Your browser doesn't support javascript.
loading
A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning.
Jathar, Laxmikant D; Nikam, Keval; Awasarmol, Umesh V; Gurav, Raviraj; Patil, Jitendra D; Shahapurkar, Kiran; Soudagar, Manzoore Elahi M; Khan, T M Yunus; Kalam, M A; Hnydiuk-Stefan, Anna; Gürel, Ali Etem; Hoang, Anh Tuan; Agbulut, Ümit.
Afiliación
  • Jathar LD; Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India.
  • Nikam K; Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Engineering, Management and Research, Akurdi, Pune, 411044, India.
  • Awasarmol UV; Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India.
  • Gurav R; Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India.
  • Patil JD; Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India.
  • Shahapurkar K; Department of Mechanical Engineering, School of Mechanical, Chemical and Materials Engineering, Adama Science and Technology University, Adama, 1888, Ethiopia.
  • Soudagar MEM; Faculty of Mechanical Engineering, Opole University of Technology, 45-758 Opole, Poland.
  • Khan TMY; Department of Mechanical Engineering, Graphic Era (Deemed to Be University), Dehradun, Uttarakhand, 248002, India.
  • Kalam MA; Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia.
  • Hnydiuk-Stefan A; School of Civil and Environmental Engineering, FEIT, University of Technology Sydney, Sydney, NSW, 2007, Australia.
  • Gürel AE; Faculty of Production Engineering and Logistics, Opole University of Technology, 45-758 Opole, Poland.
  • Hoang AT; Department of Electricity and Energy, Düzce Vocational School, Düzce University, 81010, Düzce, Turkiye.
  • Agbulut Ü; Faculty of Automotive Engineering, Dong A University, Danang, Viet Nam.
Heliyon ; 10(3): e25407, 2024 Feb 15.
Article en En | MEDLINE | ID: mdl-38371991
ABSTRACT
Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido