AgriculturalProduceForecast
(sunlight, temperature, humidity, electrical conductivity, rainfall). Capture the data with all this information. The idea is to get the data in the platform or upload the excel data (via .csv, .txt or xml) to the application, compare with the historical farm parameter data, develop a model/algorithm & be able to forecast yield and display the output of the past 3 and next 3 months. To integrate the application with a social media module (say a farmer’s network) or a community (of botanists, entomologists) and be able to provide answers to real farm problems – pests, leaf conditions etc. within 24 hours.
Install / Use
/learn @InternityFoundation/AgriculturalProduceForecastREADME
AgriculturalProduceForecast
Web Application in app.py Model building in models/Agriculture.ipynb
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