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Data analytics in Agriculture

Big data in Agriculture collected from interactions regarding crops, weather, terrain, geographic conditions, water and more is stored and processed. http://bit.ly/2FO1gCy

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Data analytics in Agriculture

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  1. Application of Big Data Analytics in Agriculture

  2. Problem Statement • Farmers have limited knowledge of current technological advancements in agriculture, limiting production. • Consultants to guide Farmers limited, in remote areas. • Agricultural products are tried in a test environment ONLY, constraining usability.

  3. Business Solution A Mobile and Web-based IoT Application can solve the above problems by providing an Organized crop-planning and process management platform: • It enables farmers to analyze crop health in real-time. With secure messaging channel between consultants and farmers, help is readily available to farmers, thereby reducing damage to the crops. • It also allows Consultants to reach out to as many farmers as possible.

  4. Business Solution The Big data in Agriculture thus collected from such interactions regarding crops, weather, terrain, geographic conditions, water and more is stored and processed. This leads to the analytics part of our solution. By processing this data, the application will be able to assist: • Agriculture companies regarding the prospective success of products in different markets • Farmers about the success of various crops, the predictive impact of natural conditions, etc. • Consultants will learn more about the most affected geographic areas where farmers could be assisted to deliver higher productivity.

  5. Technology Solution Such a Web Application server can be developed using Golang and an android application using React Native. Hadoop Platform stores Big Data and deep learning/Machine learning allow the platform to provide: • Predictive Analytics: To predict the success of a product or crop or predict ill effects of a natural event on crops. • Historical Data Analysis: Process vast volumes of historical data regarding crops, geography, etc. • Real-Time Analytics: To provide Farmers with real-time assistance by analyzing information provided by them in real time.

  6. Business Benefit • Increased Agricultural Productivity through Agriculture Data • Greater success of Fertilizing Products across a variety of geographic conditions for Agriculture Companies. • Avoid ill effects of a particular natural occurrence.

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