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Home page of the website
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Agricultural data analysis
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Total number of states and the states whose data analysis has been done
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Grouping states into different sets for rainfall analysis
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Rainfall analysis graphs ( growth vs year )
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Temperature analysis ( temp vs year )
Agriculture prediction web application built using python and R programming.
It was way back in 2017 when farmer's protest begin to gain my attention and still then i am catching up with all the news and updates about their protests and how they're eventually ending their life.The state governments have also taken upon themselves to introduce many other new initiatives but it still remains an uphill task to initially put an end to these suicides and secondly actually improve the conditions set for the farmers in order to prevent such accidents in the future. Loss of a large number of farmer's life was the main reason behind building this project.
Agriculture prediction web application let farmers predict several natural factors such as rain and temperature in a particular place in advance. It helps them to be prepared before hand and take necessary steps to stop crop failure. The web application also contains agricultural data analysis which helps farmers to have a better understanding through graphs.
The web application was built using python . Editor used in building this project is VsCode. Rainfall, Temperature and other API's are taken from Kaggle as csv formats and the web application is hosted using Github pages.
As i was working solo , the most difficult challenge i faced is to complete the entire project on time and submit it before deadline, which i am doing right now . It took me 17 hour's of continuous coding to get everything on time.
Accomplishments that I'm proud of is i tried to solve one major socio-economic problems of our society through available technologies and hardworking.
I learned a lot of things building this web application. Got a more stronger hold of python, studying rainfall graphs gave me a brief idea about the places facing water scarcity and how miserable a farmer's life would be there. Overall studying gave me a idea about the variety of crops and the temperature they are best suited for.
I would take Agriculture Prediction web application further into different segments and make its UI and language a bit easier for less educated farmers to understand and take the best of it.
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