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mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Applications of Big Data and Artificial Intelligence in Smart Energy Systems
    sub title: Volume 1 Smart Energy System: Design and Its State-Of-the Art Technologies
  title info:
    title: Smart energy system
  name:
    name part: Nagpal, Neelu.
  name:
    name part: Alhelou, Hassan Haes
    name part: 1988-
  name:
    name part: Siano, Pierluigi.
  name:
    name part: Sanjeevikumar, Padmanaban
    name part: 1978-
  name:
    name part: Lakshmi, D.
  type of resource: text
  origin info:
    place:
      place term: xx
    place:
      place term: Milton
    publisher: River Publishers
    date issued: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (318 pages).
  abstract: This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management.
  table of contents: Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- List of Figures -- List of Tables -- List of Contributors -- List of Abbreviations -- Chapter 1: Introduction to Smart Energy Systems in Recent Trends -- 1.1: Introduction -- 1.2: Global Emission -- 1.3: Evolution for Clean Energy: A Transition -- 1.4: Smart Energy System -- 1.5: Internet of Things (IoT) for Smart and Sustainable Future -- 1.5.1: IoT in smart city -- 1.5.2: IoT in agriculture -- 1.5.3: IoT in healthcare -- 1.5.4: IoT in smart grid and power management system
  table of contents: 1.6: Recent Developments in Smart Energy Systems -- 1.7: Conclusion and Future Measures to be Considered -- Chapter 2: An Overview of Artificial Intelligence, Big Data, and Internet of Things for Future Energy Systems -- 2.1: Introduction -- 2.2: Related Work -- 2.3: Sectors Involved in Energy Need Big Data, AI, and IoT -- 2.3.1: The energy sector requires big data -- 2.3.2: Big data techniques -- 2.3.3: Data communication techniques -- 2.3.4: Techniques for analyzing data -- 2.3.5: Data analytics techniques in smart grid -- 2.3.6: Mining data from a power system
  table of contents: 2.3.7: Modern grid systems and power consumption advanced analytics -- 2.4: Supporting Power Usage with IoT and Artificial Intelligence -- 2.4.1: The need for artificial intelligence in the renewable energy industry -- 2.4.2: Artificial intelligence (AI) research techniques classification -- 2.4.2.1: The use of computer-assisted learning systems -- 2.4.2.2: Fuzzy logic -- 2.4.2.3: Computer-aided translation -- 2.4.2.4: Robotics -- 2.4.2.5: Need of robotics in the energy sector -- 2.4.3: The energy sector requires IoT -- 2.5: Role of IoT in Energy Sectors
  table of contents: 2.5.1: IoT Impacts for the energy sector -- 2.5.2: Internet of Things applications in energy policy, economics, and production -- 2.5.2.1: Sectors of regulation and the market -- 2.5.2.2: Energy supply sector -- 2.5.2.3: Power transmission grids or energy grids -- 2.5.2.4: Energy demand sector -- 2.6: Future Energy Systems' Unsolved Problems -- 2.6.1: IoT energy sector challenges -- 2.6.2: Open challenges in AI energy sector -- 2.6.3: Open data analytics challenges in energy -- 2.7: Conclusion -- Chapter 3: LoRa: A New Technology for Smart Grid Applications -- 3.1: Introduction
  table of contents: 3.2: Related Work and Background -- 3.3: LoRa Challenges -- 3.4: LoRa Applications -- 3.5: Characteristics and Future Direction of LoRa Technology -- 3.5.1: Communication Range: -- 3.5.2: Placement of Multiple Gateways: -- 3.5.3: Link Coordination: -- 3.5.4: Security -- 3.5.5: Big data and AI -- 3.6: Case Study -- 3.7: Conclusion -- Chapter 4: Clustering Hybrid Application for Load Forecasting in Smart Grids -- 4.1: Introduction -- 4.1.1: Dataset pre-processing -- 4.1.2: Clustering techniques -- 4.1.2.1: K-means -- 4.1.2.2: Partitioning around medoids (PAM)
  note: Description based upon print version of record.
  note: 4.1.2.3: Gaussian mixture model (GMM)
  note: Dr. Neelu Nagpal (Senior Member, IEEE), an Associate Professor at GGSIP University, has been working for the last 16 years in the EEE Department of Maharaja Agrasen Institute of Technology, Delhi, India. Her Ph.D. in Electrical Engineering was accomplished at Delhi Technological University, Delhi. She was the recipient of a research award from Delhi Technological University during her Ph.D. course. She completed her Masters with distinction from Delhi University in Control and Instrumentation specialization. Besides having 22 years of experience in teaching, she has 5 years of industrial experience and a lot more educational contributions to her name. She has 20 research publications in top-tier journals and conferences and has a grant of one Australian patent. Her area of research is investigations into the dynamics, control, and estimation in the field of nonlinear stochastic systems (power systems and robotics), smart grid technologies, and artificial intelligence. She has been involved in many reputed conferences in various capacities such as advisor, reviewer, session-chair, track-chair, organizing committee member, and publication chair (IEEE conference-ICIERA-2021). She is an IEEE Smart Cities Ambassador, 2022. Professor Hassan Haes Alhelou (Senior Member, IEEE) is with Monash University, Australia. He is also a Professor at Tishreen University in Syria, and a consultant with Sultan Qaboos University in Oman. Previously, He was with UCD-Ireland and IUT-Iran. He was included in the 2018 and 2019 Publons list of the top 1% best reviewers in the world. He is the recipient of the Outstanding Reviewer Award from many journals, e.g., ECM, ISA Transactions, and Applied Energy; and the recipient of the best young researcher in the Arab Student Forum Creative among 61 researchers from 16 countries at Alexandria University, Egypt, 2011. He also received the Excellent Paper Award 2021 from IEEE CSEE Journal of Power and Energy Systems. He has published more than 200 res…
  subject:
    topic: Smart power grids
  subject:
    topic: Big data
    topic: Industrial applications
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Réseaux électriques intelligents
  subject:
    topic: Données volumineuses
    topic: Applications industrielles
  subject:
    topic: Intelligence artificielle
    topic: Applications industrielles
  subject:
    topic: SCIENCE / Energy
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Smart power grids
  classification: TK3105
  classification: 621.31028557
  related item:
    title info:
      title: Applications of Big Data and Artificial Intelligence in Smart Energy Systems
    name:
      name part: Nagpal, Neelu
    origin info:
      publisher: Milton : River Publishers,c2023
  related item:
    title info:
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  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: EBLCP
    record creation date: 230729
    record change date: 20240106193008.6
    record identifier: in00004763796
    language of cataloging:
      language term: eng