Cognitive Sensing Technologies and Applications
Institution of Engineering and Technology (Verlag)
978-1-83953-689-2 (ISBN)
Cognitive sensing systems combined with IoTs and smart technologies are used in countless applications such as industrial robotics, computer-aided diagnosis, brain-computer interface (BCI), human-computer interaction (HCI), telemedicine, driverless cars and smart energy systems.
With contributions from an international team of experts from a wide range of research areas including sensing, computer vision, signal processing and device and control applications, this book highlights the emerging role of cognitive sensors in a growing number of real time applications including smart health, smart cities, smart transportation and smart agriculture.
The volume will be suitable for a broad audience of researchers in the fields of smart sensing, signal processing, automation and robotics, environmental engineering, energy engineering, biomedical engineering and allied disciplines where smart sensors are part of the curriculum.
G.R. Sinha is a professor at the International Institute of Information Technology Bangalore (IIITB) India. He has been visiting professor in Taiwan, Italy, and Sri Lanka. His research interests include cognitive science, computer vision, biometrics, medical image processing and ICT tools. He has published 280 research papers, book chapters, and books. He owns two Australian patents and one German patent in his area of research. He is an associate editor of several journals. He has been ACM Distinguished Speaker, IEEE Distinguished Lecturer and CSI Distinguished Speaker. He is a senior member of the IEEE, Fellow of the Institute of Engineers India and Fellow of the IETE (India). He is also a member of several national professional bodies such as ISTE, CSI, ISCA, and IEI. He received his PhD degree in electronics & telecommunication engineering from Chhattisgarh Swami Vivekanand Technical University (CSVTU) Bhilai, India. Bidyadhar Subudhi is a professor at the School of Electrical Sciences and Dean (R&D) of the Indian Institute of Technology (IIT), Goa, India. His research interests include machine learning and adaptive systems, biomedical engineering, marine robotics and microgrid systems. He has published his research in over 150 reputed international journals and 70 conference papers and has edited 3 books. He has been appointed as a distinguished speaker by ACM (2020-2023). He was elected as fellow of the Indian National Academy of Engineering for his distinguished contribution in Electrical Engineering. He serves as a technical committee member of the IEEE Intelligent Control Group, and an associate editor for IEEE Transactions on Sustainable Energy and IEEE Access, and he is on the editorial board of the IEEE Technology Conference. He is a senior member of the IEEE, a fellow of the IET (UK), the Institution of Engineers (India) and the Institution of Electronics & Telecommunication Engineers (India). He received his PhD degree in Control System Engineering from the University of Sheffield, UK. Chih-Peng Fan is a full professor in the Department of Electrical Engineering at the National Chung Hsing University, Taiwan. His research interests include deep learning for digital image processing and pattern recognition, digital video coding and processing, digital baseband transceiver design, VLSI design for digital signal processing, and fast prototype of DSP systems with FPGA-based and embedded SOC platforms. He has over 100 publications, including technical journals, technical reports, book chapters, and conference papers. He is an IEEE CTSoc Representative at the IEEE Systems Council's AdCom (2020-2021); member of IEEE CTSoc Awards Committee, secretary of the IEEE CTSoc Sensors and Actuators Technical Committee. He is also a member of several journal editorial boards. He is a supervisor of the Taiwan Consumer Electronics Society, a member of the IEEE, the IEICE, and the Taiwan IC Design Society (TICD). He received his PhD degree in Electrical Engineering from the National Cheng Kung University, Taiwan, ROC. Humaira Nisar is a full professor and head of the Master of Engineering (Electronic Systems) Programme in the Department of Electronic Engineering at the Universiti Tunku Abdul Rahman, Malaysia. Her research interests include signal and image processing, image analysis for wastewater treatment, biomedical imaging, neuro-signal processing and analysis, brain computer interface, and neurofeedback. She has published over 150 international journals, conference papers and book chapters. She has also edited three books. She is an academic editor for IEEE Access and PLOS. She is a senior member of IEEE and a member of IEEE Signal Processing Society, Malaysia Section. She has also served as an auditor for IEEE EMBS Society, Malaysia Section. She is serving as professional technologist under the Malaysia Board of Technologists, professional engineer under the Pakistan Engineering Council and Graduate Member of the Board of Engineers Malaysia. She holds a PhD degree in Information and Mechatronics from Gwangju Institute of Science and Technology, South Korea.
Chapter 1: Introduction to cognitive sensing technologies and applications
Chapter 2: Hardware architectures for some sparse signal recovery approaches
Chapter 3: Performance evaluation of cognitive sensor frameworks for IoT applications in healthcare and environment monitoring
Chapter 4: Cognitive sensors for rehabilitation and therapeutic treatment
Chapter 5: An ensemble machine learning-based intelligent system for human activity recognition using sensory data
Chapter 6: Challenges in the acquisition of non-invasive brain signals - electroencephalographic signals (EEG)
Chapter 7: Cognitive task and workload classification using EEG signal
Chapter 8: Automatic detection of Parkinson's disease using non-linear signal decomposition and machine learning techniques
Chapter 9: A review on gait kinematics acquisition sensors and its advancements in IoT and machine learning
Chapter 10: Cognitive IoT sensors for smart industrial and biomedical applications
Chapter 11: Intelligent automation using IoT and machine learning
Chapter 12: Recent trends in applications of cognitive sensors for smart manufacturing and control
Chapter 13: A systematic study on cognitive sensors in robotics, UAVs, and drones
Chapter 14: Sensor data fusion and processing in smart agriculture: crop quality assessment, crop damage, smart planning
Chapter 15: Incremental learning of plant diseases and new plant types: moving towards a smart agriculture system
Chapter 16: Disaster susceptibility analysis in remote sensing
Chapter 17: Topological assessment of road transportation network
Chapter 18: Future perspective and research direction in cognitive sensing technologies
| Erscheinungsdatum | 08.08.2023 |
|---|---|
| Reihe/Serie | Control, Robotics and Sensors |
| Verlagsort | Stevenage |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-83953-689-6 / 1839536896 |
| ISBN-13 | 978-1-83953-689-2 / 9781839536892 |
| Zustand | Neuware |
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