Inspiration
Agricultural Runoff is water that originates from farms due to irrigation, rain, or melted snow. This runoff water can contain fertilizers, pesticides, animal waste, or soil particles, which can enter and contaminate sources of drinking water.
What it does
It uses a complex mathematical equation to find optimal irrigation levels.
How we built it
We used an express.js backend in order to make requests to the DarkSky weather API, gving us highly localized and accurate predictions of the weather based on latitude and longitude. From there, based on our research, we formulated a complex mathematical equation based on exponential regression allowing our algorithm to predict the optimal time for watering. The result is a mobile application built in React-Native that interfaces with our API and provides hyper localized, accurate weather data and shows the increase in irrigation needed in the next 7 days of the week, as well as the best day to irrigate that will use the least water.
Challenges we ran into
Initially, we wanted to implement a form of multivariable regression to determine the optimal time for watering, but even after extensive research, we were not able to find sufficient training data. We then decided on using exponential regression as a proof of concept instead.
Accomplishments that we're proud of
The use of a complex algorithm that accurately predicts the percentage of ideal irrigation levels needed to water a plant based on environmental conditions.
What we learned
We learned about the optimal conditions for water absorption in plants.
What's next for e-rrigation
We want to modify our current algorithm to account for variables such as ground incline, altitude, and cloud cover, to give us more realistic results. We also want to implement a way to take plant types into account using a picture of a given plant and a classification algorithm.
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