Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation


Autoria(s): Gonzalez, Luis F.; Montes, Glen; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.
Data(s)

14/02/2016

Resumo

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/93328/

Publicador

Molecular Diversity Preservation International (MDPI)

Relação

http://eprints.qut.edu.au/93328/1/sensors-16-00097.pdf

DOI:10.3390/s16010097

Gonzalez, Luis F., Montes, Glen, Puig, Eduard, Johnson, Sandra, Mengersen, Kerrie, & Gaston, Kevin J. (2016) Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors, 16(1), Article-97.

Direitos

Copyright 2016 the authors; licensee MDPI, Basel, Switzerland.

This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

Fonte

ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS); Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Institute for Future Environments; School of Mathematical Sciences; Science & Engineering Faculty

Palavras-Chave #010300 NUMERICAL AND COMPUTATIONAL MATHEMATICS #050100 ECOLOGICAL APPLICATIONS #090600 ELECTRICAL AND ELECTRONIC ENGINEERING #Unmanned Aerial Vehicles (UAVs) #Wildlife Monitoring and Conservation #Artificial Intelligence #target detection #computer vision #ecology #Koala #deer #Kangaroo
Tipo

Journal Article