Convergence of 'the Cloud' and Laboratory Science

By Mark Burke, CIO, Accelerated Technology...

Convergence of 'the Cloud' and...

The Highway's Jammed With Broken Heroes on A Last Chance Power Drive

By Jonathan Alboum, CIO, The United States...

The Highway's Jammed With Broken...

Do IT Professionals Have a Social Responsibility?

By Sam Segran, CIO, Texas Tech University

Do IT Professionals Have a Social...

Leveraging GIS to Empower House Hunters in their Search

By Jeff McConathy, VP of Engineering of Consumer...

Leveraging GIS to Empower House...

The Future of Agriculture Technology

By Enterprise Technology Review | Wednesday, May 15, 2019

FREMONT, CA: The agricultural industry is one of the prime sectors and contributors to a country's gross domestic product (GDP). The primary challenges faced by agribusiness and farmers are the use of downgraded machinery and heavy dependence on archaic fundamental methodologies. The agriculture industry is in immediate need for a significant upgrade; the influx of contemporary technologies such as mixed reality (MR) and artificial intelligence (AI) can provide innovative and exciting avenues for agribusiness innovators.

MR, the result of curving concepts of the digital world with physical geography has gained tremendous traction in recent times. In 1994, Paul Milgram and Fumio Kishino introduced the term MR in their paper "A Taxonomy of Mixed Reality Visual Displays." Even though the concept of MR is in its nascent stage, the layering of digitally simulated objects on the real world has opened a box of limitless possibilities. Using the advanced computerized vision technology, graphical processing power, and display technology of MR, the innovators can access a multitude of application ranging from jotting the entire farming operations to having an algorithmic idea of every process. The 3D augmentation atmosphere allows the farmers to visualize different scenarios of crop cultivation and aid remote equipment monitoring or control systems.

AI and machine learning (ML) are statistical and analytical models that mimic the human behavioral pattern and execute the task accordingly. AI offers a detailed guideline procedure, which helps farmers to accomplish growing, sowing, harvesting and selling of produce. The integration of ML into robotics assists breeders in improving the operations of crop productivity, soil management, and animal husbandry.

Applications such as radio navigation, laser gyroscopes, AI-induced farming automotive, and MR-enabled helmets or goggles assist farmers in booming their crop yield and product quality by statistically analyzing a large amount of structured and unstructured data from multiple sources while reaching full automation.

In 2017, Global AI in the agriculture market size was evaluated at US$240 million, and it is expected to reach US$1100 million by the end of 2025.  With the integration of AI and MR, agribusinesses can equip the farmers with the right tools necessary for doubling their profits and increasing the nation's GDP.

Insurance in Agriculture: How technology is Creating Opportunities

The software-based supply chain has enhanced management and visibility....

Insurance in Agriculture:...

Agriculture Advancements: Paving the Way for Smarter and Sustainable Farming

Technological change has been the primary catalyst for increasing...

Agriculture Advancements:...

Big Data is now an Entrant to Agriculture, Farmers Must be Set to Its Course

Big data helps to predict the yield accurately with the use of...

Big Data is now an...

The Introduction of AI and Robotics in High-Tech Farming

Artificial intelligence (AI) technologies have revolutionized...

The Introduction of AI...

follow on linkedin follow on twitter Copyright © 2019 www.enterprisetechnologyreview.com All Rights Reserved | Privacy Policy
Top