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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: Edge AI for Industry 5.0 and Healthcare 5.0 Applications
  name:
    name part: Raj, Pethuru
    affiliation: IBM Pvt.Ltd., India.
    role:
      role term: editor.
  name:
    name part: Sundaravadivazhagan, B.
    role:
      role term: editor.
  name:
    name part: Raja, A. Saleem
    role:
      role term: editor.
  name:
    name part: Alani, Mohammed M.
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2025
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (344 pages).
  abstract: Edge AI is the seamless and spontaneous combination of Edge or Fog computing and AI. It enables acquiring real-time insights, which, in turn, leads to the realization of real-time, people-centric, event-driven, business-critical, process-aware, and knowledge-filled software services and applications. Edge AI for Industry 5.0 and Healthcare 5.0 Applications looks at the unique contributions of Edge AI for developing solutions for Industry 5.0 and Healthcare 5.0. It explains how Industry 5.0 fine tunes the human-machine connection and leverages tiny, high-performance AI-centric processors in IoT edge devices for real-time decision-making and application processing. Focusing on Explainable AI (XAI), the book discusses: · The role of XAI in Healthcare 5.0 · Best practices, challenges, and opportunities of applying XAI in healthcare setting · How to enhance transparency and trust of XAI in Healthcare 5.0 · XAI and its methods in predicting healthcare outcomes Other highlights of the book include: · 5G communication networks requirements · The fusion of IoT, AI, Edge, Cloud, and blockchain · Trustworthiness of blockchain technology in healthcare 5.0 and Industry 5.0 · The future of trust and the potential of blockchain technology By explaining how Edge AI can transform healthcare and industry, this book empowers researchers and professionals to envisage and implement sophisticated and smart digital solutions.
  table of contents: 1 Digital Twins for Smart Grids Pooja Jain, Tapan Kumar, Yaman Birla, and Anshul Mishra2 Delineating the Healthcare 5.0 Nancy Deborah R, Gobinath A, Soundarya M, Manjula Devi C3 Virus Dispersion in Environment: Fuzzy Approach for Infectious Diseases Dilip Kumar Jaiswal and Sudhakar Kumar Chaubey4 Revolutionizing COVID-19 Diagnosis: A Hybrid Quantum Neural Network-based Framework for Accurate Detection of Lung Abnormalities from CT Scans using a Custom Computer Vision Model and AI Edge Device Senthilkumar Vijayakumar5 The Role of Explainable AI for Healthcare 5.0: Best Practices, Challenges, and Opportunities Srija Chattopadhyay, Subhadeep Barman, and Lakshmi D6 Explainable AI for Healthcare 5.0: Enhancing Transparency and Trust Deepa S, Vinay M, Jayaprada J., and Sundaravadivazhagan7 A Complete Analysis of Explainable AI and its Methods for Healthcare Prediction A.Vinora, E.Lloyds, and M.Soundarya8 Artificial Intelligence (AI) Algorithms and Approaches for Edge AI Samar Mouti and Samer Rihawi9 Integrating Fuzzy Clustering into CNN for Improved Brain Tumour Detection B Kannaki Devi, D.Ramyachitra, and T Akalya10 Leveraging Edge AI for Real-Time Detection and Prevention of Online Harassment and Cyberbullying: Enhancing Women's Safety and Mental Health Kathiravan Pannerselvam, Saranya Rajiakodi, and Shanmugavadivu Pichai11 Leveraging Artificial Intelligence and IoT for Health Care 5.0: Use Cases, Applications, and Challenges Gnanasankaran Natarajan, Elakkiya Elango, Sandhya Soman, and Shirley Chellathurai Pon Anna Bai12 Unleashing Patient Insights: Leveraging Edge AI in Sentiment Analysis for Enhanced Healthcare Experiences Kathiravan Pannerselvam, Saranya Rajiakodi, and Shanmugavadivu Pichai13 Edge AI in LoRa-Based Health Monitoring Manjula Devi C, Sivakarthi G, Srinivasan A, Gobinath A, and Rajeswari P14 IoT Based Smart Health Monitoring with Convulational Neural Network (CNN) Using Edge Computing Rajeswari P, Gobinath A, Suresh Kumar N, and Anandan M15 Enhancing Hea…
  target audience: adult
  note: edited by Pethuru Raj, B. Sundaravadivazhagan, A. Saleem Raja and Mohammed M. Alani.
  note: “An Auerbach Book.”
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Intelligence artificielle
    topic: Applications industrielles
  subject:
    topic: COMPUTERS / Artificial Intelligence
  classification: TA347.A78
  classification: 658/.0563
  identifier: 9781003442066
  identifier: 1003442064
  identifier: 9781040312094
  identifier: 1040312098
  identifier: 9781032577944
  identifier: 9781040312124
  identifier: 1040312128
  identifier: 9781032580135
  identifier: 9781003442066 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: TYFRS
    record creation date: 250218
    record change date: 20250507145909.4
    record identifier: in00005644636
    language of cataloging:
      language term: eng