Energy per Operation Optimization for Energy-Harvesting Wearable IoT Devices.

Jaehyun Park,Cemil S Geyik,Hyung Gyu Lee,Anish Nk,Umit Y Ogras,Ganapati Bhat

doi:10.3390/s20030764

Abstract

Wearable internet of things (IoT) devices can enable a variety of biomedical applications, such as gesture recognition, health monitoring, and human activity tracking. Size and weight constraints limit the battery capacity, which leads to frequent charging requirements and user dissatisfaction. Minimizing the energy consumption not only alleviates this problem, but also paves the way for self-powered devices that operate on harvested energy. This paper considers an energy-optimal gesture recognition application that runs on energy-harvesting devices. We first formulate an optimization problem for maximizing the number of recognized gestures when energy budget and accuracy constraints are given. Next, we derive an analytical energy model from the power consumption measurements using a wearable IoT device prototype. Then, we prove that maximizing the number of recognized gestures is equivalent to minimizing the duration of gesture recognition. Finally, we utilize this result to construct an optimization technique that maximizes the number of gestures recognized under the energy budget constraints while satisfying the recognition accuracy requirements. Our extensive evaluations demonstrate that the proposed analytical model is valid for wearable IoT applications, and the optimization approach increases the number of recognized gestures by up to 2.4× compared to a manual optimization.

Highlights

Designing small form factor wearable devices without degrading user experience can enable pervasive biomedical applications such as gesture-based control, health monitoring, and activity tracking [1,2,3,4]
The detailed energy characterization presented in this paper enabled us to develop a novel compact energy model that can be used at runtime by energy-optimization algorithms
Our goal is to achieve 90% or higher accuracy on a small wearable internet of things (IoT) device

Summary

Introduction

Designing small form factor wearable devices without degrading user experience can enable pervasive biomedical applications such as gesture-based control, health monitoring, and activity tracking [1,2,3,4]. Lighter flexible batteries have advantages in size and weight, but their capacities (200 mAh @ 1.2 g) [5] are not enough for the seamless operation of wearable devices. Maximizing the utilization (i.e., useful work) under a tight energy budget is key to the success of wearable IoT devices [6]. Harvesting energy from ambient sources is an attractive way to alleviate the battery problem [7], especially for wearable IoT devices. Among various energy-harvesting resources, it is known that photovoltaic cells (PV-cells) generate 10–100 mW/cm2 [8,9], which can operate the wearable device even without a battery. Researchers have recently studied other ambient energy sources, most

Objectives

Methods

Results

Conclusion