Global Artificial Intelligence in Livestock Farming Market

Report ID : 1323 | Published : 2022-07-29 | Pages: | Format: PDF/EXCEL

The market size of the Global Artificial Intelligence in Livestock Farming Market is predicted to show an 26.2% CAGR during the forecast period.

A large portion of livestock processes and steps are manual. By improving already-adopted Technology, AI may simplify even the most routine and challenging tasks. It can gather and analyze a lot of data on a digital platform, choose the best course of action, and even start that action when used in concert with other technologies. The primary market growth driving drivers will emerge as increasing globalization and an increase in the use of new cutting-edge Technology by the livestock industry. The market value will be further positively impacted by rising demand for high-quality livestock products, encouraging government programs and initiatives to promote advanced livestock tools and practices, and growing industrialization. The rising costs associated with conducting research and development projects and the increasing use of drones in livestock fields will further expand the market. Improvements in feed quality, computer-aided vision algorithms, livestock health monitoring, supply chain optimization, and real-time behaviour monitoring are among the application areas covered by AI technology. With AI's disruption of the livestock business, numerous start-up companies have entered the market and developed cutting-edge IoT sensors to address farmers' unmet demands.

However, a lack of technological know-how and knowledge will prevent the market from expanding. Technological difficulties, interoperability problems, and a lack of standardization will further slow the market's development pace. The developing economies' extensive technological restrictions and the significant expenses involved in precise field data gathering will make achieving the market development rate even more difficult.

Market Segmentation:

The Artificial Intelligence in Livestock Farming Market is segmented on the basis of Component, Application, Type, Farm Size, and Technology. Based on the Component, the market is segmented as Solution/ Software/ App, IoT Sensors, and Services. Based on Application, the market is segmented as Real-Time Livestock Behavior Monitoring, Healthcare & Disease Monitoring, Livestock Feed & Water Monitoring, Livestock Control & Fencing Management, and Livestock Production Management. Based on Type, the market is segmented as Semi-Automatic and Fully-Automatic. Based on Farm Size, the market is segmented into Small and Medium-Sized Farms and Large Sized Farms. Based on Technology, the market is segmented into Computer Vision, Machine Learning, and Predictive Analysis.

Based on Components, the IoT sensors segment is accounted as a major contributor in the Artificial Intelligence in Livestock Farming Market.

The Internet of Things (IoT) sensors market will have the fastest growth with the greatest CAGR because of the increased requirement for sensors and intelligent devices in farm setups to reduce labour and manual maintenance costs. The segment's expansion is greatly influenced by farmers in developed regions being more knowledgeable about the sensors and gadgets that can track the feed levels and vital signs of the livestock on their farms. This has substantially contributed to the sensor sector's overall growth. In recent years, smaller sensors have been fast incorporated into gadgets, including wearables, smartphones, drones, and robotics, which is also assisting the market's expansion. The rapid adoption of the Internet of Things (IoT) by farmers and growers, the growing emphasis on livestock monitoring and disease detection, the high demand for fresh produce, population growth, the loss of arable land, the rapid adoption of aquaculture monitoring and feed optimization devices in developing countries and the strong government support for precision farming practices are some of the factors that are driving the growth of the IoT sensors segment.

Based on Technology, the computer vision segment is accounted as a significant contributor to Artificial Intelligence in Livestock Farming Market.

The market's most significant stakeholder will be computer vision. The use of computer vision for animal monitoring opens the door to non-intrusive livestock monitoring. Visual Artificial Intelligence (AI) is one of the most promising technologies to automate inspection and decrease expenses to survive under solid cost pressure and severe competition as a result of the growing demand for animal monitoring systems. This is motivated by things like managing animal comfort, managing reproduction, or early disease detection. It is now feasible to create autonomous computer vision systems for animal monitoring and observation that can match or even outperform human accuracy because of the quick advancements in machine learning.

The North America Artificial Intelligence in Livestock Farming Market in the region holds a significant revenue share.

North America will control a sizable portion of the market throughout the forecast period. With the expanding use of IoT and computer vision technologies in the livestock sector, the market will expand significantly during the anticipated period. The region's growing demand for hands-free cattle handling, rise in the prevalence of low-quality milk and dairy products, and improved awareness of the most recent technologies for managing farm animals may contribute to North America's market share dominance. Businesses like IBM Corporation and Raven Industries Inc. are increasingly collaborating with other firms to better their goods for the livestock sector. Additionally, through agreements with other major firms, a number of regional players offer services to local customers. In the Americas, significant players in livestock are already implementing AI technology to improve their management processes' effectiveness and precision dramatically.

Competitive Landscape

Some of the major key players in the Artificial Intelligence in Livestock Farming Market are Connecterra, Rex, Cainthus, Vence, SmartShepherd, Quantified AG, AgriWebb, BovControl, BinSentry Inc, Faromatics, FarrPro, H2Oalert, Hencol, Jaguza Tech, Moonsyst, Roper, Simple Ag Solutions, SomaDetect, and SwineTech.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Artificial Intelligence in Livestock Farming Market Snapshot

Chapter 4. Global Artificial Intelligence in Livestock Farming Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: By Component Estimates & Trend Analysis

5.1. By Component & Market Share, 2020 & 2030

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Component:

5.2.1. Solution/ Software/ App

5.2.2. IoT Sensors

5.2.3. Service

Chapter 6. Market Segmentation 2: By Application Estimates & Trend Analysis

6.1. By Application & Market Share, 2020 & 2030

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Application:

6.2.1. Real-Time Livestock Behavior Monitoring

6.2.2. Healthcare & Disease Monitoring

6.2.3. Livestock Feed & Water Monitoring

6.2.4. Livestock Control & Fencing Management

6.2.5. Livestock Production Management

Chapter 7. Market Segmentation 3: By Type Estimates & Trend Analysis

7.1. By Type & Market Share, 2020 & 2030

7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Type:

7.2.1. Semi-Automatic

7.2.2. Fully-Automatic

Chapter 8. Market Segmentation 4: By Farm Size Estimates & Trend Analysis

8.1. By Farm Size & Market Share, 2020 & 2030

8.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Farm Size:

8.2.1. Small and Medium-Sized Farms

8.2.2. Large Sized Farms

Chapter 9. Market Segmentation 5: By Technology Estimates & Trend Analysis

9.1. By Technology & Market Share, 2020 & 2030

9.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Technology:

9.2.1. Computer Vision

9.2.2. Machine Learning

9.2.3. Predictive Analysis

Chapter 10. Artificial Intelligence in Livestock Farming Market Segmentation 6: Regional Estimates & Trend Analysis

10.1. North America

10.1.1. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts By Component, 2020-2030

10.1.2. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts By Application, 2020-2030

10.1.3. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Type, 2020-2030

10.1.4. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Farm Size, 2020-2030

10.1.5. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Technology, 2020-2030

10.1.6. North America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by country, 2020-2030

10.2. Europe

10.2.1. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Component, 2020-2030

10.2.2. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Application, 2020-2030

10.2.3. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Type, 2020-2030

10.2.4. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Farm Size, 2020-2030

10.2.5. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Technology, 2020-2030

10.2.6. Europe Artificial Intelligence in Livestock Farming Market revenue (US$ Million) by country, 2020-2030

10.3. Asia Pacific

10.3.1. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Component, 2020-2030

10.3.2. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Application, 2020-2030

10.3.3. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Type, 2020-2030

10.3.4. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Farm Size, 2020-2030

10.3.5. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Technology, 2020-2030

10.3.6. Asia Pacific Artificial Intelligence in Livestock Farming Market revenue (US$ Million) by country, 2020-2030

10.4. Latin America

10.4.1. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Component, (US$ Million)

10.4.2. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Application, (US$ Million)

10.4.3. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Type, 2020-2030

10.4.4. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Farm Size, 2020-2030

10.4.5. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Technology, 2020-2030

10.4.6. Latin America Artificial Intelligence in Livestock Farming Market revenue (US$ Million) by country, 2020-2030

10.5. Middle East & Africa

10.5.1. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Component, (US$ Million)

10.5.2. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) By Application, (US$ Million)

10.5.3. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Type, 2020-2030

10.5.4. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Farm Size, 2020-2030

10.5.5. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) estimates and forecasts by Technology, 2020-2030

10.5.6. Middle East & Africa Artificial Intelligence in Livestock Farming Market revenue (US$ Million) by country, 2020-2030

Chapter 11. Competitive Landscape

11.1. Major Mergers and Acquisitions/Strategic Alliances

11.2. Company Profiles

11.2.1. Connecterra

11.2.2. Rex

11.2.3. Cainthus

11.2.4. Vence

11.2.5. SmartShepherd

11.2.6. Quantified AG

11.2.7. AgriWebb

11.2.8. BovControl

11.2.9. BinSentry Inc.

11.2.10. Faromatics

11.2.11. FarrPro

11.2.12. H2Oalert

11.2.13. Hencol

11.2.14. Jaguza Tech, Moonsyst

11.2.15. Roper

11.2.16. Simple Ag Solutions

11.2.17. SomaDetect

11.2.18. SwineTech

11.2.19. Other Prominent Players

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

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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26.2% CAGR during the forecast period.

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