Food for Thought

Your challenge is to consider the journey of food to your plate, determine how disruptions from the COVID-19 pandemic are affecting the food supply locally and globally, and propose solutions to address these issues.

SmartAgro ( An innovative way of farming)

Summary

In this period of pandemic with borders sealed , food crisis has become a major concern. According to some statistics in Nepal currently more people are dying due to scarcity of food than COVID-19 itself. Luckily we are born in an era of technological advancement, here we propose a smart way to tackle the food crisis by increasing the crops production rate, ensuring proper health of crops, market value and demand of the crops and plantation of the specific crop in response to the AI predicted.

How We Addressed This Challenge

To tackle the problem raised in agriculture because of climate change , our system uses NASA open source data and trained AI model predicts the future temperature and precipitation . This way farmers  can cultivate the crops as per the predicted climate(Season). Besides this to tackle the problem of lack of PH test and expert guidance we have implemented chat service with our agriculture experts and PH  test request .Also , we have on market  demand crops and brief description of any specific crop grown in that locality . In our model we have only implemented the data of Kathmandu district  .

How We Developed This Project

Since, Nepal is an agricultural country if technology and agriculture are put together , our team believe that the crops production rate will drastically increase . In this period of pandemic high production of crops in local level could be the potential solution to tackle the food crisis  . This  was our main inspiration to choose this challenge . 

First we imported the open source data from NASA ,  After  data cleaning , pre -processing and analyzing to understand the Data. we did visualization of the data using Seaborn , Plotly  . Then we implemented Random Forest Regressor on the top of pre- processed data to predict future temperature and precipitation . We used python to make a backend server and a RestAPI using Django . so , that anyone with the valid authentication can use our prediction . Using this feature we have developed  web app using HTML   and Mobile App using flutter SDK  . 

 We had some trouble to get the  higher accuracy on trained model and some specific details on few crops were not available . 

Project Demo

https://drive.google.com/open?id=1AFHHOkvcA1_wG3dlZf1dXJETG0SvVAN7

Tags
#SmartAgro #InnovativeAgriculture #FSociety
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.