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- Leidėjas: Springer
- ISBN-10: 3030375250
- ISBN-13: 9783030375256
- Formatas: 15.6 x 23.4 x 1.9 cm, kieti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Internet of Things Use Cases for the Healthcare Industry + nemokamas atvežimas! | knygos.lt
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Aprašymas
This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.
EXTRA 15 % nuolaida su kodu: ENG15
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- Leidėjas: Springer
- ISBN-10: 3030375250
- ISBN-13: 9783030375256
- Formatas: 15.6 x 23.4 x 1.9 cm, kieti viršeliai
- Kalba: Anglų
This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.
Atsiliepimai