Deployment Optimization for Meta-material Based Internet of Things

TL;DR

This paper introduces a Meta-IoT system utilizing meta-material sensors for energy-efficient, pervasive 3D environmental sensing, and proposes an optimization algorithm for device placement to enhance sensing accuracy.

Contribution

It presents a novel Meta-IoT system with a mathematical model and an optimization algorithm for device placement to improve 3D environmental sensing accuracy.

Findings

High accuracy in 3D environmental distribution reconstruction

Effective interference minimization through position optimization

Validated by simulation results

Abstract

In this paper, we propose a Meta-IoT system to achieve ubiquitous deployment and pervasive sensing for future Internet of Things (IoT). In such a system, sensors are composed of dedicated meta-materials whose frequency response of wireless signal is sensitive to environmental conditions. Therefore, we can obtain sensing results from reflected signals through Meta-IoT devices and the energy supplies for IoT devices can be removed. Nevertheless, in the Meta-IoT system, because the positions of the Meta-IoT devices decide the interference among the reflected signals, which may make the sensing results of different positions hard to be distinguished and the estimation function should integrate the results to reconstruct 3D distribution. It is a challenge to optimize the positions of the Meta-IoT devices to ensure sensing accuracy of 3D environmental conditions. To handle this challenge, we establish a mathematical model of Meta-IoT devices' sensing and transmission to calculate the interference between Meta-IoT devices. Then, an algorithm is proposed to jointly minimize the interference and reconstruction error by optimizing the Meta-IoT devices' position and the estimation function. The simulation results verify that the proposed system can obtain a 3D environmental conditions' distribution with high accuracy.