Evolution Of Machine Learning And Internet Of Things Applications In Biomedical Engineering
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Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering
This book provides a platform for presenting machine learning (ML)-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes ML techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world. Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses the Internet of Things (IoT) and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed at different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for Internet-based uses. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography and magnetic resonance imaging, which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks. This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval and brain image segmentation.
Internet of Things in Biomedical Engineering
Author: Valentina Emilia Balas
language: en
Publisher: Academic Press
Release Date: 2019-06-14
Internet of Things in Biomedical Engineering presents the most current research in Internet of Things (IoT) applications for clinical patient monitoring and treatment. The book takes a systems-level approach for both human-factors and the technical aspects of networking, databases and privacy. Sections delve into the latest advances and cutting-edge technologies, starting with an overview of the Internet of Things and biomedical engineering, as well as a focus on 'daily life.' Contributors from various experts then discuss 'computer assisted anthropology,' CLOUDFALL, and image guided surgery, as well as bio-informatics and data mining. This comprehensive coverage of the industry and technology is a perfect resource for students and researchers interested in the topic. - Presents recent advances in IoT for biomedical engineering, covering biometrics, bioinformatics, artificial intelligence, computer vision and various network applications - Discusses big data and data mining in healthcare and other IoT based biomedical data analysis - Includes discussions on a variety of IoT applications and medical information systems - Includes case studies and applications, as well as examples on how to automate data analysis with Perl R in IoT
AI and Data Analytics in Precision Agriculture for Sustainable Development
This book offers a comprehensive analysis of artificial intelligence (AI) and data analytics in precision agriculture. The integration of technology in agriculture is revolutionizing traditional farming practices, paving the way for sustainability. Precision farming, powered by AI, IoT, and big data, optimizes resource use by enabling real-time monitoring of soil health, weather conditions, and crop growth. Automated irrigation systems and drones reduce water wastage and enhance productivity. Biotechnology advances, such as genetically modified crops and CRISPR gene editing, improve yield, pest resistance, and climate adaptability. Vertical farming and hydroponics offer space-efficient solutions, minimizing land degradation and water consumption. Robotics and autonomous machinery streamline labor-intensive tasks, reducing reliance on chemical inputs. Blockchain ensures transparency in the food supply chain, promoting fair trade and reducing food fraud. Renewable energy sources, like solar-powered farms, further lower agriculture’s carbon footprint. By adopting these innovations, farmers can produce more with fewer resources, ensuring food security while preserving the environment. Embracing technology-driven agriculture is crucial for meeting global food demands sustainably, combating climate change, and fostering economic resilience in farming communities. The future of agriculture lies in intelligent, data-driven, and eco-friendly solutions that balance productivity with environmental stewardship.