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Challenges and opportunities for the convergence of IoT, big data, and cloud computing

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Challenges and opportunities for the convergence of IoT, big data, and cloud computing/ Velayutham Sathiyamoorthi, editor.
其他作者:	Sathiyamoorthi, V.,
出版者:	Hershey, Pennsylvania :IGI Global, : 2020.,
面頁冊數:	1 online resource (xvii, 381 p.)
標題:	Convergence (Telecommunication) -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-3111-2
ISBN:	9781799831136 (ebk.)

Challenges and opportunities for the convergence of IoT, big data, and cloud computing
Challenges and opportunities for the convergence of IoT, big data, and cloud computing[electronic resource] /Velayutham Sathiyamoorthi, editor. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xvii, 381 p.)

Includes bibliographical references and index.

Chapter 1. The age of autonomous internet of things devices: opportunities and challenges of IoT -- Chapter 2. Challenges for convergence of cloud and IoT in applications and edge computing -- Chapter 3. Emerging trends and techniques in cloud-based data analytics -- Chapter 4. An IoT-based energy meter for energy level monitoring, predicting, and optimization -- Chapter 5. Artificial intelligence based on biological neurons: constructing neural circuits for IoT -- Chapter 6. Best practices: adopting security into the cloud-based internet of things -- Chapter 7. Big data IoT analytics for smart cities with cloud computing technique -- Chapter 8. Big data issues: gathering, governance, GDPR, security, and privacy -- Chapter 9. Big data analytics and its applications in IoT -- Chapter 10. Big data analytics in cloud platform -- Chapter 11. Convergence of AI, ML, and DL for enabling smart intelligence: artificial intelligence, machine learning, deep learning, internet of things -- Chapter 12. Impact of deep learning techniques in IoT -- Chapter 13. IoT device onboarding, monitoring, and management: approaches, challenges, and future -- Chapter 14. Machine and deep learning techniques in IoT and cloud -- Chapter 15. Perspectives of machine learning and deep learning in internet of things and cloud: artificial intelligence-based internet of things system -- Chapter 16. Real-time problems to be solved by the combination of IoT, big data, and cloud technologies -- Chapter 17. Survelliance of type i and II diabetic subjects on physical characteristics: IoT and big data perspective in healthcareNCR, India.

"This book focuses on the applications, issues, and challenges in the convergence of the internet of things, big data, and cloud computing"--

ISBN: 9781799831136 (ebk.)Subjects--Topical Terms:

574469
Convergence (Telecommunication)

LC Class. No.: TK5105.8857 / .C43 2020e

Dewey Class. No.: 004

Challenges and opportunities for the convergence of IoT, big data, and cloud computing
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504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. The age of autonomous internet of things devices: opportunities and challenges of IoT -- Chapter 2. Challenges for convergence of cloud and IoT in applications and edge computing -- Chapter 3. Emerging trends and techniques in cloud-based data analytics -- Chapter 4. An IoT-based energy meter for energy level monitoring, predicting, and optimization -- Chapter 5. Artificial intelligence based on biological neurons: constructing neural circuits for IoT -- Chapter 6. Best practices: adopting security into the cloud-based internet of things -- Chapter 7. Big data IoT analytics for smart cities with cloud computing technique -- Chapter 8. Big data issues: gathering, governance, GDPR, security, and privacy -- Chapter 9. Big data analytics and its applications in IoT -- Chapter 10. Big data analytics in cloud platform -- Chapter 11. Convergence of AI, ML, and DL for enabling smart intelligence: artificial intelligence, machine learning, deep learning, internet of things -- Chapter 12. Impact of deep learning techniques in IoT -- Chapter 13. IoT device onboarding, monitoring, and management: approaches, challenges, and future -- Chapter 14. Machine and deep learning techniques in IoT and cloud -- Chapter 15. Perspectives of machine learning and deep learning in internet of things and cloud: artificial intelligence-based internet of things system -- Chapter 16. Real-time problems to be solved by the combination of IoT, big data, and cloud technologies -- Chapter 17. Survelliance of type i and II diabetic subjects on physical characteristics: IoT and big data perspective in healthcareNCR, India.
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