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

Admela Jukan, Xavi Masip-Bruin, Nina Amla

arXiv:1609.00627v1cs.CY

TL;DR

Animal welfare involves health, freedom from pain and suffering, and positive stimulation across domestic, farm, and wild animals. This review categorizes smart computing and sensing technologies across these populations and application areas. It finds such technologies promising and potentially economically sustainable for animal welfare.

  • Problem

    Assessing animal welfare across domestic, farm, and wild animals involves health, freedom from pain and suffering, and positive stimulation in their environments.

    Source: §I · p. 1

  • Method

    The paper systematically reviews and categorizes smart systems for domestic, farm, and wild animals across technology and animal categories.

    Source: §I · p. 2, B. Conducting the Review · p. 2

  • Results

    The review finds innovative smart technologies promising and economically sustainable as options for ensuring animal welfare.

    Source: §I · p. 2, §VII · p. 12

  • Takeaways & Limitations

    The review identifies integrated, open cloud systems and greater cross-species reuse as priorities for future animal-welfare technologies.

    Source: §VII · p. 11

    Policy considerations are outside the scope of the review.

    Source: §I · p. 2

Abstract

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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.

I. INTRODUCTION

The review frames animal welfare broadly and surveys networked computing and sensing technologies for domestic, farm, and wild animals. It categorizes the literature and identifies these technologies as promising for welfare.

I. INTRODUCTION

  • Smart computing and sensing refers to networked systems that collect, process, exchange, and analyze data, rather than isolated devices.Examples include networked wearable devices, sensors, cellular networks, and big-data processing.Source: §I · p. 1
  • Animal welfare encompasses animals’ basic needs, health, freedom from pain and suffering, and positive stimulation in their environments.The review notes that connected transport systems could support monitoring the Twenty-Eight Hour Law for food-animal transportation.Source: §I · p. 1
  • Prior tracking and monitoring work for pets and wild animals, alongside emerging farm applications, motivates a joint review of these areas.The paper describes smart technologies as promising and economically sustainable options for animal welfare.Source: §I · pp. 1–2
  • The review surveys smart technologies for domestic, farm, and wild animals, categorizing systems discussed or implemented in research over the past decade.It focuses on categorization as a basis for managing information, collecting data, and improving knowledge sharing.Source: §I · p. 2

II. SCOPE AND CRITERIA FOR THE REVIEW

  • The review follows planning, conducting, and reporting steps, with this paper focused on reporting the results.The introduction previews sections on domestic animals, farming, wilderness, findings, and conclusions.Source: §II · p. 2, §I · p. 2

A. Planning the Review

The review defines animal welfare and its animal populations, then applies explicit scope criteria and a framework for organizing technologies and relationships among categories.

A. Planning the Review

  • Animal welfare is reviewed through technologies relevant to living without pain, species-adequate environments, and positively stimulated activities and social interactions.The review excludes specific treatment of ethics, animal rights, and laws.Source: A. Planning the Review · p. 2
  • The review includes accessible and reproducible studies of smart technologies involving animals, while excluding commercial white papers and several non-welfare technology or opinion sources.It also excludes work focused solely on animal law, rights, or ethics.Source: A. Planning the Review · p. 2
  • The review excludes animal-like robots and virtual animals, considering only research in which live animals are involved.Examples of excluded efforts include robots used for herding and canine virtual environments.Source: A. Planning the Review · p. 2

B. Conducting the Review

  • The technology framework groups work into communication, health, monitoring, and environment, while the animal framework distinguishes domestic, farm, and wild animals.Domestic systems target individuals; farm systems address groups reared for food or commercial goods; wild-animal systems concern habitats, zoos, or sanctuaries.Source: B. Conducting the Review · p. 2
  • The review quantifies work in each category and identifies relationships among subcategories; absent research may signal a need for future work or limited application importance.Figure 1 does not show relationships between individual categories and subcategories.Source: B. Conducting the Review · p. 3

III. DOMESTIC ANIMALS: ONE AT A TIME

The domestic-animal review focuses on individually treated animals, covering human-animal communication, tracking and monitoring, and health applications.

III. DOMESTIC ANIMALS: ONE AT A TIME

  • Domestic-animal systems are reviewed as applications for individual animals, grouped into communication, tracking and health, and service or working dogs.The paper summarizes the domestic-animal literature in tables.Source: §III · p. 3

A. Human-animal communication

  • Animal-Computer Interface (ACI) research includes species-appropriate interfaces, communication prototypes, and digital play intended to stimulate companion animals.Examples include a system transmitting human contact to a chicken and digital games for cats.Source: A. Human-animal communication · p. 3
  • Proposed pet communication systems include multisensory smartphone interfaces, GPS collars, RFID-based social media, and video chat.Dog-owner case studies also found usability limitations in current communication technologies.Source: A. Human-animal communication · p. 3

B. Tracking and monitoring of human’s best friends

  • Wearable accelerometers and gyroscopes support recognition of dogs’ postures and activities, while other systems enable dog-handler signaling and wearable health monitoring.Reported recognized behaviors include sitting, lying down, walking, and climbing stairs.Source: B. Tracking and monitoring of human’s… · p. 3

C. Service dogs and working dogs

The review describes sensing and communication systems for service dogs and working dogs, including assistance interfaces, therapy-related applications, and search-and-rescue equipment.

C. Service dogs and working dogs

  • Service-dog technologies include alarms, audio and vibrotactile feedback, and activity trackers for assessing suitability for particular work.The review also identifies sensor-based toys for guide dogs as a future research direction.Source: C. Service dogs and working dogs · p. 3
  • Animal-assisted therapy is reported as potentially beneficial for people with dementia, while sensors can monitor pressure differences as cancer-detection dogs sniff samples.The pressure distinction is between positive and negative cancer samples.Source: C. Service dogs and working dogs · pp. 3–4
  • Working-dog systems combine cameras, audio, GPS, and networks for search and rescue, including barking-based victim localization and pose transmission over mesh networks.Health monitoring for USAR dogs in heat is also proposed; dogs have carried snake robots into hazardous or inaccessible spaces.Source: C. Service dogs and working dogs · p. 4

IV. FARM ANIMALS: MANAGING ANIMAL GROUPS

The review treats farm-animal welfare as group management shaped by commercial utility and economic factors, organized by indoor and outdoor settings. Indoor work spans animal monitoring and environmental control, but data collection and analysis receive less attention than system engineering and connectivity.

IV. FARM ANIMALS: MANAGING ANIMAL GROUPS

  • Farm-animal welfare is managed at group level, with commercial utility and deployment economics shaping smart-system use across indoor and outdoor settings.The review covers cows, pigs, chickens, rabbits, and sheep.Source: §IV · p. 4

A. Indoor farm animals

  • Indoor farming is the most common setting with the largest amount of reported work, while efficient smart farming has received less attention than agricultural farming.The review organizes the indoor and outdoor literature by habitation setting and summarizes indoor applications and technologies in Table III.Source: §IV · p. 5, A. Indoor farm animals · p. 5
  • Indoor systems envision a coordinated smart ecosystem, yet much reviewed work addresses isolated components and activity monitoring relevant to animals’ ability to move.Animals may remain indoors for their entire lifetime, making movement a critical welfare factor.Source: A. Indoor farm animals · p. 5
  • Cattle studies emphasize health monitoring, including remote health assessment, vital signs, estrus, heat stress, calving, lameness, and indoor location or behavior.Examples use wearable sensors and Bluetooth, magnetometers and accelerometers, ZigBee networks, and camera-based posture analysis –.Source: A. Indoor farm animals · pp. 5–6
  • Work on pigs, hens, and smaller species often emphasizes ambient monitoring, while some systems also assess animal health, growth, activity, or adaptable living space.Systems include climate control and monitoring, pig-space reconfiguration, pig respiratory-rate measurement, hen vital-parameter and activity monitoring, and rabbit-cage temperature sensing –.Source: A. Indoor farm animals · p. 6
  • Most reviewed systems emphasize engineering and connectivity more than collecting and analyzing sensor data, although web applications and databases address behavior, disease screening, product information, and health or growth.Examples include cattle simulators and online disease screening,, poultry product tracking, and a pig health and growth database.Source: A. Indoor farm animals · p. 6

B. Outdoor farm animals

Outdoor farm systems operate in more natural settings using existing cellular infrastructure or ad hoc wireless sensor networks. The reviewed work focuses mainly on cattle tracking and activity, with additional health-monitoring and movement-control applications.

B. Outdoor farm animals

  • Outdoor monitoring primarily tracks animals and their activity, often with wearable smart collars, and most reviewed work concerns cattle.Systems can use existing cellular infrastructure or infrastructure-less ad hoc wireless sensor networks.Source: B. Outdoor farm animals · p. 6
  • Cattle activity studies use accelerometers, pedometers, or magnetometers to classify activity and inactivity, while GPS collars and communication links track location and movement.Examples include pasture location, feed intake, walking intensity, and movement evaluated using GPS and a local server –.Source: B. Outdoor farm animals · p. 6
  • Other outdoor systems monitor cattle health or detect disease and pregnancy, while a sheep monitor records physiological data and virtual fences guide cattle movement without permanent structures.The sheep system measures nervous-system activity and cardiovascular response; virtual-fence collars use GPS and sound amplification, –.Source: B. Outdoor farm animals · p. 6

V. WILD ANIMALS: NO RULES OTHER THAN NATURE

Wildlife monitoring relies heavily on low-power, lightweight wireless sensor networks designed for intermittent connectivity and harsh conditions, alongside newer heterogeneous IoT approaches. Tracking work ranges from animal-worn devices to habitat-based sensing, with data processing and visualization also represented.

V. WILD ANIMALS: NO RULES OTHER THAN NATURE

  • Wildlife monitoring, protection, and behavioral research mainly use lightweight, low-power wireless sensor networks designed for intermittent connectivity and varied environmental conditions.More recent frameworks incorporate heterogeneous technologies such as cellular networks, alternative radio systems, and drones.Source: §V · p. 6
  • Limited wireless-sensor-network bandwidth has constrained cameras’ potential for visual recognition and in-situ image processing.The review identifies visual sensing as important in wildlife monitoring.Source: §V · p. 7

A. Tracking

  • Tracking systems often combine location with acceleration-based motion sensing, and may adapt network design to animal behavior or adapt existing systems for wildlife applications.Wild animals can be tracked with wearable or non-wearable sensors.Source: A. Tracking · p. 7
  • Wildlife tracking spans hybrid cellular and ad hoc networks for migrating whooping cranes, GPS collars, delay-tolerant systems, and low-energy peer-to-peer designs.The crane system covers an annual migration of 4,000 km, using cellular networks during migration and short-range ad hoc networks at breeding and nesting grounds –.Source: A. Tracking · pp. 7–8
  • Tracking also uses habitat-based sensor and camera networks for detection, classification, and data management, alongside lightweight or specialized sensors for different species.Examples include the DuckIsland habitat-monitoring network, camera-sensor systems –, and systems for bats, turtles, and badgers –.Source: A. Tracking · p. 8
  • Additional wildlife approaches include a framework for processing, analyzing, and visualizing tracking data used in Australia, collaborative aquatic-tracking web frameworks,, and an animal-mounted video-and-sensor system.A separate proposal shares data between animals to improve monitoring in inaccessible areas.Source: A. Tracking · p. 8

B. Human-animal cohabitation

Wildlife cohabitation systems address encounters with people and infrastructure through detection, deterrence, and alerts. Other reviewed approaches use image, sound, infrared, radar, or seismic sensing for protection and monitoring.

B. Human-animal cohabitation

  • Cohabitation systems detect or deter wildlife near human settlements and infrastructure, including elephant fence breakages, railway crossings, and village entry.The reviewed approaches include passive wireless nodes with infrasonic sounds, infrared sensors, and seismic sensors –.Source: B. Human-animal cohabitation · pp. 8–9
  • Wireless systems alert drivers to wildlife-crossing dangers and use movement sensing to protect sea turtle hatchlings from tourists.Other proposals use water levels and local deer density for water conservancy, or ultrasonic positioning for wildlife protection –.Source: B. Human-animal cohabitation · p. 9
  • Protection and monitoring methods include camera-based recognition, sound classification, infrared video, compression-based image processing, and radar detection.Applications include recognizing migratory birds to inform wind-farm allocation, detecting hidden fawns, and identifying unlawful human intrusion in protected areas –.Source: B. Human-animal cohabitation · p. 9

C. Wild animals in confinement

The review describes ACI work on wild animals in confinement and finds that sensor and network choices vary by species and setting, with practical trade-offs in monitoring.

C. Wild animals in confinement

  • In zoos and sanctuaries, ACI research addresses animal welfare as well as human-animal interaction for education and conservation, including proposed playful environments to counter isolation, poor physical condition, repetitive training, or remote-only human interaction.The review cites on ACI opportunities in zoos and on Intelligent Playful Environment for Animals (IPE4A) scenarios.Source: C. Wild animals in confinement · p. 9

A. Wearable vs. non-wearable sensor systems

  • For domestic and wild animals, wearables primarily support GPS tracking, while livestock systems prioritize sensor-data accuracy and cost; non-wearable monitoring is less developed, and limited cloud connection hinders longitudinal tracking and data sharing.Animal comfort motivates compact, lightweight devices; jackets distribute wearable weight better than collars, while indoor-farm ambient sensors measure temperature and humidity.Source: A. Wearable vs. non-wearable sensor… · p. 9

B. Networked remote sensing

  • Wild-animal tracking uses varied hybrid networks adapted to species’ migration and challenging environments, while farm monitoring faces cost, battery-power, and connectivity trade-offs; Table VI covers wild-animal applications, devices, and systems.The review also notes bandwidth and capacity challenges for video networks and maintenance needs in remote settings; commercial farm services track food, water, fresh air, temperature, and security.Source: B. Networked remote sensing · pp. 9–10, Table VI · p. 10

C. Cloud-based applications and data processing

The review finds cloud processing and data sharing limited across animal-welfare systems, while animal identification and tracking infrastructure can be costly but may support supply-chain tracing and disease response.

C. Cloud-based applications and data processing

  • Across the surveyed domains, research on representing and managing animal-sensor data remains in its infancy, and few systems extend processing and sharing to the cloud.For urban pets, commercial cellular apps offer cloud tracking and monitoring, but little is known about what data they collect or whether it can support health or living-condition assessment.Source: C. Cloud-based applications and data… · p. 10
  • Farm web services have been proposed to monitor animal growth, health, and food intake, while FAO’s Africa pilot stores vaccination and treatment records in a global database used to pinpoint and contain disease outbreaks.The passage notes that questions remain about the data collected by farm services.Source: C. Cloud-based applications and data… · p. 10

D. Economic factors

  • Livestock identification systems can be expensive upfront, but tracking animals through the supply chain could help identify and contain disease outbreaks, potentially making deployment cost-effective as prices fall.The review describes RFID identification requirements in Australia and the EU, and a U.S. system promoting microchips or other tags for lifetime monitoring.Source: D. Economic factors · p. 10

E. Research Opportunities

The review calls for affordable, low-power smart systems, shared infrastructure, and richer data analytics, alongside interdisciplinary and animal-centered research.

E. Research Opportunities

  • The authors call for ultra-low-power, ultra-low-cost hardware, more efficient data collection and storage, networking advances, and shared infrastructure for real-time information, alerts, and best practices.They also identify machine learning and natural language processing as approaches for analyzing multimodal data, and propose integrating animal-welfare requirements into early smart-city and community design for reuse and sustainability.Source: E. Research Opportunities · p. 11
  • The authors argue that interdisciplinary animal-centered research could yield gesture and posture recognition, two-way animal communication, and more interactive warnings that keep wild animals away from danger.The proposed work brings together computer scientists, engineers, animal behaviorists, conservationists, and veterinarians.Source: E. Research Opportunities · p. 11

VII. CONCLUSION

The review finds smart technologies have benefited animals in specific situations, and proposes integration and sharing to extend those benefits. Its recommendations span open systems, cross-species research, livestock-centered agriculture, wider IoT use, emergency response, and adoption.

VII. CONCLUSION

  • The review defines welfare broadly and concludes that integrated technologies and a centralized database could help animals stay healthy, free of pain and suffering, and positively stimulated, while sharing information and best practices could bring societal and economic benefits.The reviewed systems connect sensing and computing with networks and systems that collect, process, and evaluate animal-welfare data.Source: §VII · p. 11
  • More work is needed to integrate specialized sensor networks with cloud services and infrastructure and make data and systems open for sharing, programmability, and further innovation.The review recommends integrated, open cloud-based systems, applications, and services.Source: §VII · p. 11
  • Animal sensor-network systems share common features, but the review finds little or no evidence that they can be reused across species or applications.It points to low-cost, low-power wild-animal tracking and dog wearables as knowledge that could benefit farming systems.Source: §VII · p. 11
  • Smart agriculture should include more animal-centered research because current work focuses more on plants than livestock.Source: §VII · p. 11
  • The review recommends adding animal welfare to smart-X and IoT agendas, with applications spanning wildlife migration, missing animals, transport, outdoor tracking, cities, and smart homes.Source: §VII · p. 11
  • Animal welfare can be economically sustainable through low-cost smart systems or integration into existing systems, while provenance data can inform consumers and support adoption.Source: §VII · p. 11
  • Animal-derived disaster and disease warnings are proposed for scale-up, alongside systems that detect emergencies, identify animals needing help, and trigger predetermined rescue and recovery measures.Source: §VII · p. 11
  • Adoption is framed chiefly as a mindset and awareness challenge: educate farming, consumer, veterinary, and wildlife communities, and include animal-welfare smart systems in engineering curricula.The review says technical and economic challenges are minor in comparison with changing the existing mindset.Source: §VII · pp. 11–12
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