Self-Powered Internet of Things: How Energy Harvesters Can Enable Energy-Positive Sensing, Processing, and Communication

Foreword by Sajal K. Das
Foreword by Mahbub Hassan
Preface
Contents
About the Authors
Acronyms
Part I Overview of IoT and Activity Recognition
1 Introduction
	1.1 Types of IoT Devices for HAR
		1.1.1 Implantable
		1.1.2 Wearable
		1.1.3 Environmental
	1.2 Energy Challenges in the use of IoT for HAR
	1.3 Motivation
	1.4 Book Organisation
	References
2 Activity Recognition in IoT
	2.1 Activity Recognition Mechanisms
	2.2 Wearable Sensors for HAR
	2.3 Activity Recognition Using Machine Learning
		2.3.1 Data Acquisition and Preprocessing
		2.3.2 Segmentation
		2.3.3 Feature Extraction
		2.3.4 Model Training (Learning)
		2.3.5 Model Testing
		2.3.6 Evaluation Metrics
	2.4 Datasets for Developing and Evaluating HAR Algorithms
	2.5 Challenges in Current Activity Recognition Mechanisms
	References
Part II Energy Harvesting
3 Using Ambient Energy to Power IoT Sensors
	3.1 Energy Harvesting Modes
	3.2 Solar
	3.3 Kinetic
	3.4 Thermal
	3.5 RF Waves
	3.6 Kinetic Energy Harvesting
	3.7 Kinetic Energy Harvesting Circuits
	3.8 Operation of keh Transducer at MPP
		3.8.1 mpp of the keh Transducer
		3.8.2 Harvested Power Stored in the Capacitor
		3.8.3 Impact of Threshold Voltage of DC-DC Converterpg  on the Harvested Power
		3.8.4 Power Consumption of DC-DC Converter
	3.9 Solar Energy Harvesting
	3.10 Solar Energy Harvesting Circuits
	3.11 Operation of seh Transducer at MPP
	3.12 Discussion
	References
4 Energy Harvester as an Information Source
	4.1 KEH as a Sensor
		4.1.1 Step Count
		4.1.2 Audio Signal Detection
		4.1.3 Activity Recognition
		4.1.4 Transport Mode Detection
		4.1.5 Other Applications
	4.2 SEH as a Sensor
	4.3 TEH as a Sensor
	4.4 RFEH as a Sensor
	4.5 Discussion
	References
Part III Self-Powered IoT
5 Simultaneous Sensing and Energy Harvesting
	5.1 Challenges in Simultaneous Sensing and Energy Harvesting
	5.2 System Architecture for Simultaneous Sensingpg  and Energy Harvesting
		5.2.1 Sensing and Energy Harvesting
		5.2.2 Energy-Positive Sensing
		5.2.3 Exploring Multiple Sensing Points
	5.3 System Design for Simultaneous Sensing and Energy Harvesting
		5.3.1 Hardware Designs for keh Sensing and Energy Harvesting
		5.3.2 Experimental Setup
		5.3.3 The Interference Problem at Different Sensing Points
	5.4 Transport Mode Detection: A Case Study
		5.4.1 Data Collection
		5.4.2 System Model
	5.5 Performance Evaluation
		5.5.1 Detection Accuracy of keh-Based Sensing Signals
		5.5.2 Energy Harvesting
		5.5.3 Energy Consumption and System Costs
		5.5.4 Energy-Positive Sensing: Discussion and Analysis
	5.6 Discussion
	References
6 Solar Cell Based Activity Recognition
	6.1 Background
		6.1.1 Previous har Mechanisms
	6.2 Human Activity Recognition Using Solar Cell
	6.3 SolAR: System Model and Implementation
		6.3.1 Measurement Setup
		6.3.2 Solar Cell as a Novel Human Activity Sensor
		6.3.3 Implementation of SolAR
	6.4 Performance Evaluation
		6.4.1 Classification Accuracy
		6.4.2 Variability Analysis of Human Activities
		6.4.3 Varying Window Sizes
		6.4.4 Varying Signal Sampling Frequency
		6.4.5 Robustness to User Variance
		6.4.6 Environment-Agnostic Analysis
	6.5 Energy-Positive HAR
		6.5.1 SolAR Harvested Power
		6.5.2 SolAR Power Consumption
		6.5.3 Energy-Positive har
	6.6 Discussion
	References
7 Fusion-Based Activity Recognition
	7.1 Background
		7.1.1 Accelerometer-Based har
		7.1.2 keh-Based har
		7.1.3 seh-Based har
		7.1.4 Limitations and Challenges
	7.2 Fusing Solar and Kinetic Energy Signals
		7.2.1 Architecture
		7.2.2 Measurement Setup
		7.2.3 Human Activity Recognition
	7.3 Performance Evaluation
		7.3.1 Classification Accuracy
		7.3.2 Varying Window Sizes
		7.3.3 Varying Sampling Frequency of the Signal
		7.3.4 Robustness to User Variance
		7.3.5 Robustness to Diverse Lighting Conditions
		7.3.6 Robustness to Environment-Agnostic and Environment-Preserving Scenarios
	7.4 Analysis of Harvested and Consumed Power
		7.4.1 Harvested Power
		7.4.2 Power Consumption
		7.4.3 Energy-Positive har
	7.5 Discussion
	References
8 Energy-Positive Activity Recognition: Future Directions
	8.1 Energy-Efficient Communication Using Energy Harvesters
	8.2 Deep Learning
	8.3 Federated Learning
	8.4 Personalised AI Models
	8.5 Real-Time Activity Recognition
	8.6 Multi-source Energy Harvesters
	8.7 Hardware Implementation on the Edge Device
	8.8 Batteryless Operation
	8.9 Security and Privacy
	8.10 Reducing the System Cost
	8.11 Exploring Other Applications
	References
Author Index
Appendix  Subject Index
Index