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Abstract Drones have become invaluable tools for studying animal behaviour in the wild, enabling researchers to collect aerial video data of group‐living animals. However, manually piloting drones to track animal groups consistently is challenging due to complex factors such as terrain, vegetation, group spread and movement patterns. The variability in manual piloting can result in unusable data for downstream behavioural analysis, making it difficult to collect standardized datasets for studying collective animal behaviour.To address these challenges, we present WildWing, a complete hardware and software open‐source unmanned aerial system (UAS) for autonomously collecting behavioural video data of group‐living animals. The system's main goal is to automate and standardize the collection of high‐quality aerial footage suitable for computer vision‐based behaviour analysis. We provide a novel navigation policy to autonomously track animal groups while maintaining optimal camera angles and distances for behavioural analysis, reducing the inconsistencies inherent in manual piloting.The complete WildWing system costs only $650 and incorporates drone hardware with custom software that integrates ecological knowledge into autonomous navigation decisions. The system produces 4 K resolution video at 30 fps while automatically maintaining appropriate distances and angles for behaviour analysis. We validate the system through field deployments tracking groups of Grevy's zebras, giraffes and Przewalski's horses at The Wilds conservation centre, demonstrating its ability to collect usable behavioural data consistently.By automating the data collection process, WildWing helps ensure consistent, high‐quality video data suitable for computer vision analysis of animal behaviour. This standardization is crucial for developing robust automated behaviour recognition systems to help researchers study and monitor wildlife populations at scale. The open‐source nature of WildWing makes autonomous behavioural data collection more accessible to researchers, enabling wider application of drone‐based behavioural monitoring in conservation and ecological research.
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Monitoring Bivalve Behavior and Physiology in the Laboratory and Field Using Open-Source Tools
Abstract Bivalve molluscs have been the focus of behavioral and physiological studies for over a century, due in part to the relative ease with which their traits can be observed. The author reviews historical methods for monitoring behavior and physiology in bivalves, and how modern methods with electronic sensors can allow for a number of parameters to be measured in a variety of conditions using low-cost components and open-source tools. Open-source hardware and software tools can allow researchers to design and build custom monitoring systems to sample organismal processes and the environment, systems that can be tailored to the particular needs of a research program. The ability to leverage shared hardware and software can streamline the development process, providing greater flexibility to researchers looking to expand the number of traits they can measure, the frequency and duration of sampling, and the number of replicate devices they can afford to deploy.
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- Award ID(s):
- 1904185
- PAR ID:
- 10377661
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Integrative and Comparative Biology
- Volume:
- 62
- Issue:
- 4
- ISSN:
- 1540-7063
- Page Range / eLocation ID:
- p. 1096-1110
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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