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Autor(en): 
  • Adel Mellit
  • Embedded Artificial Intelligence and the Internet of Things for Photovoltaic Systems: From Monitoring to Maintenance and Security 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (September 2026)  
    Genre:  Naturwissensch., Medizin, Technik 
     
    AI / Alternative & renewable energy sources & technology / Alternative and renewable energy sources and technology / Artificial / Artificial Intelligence / Artificial Intelligence (AI) / COMPUTERS / Artificial Intelligence / General / Embedded
    ISBN:  9780443448355 
    EAN-Code: 
    9780443448355 
    Verlag:  Elsevier 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 152 mm / D  
    Gewicht:  450 gr 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    Embedded Artificial Intelligence and the Internet of Things for Photovoltaic Systems: From Monitoring to Maintenance and Security is a new handbook that explores the concepts of embedded AI (EAI), Internet of Things (IoT), and related techniques, and their role in addressing key problems in PV whilst enabling the transition from laboratory-scale developments to real-world applications. The book offers thorough, detailed coverage of methods and modern, end-to-end solutions to applying EAI techniques in PV systems, including in supervision, fault detection and diagnosis, smart monitoring systems, and predictive maintenance and security, guiding readers from AI model development to deployment. The first four chapters introduce and define key concepts, including photovoltaics, embedded artificial intelligence, edge devices and platforms, and Internet of Things, before an in-depth chapter describes databases and datasets, an essential component in the development of AI and EAI. The final five chapters focus on applications, by outlining key problems and giving case studies that address real-world issues in PV plants. This is a valuable resource to all those with an interest in photovoltaics and AI, particularly those who are looking to effectively apply embedded AI techniques in PV systems, including researchers, advanced students, faculty, engineers, project managers, technicians, R&D, and other industry professionals.

      



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