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Animals
Special Issues
Animal–Computer Interaction: New Horizons in Animal Welfare
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Animal–Computer Interaction: New Horizons in Animal Welfare

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Welfare".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 7823

Special Issue Editors

Prof. Dr. Clara Mancini

E-Mail Website
Guest Editor
Animal–Computer Interaction (ACI) Laboratory, School of Computing and Communications, STEM Faculty, The Open University, Milton Keynes MK7 6AA, UK
Interests: animal–computer interaction; multispecies interaction design; animal-centered computing; animal-centered design; biosemiotics
Special Issues, Collections and Topics in MDPI journals
Dr. Jake Veasey

E-Mail Website
Guest Editor
Care for the Rare, School of Animal, Rural and Environmental Sciences, Nottingham Trent University, Southwell, Nottingham, UK
Interests: behavioural ecology; animal welfare; animal conservation; animal welfare-centered habitat design; zoos
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Improving animal welfare through animal-centered technologies, designed from the perspective and for the benefit of animals, is a fundamental aim for the field of animal–computer interaction (ACI). Particularly with the rise of technologies such as artificial intelligence and the internet of things, technological interventions have the potential to radically transform welfare provisioning by:

  • monitoring and processing objectively behavioural and physiological data to improve our understanding of the immediate and long-term psychological and physical needs of animals;
  • providing dynamic settings and opportunities for animals to fulfill their species-specific behavioral and cognitive needs, as well as biologically appropriate levels of control over their environment and activities.

For this Special Issue, we invite contributions that exemplify how an animal-centered perspective on the design of computing technologies may inform novel approaches for improving the welfare of animals in different contexts, whether in managed or wild settings. We also invite contributions that discuss what limitations such approaches might suffer from, what risks they might pose and how these might be addressed. We particularly welcome transdisciplinary contributions among researchers and practitioners with expertise in interaction design, ergonomics, software engineering, artificial intelligence, ubiquitous computing, animal cognition, behavior, welfare and management and other relevant fields.

Prof. Dr. Clara Mancini
Dr. Jake Veasey
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • animal–computer interaction
  • interaction design
  • animal-centered research
  • animal-centered design
  • animal-centered computing
  • animal-centered technology
  • animal welfare
  • animal behavior
  • animal cognition
  • animal management
  • animal welfare approaches
  • animal ethics

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

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Research

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28 pages, 10772 KiB  
Article
PBC-Transformer: Interpreting Poultry Behavior Classification Using Image Caption Generation Techniques
by Jun Li, Bing Yang, Jiaxin Liu, Felix Kwame Amevor, Yating Guo, Yuheng Zhou, Qinwen Deng and Xiaoling Zhao
Animals 2025, 15(11), 1546; https://doi.org/10.3390/ani15111546 - 25 May 2025
Viewed by 285
Abstract
Accurate classification of poultry behavior is critical for assessing welfare and health, yet most existing methods predict behavior categories without providing explanations for the image content. This study introduces the PBC-Transformer model, a novel model that integrates image captioning techniques to enhance poultry [...] Read more.
Accurate classification of poultry behavior is critical for assessing welfare and health, yet most existing methods predict behavior categories without providing explanations for the image content. This study introduces the PBC-Transformer model, a novel model that integrates image captioning techniques to enhance poultry behavior classification, mimicking expert assessment processes. The model employs a multi-head concentrated attention mechanism, Head Spatial Position Coding (HSPC), to enhance spatial information; a learnable sparse mechanism (LSM) and RNorm function to reduce noise and strengthen feature correlation; and a depth-wise separable convolutional network for improved local feature extraction. Furthermore, a multi-level attention differentiator dynamically selects image regions for precise behavior descriptions. To balance caption generation with classification, we introduce the ICL-Loss function, which adaptively adjusts loss weights. Extensive experiments on the PBC-CapLabels dataset demonstrate that PBC-Transformer outperforms 13 commonly used classification models, improving accuracy by 15% and achieving the highest scores across image captioning metrics: Bleu4 (0.498), RougeL (0.794), Meteor (0.393), and Spice (0.613). Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
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15 pages, 246 KiB  
Article
Animal Welfare, Agency, and Animal–Computer Interaction
by Heather Browning and Walter Veit
Animals 2025, 15(2), 219; https://doi.org/10.3390/ani15020219 - 15 Jan 2025
Viewed by 2324
Abstract
Recent discussions in animal welfare have emphasised the importance of animal agency—the ability of animals to make choices and exert control over their environment in a way that aligns with their needs and preferences. In this paper, we discuss the importance of animal [...] Read more.
Recent discussions in animal welfare have emphasised the importance of animal agency—the ability of animals to make choices and exert control over their environment in a way that aligns with their needs and preferences. In this paper, we discuss the importance of animal agency for welfare and examine how use of some types of animal–computer interaction can enable animals to exercise more agency in captive environments through increased choice and control, cognitive challenge, and social interactions; as well as considering some of the potential limitations of such efforts. Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
36 pages, 3858 KiB  
Article
Exploring the Dynamics of Canine-Assisted Interactions: A Wearable Approach to Understanding Interspecies Well-Being
by Timothy R. N. Holder, Colt Nichols, Emily Summers, David L. Roberts and Alper Bozkurt
Animals 2024, 14(24), 3628; https://doi.org/10.3390/ani14243628 - 16 Dec 2024
Cited by 1 | Viewed by 1548
Abstract
Canine-assisted interactions (CAIs) have been explored to offer therapeutic benefits to human participants in various contexts, from addressing cancer-related fatigue to treating post-traumatic stress disorder. Despite their widespread adoption, there are still unresolved questions regarding the outcomes for both humans and animals involved [...] Read more.
Canine-assisted interactions (CAIs) have been explored to offer therapeutic benefits to human participants in various contexts, from addressing cancer-related fatigue to treating post-traumatic stress disorder. Despite their widespread adoption, there are still unresolved questions regarding the outcomes for both humans and animals involved in these interactions. Previous attempts to address these questions have suffered from core methodological weaknesses, especially due to absence of tools for an efficient objective evaluation and lack of focus on the canine perspective. In this article, we present a first-of-its-kind system and study to collect simultaneous and continuous physiological data from both of the CAI interactants. Motivated by our extensive field reviews and stakeholder feedback, this comprehensive wearable system is composed of custom-designed and commercially available sensor devices. We performed a repeated-measures pilot study, to combine data collected via this system with a novel dyadic behavioral coding method and short- and long-term surveys. We evaluated these multimodal data streams independently, and we further correlated the psychological, physiological, and behavioral metrics to better elucidate the outcomes and dynamics of CAIs. Confirming previous field results, human electrodermal activity is the measure most strongly distinguished between the dyads’ non-interaction and interaction periods. Valence, arousal, and the positive affect of the human participant significantly increased during interaction with the canine participant. Also, we observed in our pilot study that (a) the canine heart rate was more dynamic than the human’s during interactions, (b) the surveys proved to be the best indicator of the subjects’ affective state, and (c) the behavior coding approaches best tracked the bond quality between the interacting dyads. Notably, we found that most of the interaction sessions were characterized by extended neutral periods with some positive and negative peaks, where the bonded pairs might display decreased behavioral synchrony. We also present three new representations of the internal and overall dynamics of CAIs for adoption by the broader field. Lastly, this paper discusses ongoing options for further dyadic analysis, interspecies emotion prediction, integration of contextually relevant environmental data, and standardization of human–animal interaction equipment and analytical approaches. Altogether, this work takes a significant step forward on a promising path to our better understanding of how CAIs improve well-being and how interspecies psychophysiological states can be appropriately measured. Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
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16 pages, 2274 KiB  
Article
Do Cockatiels Choose Their Favourite Tunes? Use of Touchscreen for Animal Welfare Enhancement and Insights into Musical Preferences
by Mathilde Le Covec, Romain Di Stasi, Carla Aimé, Léa Bouet, Shigeru Watanabe and Dalila Bovet
Animals 2024, 14(24), 3609; https://doi.org/10.3390/ani14243609 - 14 Dec 2024
Viewed by 834
Abstract
Music may be one of the oldest forms of art, and its appreciation is thought to be universal among humans. Music could also represent a useful tool to improve captive animals’ welfare, especially if individuals can choose the music they prefer. The ability [...] Read more.
Music may be one of the oldest forms of art, and its appreciation is thought to be universal among humans. Music could also represent a useful tool to improve captive animals’ welfare, especially if individuals can choose the music they prefer. The ability to discriminate between different kinds of music or composers has been demonstrated in numerous non-human species. However, a reinforcing effect of music was found in only a few species, particularly in vocal learner birds such as Passeriformes and Psittaciformes. In this study, we explored whether cockatiels could learn to use a touchscreen to choose between two different pieces of music: first between rock and roll and calm music, and then between consonant and dissonant music. Some birds showed individual preferences for either rock and roll or calm music, but no preferences were found for consonance or dissonance. These results are in line with the hypothesis that vocal learners would be sensitive to music. Our findings offer new prospects for the study of musicality in non-humans and its potential applications for promoting welfare in captive animals: interacting with a touchscreen would allow them to have some control over their environment and to choose their preferred type of music as a form of environmental enrichment. Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
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12 pages, 2738 KiB  
Communication
Application of Machine Learning for Automating Behavioral Tracking of Captive Bornean Orangutans (Pongo Pygmaeus)
by Frej Gammelgård, Jonas Nielsen, Emilia J. Nielsen, Malthe G. Hansen, Aage K. Olsen Alstrup, Juan O. Perea-García, Trine H. Jensen and Cino Pertoldi
Animals 2024, 14(12), 1729; https://doi.org/10.3390/ani14121729 - 8 Jun 2024
Viewed by 1834
Abstract
This article applies object detection to CCTV video material to investigate the potential of using machine learning to automate behavior tracking. This study includes video tapings of two captive Bornean orangutans and their behavior. From a 2 min training video containing the selected [...] Read more.
This article applies object detection to CCTV video material to investigate the potential of using machine learning to automate behavior tracking. This study includes video tapings of two captive Bornean orangutans and their behavior. From a 2 min training video containing the selected behaviors, 334 images were extracted and labeled using Rectlabel. The labeled training material was used to construct an object detection model using Create ML. The use of object detection was shown to have potential for automating tracking, especially of locomotion, whilst filtering out false positives. Potential improvements regarding this tool are addressed, and future implementation should take these into consideration. These improvements include using adequately diverse training material and limiting iterations to avoid overfitting the model. Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
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24 pages, 914 KiB  
Systematic Review
Beyond the Camera Trap: A Systematic Review of Computing Technology Used to Monitor and Interact with (More) Varied Taxa in Zoos and Aquariums
by Lilliana Hassinger and Christena Nippert-Eng
Animals 2025, 15(12), 1721; https://doi.org/10.3390/ani15121721 - 11 Jun 2025
Abstract
Zoos and aquariums house a wide range of species, yet research remains heavily skewed toward mammals and camera-based technologies. This systematic literature review examines the use of computing technologies to monitor or interact with animals in zoos, aquariums, or wildlife parks, with a [...] Read more.
Zoos and aquariums house a wide range of species, yet research remains heavily skewed toward mammals and camera-based technologies. This systematic literature review examines the use of computing technologies to monitor or interact with animals in zoos, aquariums, or wildlife parks, with a focus on taxonomic representation and technological diversity. A total of 125 studies published between 2014 and 2024 met the inclusion criteria, encompassing 151 recorded instances of technology use. Cameras and video systems were the most frequently used tools, appearing alone in 40% of studies and in combination with other technologies in an additional 18.4%, accounting for 48.3% of all technology instances. Most studies focused on only mammals (73.5%), and behavioral monitoring was the most common research aim (40.9%). These findings suggest an uneven distribution of research shaped more by convenience and familiarity than by welfare need, highlighting a critical opportunity to diversify both species focus and technological application. Increased investment in underrepresented species and underutilized tools will help ensure that research better reflects the full spectrum of animal needs and experiences. Full article
(This article belongs to the Special Issue Animal–Computer Interaction: New Horizons in Animal Welfare)
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