We include Milk in our daily diet as it is beneficial for our health. Therefore, users should know what quality of milk they are drinking. To monitor milk quality according to its features like ph, taste, etc. so that users know which milk to take. Intake of low quality milk can give rise to health issues, which should be provided. Milk providers using the model can give assurance to the users that whatever is provided is of good quality. Such way it is beneficial to the users for their health and the providers for their business.

What it does

The system based on inputs given like pH, Temperature, Taste, etc. gives the output if the milk quality is medium, high or low.

How we built it

The model is built using R language. We used a dataset available online on Kaggle. The dataset had 8 columns, 7 of which helped to identify the milk quality and 1 column for output. The data was first preprocessed, different machine learning models were applied and accuracy was found.

Challenges we ran into

Python is the commonly used language to develop any machine learning model. It was a challenge to use R, to find commands in R for various operations.

Accomplishments that we're proud of

We were able to get accuracy nearer to previous models. Tried out various machine learning models on our dataset.

What we learned

We learnt that model can predict milk quality using selected factors from the given dataset.

What's next for Milk Quality Prediction

Milk Quality Predictor combined with IOT will help in continuous monitoring of milk quality in our houses. A system can be developed that will notify the user the moment it finds milk is not of good quality after sensing the factors.

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