Artificial Intelligence in Agriculture Market Growing at the Fastest Rate in APAC Region

A plethora of artificial intelligence services such as recommendation engines, predictive analytics, computer vision, coupled with IoT devices can significantly boost agricultural productivity.

The technology is an application under machine learning development services can display stats remotely via a smartphone or similar device, allowing farmers to see instant alerts about what’s happening in their fields, whether it has to do with pests, disease, or something else.Learn more: Artificial Intelligence in Agriculture and Farming

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.

In 2016, the calculable worth additional by the agriculture business was calculable at but one percent people GDP.

Factors like global climate change, increase and food security considerations have pushed the business to hunt a lot of innovative approaches to safeguard and improve crop yields.

As a result, AI is bit by bit evolving as a part of the technology evolution of the business.In this article we have a tendency to explore the applications of computer science to know current and rising trends for business leaders, and gift representative samples of common applications.Artificial Intelligence within the Agricultural business - Insights Before:Based on our analysis, the foremost common applications of AI in agriculture make up 3 main categories:Agricultural robots: - corporation’s area unit developing autonomous robots to perform the required agricultural tasks, like harvest crops and fast quicker than human labor.

Crop and Soil observation: - corporation’s area unit developing laptop vision and deep learning algorithms to method knowledge compiled by drones and / or software-based technology to watch crop and soil health.Predictive Analytics: - Machine learning models area unit being developed to find out and predict numerous environmental impacts on crop yields like global climate change.Blue watercourse Technology - Weed management:The ability to regulate weeds may be a high priority for farmers associate degreed an in progress challenge as weed killer resistance becomes a lot of common.

per a quest study conducted by the Weed Science Society of America on the impact of uncontrolled weeds on corn and soybean crops, annual losses to farmers area unit calculable at $ forty three billion.

Companies’ area unit exploitation automation and artificial intelligence to assist farmers realize a lot of economical ways in which to safeguard their crops from weeds.

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