Algorithms for Detecting and Refining the Area of Intangible Continuous Objects for Mobile Wireless Sensor Networks

Shih-Chang Huang,Cong-Han Huang

doi:10.3390/a15020031

Abstract

Detecting the intangible continuous object (ICO) is a significant task, especially when the ICO is harmful as a toxic gas. Many studies used steady sensors to sketch the contour and find the area of the ICO. Applying the mobile sensors can further improve the precision of the detected ICO by efficiently adjusting the positions of a subset of the deployed sensors. This paper proposed two methods to figure out the area of the ICO, named Delaunay triangulation with moving sensors (MDT) and convex hull with moving sensors (MCH). First, the proposed methods divide the sensors into ICO-covered and ICO-uncovered sensors. Next, the convex hull algorithm and the Delaunay triangulation geometric architecture are applied to figure out the rough boundary of the ICO. Then, the area of the ICO is further refined by the proposed sensor moving algorithm. Simulation results show that the figured out area sizes of MDT and MCH are 135% and 102% of the actual ICO. The results are better than the planarization algorithms Gabriel Graph (GG) and Delaunay triangulation without moving sensors, that amount to 137% and 145% of the actual ICO. The simulation also evaluates the impact of the sensors’ moving step size to find the compromise between the accuracy of the area and the convergence time of area refinement.

Highlights

Wireless sensor networks help us remotely explore unknown fields or dangerous areas such as military areas, hazard environment sensing, and high-temperature industrial monitoring
This paper proposed two algorithms to detect the area of intangible continuous objects (ICO), with mobile sensors named Delaunay triangulation with moving sensors (MDT) and convex hull with moving sensors (MCH)
MDT and MCH classified sensors into ICO-covered ones and ICO-uncovered ones. They applied the Delaunay triangulation and the convex hull techniques on the steady sensors to estimate the rough area of the continuous object, respectively

Summary

Introduction

Wireless sensor networks help us remotely explore unknown fields or dangerous areas such as military areas, hazard environment sensing, and high-temperature industrial monitoring These tiny devices can monitor the information of their locations and deliver the collected data to the data center via the wireless communication technique. Numerous studies have focused on detecting the boundary area of the intangible continuous object Some of these studies organize the deployed sensors into multiple clusters [1,2]. The methods in these studies provide rough boundary results of the continuous object. Similar proposed studies trace the boundary of a mobile object by using grid architecture [3,4] These methods divided the deployed region into multiple grids. For refining the detected results, each grid is further divided into multiple smaller grids [4] to improve the detection precision

Methods

Results

Conclusion