Food is by far one of the most important needs of humanity. If we can get to reduce hunger by improving agricultural productivity, we can as well through the process improve the quality of life and also bring about social good.

What it does

FarmPro is a handheld device that can be used by farmers to carry out soil analysis on their farmland in order to make predictions on the best crop suitable for the soil.

How we built it

The device was built with a Raspberry Pi microprocessor integrated with sensors like moisture sensor, temperature, and humidity sensor. The Raspberry pi takes in the input of these sensors based on a soil sample and gives out a prediction on whether a crop is fit for the soil or not. Based on locally available soil data, a model was trained and the model is used in real-time by the raspberry pi to output predictions.

Challenges we ran into

A number of challenges were run into while building this project, first was getting a dataset to be used for model training. Another challenge is getting sensors to be integrated with the Raspberry pi.

Accomplishments that we're proud of

An accomplishment we are proud of is being able to make real-time predictions using Machine Learning on the raspberry pi. Due to time, our project was not well packaged in a device but we are able to have the whole engine functional.

What we learned

We learnt how the availability of nutrients and other environmental factors contribute to crop yield and productivity

What's next for FarmPro

Having FarmPro well packaged and compacted and having support for other crops that can be planted

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