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Table of Contents
Intro
Preface
Acknowledgments
Editor biography
G R Sinha
List of contributors
Chapter 1 Introduction to sensors
1.1 Introduction
1.2 Sensor characteristics
1.2.1 Transfer function
1.2.2 Full-scale input (FSI)
1.2.3 Full-scale output (FSO)
1.2.4 Accuracy
1.2.5 Calibration
1.2.6 Hysteresis
1.2.7 Non-linearity
1.2.8 Resolution
1.2.9 Saturation
1.2.10 Repeatability
1.2.11 Dead band
1.2.12 Reliability
1.2.13 Output characteristics
1.2.14 Impedance
1.2.15 Excitation
1.2.16 Dynamic characteristics
1.2.17 Precision
1.2.18 Environmental factors
1.2.19 Uncertainty
1.2.20 Application characteristics
1.3 Types of sensors
1.3.1 Temperature sensors
1.3.2 Position sensors
1.3.3 Light sensors
1.3.4 Sound sensor
1.3.5 Proximity sensor
1.3.6 Accelerometer
1.3.7 Infrared sensor
1.3.8 Pressure sensor
1.3.9 Ultrasonic sensors
1.3.10 Touch sensor
1.3.11 Humidity sensor
1.3.12 Colour sensor
1.3.13 Chemical sensor
1.3.14 Seismic sensor
1.3.15 Magnetic sensor
1.4 Comparison of different sensors
1.5 Modern sensors
1.6 Conclusions
References
Chapter 2 Classification and characteristics of sensors
2.1 Introduction
2.2 Classification
2.3 Commonly used sensors and their features
2.4 Transfer function
2.5 Characteristics of sensors
2.6 Sensors should meet the following basic requirements
2.7 Factors for choosing sensors
2.8 Conclusion
References
Chapter 3 Optical sensors: overview, characteristics and applications
3.1 Introduction
3.2 Optical sensors: fundamentals
3.2.1 Modes of operation
3.2.2 Light sources for optical sensors
3.2.3 Advantages of optical sensors
3.3 Optical sensing devices (detectors)
3.3.1 Photoemissive cells (photoemitters).
3.3.2 Photoresistor or light dependent resistors
3.3.3 Photodiodes
3.3.4 Phototransistor
3.3.5 Infrared sensors
3.3.6 Fiber optic sensor
References
Chapter 4 Recent applications of chalcogenide glasses (ChGs) based sensors
4.1 ChGs based sensors: a brief introduction
4.2 Fabrication and molding of ChGs in the form of different devices for sensing applications
4.2.1 Infrared optical fibers
4.2.2 Infrared optical lenses
4.2.3 Thin film membranes
4.3 Description of some principals behind the sensing applications
4.3.1 Attenuated total internal reflection
4.3.2 Fiber evanescent wave spectroscopy
4.3.3 Thermal imaging
4.4 Some exclusive examples of sensing applications of ChGs based sensors
4.4.1 Application in bio-sensing and food security
4.4.2 Early cancer diagnostics
4.4.3 Monitoring of pollutants in groundwater
4.4.4 Night vision systems for surveillance assignments
4.4.5 Monitoring of global warming
4.4.6 Other significant applications
4.5 Conclusions
References
Chapter 5 Advanced dynamic and static calibration methods for optical imaging sensors
5.1 Introduction
5.2 Principle of camera calibrations
5.2.1 Position determination principle using optical cameras
5.2.2 Camera calibration principle
5.2.3 Camera calibration model
5.2.4 Distortion model in camera calibration
5.3 Dynamic calibration approaches
5.3.1 The principle of the dynamic camera calibration
5.3.2 Calibration model used for the dynamic calibration
5.3.3 Dynamic calibration with multi-aperture MEMS light lead-in devices
5.4 Static calibration principle with mSOL
5.4.1 Static calibration general principle
5.4.2 Static calibration principle with DOEs
5.4.3 Calibration configurations with mSOL
5.4.4 Calibration theory.
5.4.5 The position extraction approach of the predefined target images
5.4.6 Applied examples
5.5 Discussion and future development directions
5.6 Conclusion
References
Chapter 6 Smart and wearable sensors used in numerous modern applications and their significance
6.1 Introduction
6.2 Smart sensors properties
6.2.1 Self-calibration
6.2.2 Reliability or self-health assessment
6.2.3 Self-healing
6.2.4 Compensated measurements
6.2.5 Self-adaptability: exchange accuracy for speed and vice versa
6.3 Smart sensors types
6.4 Smart sensor applications
6.4.1 Smart cities
6.4.2 Smart environment
6.4.3 Smart factories
6.5 Case study: smart home surveillance system using a smart camera
6.6 Wearable sensors
6.7 Applications of wearable sensors
6.7.1 Programmable bio-electric ASIC sensors
6.7.2 Diabetes wearable medical device
6.7.3 Cancer detecting wearable device
6.7.4 Wearable sweat-sensor
6.7.5 Wearable peritoneal dialysis device
6.7.6 Predicting the progress of Alzheimer's and dementia diseases
6.7.7 Monitoring Parkinson's disease
6.7.8 Vision-related biosensors
6.8 Conclusion
References
Chapter 7 Smart stick for the visually impaired
7.1 Introduction
7.2 Smart blind stick
7.3 Hardware description
7.3.1 Arduino UNO
7.3.2 Ultrasonic sensor
7.3.3 Water sensor
7.3.4 GPS module
7.3.5 LDR-light dependent resistor
7.3.6 Alarm unit
7.4 Results
7.4.1 Ultrasonic sensor
7.4.2 Detection of water by water sensor
7.4.3 Detection of light by using LDR
7.4.4 Location of the stick
7.5 Conclusion
References
Chapter 8 Smart and wearable sensors
8.1 Introduction
8.2 Features of smart sensors
8.3 Evaluation of smart sensors
8.3.1 Third-generation
8.3.2 Fourth-generation
8.3.3 Fifth-generation.
8.4 Design of a smart sensor
8.4.1 Data acquisition
8.4.2 Data transfer
8.4.3 Data processing
8.5 Consequences
8.5.1 Advantages of smart sensor
8.5.2 Disadvantages
8.6 General applications
8.7 Wearable sensors
8.7.1 Need for wearable sensors
8.7.2 Smart sensor as a wearable sensor
8.8 Wearable sensor devices
8.8.1 Wristwatches architecture and performance
8.8.2 Electronic T-Shirt architecture and working principle
8.8.3 BP monitoring using PPG
8.9 Conclusion
References
Chapter 9 Cognitive and biosensors: an overview
9.1 Introduction and background
9.2 Cognitive sensors
9.2.1 Research challenges
9.2.2 Application of cognitive sensors
9.2.3 Cognitive sensors and machine learning
9.2.4 Cognitive sensors and security threats
9.3 Biosensors
9.3.1 Research challenges
9.3.2 Application of biosensors
9.4 Conclusion
Acknowledgment
References
Chapter 10 Sensor technologies combined with AI helping in smart transport systems as driverless cars
10.1 History of driverless cars using smart sensors
10.2 Automation levels
10.3 Sensors and other technologies used by manufacturing companies
10.4 Design components
10.5 Sensor technology
10.5.1 GPS
10.5.2 LiDAR
10.5.3 Cameras
10.5.4 Radar sensors
10.5.5 Ultrasonic sensors
10.6 Challenges and future research
10.7 Conclusions
References
Chapter 11 Recent advancements in smart and wearable sensors
11.1 Introduction
11.1.1 Basics of SWSs
11.1.2 Working principle of a smart sensor
11.2 Types of wearable sensors
11.2.1 Optical sensors
11.2.2 Physical sensors
11.2.3 Chemical sensors
11.2.4 Multiplexed sensors
11.2.5 Wireless sensors
11.3 Challenges in wearable chemical sensors and possible solutions
11.3.1 Materials-based challenges with possible solution.
11.3.2 Operational challenges and possible solutions
11.4 Conclusion and future direction
References
Chapter 12 Design and implementation of a wearable gaze tracking device with near-infrared and visible-light image sensors
12.1 Introduction
12.2 Proposed wearable gaze tracking design
12.2.1 Near-infrared image sensor based wearable eye tracker design [13, 14]
12.2.2 Visible-light image sensor based wearable eye tracker design [17-19]
12.2.3 Calibration and gaze tracking function for wearable eye tracking device
12.3 Experimental results and comparisons
12.4 Conclusion and future works
Acknowledgments
References
Chapter 13 Vibration powered wireless sensor networks-harvesting energy from good vibrations
13.1 Introduction
13.2 literature survey
13.2.1 Piezoelectric sensors
13.2.2 Modeling and analysis of a bimorph piezoelectric cantilever beam for voltage generation
13.2.3 Feasibility of structural monitoring with vibration powered sensors
13.2.4 Vibration powered wireless sensor networks
13.3 Existing methodology
13.3.1 Proposed methodology
13.3.2 Comparison of proposed methodology with existing methodology
13.3.3 Advantages
13.3.4 Disadvantages
13.4 Conclusion
References
Chapter 14 Comprehensive review on brain-computer interface sensor-based smart home appliances control system
14.1 Introduction
14.1.1 Motivation and requirement
14.2 Background
14.2.1 Electroencephalography (EEG)
14.2.2 Brain waves
14.2.3 EEG artifacts
14.2.4 Control signal of BCI
14.3 Step involved in BCI-based controlling home appliances system
14.3.1 Data acquisition framework
14.3.2 Preprocessing and feature extraction
14.3.3 Classification results
14.4 Controlling methods based on single and multiple appliances
14.4.1 Single appliance control.
14.4.2 Multiple appliance control.
Preface
Acknowledgments
Editor biography
G R Sinha
List of contributors
Chapter 1 Introduction to sensors
1.1 Introduction
1.2 Sensor characteristics
1.2.1 Transfer function
1.2.2 Full-scale input (FSI)
1.2.3 Full-scale output (FSO)
1.2.4 Accuracy
1.2.5 Calibration
1.2.6 Hysteresis
1.2.7 Non-linearity
1.2.8 Resolution
1.2.9 Saturation
1.2.10 Repeatability
1.2.11 Dead band
1.2.12 Reliability
1.2.13 Output characteristics
1.2.14 Impedance
1.2.15 Excitation
1.2.16 Dynamic characteristics
1.2.17 Precision
1.2.18 Environmental factors
1.2.19 Uncertainty
1.2.20 Application characteristics
1.3 Types of sensors
1.3.1 Temperature sensors
1.3.2 Position sensors
1.3.3 Light sensors
1.3.4 Sound sensor
1.3.5 Proximity sensor
1.3.6 Accelerometer
1.3.7 Infrared sensor
1.3.8 Pressure sensor
1.3.9 Ultrasonic sensors
1.3.10 Touch sensor
1.3.11 Humidity sensor
1.3.12 Colour sensor
1.3.13 Chemical sensor
1.3.14 Seismic sensor
1.3.15 Magnetic sensor
1.4 Comparison of different sensors
1.5 Modern sensors
1.6 Conclusions
References
Chapter 2 Classification and characteristics of sensors
2.1 Introduction
2.2 Classification
2.3 Commonly used sensors and their features
2.4 Transfer function
2.5 Characteristics of sensors
2.6 Sensors should meet the following basic requirements
2.7 Factors for choosing sensors
2.8 Conclusion
References
Chapter 3 Optical sensors: overview, characteristics and applications
3.1 Introduction
3.2 Optical sensors: fundamentals
3.2.1 Modes of operation
3.2.2 Light sources for optical sensors
3.2.3 Advantages of optical sensors
3.3 Optical sensing devices (detectors)
3.3.1 Photoemissive cells (photoemitters).
3.3.2 Photoresistor or light dependent resistors
3.3.3 Photodiodes
3.3.4 Phototransistor
3.3.5 Infrared sensors
3.3.6 Fiber optic sensor
References
Chapter 4 Recent applications of chalcogenide glasses (ChGs) based sensors
4.1 ChGs based sensors: a brief introduction
4.2 Fabrication and molding of ChGs in the form of different devices for sensing applications
4.2.1 Infrared optical fibers
4.2.2 Infrared optical lenses
4.2.3 Thin film membranes
4.3 Description of some principals behind the sensing applications
4.3.1 Attenuated total internal reflection
4.3.2 Fiber evanescent wave spectroscopy
4.3.3 Thermal imaging
4.4 Some exclusive examples of sensing applications of ChGs based sensors
4.4.1 Application in bio-sensing and food security
4.4.2 Early cancer diagnostics
4.4.3 Monitoring of pollutants in groundwater
4.4.4 Night vision systems for surveillance assignments
4.4.5 Monitoring of global warming
4.4.6 Other significant applications
4.5 Conclusions
References
Chapter 5 Advanced dynamic and static calibration methods for optical imaging sensors
5.1 Introduction
5.2 Principle of camera calibrations
5.2.1 Position determination principle using optical cameras
5.2.2 Camera calibration principle
5.2.3 Camera calibration model
5.2.4 Distortion model in camera calibration
5.3 Dynamic calibration approaches
5.3.1 The principle of the dynamic camera calibration
5.3.2 Calibration model used for the dynamic calibration
5.3.3 Dynamic calibration with multi-aperture MEMS light lead-in devices
5.4 Static calibration principle with mSOL
5.4.1 Static calibration general principle
5.4.2 Static calibration principle with DOEs
5.4.3 Calibration configurations with mSOL
5.4.4 Calibration theory.
5.4.5 The position extraction approach of the predefined target images
5.4.6 Applied examples
5.5 Discussion and future development directions
5.6 Conclusion
References
Chapter 6 Smart and wearable sensors used in numerous modern applications and their significance
6.1 Introduction
6.2 Smart sensors properties
6.2.1 Self-calibration
6.2.2 Reliability or self-health assessment
6.2.3 Self-healing
6.2.4 Compensated measurements
6.2.5 Self-adaptability: exchange accuracy for speed and vice versa
6.3 Smart sensors types
6.4 Smart sensor applications
6.4.1 Smart cities
6.4.2 Smart environment
6.4.3 Smart factories
6.5 Case study: smart home surveillance system using a smart camera
6.6 Wearable sensors
6.7 Applications of wearable sensors
6.7.1 Programmable bio-electric ASIC sensors
6.7.2 Diabetes wearable medical device
6.7.3 Cancer detecting wearable device
6.7.4 Wearable sweat-sensor
6.7.5 Wearable peritoneal dialysis device
6.7.6 Predicting the progress of Alzheimer's and dementia diseases
6.7.7 Monitoring Parkinson's disease
6.7.8 Vision-related biosensors
6.8 Conclusion
References
Chapter 7 Smart stick for the visually impaired
7.1 Introduction
7.2 Smart blind stick
7.3 Hardware description
7.3.1 Arduino UNO
7.3.2 Ultrasonic sensor
7.3.3 Water sensor
7.3.4 GPS module
7.3.5 LDR-light dependent resistor
7.3.6 Alarm unit
7.4 Results
7.4.1 Ultrasonic sensor
7.4.2 Detection of water by water sensor
7.4.3 Detection of light by using LDR
7.4.4 Location of the stick
7.5 Conclusion
References
Chapter 8 Smart and wearable sensors
8.1 Introduction
8.2 Features of smart sensors
8.3 Evaluation of smart sensors
8.3.1 Third-generation
8.3.2 Fourth-generation
8.3.3 Fifth-generation.
8.4 Design of a smart sensor
8.4.1 Data acquisition
8.4.2 Data transfer
8.4.3 Data processing
8.5 Consequences
8.5.1 Advantages of smart sensor
8.5.2 Disadvantages
8.6 General applications
8.7 Wearable sensors
8.7.1 Need for wearable sensors
8.7.2 Smart sensor as a wearable sensor
8.8 Wearable sensor devices
8.8.1 Wristwatches architecture and performance
8.8.2 Electronic T-Shirt architecture and working principle
8.8.3 BP monitoring using PPG
8.9 Conclusion
References
Chapter 9 Cognitive and biosensors: an overview
9.1 Introduction and background
9.2 Cognitive sensors
9.2.1 Research challenges
9.2.2 Application of cognitive sensors
9.2.3 Cognitive sensors and machine learning
9.2.4 Cognitive sensors and security threats
9.3 Biosensors
9.3.1 Research challenges
9.3.2 Application of biosensors
9.4 Conclusion
Acknowledgment
References
Chapter 10 Sensor technologies combined with AI helping in smart transport systems as driverless cars
10.1 History of driverless cars using smart sensors
10.2 Automation levels
10.3 Sensors and other technologies used by manufacturing companies
10.4 Design components
10.5 Sensor technology
10.5.1 GPS
10.5.2 LiDAR
10.5.3 Cameras
10.5.4 Radar sensors
10.5.5 Ultrasonic sensors
10.6 Challenges and future research
10.7 Conclusions
References
Chapter 11 Recent advancements in smart and wearable sensors
11.1 Introduction
11.1.1 Basics of SWSs
11.1.2 Working principle of a smart sensor
11.2 Types of wearable sensors
11.2.1 Optical sensors
11.2.2 Physical sensors
11.2.3 Chemical sensors
11.2.4 Multiplexed sensors
11.2.5 Wireless sensors
11.3 Challenges in wearable chemical sensors and possible solutions
11.3.1 Materials-based challenges with possible solution.
11.3.2 Operational challenges and possible solutions
11.4 Conclusion and future direction
References
Chapter 12 Design and implementation of a wearable gaze tracking device with near-infrared and visible-light image sensors
12.1 Introduction
12.2 Proposed wearable gaze tracking design
12.2.1 Near-infrared image sensor based wearable eye tracker design [13, 14]
12.2.2 Visible-light image sensor based wearable eye tracker design [17-19]
12.2.3 Calibration and gaze tracking function for wearable eye tracking device
12.3 Experimental results and comparisons
12.4 Conclusion and future works
Acknowledgments
References
Chapter 13 Vibration powered wireless sensor networks-harvesting energy from good vibrations
13.1 Introduction
13.2 literature survey
13.2.1 Piezoelectric sensors
13.2.2 Modeling and analysis of a bimorph piezoelectric cantilever beam for voltage generation
13.2.3 Feasibility of structural monitoring with vibration powered sensors
13.2.4 Vibration powered wireless sensor networks
13.3 Existing methodology
13.3.1 Proposed methodology
13.3.2 Comparison of proposed methodology with existing methodology
13.3.3 Advantages
13.3.4 Disadvantages
13.4 Conclusion
References
Chapter 14 Comprehensive review on brain-computer interface sensor-based smart home appliances control system
14.1 Introduction
14.1.1 Motivation and requirement
14.2 Background
14.2.1 Electroencephalography (EEG)
14.2.2 Brain waves
14.2.3 EEG artifacts
14.2.4 Control signal of BCI
14.3 Step involved in BCI-based controlling home appliances system
14.3.1 Data acquisition framework
14.3.2 Preprocessing and feature extraction
14.3.3 Classification results
14.4 Controlling methods based on single and multiple appliances
14.4.1 Single appliance control.
14.4.2 Multiple appliance control.