Self-Powered Sensors

A Path to Wearable Electronics
Erscheinungsjahr 2024
ISBN: 978-0-443-13792-1
Verlag: Elsevier Science

Buch, Englisch, 342 Seiten, Format (B × H): 188 mm x 234 mm, Gewicht: 710 g

Self-powered Sensors: A Path to Wearable Electronics features recent developments in chemical, photonic, pharmaceutical, microbiological, biomimetic, and bio-inspired approaches for MEMS/NEMS and medicinal self-powered sensors. Unconventional nanomaterial sensors driven by self-sufficient energy are given a contemporary review, with a focus on the categorization of energy sources and comparisons of research involving self-powered solar, piezoresistive, triboelectric, and thermodynamic technologies. This book also focuses on the different techniques, materials, comparisons of fabrication of self-powered sensors as well as thermoelectric self-powered sensors and its implantable applications.

Autoren/Hrsg.

Dhanaraj, Rajesh Kumar

Samuel, Prithi

Sathyamoorthy, Malathy

Balusamy, Balamurugan

Ravi, Vinayakumar

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie

Inhaltsverzeichnis

1. Fundamentals and applications of self-powered sensing systems 2. Wearable and portable self-powered sensor systems based on emerging energy harvesting technology 3. Augmented machine learning towards smart self-powered sensing systems 4. Next-generation self-powered integrated sensing systems for the industrial internet of things (IIoT) applications 5. Self-powered wearable implantable smart sensor and medical electronics based on nanogenerator 6. Intelligent vision sensors tracking and sensor fusion space-based surveillance and detection 7. Stretchable and flexible wearable sensors based on carbon and textile for health monitoring 8. Wearable electrochemical and biosensors for forensic analysis: Challenges and research directions 9. Self-powered triboelectric sensors for biomedical applications 10. Cybersecurity and data privacy vulnerability analysis for smart, self-powered sensors 11. Biometric and bio-inspired approaches for MEMS/NEMS enabled self-powered sensors 12. Self-powered integrated sensor system for printable fabrication 13. Self-powered wireless solution towards the smart city: Use cases and its applications 14. Deep learning algorithm and self-powered tactile sensors for gesture recognition 15. Signal processing for a self-powered vibration-based power generation

Über Autor(innen)

Samuel, Prithi
Dr Prithi Samuel is currently working as an assistant professor in the Department of Computational Intelligence at SRM Institute of Sci?ence and Technology, Kattankulathur Campus, Chennai. She has completed her Ph.D. in Information and Communication Engineering from Anna University, Chennai. She has got over 15 years of teaching experience in reputed engineering colleges in Tamil Nadu. She is a pioneer researcher in the areas of Automata Theory, Machine Learn?ing, Deep Learning, Computational Intelligence Techniques, and the Internet of Things. She has published more than 25 papers in leading SCI and Scopus Journals and more than 25 papers in International Conferences and published 1 book and more than 10 book chapters in Wiley, Taylor and Francis, Springer, and Elsevier and published 4 patents and 2 patent grants. She is an active IEEE, ACM Member and holds an ISTE and IAENG lifetime membership

Sathyamoorthy, Malathy
Dr. Malathy holds a PhD in Information and Communication Engineering from Anna University, Chennai, India. Her research areas include wireless sensor networks, Internet of Things, and applied machine learning. She is a life member of the Indian Society for Technical Education (ISTE) and the International Association of Engineers (IAENG). She is an active author/editor for Springer, CRC Press, and Elsevier. She is also a reviewer for Wireless Networks (Springer) and on the editorial board at many international conferences.

Dhanaraj, Rajesh Kumar
Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and member of the International Association of Engineers (IAENG). He is an expert advisory panel member of Texas Instruments Inc. (USA), and an associate editor of International Journal of Pervasive Computing and Communications (Emerald Publishing).

Ravi, Vinayakumar
Dr. Vinayakumar Ravi is an Assistant Research Professor at the Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia. Dr. Ravi has been a Postdoctoral Research Fellow developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining with Cincinnati Children's Hospital Medical Center, Cincinnati, USA. He received his Ph.D. in Computer Science from Amrita School of Engineering, Coimbatore, India. His current research interests include applications of data mining, Artificial Intelligence, machine learning and, deep learning for biomedical informatics, cyber security, image processing, and natural language processing. Dr. Ravi is editor of Efficient Data Handling for Massive Internet of Medical Things: Healthcare Data Analytics, Springer. Dr. Ravi is an editorial board member for Journal of the Institute of Electronics and Computer (JIEC), International Journal of Digital Crime and Forensics (IJDCF), and he has organized a shared task force on detecting malicious domain names (DMD 2018) as part of SSCC'18 and ICACCI'18.

Balusamy, Balamurugan
Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar Institution of Eminence, Delhi-NCR. He is part of the Top 2% Scientists Worldwide 2023 by Stanford University in the area of Data Science/AI/ML. He is also an Adjunct Professor in the Department of Computer Science and Information Engineering, Taylor University, Malaysia. His contributions focus on engineering education, blockchain, and data sciences