Intelligent IoT Systems in Personalized Health Care
- Indbinding:
- Paperback
- Sideantal:
- 360
- Udgivet:
- 11. november 2020
- Størrelse:
- 230x153x22 mm.
- Vægt:
- 584 g.
- 2-3 uger.
- 14. december 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Intelligent IoT Systems in Personalized Health Care
Intelligent IoT Systems in Personalized Health Care delivers a significant forum for the technical advancement of IoMT learning in parallel computing environments across biomedical engineering diversified domains and its applications. Pursuing an interdisciplinary approach, the book focuses on methods used to identify and acquire valid, potentially useful knowledge sources. The book presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT and its capabilities in solving a diverse range of problems for biomedical engineering and its real-world personalized health care applications.
The book is well suited for researchers exploring the significance of IoT based architecture to perform predictive analytics of user activities in sustainable health.
Presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoTIllustrates state-of-the-art developments in new theories and applications of IoMT techniques as applied to parallel computing environments in biomedical engineering systemsPresents concepts and technologies successfully used in the implementation of today''s intelligent data-centric IoT systems and Edge-Cloud-Big data
The book is well suited for researchers exploring the significance of IoT based architecture to perform predictive analytics of user activities in sustainable health.
Presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoTIllustrates state-of-the-art developments in new theories and applications of IoMT techniques as applied to parallel computing environments in biomedical engineering systemsPresents concepts and technologies successfully used in the implementation of today''s intelligent data-centric IoT systems and Edge-Cloud-Big data
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