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
2. Real life Application of Sensors and Systems
3. Wireless Sensor Network: Principle and Application
4. Overview of Sensor Cloud
5. Sensor Data Accumulation Methodology
6. Intelligent Sensor Network
Amartya Mukherjee, is an assistant professor 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 in computer science and engineering from the National Institute of Technology, Durgapur, India. His primary research interest includes embedded application development, Robotics, Unmanned Aircraft Systems, Internet of things and Intelligent Sensor Networks. He has written various papers and book in the field of Robotics, Embedded systems and IoT.
Kumar Panja, Ayan
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.
Nilanjan Dey received his Ph. D. Degree from Jadavpur University, India, in 2015. He is an Assistant Professor in the Department of Information Technology, Techno International New Town, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, Bulgaria. Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. His research topic is Medical Imaging, Data mining, Machine learning, Computer Aided Diagnosis, Atherosclerosis etc. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IGI Global), US, (Co-EinC) and International Journal of Natural Computing Research (IGI Global), US. Series Editor (Co.) of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier, Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He has 20 books and more than 200 research articles in peer-reviewed journals and international conferences. He is the organizing committee member of several international conferences including ITITS, W4C, ICMIR, FICTA, ICICT.