Construction and Building Materials, Год журнала: 2025, Номер 470, С. 140656 - 140656
Опубликована: Март 4, 2025
Язык: Английский
Energies, Год журнала: 2025, Номер 18(5), С. 1192 - 1192
Опубликована: Фев. 28, 2025
The transition from fossil fuels to renewable energy (RE) sources is an essential step in mitigating climate change and ensuring environmental sustainability. However, large-scale deployment of renewables accompanied by new challenges, including the growing demand for rare-earth elements, need recycling end-of-life equipment, rising footprint digital tools—particularly artificial intelligence (AI) models. This systematic review, following Preferred Reporting Items Systematic Reviews Meta-Analyses (PRISMA) guidelines, explores how lightweight, distilled AI models can alleviate computational burdens while supporting critical applications systems. We examined empirical conceptual studies published between 2010 2024 that address energy, circular economy paradigm, model distillation low-energy techniques. Our findings indicate adopting significantly reduce consumption data processing, enhance grid optimization, support sustainable resource management across lifecycle infrastructures. review concludes highlighting opportunities challenges policymakers, researchers, industry stakeholders aiming integrate principles into RE strategies, emphasizing urgent collaborative solutions incentivized policies encourage low-footprint innovation.
Язык: Английский
Процитировано
1
Thin-Walled Structures, Год журнала: 2025, Номер unknown, С. 113036 - 113036
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1
Structures, Год журнала: 2025, Номер 73, С. 108315 - 108315
Опубликована: Фев. 12, 2025
Язык: Английский
Процитировано
0
Construction and Building Materials, Год журнала: 2025, Номер 470, С. 140656 - 140656
Опубликована: Март 4, 2025
Язык: Английский
Процитировано
0