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Further information

For more information, consult the following on the RSPCA Knowledgebase:

RSPCA policies

Knowledgebase articles

Further reading and external references 

NOTE: due to copyright we cannot upload articles that aren’t open access and even some of those do not allow uploading of the paper itself (each would need to be checked for permissions). To avoid copyright infringement, add a link to the article publisher's download page and people can see for themselves whether it's free access or not. (the doi links below are fine) 

  • Acarcinom Cancer Data PortalPortal: https://www.acarcinom.org.au
  • Animal Management in Rural and Remote Indigenous Communities. https://www.amrric.org/
  • Social Media Animal Cruelty Coaltion.Coaltion: HOME - SMAC | SMACChttps://www.endcrueltyonline.com
  • Brereton JE, Tuke J, Fernandez EJ. Incorporating the enclosure MonitoR use (EMU) app to ZooMonitor observations technical report. Zoo Biology. 2025;44:383–90. https://doi.org/10.1002/zoo.21909
  • Campbell D, Erasmus M. Poultry welfare monitoring: wearable technologies. Understanding the behaviour and improving the welfare of chickens [Internet]. 1st edition. Burleigh Dodds Science Publishing; 2020. https://www.taylorfrancis.com/chapters/edit/10.1201/9781003048039-6/poultry-welfare-monitoring-wearable-technologies-dana-campbell-marisa-erasmus
  • Carvalho AF, De Morais IOB, Souza TB. Profiting from cruelty: Digital content creators abuse animals worldwide to incur profit. Biol Cons. 2023;287:110321. https://doi.org/10.1016/j.biocon.2023.110321
  • Coghlan S, Parker C. Harm to nonhuman animals from AI: a systematic account and framework. Philos Technol. 2023;36:25. https://doi.org/10.1007/s13347-023-00627-6
  • Coghlan S, Parker C. Helping and not harming animals with AI. Philos Technol. 2024;37:20. https://doi.org/10.1007/s13347-024-00712-4
  • Dawkins MS. Smart farming and Artificial Intelligence (AI): How can we ensure that animal welfare is a priority? Appl Anim Behav Sci. 2025;283:106519. https://doi.org/10.1016/j.applanim.2025.106519
  • Englefield B, Starling M, Wilson B, Roder C, McGreevy P. The australian roadkill reporting project—applying integrated professional research and citizen science to monitor and mitigate roadkill in australia. Animals. 2020;10:1112. https://doi.org/10.3390/ani10071112
  • Feighelstein M, Riccie-Bonot C, Hasan H, Weinberg H, Rettig T, Segal M, et al. Automated recognition of emotional states of horses from facial expressions. PLoS ONE. 2024;19:e0302893. https://doi.org/10.1371/journal.pone.0302893
  • Fisher A, Cornish A. 2022. Independent scientific literature review on animal welfare considerations for virtual fencing. Report for Department of Agriculture, Fisheries and Forestry. 
  • Fogarty E, Swain D, Cronin G, Trotter M. A systematic review of the potential uses of on-animal sensors to monitor the welfare of sheep evaluated using the Five Domains Model as a framework. Anim Welf. 2019;28:407–20. https://doi.org/10.7120/09627286.28.4.407
  • Geoghegan JL, Pirotta V, Harvey E, Smith A, Buchmann JP, Ostrowski M, et al. Virological sampling of inaccessible wildlife with drones. Viruses. 2018;10:300. https://doi.org/10.3390/v10060300
  • Guzhva O, Siegford JM, Lunner Kolstrup C. The hitchhiker’s guide to integration of social and ethical awareness in precision livestock farming research. Front Anim Sci. 2021;2:725710. https://doi.org/10.3389/fanim.2021.725710
  • Harrington LA, Elwin A, Paterson S, D’Cruze N. The viewer doesn’t always seem to care—response to fake animal rescues on YouTube and implications for social media self‐policing policies. People Nat. 2023;5:103–18. https://doi.org/10.1002/pan3.10416
  • Herlin A, Brunberg E, Hultgren J, Högberg N, Rydberg A, Skarin A. Animal welfare implications of digital tools for monitoring and management of cattle and sheep on pasture. Animals. 2021;11:829. https://doi.org/10.3390/ani11030829
  • Hryhorenko L, McWhorter T, Whittaker A, Fernandez EJ. The use of technology as environmental enrichment in zoos: A scoping review. Anim Welf. 2025;34:e73. https://doi.org/10.1017/awf.2025.10038
  • Lee C, Campbell DLM. A multi-disciplinary approach to assess the welfare impacts of a new virtual fencing technology. Front Vet Sci. 2021;8:637709. https://doi.org/10.3389/fvets.2021.637709
  • Mahato S, Neethirajan S. Integrating Artificial Intelligence in dairy farm management − biometric facial recognition for cows. Inf. Process. Agric. 2025;12:312–25. https://doi.org/10.1016/j.inpa.2024.10.001
  • Martvel G, Lazebnik T, Feighelstein M, Henze L, Meller S, Shimshoni I, et al. Automated video-based pain recognition in cats using facial landmarks. Sci Rep. 2024;14:28006. https://doi.org/10.1038/s41598-024-78406-2
  • Mota-Rojas D, Whittaker AL, Coria-Avila GA, Martínez-Burnes J, Mora-Medina P, Domínguez-Oliva A, et al. How facial expressions reveal acute pain in domestic animals with facial pain scales as a diagnostic tool. Front Vet Sci. 2025;12:1546719. https://doi.org/10.3389/fvets.2025.1546719
  • Neethirajan S, Scott S, Mancini C, Boivin X, Strand E. Human-computer interactions with farm animals—enhancing welfare through precision livestock farming and artificial intelligence. Front Vet Sci. 2024;11:1490851. https://doi.org/10.3389/fvets.2024.1490851
  • Park S. Digital inequalities in rural Australia: A double jeopardy of remoteness and social exclusion. J. Rural Stud. 2017;54:399–407. https://doi.org/10.1016/j.jrurstud.2015.12.018
  • Pirotta V, Hocking DP, Iggleden J, Harcourt R. Drone observations of marine life and human–wildlife interactions off Sydney, Australia. Drones. 2022;6:75. https://doi.org/10.3390/drones6030075
  • Raoult V, Colefax AP, Allan BM, Cagnazzi D, Castelblanco-Martínez N, Ierodiaconou D, et al. Operational protocols for the use of drones in marine animal research. Drones. 2020;4:64. https://doi.org/10.3390/drones4040064
  • Rayner K, Wilson M. Distance examination of livestock with drones ‐ an effective method for assessing health and welfare. Aust Vet J. 2024;102:293–5. https://doi.org/10.1111/avj.13326
  • Schork IG, Manzo IA, Oliveira MRBD, Costa FV, Young RJ, De Azevedo CS. Testing the accuracy of wearable technology to assess sleep behaviour in domestic dogs: a prospective tool for animal welfare assessment in kennels. Animals. 2023;13:1467. https://doi.org/10.3390/ani13091467
  • Siegford JM, Steibel JP, Han J, Benjamin M, Brown-Brandl T, Dórea JRR, et al. The quest to develop automated systems for monitoring animal behavior. Appl Anim Behav Sci. 2023;265:106000. https://doi.org/10.1016/j.applanim.2023.106000
  • Stumpf A, Herbrandt S, Betting L, Kemper N, Fels M. Societal perception of animal videos on social media—funny content or animal suffering? A survey. Animals. 2024;14:2234. https://doi.org/10.3390/ani14152234
  • Walter M, Lovett R, Maher B, Williamson B, Prehn J, Bodkin‐Andrews G, et al. Indigenous data sovereignty in the era of big data and open data. Aust J Social Issues. 2021;56:143–56. https://doi.org/10.1002/ajs4.141
  • Webber S, Cobb ML, Coe J. Welfare through competence: a framework for animal-centric technology design. Front Vet Sci. 2022;9:885973. https://doi.org/10.3389/fvets.2022.885973
  • Wilkins CL, McGreevy PD, Cosh SM, Henshall C, Jones B, Lykins AD, et al. Introducing the Mellorater—the Five domains Model in a welfare monitoring app for animal guardians. Animals. 2024;14:2172. https://doi.org/10.3390/ani14152172
  • Wurtz K, Camerlink I, D’Eath RB, Fernández AP, Norton T, Steibel J, et al. Recording behaviour of indoor-housed farm animals automatically using machine vision technology: A systematic review. Raboisson D, editor. PLoS ONE. 2019;14:e0226669. https://doi.org/10.1371/journal.pone.0226669

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