Some of the key players profiled in the Artificial Intelligence in Agriculture Market include IBM, Cainthus Corporation, Connecterra B.V, CropX Inc, Precision Hawk Inc., The Climate Corporation, Trace Genomics, Inc, and Vision Robotics Corporation.
— Increasing crop productivity through deep learning technology, and government support to adopt modern agricultural techniques are the major factors propelling the market growth. However, factors such as high cost of gathering precise field data, and limited availability of historic data are hampering the market growth.
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Artificial Intelligence in agriculture has various applications ranging from rural automatons, computerized water system frameworks, facial acknowledgment, and driver less tractors. This application is done in a relationship with an alternate sort of sensors, radars, GPS frameworks, other cutting-edge contraptions dependent on AI. Seeing these broad applications, artificial intelligence in agriculture is getting a colossal reaction from investors all around. The increasing utilization and rising necessity of better yield of products are evaluated to be one of the essential points that are fuelling the demand for artificial intelligence in agriculture.
Based on the technology, the computer vision segment is going to have a lucrative growth during the forecast period owing to the increased use for agricultural applications such as plant image recognition and continuous plant health monitoring and analysis. The other factors include higher adoption of robots and drones in agriculture farms and increasing demand for improved crop yield due to the rising population. The computer vision allows farmers and agribusinesses alike to make better decisions in real-time.
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By geography, Asia Pacific is going to have a lucrative growth during the forecast period due to the wide-scale adoption of AI technologies in agriculture farms in this region. AI is increasingly applied in the agriculture sector in developing countries, such as India and China. The increasing adoption of deep learning and computer vision algorithm for agriculture applications is also expected to fuel the growth of the AI in agriculture market in the Asia Pacific region.
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• Computer Vision
• Machine Learning
• Predictive Analytics
• Agriculture Robots
• Drone Analytics
• Fish Farming Mangement
• Labor Management
• Livestock Monitoring
• Precision Farming
• Smart Green House Management
• Soil Management
• Supply Chain Efficiency
• North America
o Rest of Europe
• Asia Pacific
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o South Africa
o Rest of Middle East & Africa
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