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Herausgeber: 
  • Kumar Abhishek
  • Hemant Kumar Saini
  • Vicente García Díaz
  • Ashutosh Kumar Dubey
  • Bio-Inspired Data-driven Distributed Energy in Robotics and Enabling Technologies 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (Juli 2026)  
    Genre:  Naturwissensch., Medizin, Technik 
     
    adaptive sliding mode control / Artificial Intelligence / Artificial Intelligence (AI) / Communications engineering / telecommunications / COMPUTERS / Internet of Things (IoT) / Digital and Information technology# general topics / Electrical Engineering / Information technology# general issues
    ISBN:  9781032869414 
    EAN-Code: 
    9781032869414 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Seiten:  310 
    Illustration:  schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:

    This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems.

    This book:

    • Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities.
    • Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems.
    • Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things.
    • Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum.
    • Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem.

    The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering.

      



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