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AI for Good-Innovate for Impact



               Use Case – 5: AI-based Chatbot for Farmers                                                           5 - UW












               Country: India 
               Organization: Development monitoring and evaluation office (DMEO), NITI Aayog 

               Contact person: Dr. Tejal Agarwal tejal.agarwal1994@ gmail .com


               5�1�  Use case summary table 


                Domain          Agriculture
                                Decision making by farmers is influenced by varied factors such as climate
                Problem to be   conditions; soil fertility; crop breeding; water management; seed quality,
                addressed       pesticides, fertilizers, and machinery; environmental sustainability; farmer's
                                training and education; market access, and government policies.
                                Unifying the data of various agencies and using machine learning models to
                Key solution    predict the best plans, policies, and strategies to increase crop productivity
                                and economic growth.

                Technology      AI, open data, mobile apps, ML and geospatial analysis. 
                keywords 

                                Public(The data is open source and it is available on https:// agmarknet
                Data availability  .gov .in/ PriceAndArrivals/ Com modityDail yStateWise .aspx, https:// data
                                .telangana .gov .in/ search/ ?page = 2 & sort -order = asc & theme = Agriculture)
                                Text data (Time/date, district, mandal, market, crop, arrival, crop yield,-
                Metadata (type   model, number of houses, number of people, electricity load, rain(mm),
                of data) 
                                latitude, longitude.)
                                Machine learning algorithms to process and analyze, 
                Model Training
                and fine tuning   natural language processing (NLP) algorithms to extract insights from
                                textual data.

                Testbeds or     Government agencies to identify pilot sites, 
                pilot deploy-   integration with existing agricultural systems through feedback mechanisms
                ments           and performance metrics.



               5�2�  Use case description


               5�2�1  Description

               Revolutionizing the agriculture sector by unifying multiple government agency's data using
               Artificial intelligence models.

               In India, ~59% of the total workforce is engaged in the agriculture sector, contributing ~23% to
               GDP, according to a survey conducted by the Food and Agriculture Organization of the United




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