COVID-19 Impact Analysis on Artificial Intelligence in Agriculture Market report published by Value Market Research provides a detailed market analysis comprising market size, share, value, growth and trends for the period 2019-2027. The report encompasses data regarding market share and recent developments by key players. Moreover, this market report also covers regional and country markets in detail.
The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the Artificial Intelligence in Agriculture include Microsoft, Integrated IBM Corporation, Deere & Company, The Climate Corporation, AgEagle, Aerial Systems Inc., Granular, Inc., Tule Technologies Inc, Descartes Labs, Inc., Prospera Technologies, Taranis, aWhere Inc., GAMAYA, ec2ce, PrecisionHawk, VineView. This section includes a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.
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Market Segmentation
The broad Artificial Intelligence in Agriculture has been sub-grouped into the Component, Technology, Application and Region. The report studies these subsets with respect to the geographical segmentation. The strategists can gain a detailed insight and devise appropriate strategies to target specific market. This detail will lead to a focused approach leading to identification of better opportunities.
By Component
- Hardware
- Software
- Service
By Technology
- Machine Learning & Deep Learning
- Predictive Analytics
- Computer Vision
By Application
- Precision Farming
- Drone Analytics
- Agriculture Robots
- Livestock Monitoring
- Others
By Region
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
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Regional Analysis
Furthermore, the report comprises of the geographical segmentation which mainly focuses on current and forecast demand for Artificial Intelligence in Agriculture in North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. The report further focuses on demand for individual application segments in all the regions.
Table Of Content
- Preface
- Executive Summary
- Mining Automation – Industry Analysis
- Value Chain Analysis
- Impact Analysis Of Covid-19 Outbreak
- Global Artificial Intelligence in Agriculture Analysis By Component
- Global Artificial Intelligence in Agriculture Analysis By Technology
- Global Artificial Intelligence in Agriculture Analysis By Application
- Global Artificial Intelligence in Agriculture Analysis By Region
- Global Artificial Intelligence in Agriculture Analysis By Geography
- Competitive Landscape Of The Artificial Intelligence in Agriculture Companies
- Company Profiles Of Artificial Intelligence in Agriculture Industry
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Global agriculture industry has undergone significant and dynamic changes in the past decades, specifically with the introduction of technologies introduced to improve crop yield.
With the increase in world population leading to the rise in the global demand for food, growers are prompted to adopt the most advanced and productive methods in farming operations to increase crop yield.
Introduction of precision agriculture technologies has also resulted in the creation of hundreds of thousands of data points on farms.
The rise in these data points has enabled data-driven farming, aiding the growers and consumers of agriculture products with insight-backed decision-making.
To navigate through these big data in farms and to attain efficient farming solutions, the industry is bringing about significant product innovations in farm data analysis using the artificial intelligence technology.Artificial intelligence technology brings the concept of cognitive computing to agriculture where the farm equipment intelligence is modeled on human intelligence.
Artificial intelligence technologies help farmers in optimizing their planning to generate profitable crop yields using predictable analytics for agri-input choices and farm process planning.
Global Artificial Intelligence in Agriculture Market was valued US$ 575.3 Mn in 2017 and is expected to reach US$ 3090.8 Mn by 2026, at a CAGR of 23.39 % during forecast period.
By way of the farmers are moving more towards automation, drones and robots are becoming essential part of agriculture farms and are improving yield and improving the product quality.
With the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are currently being able to independently monitor all behavioral aspects in a group of cattle.
So that, with the implementation of AI in agriculture, cattle facial recognition can enable diagnoses of lame cows before they show plain symptoms, so, saving farmers from the loss of low milk production.
It collects data from the field like water, soil, aerial images, and integrates with the device to take required decisions and use the available resources in an optimum method.
Major obstacles in the growth of AI market in agriculture are high cost of cutting-edge AI technology and lack of awareness of AI in agriculture between end users.
