AI Challenge Crop Recommendation Using TPOT Model

AI Challenge Crop Recommendation Using TPOT Model

Use Case Description

Precision agriculture is in trend nowadays. It helps the farmers to get informed decisions about the farming strategy. Here, I build a predictive model to recommend the most suitable crops to grow on a particular farm based on various parameters.

Machine learning is an important decision support tool for crop yield prediction, including supporting decisions on what crops to grow and what to do during the growing season of the crops. Several machine learning algorithms have been applied to support crop yield prediction research

Parameters :
N - ratio of Nitrogen content in soil
P - ratio of Phosphorous content in soil
K - ratio of Potassium content in soil
temperature - the temperature in degree Celsius
humidity - relative humidity in %
ph - ph value of the soil
rainfall - rainfall in mm

How to use :

Crop Recommendation system For this go to the Predict section of UiPath Apps and then enter the corresponding nutrient values of your soil, Note that, the N-P-K (Nitrogen-Phosphorous-Potassium) temperature - the temperature in degree Celsius, humidity - relative humidity in %, ph - ph value of the soil, rainfall - rainfall in mm values to be entered should be the ratio between them. the crop Recommender system will suggest which type of crop/fruit to grow in order to increase production.


Other information about the use case

Industry categories for this use case: Other Sector

Skill level required: Intermediate

UiPath Products that were used: UiPath Studio, UiPath AI Center, UiPath Apps, UiPath Data Services

Other applications that were used: EXCEL

Other resources: -

What is the top ROI driver for this use case?: Accelerate growth and operational efficiency


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