458
Опубликована: Сен. 12, 2024
Язык: Английский
Процитировано
6