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A Beginners Guide to Data Agglomeration and Intelligent Sensing provides an overview of the Sensor Cloud Platform, Converge-casting, and Data Aggregation in support of intelligent sensing and relaying of information. The book begins with a brief introduction on sensors and transducers, giving readers insight into the various types of sensors and how one can work with them. In addition, it gives several real-life examples to help readers properly understand concepts. An overview of concepts such as wireless sensor networks, cloud platforms, and device-to-cloud and sensor cloud architecture are explained briefly, as is data gathering in wireless sensor networks and aggregation procedures.
Final sections explore how to process gathered data and relay the data in an intelligent way, including concepts such as supervised and unsupervised learning, software defined networks, sensor data mining and smart systems.
- Presents the latest advances in data agglomeration for intelligent sensing
- Discusses the basic concepts of sensors, real-life applications of sensors and systems, the protocols and applications of wireless sensor networks, the methodology of sensor data accumulation, and real-life applications of Intelligent Sensor Networks
- Provides readers with an easy-to-learn and understand introduction to the concepts of the cloud platform, Sensor Cloud and Machine Learning
Computer/data scientists, biomedical engineers, researchers and software engineers in the areas of data aggregation, sensor cloud architecture, intelligent sensing, and its applications
1. Introduction to sensors and system
1.1 Fundamentals of sensors/transducers
1.2 Principles and properties
1.3 Classification of sensors
1.4 Networking methodology
1.5 Types of sensors
1.6 Smart sensors and transducers
2. Real-life application of sensors and systems
2.1 Overview of Internet of things
2.2 Design perspective
2.3 Related platform
2.4 Real-life examples and implementation
2.5 WSN simulation environments
3. Wireless sensor network: principle and application
3.1 Wireless communication and sensor networks
3.2 Sensor components and technology
3.3 Sensor network protocols
3.4 Sensor networks application scenario
4. Overview of sensor cloud
4.1 Basics of cloud computing
4.2 Types of clouds
4.3 Cloud computing models
4.4 Sensor cloud platform
4.5 Sensor cloud architecture
4.6 Sensor cloud workflow
4.7 Application scenario
5. Sensor data accumulation methodologies
5.1 Sensor data classification
5.2 Data transmission methodology
5.3 Convergecast: inverse of broadcasting
5.4 Data aggregation
5.5 Choice of MAC layer
5.6 Energy analysis
5.7 Data collection methodologies
5.8 Types of aggregation
6. Intelligent sensor network
6.2 Intelligence hierarchy
6.3 Preliminary concepts of AI and Machine Learning
6.4 Intelligent approaches in WSN node deployment
6.5 Intelligent routing overview
6.6 Sensor data mining
6.7 Intelligent sensor network applications
7.1 Chapters 1 and 2
7.2 Chapters 3 and 4
7.3 Chapters 5 and 6
7.4 Scope for future enhancement
- No. of pages:
- © Academic Press 2020
- 24th February 2020
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Amartya Mukherjee, is an assistant professor of Computer Science & Engineering at Institute of Engineering & Management, Salt Lake Kolkata, India. He holds a bachelor’s degree in Computer Science and Engineering from West Bengal University of Technology and Master’s (M.Tech) in Computer Science and Engineering from the National Institute of Technology, Durgapur, India. His primary research interest includes Delay tolerant Networks modelling, Embedded application development, Robotics, Unmanned Aircraft Systems, Internet of Things and Intelligent Sensor Networks. He has written various articles and book in the field of Robotics, Embedded systems, Intelligent Sensor Networks in renowned SCI Journals and publication houses such as Springer, Elsevier, CRC Press, World Scientific and IGI Global.
Assistant Professor, Institute of Engineering & Management, Salt Lake, Kolkata, India
Ayan Kumar Panja is currently Assistant Professor at the Institute of Engineering and Management, Kolkata, India. His main research is Machine Learning, Pattern Recognition, Audio Signal Processing, Wireless Communication and Sensor Networks.
Assistant Professor, Institute of Engineering and Management, Salt Lake, Kolkata, India
Nilanjan Dey is an Assistant Professor in the Department of Information Technology at Techno India College of Technology, Kolkata, India. He is a visiting fellow of the University of Reading, UK, and is also a Visiting Professor at Wenzhou Medical University, China and Duy Tan University, Vietnam. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his PhD. from Jadavpur University in 2015. Dr. Dey has authored/edited more than 45 books with Elsevier, Wiley, CRC Press, and Springer, and published more than 300 papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, IGI Global, Associated Editor of IEEE Access and International Journal of Information Technology published by Springer. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer Nature, Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and data analysis, CRC. His main research interests include medical imaging, machine learning, computer-aided diagnosis and data mining. He is the Indian Ambassador of International Federation for Information Processing (IFIP) – Young ICT Group and has recently been awarded as one among the top 10 most published academics in the field of Computer Science in India (2015-17).
Assistant Professor, Department of Information Technology, Techno India College of Technology, West Bengal, India
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