Evaluating flight coordination approaches of UAV squads for WSN data collection enhancing the internet range on WSN data collection

Bruno José Olivieri De Souza,Markus Endler

doi:10.1186/s13174-020-00125-4

Abstract

Wireless sensor networks (WSNs) are an important means of collecting data in a variety of situations, such as the monitoring of large or hazardous areas. The retrieval of WSN data can yield better results through the use of unmanned aerial vehicles (UAVs), for example, concerning the increase in the amount of data collected and the decrease in the time between the collection and use of the data. In particular, disaster areas may be left without communication resources and with high residual risk to humans, at which point a WSN can be quickly launched by air to collect relevant data until other measures can be established. The set of rules of each problem’s component (e.g., number of UAVs, UAVs dislocation control, sensors, communication) is considered the approaches to solve the problem. In this meaning, some studies present approaches for the use of UAVs for the collection of WSN data, focusing primarily on optimizing the path to be covered by a single UAV and relying on long-range communication that is always available; these studies do not explore the possibility of using several UAVs or the limitations on the range of communication. This work describes DADCA, a distributed scalable approach capable of coordinating groups of UAVs in WSN data collection with restricted communication range and without the use of optimization techniques. The results reveal that the amount of data collected by DADCA is similar or superior to path optimization approaches by up to 1%. In our proposed approach, the delay in receiving sensor messages is up to 46% shorter than in other approaches, and the required processing onboard UAVs can reach less than 75% of those using optimization-based algorithms. The results indicate that the DADCA can match and even surpass other presented approaches, since the path optimization is not a focus, while also incorporating the advantages of a distributed approach.

Highlights

This work extends and details a distributed approach for coordinating multiple unmanned aerial vehicles (UAVs) for collecting data from wireless sensor networks (WSNs)
Each UAV is controlled by Algorithm 2 and Algorithm 3, which we describe in the following paragraphs
7 Conclusions Typically, research on WSN data collection with UAVs focuses on the use of only a single UAV

Summary

Introduction

This work extends and details a distributed approach for coordinating multiple unmanned aerial vehicles (UAVs) for collecting data from wireless sensor networks (WSNs). Wireless sensor networks are deployed to collect environmental data for various applications (e.g., seismic monitoring, wildlife tracking, soil, air condition control, etc.). In scenarios in which no infrastructure or regions lack communication, the data collection from sensors of the WSN encounters serious difficulties [2]. The use of UAVs as such mobile agents can enhance the WSN data collection in areas that are difficult to reach due to hazardous conditions or communication limitations. In many applications, UAVs are well suited as mobile agents for collecting data from a WSN, increasing the network’s capacity and flexibility [4]

Objectives

Results

Conclusion