Smart Healthcare Monitoring Using IoT with 5G (eBook, PDF)
Challenges, Directions, and Future Predictions
Redaktion: Gupta, Meenu; de Albuquerque, Victor Hugo C.; Chaudhary, Gopal
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Smart Healthcare Monitoring Using IoT with 5G (eBook, PDF)
Challenges, Directions, and Future Predictions
Redaktion: Gupta, Meenu; de Albuquerque, Victor Hugo C.; Chaudhary, Gopal
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Focusing on the challenges, directions, and future predictions and the role 5G plays in smart healthcare monitoring, this book offers the fundamental concepts and analysis on methods to apply IoT in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their experience of care.
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Focusing on the challenges, directions, and future predictions and the role 5G plays in smart healthcare monitoring, this book offers the fundamental concepts and analysis on methods to apply IoT in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their experience of care.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 272
- Erscheinungstermin: 22. Dezember 2021
- Englisch
- ISBN-13: 9781000486421
- Artikelnr.: 62879153
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 272
- Erscheinungstermin: 22. Dezember 2021
- Englisch
- ISBN-13: 9781000486421
- Artikelnr.: 62879153
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Meenu Gupta completed her PhD in Computer Science & Engineering with emphasis on Traffic Accident Severity problem from the Ansal University, Gurugram, India (2020), an M.Tech in Computer Science & Engineering from the M.D. U University, Rohtak, India (2010), and she graduated in Information Technology at the K.U.K University, Kurukshetra, India (2006). She is currently Associate Professor in Chandigarh University. She has 13 years of teaching experience. Her areas of research are Machine Learning, Intelligent Systems, Data mining, with specific interest in, Artificial Intelligence, Image Processing and Analysis, Smart cities, Data Analysis, and human/brain-machine interaction. She also completed two edited books of CRC press on Healthcare and Cancer diseases. She also has 4 authored books on engineering streams. She worked as a reviewer of many journals like, Big Data, CMC, Scientific Report, TSP, etc. She is a life member of ISTE and IAENG. She has authored or co-authored over 50 papers in refereed international journals (SCI/SCIE/WoS/Scopus/etc.), conferences, and more than 20 book chapters. She also chaired IEEE international Conference and convened many workshops/FDP. Gopal Chaudhary is currently working as an assistant professor in Bharati Vidyapeeth's College of Engineering, Guru Gobind Singh Indraprastha University, Delhi, India. He holds a Ph.D. in biometrics at the division of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, University of Delhi, India. He received B.E. degree in electronics and communication engineering in 2009 and the MTech degree in microwave and optical communication from Delhi Technological University (formerly known as Delhi College of Engineering), New Delhi, India, in 2012. He has 30 publications in refereed national/international journals and conferences (e.g. Elsevier, Springer, Inderscience) in the area of biometrics and its applications. His current research interests include soft computing, intelligent systems, information fusion, and pattern recognition. He has organized many conferences and contributed to special issues. Victor Hugo C. de Albuquerque [M17, SM19] has a Ph.D. in Mechanical Engineering with emphasis on Materials from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Technology at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is currently Full Professor of the Graduate Program in Applied Informatics, and coordinator of the Laboratory of Industrial Informatics, Electronics and Health at the University of Fortaleza (UNIFOR). Data Science Director at the Superintendency for Research and Public Safety Strategy of Ceará State (SUPESP/CE), Brazil. He has experience in Computer Systems, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, image segmentation, biomedical circuits and human/brain-machine interaction, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Additionally, he has research at the microstructural characterization field through the combination of non-destructive techniques with signal/image processing and analysis and pattern recognition. Prof. Victor is the leader of the Industrial Informatics, Electronics and Health Research Group. He is Editor-in-Chief of the Journal of Artificial Intelligence and Systems and Associate Editor of the IEEE Access, Applied Soft Computing, Frontiers in Communications and Networks, Computational Intelligence and Neuroscience, Journal of Nanomedicine and Nanotechnology Research, Computational Physiology and Medicine, and Journal of Mechatronics Engineering, and he has been Lead Guest Editor of several high-reputed journals, and TPC member of many international conferences.
1. The Internet of Things in Healthcare Management: Potential Applications
and Challenges. 2. Blending of Internet of Things and Deep Transfer
Learning (DTL): Enabling Innovations in Healthcare (COVID-19) and
Applications. 3. Potential Applications and Challenges of Internet of
Things in Healthcare. 4. IoT and Smart Health Management. 5. Current Status
of Alzheimer's Disease in India: Prevalence, Stigma, and Myths. 6.
Phytochemicals' Potential to Reverse the Process of Neurodegeneration. 7.
Existing Methods and Emerging Trends for Novel Coronavirus (COVID-19)
Detection Using Residual Network (ResNet): A Review on Deep Learning
Analysis. 8. Clinical Impact of COVID on Diabetic Patients. 9. Smart
Hospitals Using Artificial Intelligence and Internet of Things for COVID-19
Pandemic. 10. Researcher Issues and Future Directions in Healthcare Using
IoT and Machine Learning. 11. Diseases Prediction and Diagnosis System for
Healthcare Using IoT and Machine Learning. 12. Challenges and Solution of
COVID-19 Pandemic Based on AI and Big Data. 13. A Review of Artificial
Intelligence Applications for COVID-19 Contact Tracing.
and Challenges. 2. Blending of Internet of Things and Deep Transfer
Learning (DTL): Enabling Innovations in Healthcare (COVID-19) and
Applications. 3. Potential Applications and Challenges of Internet of
Things in Healthcare. 4. IoT and Smart Health Management. 5. Current Status
of Alzheimer's Disease in India: Prevalence, Stigma, and Myths. 6.
Phytochemicals' Potential to Reverse the Process of Neurodegeneration. 7.
Existing Methods and Emerging Trends for Novel Coronavirus (COVID-19)
Detection Using Residual Network (ResNet): A Review on Deep Learning
Analysis. 8. Clinical Impact of COVID on Diabetic Patients. 9. Smart
Hospitals Using Artificial Intelligence and Internet of Things for COVID-19
Pandemic. 10. Researcher Issues and Future Directions in Healthcare Using
IoT and Machine Learning. 11. Diseases Prediction and Diagnosis System for
Healthcare Using IoT and Machine Learning. 12. Challenges and Solution of
COVID-19 Pandemic Based on AI and Big Data. 13. A Review of Artificial
Intelligence Applications for COVID-19 Contact Tracing.
1. The Internet of Things in Healthcare Management: Potential Applications
and Challenges. 2. Blending of Internet of Things and Deep Transfer
Learning (DTL): Enabling Innovations in Healthcare (COVID-19) and
Applications. 3. Potential Applications and Challenges of Internet of
Things in Healthcare. 4. IoT and Smart Health Management. 5. Current Status
of Alzheimer's Disease in India: Prevalence, Stigma, and Myths. 6.
Phytochemicals' Potential to Reverse the Process of Neurodegeneration. 7.
Existing Methods and Emerging Trends for Novel Coronavirus (COVID-19)
Detection Using Residual Network (ResNet): A Review on Deep Learning
Analysis. 8. Clinical Impact of COVID on Diabetic Patients. 9. Smart
Hospitals Using Artificial Intelligence and Internet of Things for COVID-19
Pandemic. 10. Researcher Issues and Future Directions in Healthcare Using
IoT and Machine Learning. 11. Diseases Prediction and Diagnosis System for
Healthcare Using IoT and Machine Learning. 12. Challenges and Solution of
COVID-19 Pandemic Based on AI and Big Data. 13. A Review of Artificial
Intelligence Applications for COVID-19 Contact Tracing.
and Challenges. 2. Blending of Internet of Things and Deep Transfer
Learning (DTL): Enabling Innovations in Healthcare (COVID-19) and
Applications. 3. Potential Applications and Challenges of Internet of
Things in Healthcare. 4. IoT and Smart Health Management. 5. Current Status
of Alzheimer's Disease in India: Prevalence, Stigma, and Myths. 6.
Phytochemicals' Potential to Reverse the Process of Neurodegeneration. 7.
Existing Methods and Emerging Trends for Novel Coronavirus (COVID-19)
Detection Using Residual Network (ResNet): A Review on Deep Learning
Analysis. 8. Clinical Impact of COVID on Diabetic Patients. 9. Smart
Hospitals Using Artificial Intelligence and Internet of Things for COVID-19
Pandemic. 10. Researcher Issues and Future Directions in Healthcare Using
IoT and Machine Learning. 11. Diseases Prediction and Diagnosis System for
Healthcare Using IoT and Machine Learning. 12. Challenges and Solution of
COVID-19 Pandemic Based on AI and Big Data. 13. A Review of Artificial
Intelligence Applications for COVID-19 Contact Tracing.