Towards an autonomous vision-based unmanned aerial system againstwildlife poachers

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.Peer Reviewe

Towards an autonomous vision-based unmanned aerial system against wildlife poachers.

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges

In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions, and the inherent challenges that come with this relationship. The study examines how AI plays a role in enabling navigation, detecting and tracking objects, monitoring wildlife, enhancing precision agriculture, facilitating rescue operations, conducting surveillance activities, and establishing communication among UAVs using environmentally conscious computing techniques. By delving into the interaction between AI and UAVs, this analysis highlights the potential for these technologies to revolutionise industries such as agriculture, surveillance practices, disaster management strategies, and more. While envisioning possibilities, it also takes a look at ethical considerations, safety concerns, regulatory frameworks to be established, and the responsible deployment of AI-enhanced UAV systems. By consolidating insights from research endeavours in this field, this review provides an understanding of the evolving landscape of AI-powered UAVs while setting the stage for further exploration in this transformative domain

Monitoring dugongs within the Reef 2050 Integrated Monitoring and Reporting Program: final report of the dugong team in the megafauna expert group

The objectives of this report are to determine for the dugong: An assessment of the current status of the relevant elements of the Great Barrier Reef (the Reef), including an evaluation of primary drivers, pressures and responses using the Driving Forces, Pressures, States, Impacts, Responses (DPSIR) Framework; Identification of priority indicators for monitoring the key values associated with these elements; Summary of potential sources of data; Evaluation of adequacy of existing monitoring activities within each theme to achieve the objectives and requirements of RIMReP; Recommendations for the design of an integrated monitoring program as a component of RIMReP, specifically considering: The information requirements for each key element of the Reef to ensure that appropriate data and information are being collected to meet the fundamental objectives of RIMReP; The spatial and temporal sampling design to ensure that greatest value can be extracted from the data collected; The logistics of the design to ensure that it can be implemented efficiently; Likely funding required to implement the recommended monitoring design.An accessible copy of this report is not yet available from this repository, please contact [email protected] for more information

Drones for research on sea turtles and other marine vertebrates – A review

We review how unmanned aerial vehicles (UAVs), often referred to as drones, are being deployed to study the abundance and behaviour of sea turtles, identifying some of the commonalities and differences with studies on other marine vertebrates, including marine mammals and fish. UAV studies of all three groups primarily focus on obtaining estimates of abundance, distribution and density, while some studies have provided novel insights on the body condition, movement and behaviour of individuals (including inter-specific interactions). We discuss the emerging possibilities of how UAVs can become part of the standard methodologies for sea turtle ecologists through combining information on abundance and behaviour. For instance, UAV surveys can reveal turtle densities and hence operational sex ratios of sea turtles, which could be linked to levels of multiple paternity. Furthermore, embedding UAV surveys within a mark-recapture framework will enable improved abundance estimates. The complexity of behaviours revealed by direct observations of sea turtles and animal-borne cameras can also be examined using UAV footage, complementing studies using electronic tags, such as time-depth recorders and satellite transmitters. Overall, UAVs provide a low-cost approach of quantifying the flexibility of marine animal behaviour, allowing us to integrate information on abundance to establish how individuals respond to the presence of other organisms and the immediate environment

Autonomous surveillance for biosecurity

The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environmental costs. Conventional manual biosecurity surveillance methods are limited by their scalability in space and time. This article focuses on autonomous surveillance systems, comprising sensor networks, robots, and intelligent algorithms, and their applicability to biosecurity threats. We discuss the spatial and temporal attributes of autonomous surveillance technologies and map them to three broad categories of biosecurity threat: (i) vector-borne diseases; (ii) plant pests; and (iii) aquatic pests. Our discussion reveals a broad range of opportunities to serve biosecurity needs through autonomous surveillance.Comment: 26 pages, Trends in Biotechnology, 3 March 2015, ISSN 0167-7799, http://dx.doi.org/10.1016/j.tibtech.2015.01.003. (http://www.sciencedirect.com/science/article/pii/S0167779915000190