Articles liés à Intelligent Automation and Analytics for Business Resilience

Intelligent Automation and Analytics for Business Resilience - Couverture rigide

 
9781394271856: Intelligent Automation and Analytics for Business Resilience

Synopsis

Unlock the full potential of AI-driven automation with this comprehensive guide to building agile, resilient, and sustainable organizations through real-world applications.

In an era defined by rapid technological advancements and unprecedented global challenges, businesses must embrace innovation to remain resilient, agile, and competitive. This book explores the transformative role of AI-driven automation in enabling organizations to improve intelligence. It covers a wide spectrum of topics including the integration of AI in automation, cybersecurity, sustainability, performance measurement, and ethical applications in healthcare. It provides readers with insights into how automation technologies are reshaping industries, improving scalability and flexibility, and driving measurable returns on investment. The volume emphasizes practical applications, such as using AI analytics to assess green equity markets, employing automation in education, and ensuring responsible adoption of intelligent systems. By combining theoretical frameworks with real-world case studies, this book serves as a practical reference for academics, industry leaders, and professionals seeking to leverage intelligent automation to achieve resilience, sustainability, and competitive advantage.

Readers will find the volume:

  • Provides a multi-disciplinary perspective on intelligent automation, covering AI, machine learning, cybersecurity, and ROI evaluation;
  • Bridges academia and industry with applied case studies, frameworks, and research insights;
  • Addresses timely topics such as sustainability, ethical AI, and automation in healthcare and education;
  • Highlights future trends and research directions for business resilience in a rapidly changing technological landscape.

Audience

Researchers, academics, IT professionals, and policymakers in the fields of computer science, engineering, management, and data analytics.

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À propos de l'auteur

Daniel Arockiam, PhD, School of Engineering and IT, Manipal Academy of Higher Education, Dubai Campus, Dubai, UAE, with more than 14 years of academic and research experience. He has published more than 100 papers in international journals, authored six books, and filed 30 patents. His work spans AI, Internet of Things, and cybersecurity, with certifications in Python, Quantum Computing, and UiPath.

Balamurugan Balusamy, PhD is a Professor and the Dean of the School of Engineering and IT at the Manipal Academy of Higher Education in Dubai Campus, UAE. Over his career, he has given more than 300 talks at international conferences and published more than 200 books and 300 journal articles. His research focuses on XAI, data science, blockchain technology, and the Internet of Things.

Prasenjit Chatterjee, PhD is a Professor of Mechanical Engineering and the Dean of Research and Consultancy at the MCKV Institute of Engineering, West Bengal, India. He has published more than 155 research papers in international journals and peer-reviewed conferences, authored and edited more than 55 books. His research interests include intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modelling.

Abhijit Saha, PhD is an Assistant Professor in the Department of Computing Technologies at the SRM Institute of Science and Technology, Chennai, Tamil Nadu, India, with more than ten years of teaching and research experience. He has published more than 50 research articles in various journals of international repute. His areas of research interest are fuzzy set theory, soft set theory, aggregation operators, optimization, and decision-making.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.