PRESS REALESE

Global Artificial Intelligence in Livestock Farming Market | Key Players are Faromatics, FarrPro, H2Oalert, Hencol, Jaguza Tech, Moonsyst, Roper, Simple Ag Solutions, SomaDetect, and SwineTech

The Global Artificial Intelligence in Livestock Farming Market is estimated to exhibit a CAGR of 26.2% during the forecast period.

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The majority of the procedures and steps involved in livestock are manual. AI can simplify the most difficult and common activities by enhancing already-adopted technology. When used in conjunction with other technology, it can collect and analyze large amounts of data on a digital platform, determine the best course of action, and even start that action. The market for artificial intelligence in livestock farming is expanding as people become more aware of data-driven decision-making methodologies for managing livestock feed, end products, and general herd health. The expanding government support for the adoption of contemporary livestock management platforms and software, as well as the rising demand for livestock productivity through deep-learning technology, are some of the additional factors promoting the growth of this market. Additionally, the market will develop as a result of the population’s rapid increase, rising consumption of poultry and dairy products, and growing worries about the health of livestock and the spread of disease. With the introduction of AI technologies in livestock farming, many farmers were able to increase their overall profitability, improve the health of their livestock, and closely monitor diseases that can pose harm to the animals.

List of Prominent Players in the Artificial Intelligence in Livestock Farming Market:

Connecterra

Rex

Cainthus

Vence

SmartShepherd

Quantified AG

AgriWebb

BovControl

BinSentry Inc.

Faromatics

FarrPro

H2Oalert

Hencol

Jaguza Tech, Moonsyst

Roper

Simple Ag Solutions

SomaDetect

SwineTech

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Market Dynamics:

Drivers-

The growing demand for livestock monitoring is an essential element influencing the market for AI in livestock. Dairy farms can now individually monitor all herd behavioural elements owing to the implementation of modern AI solutions, such as facial recognition for livestock and image classification combined with body condition scores and eating patterns. Additionally, farmers are increasingly employing machine vision to track the health of their livestock. This technology can identify facial patterns and hiding patterns, keep track of the animals’ water and food consumption, and even record their body temperatures and behaviour. A shortage of qualified workers, ageing farmers, and younger generations who find farming unappealing all contribute to the downturn, driving trends toward automated farming operations. Governments and corporate organizations are being prompted by the trend of a shrinking livestock workforce to concentrate on automating activities by implementing artificial intelligence technologies in the livestock industry.

Challenges:

The livestock industries in developing nations are distinct from those in Western Europe and the US. Artificial intelligence in livestock may be advantageous in some areas, but it may be challenging to market such technology in places where livestock technology is uncommon. Farmers will probably require assistance implementing it, and their reluctance results from a lack of knowledge about how AI tools are applied in real-world situations. Despite the potential benefits of AI, there is still much that needs to be done by technology companies to assist farmers in adequately using it. Precision livestock and smart farming create a number of legal questions that frequently go unresolved because there are no defined norms and regulations surrounding the use of AI in general, not just in livestock. Farmers may experience severe issues as a result of privacy and security threats like cyberattacks and data leaks.

Regional Trends:

During the forecast period, North America will hold the major share of the market. The majority of North America’s market share may be linked to the region’s growing need for hands-free cattle handling, increased low-quality milk and dairy product cases and growing knowledge of the latest technologies for managing farm animals. The market will experience significant growth during the projected period due to the growing implementation of IoT and computer vision technologies in the livestock sector. Additionally, several regional players provide services to local consumers through agreements with other top players. Companies like IBM Corporation and Raven Industries Inc. are increasingly working with other players to improve their livestock sector products. Large-scale livestock players are already adopting AI technology in the Americas to significantly increase the efficiency and precision of their management procedures.

Recent Developments:

  • In December 2020, Cainthus, an agtech firm, launched Alus Behavior to help large dairies improve milk output and animal welfare. Alus Behavior monitors the cows and their behaviours around the clock, including lying down, eating, and drinking (the 24-hour cow time budget, also known as a cow’s reaction to its surroundings), to make sure they are acting in ways that maximize milk output.
  • In June 2020, a division of Merck & Co., Inc., Kenilworth, New Jersey, USA, Merck Animal Health, also known as MSD Animal Health announced the completion of its acquisition of Quantified Ag®, a leading data and analytics firm that tracks cattle body temperature and movement to identify illness early.

Segmentation of Artificial Intelligence in Livestock Farming Market-

By Component

  • Solution/ Software/ App
  • IoT Sensors
  • Service

By Application

  • Real-Time Livestock Behavior Monitoring
  • Healthcare & Disease Monitoring
  • Livestock Feed & Water Monitoring
  • Livestock Control & Fencing Management
  • Livestock Production Management

By Type

  • Semi-Automatic
  • Fully-Automatic

By Farm Size

  • Small and Medium-Sized Farms
  • Large Sized Farms

By Technology

  • Computer Vision
  • Machine Learning
  • Predictive Analysis

By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

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