Tag: Enabled

Edge Intelligence Deep learning-enabled edge computing


Free Download Edge Intelligence: Deep learning-enabled edge computing by Shajulin Benedict
English | June 20, 2024 | ISBN: 0750355913 | 276 pages | MOBI | 6.49 Mb
The book explores edge intelligent techniques and solutions that can be incorporated into IoT-enabled applications. It paves way for researchers and innovators to rethink the application of edge intelligent techniques for their problem domains.

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Artificial Intelligence-Enabled Businesses


Free Download Artificial Intelligence-Enabled Businesses: How to Develop Strategies for Innovation
English | 2025 | ISBN: 1394233973 | 525 Pages | PDF | 104 MB
Artificial Intelligence-Enabled Businesses demonstrates how AI is a catalyst for change in business functional areas. Though still in the experimental phase, AI is instrumental in redefining the workforce, predicting consumer behavior, solving real-life marketing dynamics and modifications, recommending products and content, foreseeing demand, analyzing costs, strategizing, managing big data, enabling collaboration of cross-entities, and sparking new ethical, social and regulatory implications for business. Thus, AI can effectively guide the future of financial services, trading, mobile banking, last-mile delivery, logistics, and supply chain with a solution-oriented focus on discrete business problems. Furthermore, it is expected to educate leaders to act in an ever more accurate, complex, and sophisticated business environment with the combination of human and machine intelligence.

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Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems


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English | 2024 | ISBN: 1032752378 | 342 Pages | EPUB | 10 MB
The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled IFD are also explored, such as data augmentation, multi-sensor fusion, unsupervised deep transfer learning, neural architecture search, self-supervised learning, and reinforcement learning. Aiming to revolutionize the nature of IFD, Deep Neural Networks-Enabled Intelligent Fault Diangosis of Mechanical Systems contributes to improved efficiency, safety, and reliability of mechanical systems in various industrial domains.

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IoT-Enabled Healthcare Systems Applications, Benefits, and Challenges


Free Download IoT-Enabled Healthcare Systems: Applications, Benefits, and Challenges
English | 2025 | ISBN: 1774916843 | 257 Pages | PDF (True) | 12 MB
IoT technology for healthcare is a modern innovation that provides reliable and secure use of available resources for serving the healthcare industry. It not only helps improve contact between the community and public healthcare providers but also significantly lowers healthcare costs and improves treatment outcomes. This book highlights the latest in IoT technology for revolutionizing current healthcare systems, focusing on how IoT can make healthcare smarter and more beneficial for people. It explores such technologies as medical blockchain, biosensing for bioanalyses, pesticide monitoring in humans, and more. It also discusses how the cloud platform can be used for health monitoring systems and the applications of IoT for cancer.

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Internet of Things enabled Machine Learning for Biomedical Application


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English | 2025 | ISBN: 1032550821 | 427 Pages | PDF (True) | 14 MB
The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.

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Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing


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English | 2024 | ISBN: 1394303572 | 624 Pages | EPUB | 43 MB
In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin―an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities.

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Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals


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English | 2024 | ISBN: 1394287399 | 725 Pages | EPUB | 24 MB
Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals provides fundamental information on blockchain and digital twin technology as effective solutions in smart hospitals. Digital twin technology enables the creation of real-time virtual replicas of hospital assets and patients, enhancing predictive maintenance, operational efficiency, and patient care. Blockchain technology provides a secure and transparent platform for managing and sharing sensitive data, such as medical records and pharmaceutical supply chains. By combining these technologies, smart hospitals can ensure data security, interoperability, and streamlined operations while providing patient-centered care. The book also explores the impact of collected medical data from real-time systems in smart hospitals, and by making it accessible to all doctors via a smartphone or mobile device for fast decisions.

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Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications


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English | 2024 | ISBN: 9819753643 | 216 Pages | EPUB (True) | 29 MB
This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery.

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