Inspiration

We are students from developing countries. Though there countries have are progressing with passing time, farming still remains a major occupation. It is sad to know that even though farming runs a major part of the country's economy, it is still widely under developed. We thrive to use out knowledge in technology to make farming more efficient and automated. Using machine learning in analyzing weather and farms to need to make farming simpler and easier.

What it does

It analyzes your farm and its needs (water in our demo) and makes sure your crops are healthy and well maintained. You can ask Alexa for suggestions and also esquire whether or not your crops need water, and if they do, it will automatically trigger the irrigation system. If you forgot to water your crops and if they're in need of water, you'll get alerts asking you to water them at the soonest.

How we built it

We first gathered data and made a webpage which stores and analyses your farm and it's needs. Then we used Twilio's API and ran it using PHP to send alerts as and when required. Alexa Skill kit was used to develop the Alexa skills and IFTTT to contact the irrigation system.

Challenges we ran into

Being Freshman with very limited knowledge, our biggest challenge was the coding for the project. All of us watched tons of tutorials to get the best of what we could out there. We learnt Alexa and using the Twilio API from scratch. None of us had ever tried our hands on Alexa skill development or using and API before this.

Accomplishments that we're proud of

We finished it! At the start, none of thought we would be able to but we did. We had quarrels, problems, lack of knowledge and resources but we did it. We made through all these problems and are proud of what we present to everyone today.

What we learned

There are endless possibilities and endless knowledge. We learnt how to make an Alexa skill and use APIs and develop new custom skills. We learnt to analyse Data and classify with Machine Learning APIs from Nvidia. We also set up multiple IFTTT tasks for Alexa to

What's next for Crop Check

The world is the limit and no one knows where this technology can be used. IoT, Machine Learning, Automated Systems and alerts, this project can be implemented and modified to meet the requirements of various fields. In the future, we plan to extend Crop Check by adding a reply system with Twilio, which will activate the irrigation system by a SMS. We also plan to extend the crop management services to sunlight, soil quality, pesticides, etc using sensors. Using Machine Learning, we also plan to make the harvesting and sorting of the harvest more efficient and fast.

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