In today s industrial landscape, enhancing operational efficiency and implementing predictive maintenance strategies have become critical goals for organizations seeking sustainable growth and competitiveness. Digital innovation has the potential to optimize workflows, reduce downtime, and predict equipment failures. By utilizing real-time data and intelligent systems, companies can move from reactive to proactive maintenance models, streamline operations, and cut costs. Further research into this shift may boost productivity while driving long-term value creation across industries. Enhancing Operational Efficiency and Predictive Maintenance Through Digital Innovation explores the synergistic impact of cutting-edge technologies on our lives. It delves into the interconnected world of devices, the immense data they generate, and the immense potential of advanced analytics and machine learning algorithms to derive valuable insights. This book covers topics such as smart technology, disease detection, and environmental monitoring, and is a useful resource for business owners, engineers, educators, academicians, researchers, and scientists.
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Dr. Minakshi is an accomplished academician with 18+ years of experience in computer science and engineering domains. Currently an Assistant Professor at King Khalid University, she has taught at esteemed institutions like Uttaranchal University and Tula's Institute. A prolific researcher with 80 Scopus publications, 18 patents, and 3 software copyrights, she has received accolades like Outstanding Section Volunteer Award (IEEE UP Section), Research Excellence Award, and HOD of the Year Award. Adept at curriculum development, research guidance, project management, and team leadership, Dr. Minakshi brings a holistic approach to education, fostering student success through quality instruction and innovative pedagogical methods.
Tarun Kumar received his Ph.D. degree from the National Institute of Technology Patna, Bihar, India. Dr. Kumar has more than 20 years of experience in teaching and is currently working as an Associate Professor in the School of Computer Science at the University of Petroleum and Energy Studies (UPES), Dehradun, India. His research interests include cloud computing, IoT, and DNA computing. Dr. Kumar has published several edited books, book chapters, patents and papers in conference proceedings and refereed journals. He has also participated in many international conferences as an organizer and session chair. Dr. Kumar is a senior member of IEEE, ACM, IEEE Computer Society, and a Member IEEE Computational Intelligence Society. Dr. Kumar brings a holistic approach to education, fostering student success through quality instruction and innovative pedagogical methods.
Dr. Madhulika Bhatia is working as Software Development Officer with Digital Healthcare Wales, UK. She holds a Diploma in Computer Science and Engineering, B.E in Computer Science and Engineering, MBA in Information Technology, M. Tech in Computer Science and PhD from Amity University, Noida. She has a total of 18 years of teaching experience. She published almost 58 Research Papers in National, International conferences and Journals. She is also the author of two books. She Filed two Provisional Patent. She attended and organized many workshops, Guest Lectures, seminars. She is also a member of many technical societies like IET, ACM, UACEE, IEEE She reviewed for Elsevier-Heliyon, IGI, IEEE ACCESS, and as well as did Editorial for Springer Nature, Switzerland. She has guided 12 M.Tech. Thesis and around 50 B. Tech. Major and Minor Projects and guiding PhD scholars, Research collaborations. She delivered Expert talks and hands on sessions in AICTE Sponsored workshops in collaboration with IIT Roorkie. She was also invited for Expert talk by NIFT, Patna.She has international exposure on various Projects and Research collaborations with University of Cape Town, South Africa and Lancaster University, UK. She was also invited as Visiting researcher by Cardiff Metropolitan University, UK. She is pursuing her Post doctorate Federal University of Ceira, Brazil.
Dr. Ranjna Jain is an Associate Professor at Manav Rachna University, Faridabad, with over 14 years of experience in the field of Computer Science and Technology. She holds a Ph.D., M.Tech from J.C. Bose University of Science & Technology, YMCA and B.E. from MDU. Her research interests lie in Information Retrieval, Semantic Web, Ontologies, Machine Learning, and Deep Learning. She has published research in various reputable journals indexed in Scopus, WoS, and other databases, focusing on ontology alignment, semantic search engines, and data mining. She has participated in numerous Faculty Development Programs (FDPs), workshops, and conferences, covering topics from Wireless Networks and the Internet of Things to Data Science and Artificial Intelligence. She has patent for a “Smart Device for Mental Health Assessment,” granted on November 23, 2023.
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Hardcover. Condición: new. Hardcover. In today s industrial landscape, enhancing operational efficiency and implementing predictive maintenance strategies have become critical goals for organizations seeking sustainable growth and competitiveness. Digital innovation has the potential to optimize workflows, reduce downtime, and predict equipment failures. By utilizing real-time data and intelligent systems, companies can move from reactive to proactive maintenance models, streamline operations, and cut costs. Further research into this shift may boost productivity while driving long-term value creation across industries. Enhancing Operational Efficiency and Predictive Maintenance Through Digital Innovation explores the synergistic impact of cutting-edge technologies on our lives. It delves into the interconnected world of devices, the immense data they generate, and the immense potential of advanced analytics and machine learning algorithms to derive valuable insights. This book covers topics such as smart technology, disease detection, and environmental monitoring, and is a useful resource for business owners, engineers, educators, academicians, researchers, and scientists. "This book aims to explore how integrating Internet of Things (IoT) sensors, artificial intelligence, and machine learning can revolutionize operational efficiency and predictive maintenance across manufacturing sectors"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798337324746
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Buch. Condición: Neu. Enhancing Operational Efficiency and Predictive Maintenance Through Digital Innovation | Minakshi (u. a.) | Buch | Englisch | 2025 | IGI Global | EAN 9798337324746 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 134040620
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