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 Название: AIoT and Big Data Analytics for Smart Healthcare Applications
Автор: Shreyas Suresh Rao, Steven Lawrence Fernandes, Chandra Singh
Издательство: Bentham Books
Серия: IoT and Big Data Analytics
Год: 2024
Страниц: 318
Язык: английский
Формат: pdf (true), epub
Размер: 10.5 MB
AIoT (Artificial Intelligence of Things) and Big Data Analytics are catalyzing a healthcare revolution. This book is an accessible volume that summarizes the information available. In this book, researchers explore how AIoT and Big Data can seamlessly integrate into healthcare, enhancing medical services and devices while adhering to established protocols. It presents novel solutions and computational techniques powered by AIoT, Machine Learning, and Deep Learning, providing a new frontier in healthcare problem-solving.
AIoT stands for Artificial Intelligence of Things, which refers to the integration of Artificial Intelligence (AI) technologies with Internet of Things (IoT) devices. The combination of AI and IoT is intended to create smarter and more efficient devices, systems, and applications. By using AI to analyse and interpret the large amounts of data gathered from IoT devices, AIoT applications can provide insights, predictions, and automations that can optimize performance, reduce costs, and improve user experiences. Some of the noted examples of AIoT applications include smart homes, connected vehicles, intelligent manufacturing systems, and smart cities.
On the other hand, Big Data analytics refers to the process of examining and analyzing large and complex data sets to uncover patterns, correlations, and insights that can be used to make better decisions and improve business outcomes. The term “Big Data” refers to the massive amounts of data generated by various sources such as social media, sensors, mobile devices, and other digital platforms. The primary goal of Big Data analytics is to extract useful information from large volumes of data that would be impossible or too time-consuming for humans to analyze manually. By using advanced analytical techniques such as data mining, Machine Learning, and natural language processing (NLP), Big Data analytics can uncover hidden patterns, identify trends, and extract valuable insights from massive data sets. Big Data analytics has many applications across a wide range of industries, including healthcare, finance, marketing, retail, and more. It can be used to improve customer engagement, optimize business operations, reduce costs, and develop new products and services.
AIoT and Big Data analytics have a lot of potential for transforming healthcare by enabling the development of smarter and more efficient healthcare systems. AIoT devices can collect patient data in real-time from wearable devices, sensors, and other connected devices. Big Data analytics can then be used to analyze this data to provide personalized treatment recommendations and to detect early warning signs of health problems. By analyzing large amounts of patient data, Big Data analytics can be used to predict potential health problems before they occur. This can enable healthcare providers to take proactive measures to prevent or treat these problems before they become more severe.
Key Features:
Real-Life Illustrations: Real-world examples showcase AIoT and Big Data in action, highlighting their impact in healthcare.
Comprehensive Exploration: The book offers a thorough examination of AIoT, Big Data, and their harmonious synergy within the healthcare landscape.
Visual Aids: Complex concepts become approachable through diagrams, flowcharts, and infographics, making technical processes and system designs more digestible.
Ethical Insights: Delving into the ethical dimensions of AIoT and Big Data, it addresses concerns like data bias, patient consent, and transparency in healthcare.
Forward-Looking Discourse: The book engages with emerging trends, potential innovations, and the future direction of AIoT and Big Data, making it a compass for healthcare transformation.
Researchers, whether from academia, industry, or research and development organizations, interested in AIoT, Big Data, artificial intelligence, and healthcare optimization, will find this book informative. It also serves as an update for tech enthusiasts who want to explore the future of healthcare powered by AI and data.
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