Exploiting Radio Frequency Characteristics With a Support Unmanned Aerial Vehicle to Improve Wireless Sensor Location Estimation Accuracy

A lot of the devices in the Internet of Things are sensors responsible for capturing environmental information and relaying it to a system or network. Oftentimes, it is important to know the location of these sensors to better contextualize the information received from them. However, the sensors are purposely simple and cheap, meaning that conventional localization techniques, such as global navigation satellite systems are not feasible. Research has been done on using unmanned aerial vehicles to estimate the location of the sensors, but issues with signal strength fluctuation and location approximation because of it are still prevalent. In this work, we propose a new method for estimating the location of sensors by exploiting the characteristics of radio wave signal propagation and creating a new flight path design, a solution to minimize the impact of variation in measurements, a novel candidate point generation through signal strength analysis, and a method to find the location based on the candidates. Through a thought-out experiment, we show that the proposed algorithm is overall significantly better than the existing solution when it comes to identifying the location of outdoor sensors.

I. Introduction

With the spread of the Internet of Things (IoT), wireless sensor network (WSN) technology, which collects information using sensors with wireless network functions, is being used in various applications, such as environment monitoring, disaster response, and human tracking [1], [2]. In these environments, accurate sensor location information is required [3]. However, in environmental and disaster monitoring, such as when monitoring forests, large-scale farms, disaster areas, battlefields, etc., sensors are randomly scattered from the sky using airplanes, helicopters, or unmanned aerial vehicles (UAVs) [4]. Fig. 1 illustrates how a WSN can be constructed by distributing sensors using an UAV. In these cases, it would be difficult for operators to physically go to the site and check the location of each sensor [5]. Moreover, in large-scale WSNs, using the global navigation satellite system (GNSS) function in a large number of sensors is impractical from the standpoint of power consumption and cost [6], [7], [8]. As a result, it is difficult to obtain accurate location information for each sensor. Fig. 1.

How UAVs can be used to deploy and manage WSNs.