AI for Product Development

1. Auflage 2025
ISBN: 978-1-032-85775-6
Verlag: Taylor & Francis Ltd

Buch, Englisch, 318 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

AI for Product Development explores the transformative role of artificial intelligence in reshaping modern industries. This book offers a comprehensive guide, spanning the evolution of AI in product innovation to practical applications such as clustering techniques, human-autonomous vehicle interactions and personalized healthcare solutions. With contributions from leading researchers, it covers explainable AI, real-world case studies and ethical considerations in intelligent systems. The chapters delve into cutting-edge topics like YOLO model variants, AI-driven emotion detection and strategies for overcoming AI implementation challenges. Designed for researchers, professionals and students, it bridges theory and practice, emphasizing AI's profound impact on product development and beyond.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Naithani, Kanchan

Kumari, Shabnam

Tiwari, Shrikant

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Geisteswissenschaften Design Produktdesign, Industriedesign

Inhaltsverzeichnis

Preface. The Evolution of AI in Product Development. From Data to Decisions:  K-Means Clustering for Product Development and Marketing. Algorithmic Analysis and Development for Enhanced Human-Autonomous Vehicle Coexistence. Integrating AI-Driven Drug Discovery with Personalized Mental Health Interventions: Exploring Synergies for Enhanced Healthcare Solutions. Establishing Communication in Agent Based E-Commerce Platforms. AI-Driven Product Development: Real-World Case Studies. Training and Skills Development for AI in Product Development. Explainable AI. Applications of XAI in Product Development. Breaking Barriers: Strategies for Overcoming Hurdles in AI Implementation. Triple Threat: YOLO Model Variants for Reinventing X-Ray Security. Developing AI-Powered Products: Balancing Law and Ethics in the Intelligent Systems Era. AI-Powered Automation Tools for Software Product Checking and Cost Management. AI-Powered Emotion Detection: Understanding Facial Expressions through Deep-Learning. AI Adoption Across Industries. Index. Biography of Editors.

Über Autor(innen)

Kanchan Naithani received her Ph.D. in the Department of Computer Science and Engineering at H.N.B. Garhwal University (A Central University), Srinagar Garhwal, Uttarakhand, India (2024). She completed M.Tech in Computer Science and Engineering from G.B. Pant Engineering Institute of Technology, Ghurdauri, Pauri, Uttarakhand, India (2018) and B. Tech in Computer Science and Engineering from Graphic Era Hill University, Dehradun India (2016). Currently, she is working as an Assistant Professor in the School of Computing Science and Engineering (SCSE), Galgotias University, Greater Noida, Gautam Budha Nagar, Uttar Pradesh-203201 (India). She has authored and co-authored more than twenty papers (according to Scopus Database) in refereed high-impact journals, conferences, and books, and some of her articles were given best paper awards. She has filed two patents (Nationally and Internationally) in the area of Deep Learning and Internet of Things. She has edited two books for CRC Press and IGI Global. Her research interests focus on Artificial Intelligence, Machine Learning, Sentiment Analysis and Natural Language Processing. She is a lifetime member of the IAENG Society of Artificial Intelligence and the IAENG Society of Computer Science.

 

Shrikant Tiwari (Senior Member, IEEE) received his Ph.D. in the Department of Computer Science and Engineering at the Indian Institute of Technology (Banaras Hindu University), Varanasi, India, in 2012, and his M.Tech. in Computer Science and Technology from the University of Mysore, India, in 2009. Currently, he serves as an Associate Professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.

Dr. Tiwari has published over seventy-five plus papers in refereed high-impact journals, conferences, and books, with several of his articles receiving best paper awards. He has also filed more than 10 patents, both nationally and internationally, in the areas of deep learning, the Internet of Things, cyber-physical systems, and computer vision. Additionally, he has edited more than five books for prestigious publishers such as IET, Elsevier, Springer, and CRC Press. His research interests include machine learning, deep learning, computer vision, medical image analysis,

pattern recognition, and biometrics.

Dr. Tiwari is a Fellow of the Institution of Electronics and Telecommunication Engineers (IETE), a Senior Member of IEEE and a member of the Association for Computing Machinery (ACM), the Institution of Engineering and Technology (IET), the Computer Society of India (CSI), the Indian Society for Technical Education (ISTE), the International Association of Engineers (IAENG), and the Science and Engineering Institute (SCIEI). He also serves as a guest editorial board member and reviewer for numerous international journals of repute.

 

Shabnam Kumari is working as a Ph.D. scholar in the Department of Computer Science and Engineering, SRM University, Chennai, Tamil Nadu, India. She has more than 3 years of experience including teaching, research and other areas. She has completed her MCA from YMCA University of Science and Technology, Faridabad. She has filed more than five national and international patents in the area of IoTs, Machine Learning, Deep Learning and Wireless Network. She has published twenty plus research articles in International Conferences and Journals. Her areas of interest include Machine Learning, Deep Learning, and related fields. She is a lifetime member of ACM-Women and SCRS.