Assessment of Working Dog Suitability from Quantimetric Data

Copyright © ACMWe propose new approaches to assessing the suitability of potential working dogs for a given occupation. The main focus is placed on continuously-recording technology that does not rely on constant human observation. An example is provided in the form of a pilot study relying on activity and human-proximity data collected from dogs both prior to and during advanced training at Canine Companions for Independence. We conclude by noting other technologies that could also be used to achieve this purpose

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Analysis of dogs’ sleep patterns using convolutional neural networks

Video-based analysis is one of the most important tools of animal behavior and animal welfare scientists. While automatic analysis systems exist for many species, this problem has not yet been adequately addressed for one of the most studied species in animal science—dogs. In this paper we describe a system developed for analyzing sleeping patterns of kenneled dogs, which may serve as indicator of their welfare. The system combines convolutional neural networks with classical data processing methods, and works with very low quality video from cameras installed in dogs shelters

The use of wearable sensors for animal behaviour assessment

PhD ThesisThe research outlined in this thesis presents novel applications of wearable sensors in the domain of animal behaviour assessment. The use of wearable sensing technology, and in particular accelerometry, has become a mainstay of behaviour assessment in humans, allowing for detailed analysis of movement based behaviour and health monitoring. In this thesis we look to apply these methodologies to animals and identify approaches towards monitoring their health and wellbeing. We investigate the use of the technology in the animal domain through a series of studies examining the problem across multiple species and in increasingly complex scenarios. A tightly constrained scenario is presented initially, in which horse behaviour was classi ed and assessed in the context of dressage performances. The assessment of lying behaviour in periparturient sows con ned to gestation crates examines a scenario in which the movement of the subject was constrained, but not predetermined. Expanding this work to include sows housed in free-farrowing environments removed the movement constraints imposed by the gestation crates. We examine the implications of the use of multiple sensors and how this might a ect the accuracy of the assessments. Finally, a system for behaviour recognition and assessment was developed for domestic cats. Study animals were free to move and behave at their own discretion whilst being monitored through the use of wearable sensors, in the least constrained of the studies. The scenarios outlined herein describe applications with an increasing level of complexity through the removal of constraints. Through this work we demonstrate that these techniques are applicable across species and hold value for the wellbeing of both commercial and companion animals.European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement number 613574 (PROHEALTH). This project has also received funding from the Biotechnology and Biological Sciences Research Council (BBSRC) in the form of a studentshi