60% of India's economy relies on agriculture. However, education in rural India is a big problem for several reasons. One of the major reasons that contribute to this problem is the fact that parents are reluctant to send their kids to school as they would rather have the kids help with household chores or daily farming activities. Due to this, the farmers' kids grow up to have poor mathematical and cognitive skills and continue to lead the same lives as their parents. Today, India has one of the highest suicide rates amongst farmers as they are unable to manage their funds and are continually exploited by landlords and middle men. We decided it was time to alter this mindless reiterative process by making a small change.
What it does
E-Krishi ("E-Farmer" in Hindi) is meant to be a vibrant farming simulator app that enhances the mathematical and cognitive abilities of kids in rural India through everyday objects around them. In addition, the application uses geo-analytics to make the simulator as real as possible, i.e. crops in the simulator, grow similar to how they would grow around the user's location. Moreover, all the cost and selling prices of the crops featured in the simulator are scraped from the official website of the Agricultural Market of India (http://agmarknet.dac.gov.in/PriceTrends/Default.aspx). The application also uses a critical algorithm to determine what could be the best crop to grow given the location and time of the year. Furthermore, users can also gain important information about certain crops in the game, for general education purposes. At the end of all this, kids can send a text to their parents about what they learnt - which makes the parents involved in the learning process of their kids. We feel that using this familiar and engaging medium to enhance the cognitive abilities of kids in rural India will make parents less hesitant to allow their kids to learn and it would also prove be a fun activity for the kids.
How we built it
The app was built with a Python frontend and backend, using Tkinter graphics. The APIs used were: Open Weather Map API, Google Maps Elevation API, Exotel API and Geocoder 1.6.4.
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