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Self-powered sensors : a path to wearable electronics /

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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 cat...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Dhanaraj, Rajesh Kumar (Editor), Samuel, Prithi (Editor), Sathyamoorthy, Malathy (Editor), Balusamy, Balamurugan (Editor), Ravi, Vinayakumar (Editor)
Format: eBook
Language:English
Published: London ; San Diego, CA : Academic Press, [2024]
Subjects:
Biosensors.
Detectors.
Wearable technology.
Biocapteurs.
Biotechnologie
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • Self-powered Sensors: A Path to Wearable Electronics
  • Copyright
  • Contents
  • Contributors
  • Editor's biographies
  • Preface
  • Chapter 1: Fundamentals and applications of self-powered sensing systems
  • 1. Triboelectric generators
  • 2. Piezoelectric generators
  • 2.1. Flexible polymer piezoelectric materials
  • 2.2. TENG/PENG-based self-powered sensors
  • 2.3. Touchless screen sensor
  • 3. Piezoelectric energy harvesters
  • 3.1. Benefits
  • 4. Hybrid energy harvester
  • 4.1. Systems with self-powered sensors for automobiles
  • 4.2. Environmental surveillance using self-powered sensors
  • 4.3. Self-powered sensors for robotics
  • 4.4. Self-powered sensor-based sports and healthcare applications
  • 4.5. Applications for human-machine interaction based on self-powered sensors
  • 4.6. Applications for wearable and mobile self-powered sensing systems
  • 4.7. Self-powered strain sensor
  • 4.8. Active humidity sensor
  • 4.9. Photovoltaic-based self-powered smartwatch
  • 4.10. Skin sensor
  • 4.11. Self-powered actuation system
  • 4.12. Self-powered robot
  • 4.13. Self-powered portable and wearable smart system
  • 4.14. Multifunctional electronic skin
  • 4.15. Machine learning-based self-powered sensor
  • 4.16. Triboelectricity-based self-powered touchpad
  • 4.17. Medium Gaussian support vector machine
  • 5. Summary
  • Further reading
  • Chapter 2: Wearable and Portable Self-Powered Sensor Systems based on Emerging Energy Harvesting Technology
  • 1. Introduction
  • 1.1. How is energy accumulated?
  • 1.2. How is the energy stored?
  • 1.3. What is the need and the market for energy harvesting?
  • 2. Types of energy harvesting platforms
  • 2.1. Wireless energy harvesting nodes
  • 2.1.1. Introduction
  • 2.1.2. RF energy harvesting working and applications
  • 2.1.3. How does an RF energy harvester work?
  • 2.1.3.1. Antenna.
  • 2.1.3.2. Impedance matching circuit
  • 2.1.3.3. Rectifier circuit and storage unit
  • 2.2. Photovoltaic energy harvesting nodes
  • 2.2.1. Introduction
  • 2.2.2. Proposed system
  • 2.3. Acoustic energy harvesting nodes
  • 2.3.1. Introduction
  • 2.3.2. Helmholtz resonance
  • 2.3.3. Acoustic metamaterials
  • 2.3.4. Thermoacoustic engines
  • 2.4. Mechanical energy harvesting nodes
  • 2.4.1. Introduction
  • 2.4.2. Physical principles
  • 2.4.2.1. Electrostatics harvesting mode
  • 2.4.2.2. Piezoelectric energy harvesting
  • 2.4.2.3. Electromagnetism energy harvesting
  • 2.5. Thermal energy harvesting nodes
  • 2.5.1. Can it save the world by solving the energy crisis?!
  • 2.5.2. Types of thermal energy harvesting
  • 2.5.2.1. Thermoelectric harvesting
  • 2.5.2.2. Pyroelectric harvesting
  • 2.5.3. Design and implementation considerations
  • 2.5.4. Potential applications of thermal energy harvesting
  • 2.6. Hybrid energy harvesting
  • 2.6.1. Introduction
  • 2.6.2. Existing system
  • 2.6.3. Working
  • 2.6.4. Disadvantages of energy harvesting
  • 3. Conclusion
  • References
  • Chapter 3: Augmented machine learning towards smart self-powered sensing systems
  • 1. Introduction
  • 2. Self-powered components and development
  • 3. Sensors and systems for machine learning
  • 3.1. ML in triboelectric systems and sensors
  • 3.2. Machine learning in piezoelectric systems and sensors
  • 3.3. Machine learning in pyroelectric sensor technology
  • 3.4. Machine learning in hybrid sensor technology
  • 4. A revolutionary approach to self-propelled sensors and systems that have the capability to learn
  • 4.1. Agriculture
  • 4.2. Healthcare
  • 4.3. Wearable electronics
  • 4.4. Communications
  • 4.5. IoT
  • 4.6. The emergence of bioinspired sensors
  • 5. Challenges and outlook
  • 6. Conclusion
  • References.
  • Chapter 4: Next-generation self-powered integrated sensing systems for the Industrial Internet of Things (IIoT) applica
  • 1. Introduction
  • 2. Industrial internet of things applications
  • 2.1. Industrial automation
  • 2.2. Smart robotics
  • 2.3. Predictive maintenance
  • 2.4. Integration of smart tools/wearables
  • 2.5. Smart logistics management
  • 2.6. Agriculture
  • 3. Challenges faced by IIoT
  • 3.1. Connectivity and visibility
  • 3.2. IIoT integration
  • 3.3. Security
  • 3.4. Data storage
  • 3.5. Analytics challenges
  • 4. Open issues
  • 4.1. Data integration [14]
  • 4.2. Data mining algorithms [16]
  • 4.3. Algorithms for collaborative knowledge discovery [17]
  • 4.4. Real-time algorithms [18]
  • 4.5. Design of trust-based privacy assured model [21]
  • 5. Related works
  • 6. Self-powered systems
  • 6.1. Self-powered wireless sensors in the Industrial Internet of Things
  • 6.2. Requirements for smart NDE4.0 sensor systems as elements of IIoT
  • 7. Conclusion
  • References
  • Chapter 5: Self-powered wearable implantable smart sensor and medical electronics based on nanogenerator
  • 1. Introduction
  • 2. Nanogenerator
  • 2.1. TENG theory
  • 3. Self-powered sensors
  • 3.1. TENG-based self-powered sensors in IoT
  • 3.2. TENG-based self-powered sensors in robotics field
  • 3.3. TENG-based self-powered sensors in field of human-machine interfaces
  • 4. Self-powered sensors for healthcare applications
  • 4.1. TENGs-based implantable self-powered sensors
  • 4.1.1. TENGs for monitoring the heart and breathing
  • 4.1.2. Blood pressure sensors using TENGs
  • 4.2. Wearable, self-powered sensors based on TENGs
  • 4.2.1. Smart shoes, a type of nanogenerator based on triboelectric
  • 4.2.2. Motion-sensing TENGs
  • 4.2.3. Nanogenerators for tactile sensors that are triboelectric
  • 4.2.4. Smart facial mask based on nanogenerators with triboelectric.
  • 4.2.5. Using TENGs to monitor sleep
  • 4.2.6. TENGs are used for nerve/muscle stimulation in self-powered systems
  • 5. Conclusion
  • References
  • Chapter 6: Intelligent vision sensors tracking and sensor fusion space-based surveillance and detection
  • 1. Introduction
  • 1.1. Sensor data fusion design
  • 2. Intelligent surveillance system (ISS) overview
  • 3. Sensor technology and sensor fusion overview
  • 4. Traditional sensor fusion approaches
  • 4.1. Object tracking
  • 4.2. Point tracking
  • 4.3. Kernel tracking
  • 4.4. Contour tracking
  • 5. Wide-area surveillance control techniques
  • 5.1. Multiple sensor control techniques
  • 5.2. Camera self-calibration
  • 5.2.1. Sensor installation
  • 5.3. Cooperative camera system
  • 5.4. Infrared and thermal camera
  • 5.5. Radar and LiDAR
  • 6. Conclusion
  • References
  • Chapter 7: Stretchable and flexible wearable sensors based on carbon and textile for health monitoring
  • 1. Introduction
  • 2. Carbon-based wearable sensors
  • 2.1. Fabrication technologies for carbon-based wearable sensors
  • 2.1.1. Pattern transferring process
  • 2.1.2. Spray coating and layer-by-layer assembly
  • 2.1.3. Screen printing process
  • 2.1.4. Drop casting and vacuum filtration processes
  • 2.2. Carbon-based sensors for wearable applications
  • 2.2.1. Graphene-based materials for activity sensors
  • 2.2.2. CNTs-based materials for activity sensors
  • 2.2.3. Carbon-based materials for electrophysiological sensors
  • 3. Textile-based wearable sensors
  • 3.1. Fabrication technology
  • 3.1.1. A simple coating processes: Dipping and drying
  • 3.1.2. Thread-type processes: knitting, weaving, and embroidering
  • 3.1.3. Printing process: Stamp-transfer, stencil, and screen printing
  • 3.2. Sensor devices for healthcare monitoring
  • 3.2.1. Activity sensors: Strain and pressure.
  • 3.2.2. Biophysiological sensors: ECG, EMG, EEG, sweat, and body temperature
  • 4. Challenging issues and future routes: Carbon- and textile-based wearable sensors
  • 5. Conclusions
  • References
  • Chapter 8: Wearable electrochemical and biosensors for forensic analysis: Challenges and research directions
  • 1. Introduction
  • 2. Sensor design and fabrication
  • 2.1. Miniaturisation of electrochemical and biosensors
  • 2.1.1. Sensor design and fabrication
  • 2.1.2. Miniaturised electrodes
  • 2.1.3. Miniaturised sensing elements
  • 2.1.4. Signal transduction and electronics
  • 2.1.5. Wireless communication and power supply
  • 2.2. Integration of multiple sensing modalities
  • 2.2.1. Sensor selection
  • 2.2.2. Sensor integration
  • 2.2.3. Electronics and signal processing
  • 2.2.4. Power management and communication
  • 2.2.5. Calibration and validation
  • 2.3. Flexible and stretchable sensor platforms
  • 2.3.1. Substrate materials
  • 2.3.2. Sensor integration
  • 2.3.3. Sensor design
  • 2.3.4. Encapsulation and protection
  • 2.3.5. Mechanical characterisation
  • 2.3.6. User-centric design
  • 3. Sensing techniques and detection methods
  • 3.1. Electrochemical detection techniques for forensic sample analysis
  • 3.1.1. Amperometry
  • 3.1.2. Potentiometry
  • 3.1.3. Voltammetry
  • 3.2. Biosensing techniques for specific analyte detection
  • 3.2.1. DNA-based biosensors
  • 3.3. SERS stands for surface-enhanced Raman spectroscopy
  • 3.3.1. Principle of SERS
  • 3.3.2. Application of SERS in forensic analysis
  • 3.3.2.1. Illicit drug analysis
  • 3.3.2.2. Explosive detection
  • 3.3.2.3. Counterfeit material analysis
  • 3.3.2.4. Trace evidence analysis
  • 3.3.2.5. Advantages and challenges
  • 4. Analyte detection and identification
  • 4.1. Detection of illicit drugs
  • 4.1.1. Chromatography-based methods
  • 4.1.2. Immunoassay methods
  • 4.1.3. Mass spectrometry.