AGRICULTURAL TECHNOLOGY 

                                  

                             ARTIFICIAL INTELLNCIGE IN AGRICULTURAL

     

Editor :vimal \ prajapati

SCOPE OF AI IN AGRICULTUR

Agriculture is both a major industry and foundation of the economy. In 2016, the estimated value added by the agricultural industry was estimated at just under 1 percent of the US GDP. The US Environmental Protection Agency (EPA) estimates that agriculture contributes roughly $330 billion in annual revenue to the economy.

Factors such as climate change, population growth and food security concerns have propelled the industry into seeking more innovative approaches to protecting and improving crop yield. As a result, AI is steadily emerging as part of the industry’s technological evolution.

In this article we explore applications of artificial intelligence to provide business leaders with an understanding of current and emerging trends, and present representative examples of popular applications.

Agriculture is seeing rapid adoption of Artificial Intelligence (AI) and Machine Learning (ML) both in terms of agricultural products and in-field farming techniques. Cognitive computing in particular, is all set to become the most disruptive technology in agriculture services as it can understand, learn, and respond to different situations (based on learning) to increase efficiency. Providing some of these solutions as a service like chatbot or other conversational platform to all the farmers will help them keep pace with technological advancements as well as apply the same in their daily farming to reap the benefits of this service. Currently, Microsoft is working with 175 farmers in Andhra Pradesh, India to provide advisory services for sowing, land, fertilizer and so on. This initiative has already resulted in 30% higher yield per hectare on an average compared to last year. Given below are top five areas where the use of cognitive solutions can benefit agriculture.