A Beginner’s Guide to Data Agglomeration and Intelligent Sensing 1st Edition by Amartya Mukherjee , Ayan Kumar Panja , Nilanjan Dey PhD ISBN 128203412 978-0128203415
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ISBN 10: 128203412
ISBN 13: 978-0128203415
Author: Amartya Mukherjee , Ayan Kumar Panja , Nilanjan Dey PhD
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
A Beginner’s Guide to Data Agglomeration and Intelligent Sensing 1st Table of contents:
Chapter one. Introduction to sensors and systems
Abstract
Contents
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
1.7 Summary
References
Chapter two. Real-life application of sensors and systems
Abstract
Contents
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
2.6 Summary
References
Chapter three. Wireless sensor network: principle and application
Abstract
Contents
3.1 Wireless communication and sensor networks
3.2 Sensor components and technology
3.3 Sensor network protocols
3.4 Sensor networks application scenario
3.5 Summary
References
Chapter four. Overview of sensor cloud
Abstract
Contents
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
4.8 Summary
References
Chapter five. Sensor data accumulation methodologies
Abstract
Contents
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
5.9 Summary
References
Further reading
Chapter six. Intelligent sensor network
Abstract
Contents
6.1 Introduction
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
6.8 Summary
References
Further reading
Chapter seven. Conclusion
Abstract
Contents
7.1 Chapters 1 and 2
7.2 Chapters 3 and 4
7.3 Chapters 5 and 6
7.4 Scope for future enhancement
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Amartya Mukherjee,Ayan Kumar Panja,Nilanjan Dey PhD,Data Agglomeration
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