CARNIVORE: A Disruption-Tolerant System for Studying Wildlife

Rutishauser, Matthew; Petkov, Vladislav; Williams, Terrie M.; Wilmers, Chris; Boice, Jay; Mantey, Patrick E.

doi:10.1109/icccn.2010.5560161

Cited by 11 publications

(8 citation statements)

References 16 publications

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“…We used custom-built collars [ 15 , 27 ] equipped with a tri-axial accelerometer sampling continuously at 64Hz to monitor behavior in captive and wild pumas. The tri-axial accelerometer was mounted such that the x-, y-, and z- axes were parallel to the anterior-posterior, the transverse, and the dorsal-ventral planes of the animal, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…We captured wild pumas (5 males, 7 females) from 2010-2012 using trailing hounds, cage traps, or leg hold snares as described in Wilmers et al [ 3 ]. Each animal was tranquilized using Telazol and outfitted with an off-the-shelf GPS/VHF collar (Vectronics Aerospace GPS PLUS model) combined with the custom-built archival 3-axis accelerometer tag [ 27 ], which was incorporated into the battery casing (total collar weight = 480 g) Data collected by the accelerometer were recorded in an onboard 8GB microSD card, which is capable of storing more than 200 days of accelerometer measurements.…”

Section: Methodsmentioning

confidence: 99%

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Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements

et al. 2015

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BackgroundAccelerometers are useful tools for biologists seeking to gain a deeper understanding of the daily behavior of cryptic species. We describe how we used GPS and tri-axial accelerometer (sampling at 64 Hz) collars to monitor behaviors of free-ranging pumas (Puma concolor), which are difficult or impossible to observe in the wild. We attached collars to twelve pumas in the Santa Cruz Mountains, CA from 2010-2012. By implementing Random Forest models, we classified behaviors in wild pumas based on training data from observations and measurements of captive puma behavior.ResultsWe applied these models to accelerometer data collected from wild pumas and identified mobile and non-mobile behaviors in captive animals with an accuracy rate greater than 96%. Accuracy remained above 95% even after downsampling our accelerometer data to 16 Hz. We were further able to predict low-acceleration movement behavior (e.g. walking) and high-acceleration movement behavior (e.g. running) with 93.8% and 92% accuracy, respectively. We had difficulty predicting non-movement behaviors such as feeding and grooming due to the small size of our training dataset. Lastly, we used model-predicted and field-verified predation events to quantify acceleration characteristics of puma attacks on large prey.ConclusionThese results demonstrate that accelerometers are useful tools for classifying the behaviors of cryptic medium and large-sized terrestrial mammals in their natural habitats and can help scientists gain deeper insight into their fine-scale behavioral patterns. We also show how accelerometer measurements can provide novel insights on the energetics and predation behavior of wild animals. Lastly we discuss the conservation implications of identifying these behavioral patterns in free-ranging species as natural and anthropogenic landscape features influence animal energy allocation and habitat use.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-015-0030-0) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements

et al. 2015

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“…For example, we found that the cattle testing failed to predict a failure mode encountered in the actual deployment, namely, losing a collar node. Carnivore [18] is a disruption-tolerant system deployed on mountain lions, in which nodes forward data to the node which has most recently accessed a sink. One collar of three was recovered, with no contacts reported.…”

Section: Related Workmentioning

confidence: 99%

WildSense: Monitoring Interactions among Wild Deer in Harsh Outdoor Environments Using a Delay-Tolerant WSN

et al. 2016

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Biologists and ecologists often monitor the spread of disease among deer in the wild by using tracking systems that record their movement patterns, locations, and interaction behavior. The existing commercial systems for monitoring wild deer utilize collars with GPS sensors, deployed on captured and rereleased deer. The GPS sensors record location data every few hours, enabling researchers to approximate the interaction behavior of tracked deer with their GPS locations. However, the coarse granularity of periodically recorded GPS location data provides only limited precision for determining deer interaction behavior. We have designed a novel system to monitor wild deer interaction behavior more precisely in harsh wilderness environments. Our system combines the functionalities of both GPS and RF-radio sensors with low-cost and minimal-resource motes. We designed and built our system to be able to operate robustly for a period of up to several months for continual tracking and monitoring of the locations and interaction behaviors of wild deer in harsh environments. We successfully deployed six deer collars on six wild deer that were captured and rereleased in the Soapstone Prairie Natural Area of northern Colorado over a one-month period. In this paper, we describe how we designed and built this system and evaluate its successful operation in a wilderness area.

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“…This system combines distributed sensing (each plant is equipped with a sensor node monitoring its status), navigation, manipulation and wireless networking. In [9] a disruption-tolerant system named CARNIVORE is developed for in-situ, unobtrusive monitoring of cryptic, difficult-tocatch/observe wildlife in their natural habitat. This system consists of a network of mobile and static nodes that have sensing, processing, storage, and wireless communication capabilities.…”

Section: A Distributed Cyber-physical Systemmentioning

confidence: 99%

RS-CPS: A distributed architecture of robotic surveillance cyber-physical system in the nature environment

Wang

Liu

Han

2015

2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

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Modern nature surveillance systems are highly automated and require distributed architectures in order to increase understanding of the environment by integrating data from various monitors and sensors, which are mounted not only on fixed stations, but also on robotic actuators. In this paper, we propose a distributed architecture of robotic surveillance cyber-physical system (RS-CPS) in the nature environment, which is designed as integration of computation and physical processes. The RS-CPS system consists of five levels including smart connection, datato-information conversion, cyber communication, cognition, and configuration. Based on this architecture, the nature risk such as wildfires, the activities of wild animals and the climate changes in plants can be constantly monitored by the cooperation of multiple agents such as autonomous UAVs, robotic pan-tilt-zoom cameras, forest infrared cameras, songbird acoustic recorders, GPS tracking collars and ecological factor sensors located in field. The experiments demonstrate the feasibility and effectiveness of the new architecture.

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CARNIVORE: A Disruption-Tolerant System for Studying Wildlife

Cited by 11 publications

References 16 publications

Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements

Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements

WildSense: Monitoring Interactions among Wild Deer in Harsh Outdoor Environments Using a Delay-Tolerant WSN

RS-CPS: A distributed architecture of robotic surveillance cyber-physical system in the nature environment

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