Description

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.

  • ​Covers renewable energy sector fundamentals;
  • Explains the application of big data in distributed energy domains;
  • Discusses AI and IoT prediction methods and models.


AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems

Product form

£149.99

Includes FREE delivery
Usually despatched within 3 days
Hardback by S. Vijayalakshmi , Savita .

1 in stock

Short Description:

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of... Read more

    Publisher: Springer International Publishing AG
    Publication Date: 06/04/2023
    ISBN13: 9783031150432, 978-3031150432
    ISBN10: 3031150430

    Number of Pages: 311

    Description

    AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.

    • ​Covers renewable energy sector fundamentals;
    • Explains the application of big data in distributed energy domains;
    • Discusses AI and IoT prediction methods and models.


    Customer Reviews

    Be the first to write a review
    0%
    (0)
    0%
    (0)
    0%
    (0)
    0%
    (0)
    0%
    (0)

    Recently viewed products

    © 2024 Book Curl,

      • American Express
      • Apple Pay
      • Diners Club
      • Discover
      • Google Pay
      • Maestro
      • Mastercard
      • PayPal
      • Shop Pay
      • Union Pay
      • Visa

      Login

      Forgot your password?

      Don't have an account yet?
      Create account