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Machine Learning, Deep Learning, Big Data, and Internet of Things  for Healthcare (Hardcover): Govind Singh Patel, Seema Nayak,... Machine Learning, Deep Learning, Big Data, and Internet of Things for Healthcare (Hardcover)
Govind Singh Patel, Seema Nayak, Sunil Kumar Chaudhary
R3,849 R3,650 Discovery Miles 36 500 Save R199 (5%) Ships in 12 - 17 working days

This book reviews that narrate the development of current technologies under the theme of the emerging concept of healthcare, specifically in terms of what makes healthcare more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is machine learning, deep learning, big data, and Internet of Things (IoT)-the scientific field that gives machines the ability to learn without being strictly programmed. It has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data-intensive processes in healthcare operational environments. This book offers comprehensive coverage of the most essential topics, including: Introduction to e-monitoring for healthcare Case studies based on big data and healthcare Intelligent learning analytics in healthcare sectors using machine learning and IoT Identifying diseases and diagnosis using machine learning and IoT Deep learning architecture and framework for healthcare using IoT Knowledge discovery from big data of healthcare-related processing Big data and IoT in healthcare Role of IoT in sustainable healthcare A heterogeneous IoT-based application for remote monitoring of physiological and environmental parameters

Smart Agriculture - Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things (Hardcover): Govind Singh... Smart Agriculture - Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things (Hardcover)
Govind Singh Patel, Amrita Rai, Nripendra Narayan Das, R.P. Singh
R3,223 Discovery Miles 32 230 Ships in 12 - 17 working days

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

Smart Agriculture - Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things: Govind Singh Patel, Amrita... Smart Agriculture - Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things
Govind Singh Patel, Amrita Rai, Nripendra Narayan Das, R.P. Singh
R1,444 Discovery Miles 14 440 Ships in 9 - 15 working days

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

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