國立虎尾科技大學 |

Efficient Data Handling for Massive Internet of Medical Things = Healthcare Data Analytics /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Efficient Data Handling for Massive Internet of Medical Things/ edited by Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke.
其他題名:	Healthcare Data Analytics /
其他作者:	Shelke, Yogesh.
面頁冊數:	XIV, 388 p. 100 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Biomedical Engineering and Bioengineering. -
電子資源:	https://doi.org/10.1007/978-3-030-66633-0
ISBN:	9783030666330

Efficient Data Handling for Massive Internet of Medical Things = Healthcare Data Analytics /
Efficient Data Handling for Massive Internet of Medical ThingsHealthcare Data Analytics /[electronic resource] :edited by Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke. - 1st ed. 2021. - XIV, 388 p. 100 illus.online resource. - Internet of Things, Technology, Communications and Computing,2199-1081. - Internet of Things, Technology, Communications and Computing,.

Chapter 1. An Overview of the Internet of Medical Things and its Modern Perspective -- Chapter 2. Big medical data analytics under Internet of Things -- Chapter 3. Big Medical Data Analytics using Sensor Technology -- Chapter 4. Smart Healthcare Technologies for Massive Internet of Medical Things -- Chapter 5. Sensor Informatics of IoT, AR/VR, and MR in Healthcare Applications -- Chapter 6. Body Sensor Networks as emerging trends of technology in health care system: Challenges and Future -- Chapter 7. Smart sensors technologies for Healthcare system -- Chapter 8. Cloud and IoMT-based Big Data Analytics system during COVID-19 pandemic -- Chapter 9. Remote human’s health and activities monitoring using wearable sensor based system- a review -- Chapter 10. A Healthcare Resource Management Optimization Framework for ECG Biomedical Sensors -- Chapter 11. Diabetes Detection and Sensor Based Continuous Glucose Monitoring – A Deep Learning Approach -- Chapter 12. ‘Sensing the Mind’-An Exploratory Study About Sensors used in E-Health and M-Health Applications for Diagnosis of Mental Health Condition -- Chapter 13. Role of Sensors, Devices and Technology for Detection of COVID-19 Virus -- Chapter 14. Implementation of Internet of Medical Things (IoMT): Clinical and Policy Implications -- Chapter 15. Applicability of Blockchain Technology in Healthcare Industry: Applications, Challenges & Solutions.

This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. Presents a rigorous introduction to theoretical foundations and practical solutions for Internet of Medical Things; Covers data handling, intelligence and security and related issues to guide the massive data handling techniques for healthcare; Includes examples and case studies for further study for academics, researchers, and professionals.

ISBN: 9783030666330

Standard No.: 10.1007/978-3-030-66633-0doiSubjects--Topical Terms:

1211019
Biomedical Engineering and Bioengineering.

LC Class. No.: TK7885-7895

Dewey Class. No.: 621.38

Efficient Data Handling for Massive Internet of Medical Things = Healthcare Data Analytics /
LDR:04526nam a22004335i 4500 001 1048395
003 DE-He213
005 20210901073313.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030666330 $9 978-3-030-66633-0
024 7 $a 10.1007/978-3-030-66633-0 $2 doi
035 $a 978-3-030-66633-0
050 4 $a TK7885-7895
050 4 $a TK5105.8857
072 7 $a THR $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a THR $2 thema
072 7 $a GPFC $2 thema
082 0 4 $a 621.38 $2 23
245 1 0 $a Efficient Data Handling for Massive Internet of Medical Things $h [electronic resource] : $b Healthcare Data Analytics / $c edited by Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XIV, 388 p. 100 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Internet of Things, Technology, Communications and Computing, $x 2199-1081
505 0 $a Chapter 1. An Overview of the Internet of Medical Things and its Modern Perspective -- Chapter 2. Big medical data analytics under Internet of Things -- Chapter 3. Big Medical Data Analytics using Sensor Technology -- Chapter 4. Smart Healthcare Technologies for Massive Internet of Medical Things -- Chapter 5. Sensor Informatics of IoT, AR/VR, and MR in Healthcare Applications -- Chapter 6. Body Sensor Networks as emerging trends of technology in health care system: Challenges and Future -- Chapter 7. Smart sensors technologies for Healthcare system -- Chapter 8. Cloud and IoMT-based Big Data Analytics system during COVID-19 pandemic -- Chapter 9. Remote human’s health and activities monitoring using wearable sensor based system- a review -- Chapter 10. A Healthcare Resource Management Optimization Framework for ECG Biomedical Sensors -- Chapter 11. Diabetes Detection and Sensor Based Continuous Glucose Monitoring – A Deep Learning Approach -- Chapter 12. ‘Sensing the Mind’-An Exploratory Study About Sensors used in E-Health and M-Health Applications for Diagnosis of Mental Health Condition -- Chapter 13. Role of Sensors, Devices and Technology for Detection of COVID-19 Virus -- Chapter 14. Implementation of Internet of Medical Things (IoMT): Clinical and Policy Implications -- Chapter 15. Applicability of Blockchain Technology in Healthcare Industry: Applications, Challenges & Solutions.
520 $a This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. Presents a rigorous introduction to theoretical foundations and practical solutions for Internet of Medical Things; Covers data handling, intelligence and security and related issues to guide the massive data handling techniques for healthcare; Includes examples and case studies for further study for academics, researchers, and professionals.
650 2 4 $a Biomedical Engineering and Bioengineering. $3 1211019
650 2 4 $a Health Informatics. $3 593963
650 2 4 $a Communications Engineering, Networks. $3 669809
650 1 4 $a Cyber-physical systems, IoT. $3 1226036
650 0 $a Biomedical engineering. $3 588770
650 0 $a Health informatics. $3 1064466
650 0 $a Electrical engineering. $3 596380
650 0 $a Embedded computer systems. $3 562313
650 0 $a Internet of things. $3 1023130
650 0 $a Computer engineering. $3 569006
700 1 $a Shelke, Yogesh. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1352259
700 1 $a Ravi, Vinayakumar. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1352258
700 1 $a Ghosh, Uttam. $e editor. $1 https://orcid.org/0000-0003-1698-8888 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1352257
700 1 $a Chakraborty, Chinmay. $e editor. $1 https://orcid.org/0000-0002-4385-0975 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1321565
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030666323
776 0 8 $i Printed edition: $z 9783030666347
776 0 8 $i Printed edition: $z 9783030666354
830 0 $a Internet of Things, Technology, Communications and Computing, $x 2199-1073 $3 1270994
856 4 0 $u https://doi.org/10.1007/978-3-030-66633-0
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)