Inspiration

We have started with a single aim that we should create a service that should be useful and that should be around the theme of the hackathon. Then we figured out that IBM Bluemix services can be leveraged to help farmers in reducing risks.

What it does

We have developed an advisor to reduce risks while farming. We help farmers to decide what corp can yield more benefit for the year in that particular location. We analyse data based on past history, current weather, climate conditions and satellite imagery. While farming, we help them to take best decisions.

Problem

Taking decision to decide the crop will be the biggest risk, a farmer take while farming.

Solution

SuperAgro suggest them to utilise their agricultural land in the most efficient way.

How we built it

We have built this application with a help of bunch of IBM bluemix and watson services. We have our server running on node.js runtime which gives previous year statistics data. We pulled data from NASS USDA server and kept it in bluemix server. We use tradeoff analytics service for finding the best crop for the year in a particular area. We use insight weather service to pull weather and climate based intelligence. We use analytics server integration and also auto scaling option for ever growing statistics data. We use staellite imagery from urethecast service to do histogram based image comparison to analyze changes in the field.

Challenges we ran into

Intergrating satellite imagery and analyzing the data using bluemix services was a tedious process and we were able to get the optimized result at the end.

Accomplishments that we're proud of

Learning the new things in 24 hours and completing an awesome app is our proudest achievement.

What we learned

We have used a bunch of IBM services and also we have learnt how to use real time satellite image and how to make it useful to someone on a village side

What's next for SuperAgro

If Swiss Re can fund us, we can create the revolution in Agriculture field and no farmer would sleep hungry ever.

Along with that, this is a product which has a lot of interesting use cases and could make more mature with space data, government data and other.

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