| Description |
1 online resource (510 pages). |
| Physical Medium |
polychrome |
| Description |
text file |
| Series |
Computing and Networks Ser.
|
|
Computing and Networks Ser.
|
| Note |
Description based upon print version of record. |
| Contents |
Intro -- Title -- Copyright -- Contents -- Foreword -- About the editors -- 1 Introduction to big data-enabled Internet of Things -- 1.1 Introduction -- 1.1.1 Internet of Things -- 1.1.2 Big data-enabled IoT -- 1.2 Platforms for big data-enabled IoT -- 1.2.1 Cloud computing -- 1.2.2 Fog computing -- 1.2.3 Edge computing -- 1.2.4 MapReduce platforms -- 1.2.5 Columnar database -- 1.3 Applications of big data-enabled IoT -- 1.3.1 Traffic applications -- 1.3.2 Wearable IoT applications in health care -- 1.3.3 Smart homes -- 1.3.4 Smart cars -- 1.3.5 Smart grids -- 1.4 Challenges |
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1.4.1 Real-time analysis -- 1.4.2 Storage -- 1.4.3 Quality of service -- 1.4.4 Security challenges -- 1.5 Recent studies in the field of big data-enabled IoT -- 1.6 Conclusions -- References -- 2 Smarter big data analytics for traffic applications in developing countries -- 2.1 Introduction -- 2.1.1 Research challenges -- 2.1.2 Contributions and paper structure -- 2.2 Scenario and requirements -- 2.3 Analytics system framework for traffic applications -- 2.3.1 Design objectives -- 2.3.2 Framework overview -- 2.3.3 GPS data providers -- 2.3.4 Offline analytics |
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2.3.5 Data router and real-time analytics -- 2.3.6 Decision maker -- 2.3.7 Mobile and web applications -- 2.4 Big data applications and challenges -- 2.4.1 In-memory storage -- 2.4.2 Filtering unusable data for real-time analytics -- 2.4.3 Traffic monitoring and prediction -- 2.4.4 Trip planning in city bus networks -- 2.5 Related work -- 2.6 Conclusions -- References -- 3 Using IoT-based big data generated inside school buildings -- 3.1 Introduction -- 3.2 Related work -- 3.3 IoT and real-world data in education -- 3.3.1 End-user requirements -- 3.3.2 IoT platform design aspects |
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3.4 Design aspects of an IoT platform targeting education activities -- 3.4.1 End-device level -- 3.4.2 IT service ecosystem level -- 3.4.3 User involvement level -- 3.5 The GAIA IoT platform -- 3.5.1 Continuous computation engine -- 3.5.2 Data access and acquisition -- 3.6 Using IoT-generated big data in educational buildings -- 3.6.1 High-level IoT data analysis -- 3.6.2 Thermal comfort of classrooms -- 3.6.3 Classroom thermal performance -- 3.7 Conclusions -- Acknowledgments -- References -- 4 Autonomous collaborative learning in wearable IoT applications |
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4.1 Transfer learning in wearable IoT -- 4.2 Synchronous dynamic view learning -- 4.2.1 Problem definition -- 4.2.2 Problem formulation -- 4.2.3 Overview of autonomous learning -- 4.3 Minimum disagreement labeling -- 4.3.1 Label refinement -- 4.4 Experimental analysis -- 4.4.1 Evaluation methodology -- 4.4.2 Accuracy of transferred labels -- 4.4.3 Accuracy of activity recognition -- 4.4.4 Precision, recall, and F1-measure -- 4.5 Summary -- References -- 5 A distributed approach to energy-efficient data confidentiality in the Internet of Things -- 5.1 Introduction |
| Note |
5.2 Data confidentiality in the IoT. |
| Summary |
This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Internet of things.
|
|
Internet of things. |
|
Big data.
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Big data. |
| Genre/Form |
Electronic books.
|
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Electronic books.
|
| Added Author |
Khan, Samee U.
|
|
Zomaya, Albert Y.
|
| Other Form: |
Print version: Khan, Muhammad Usman Shahid Big Data-Enabled Internet of Things Stevenage : Institution of Engineering & Technology,c2020 9781785616365 |
| ISBN |
1785616374 |
|
9781785616372 (electronic book) |
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