Sports training monitoring of energy-saving IoT wearable devices based on energy harvesting

2021 ◽  
Vol 45 ◽  
pp. 101168
Author(s):  
Shuaishuai Wang
Keyword(s):  
Energy Harvesting ◽  
Energy Saving ◽  
Wearable Devices ◽  
Sports Training

Hybrid dual-function thermal energy harvesting & storage technologies: towards self-chargeable flexible/wearable devices

2021 ◽  
Author(s):  
Joana S Teixeira ◽  
Rui S Costa ◽  
Ana Pires ◽  
Andre M Pereira ◽  
Clara Pereira
Keyword(s):  
Climate Change ◽  
Energy Harvesting ◽  
Thermal Energy ◽  
Wearable Devices ◽  
Energy Sources ◽  
Dual Function ◽  
Global Awareness ◽  
Thermal Energy Harvesting ◽  
Mitigate Climate Change ◽  
Storage Technologies

The worldwide energy scarcity arising from the massive consumption of nonrenewable energy sources raised a global awareness on the need for cleaner and affordable energy solutions to mitigate climate change...

A Self-Powered Wireless Health and Environment Monitoring System

2008 ◽  
Author(s):  
Ajay Singh ◽  
Vincent Koomson ◽  
Jaewook Yu ◽  
Goldie Nejat
Keyword(s):  
Energy Harvesting ◽  
Health Monitoring ◽  
Sensory System ◽  
Vital Signs ◽  
Wearable Devices ◽  
Processing Unit ◽  
Wireless Health ◽  
Self Powered ◽  
Remote Health ◽  
Piezoelectric Vibration

The objective of our work is to develop a novel self-powered multi-modal wireless health monitoring sensory system architecture consisting of: (i) wearable devices to continuously monitor the vital signs of a person, and (ii) environmental sensory devices which can monitor the environment and also act as multi-hop routers providing data paths from the wearable devices to a main processing unit. Together these devices can provide effective remote health monitoring of a person and also inform the person of important information. In this paper, we address the significant issue of energy depletion for the devices, which can lead to critical interruptions in monitoring, by proposing a flexible unique vibration-based energy harvesting scheme to support our architecture. This active energy harvesting scheme will allow for continuous remote monitoring of the person and his/her environment in various situations. Experimental results demonstrate the potential utilization of electromagnetic and piezoelectric vibration-based harvesting techniques for the proposed application.

Functional Materials for Wearable Sensing, Actuating and Energy Harvesting

2008 ◽  
Vol 57 ◽  
pp. 247-256 ◽  
Author(s):  
Danilo De Rossi ◽  
Federico Carpi ◽  
Fabia Galantini
Keyword(s):  
Energy Harvesting ◽  
Functional Materials ◽  
Wearable Devices ◽  
Electroactive Polymer ◽  
Electronic Textiles ◽  
Research Groups ◽  
Power Sources ◽  
Wearable Sensing ◽  
Potential Applicability ◽  
Biomedical Field

This paper describes the early conception and latest developments of electroactive polymer (EAP)- based sensors, actuators and power sources, implemented as wearable devices for smart electronic textiles (e-textiles). Such textiles, functioning as multifunctional wearable human interfaces, are today considered relevant promoters of progress and useful tools in several biomedical field, such as biomonitoring, rehabilitation and telemedicine. This paper presents the more performing EAPbased devices developed by our lab and other research groups for sensing, actuating and energy harvesting, with reference to their already demonstrated or potential applicability to electronic textiles.

scholarly journals Efficient and Energy-Saving Computation Offloading Mechanism with Energy Harvesting for IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yawen Zhang ◽  
Yifeng Miao ◽  
Shujia Pan ◽  
Siguang Chen
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Convergence Rate ◽  
Energy Saving ◽  
Gradient Descent ◽  
Optimization Problem ◽  
Computation Offloading ◽  
Total Energy Consumption ◽  
Task Processing

In order to effectively extend the lifetime of Internet of Things (IoT) devices, improve the energy efficiency of task processing, and build a self-sustaining and green edge computing system, this paper proposes an efficient and energy-saving computation offloading mechanism with energy harvesting for IoT. Specifically, based on the comprehensive consideration of local computing resource, time allocation ratio of energy harvesting, and offloading decision, an optimization problem that minimizes the total energy consumption of all user devices is formulated. In order to solve such optimization problem, a deep learning-based efficient and energy-saving offloading decision and resource allocation algorithm is proposed. The design of deep neural network architecture incorporating regularization method and the employment of the stochastic gradient descent method can accelerate the convergence rate of the developed algorithm and improve its generalization performance. Furthermore, it can minimize the total energy consumption of task processing by integrating the momentum gradient descent to solve the resource optimization allocation problem. Finally, the simulation results show that the mechanism proposed in this paper has significant advantage in convergence rate and can achieve an optimal offloading and resource allocation strategy that is close to the solution of greedy algorithm.

HARKE: Human Activity Recognition from Kinetic Energy Harvesting Data in Wearable Devices

2018 ◽  
Vol 17 (6) ◽  
pp. 1353-1368 ◽  
Author(s):  
Sara Khalifa ◽  
Guohao Lan ◽  
Mahbub Hassan ◽  
Aruna Seneviratne ◽  
Sajal K. Das
Keyword(s):  
Energy Harvesting ◽  
Kinetic Energy ◽  
Activity Recognition ◽  
Human Activity ◽  
Wearable Devices ◽  
Human Activity Recognition
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