기술
Impact of existing heterogenous bacterial composition in the soil plays one of the most critical roles in estimating how much yield is possible of A particular crop in A particular soil. Once successful in estimation, we can always increase the yield by meticulously enriching the soil by right bacterial strains.
The project i.e., app is about how to do smart agriculture and estimate the accurate crop-yield based on hundreds of different bacterial strain/composition found in the land using Machine learning models and algorithms. This was made possible by collecting, examining and processing a huge dataset of farming lands, and by building/training a machine learning model to predict crop yield from soil composition.
As this is a pure machine-learning project, the first step that I did was to access the right database. Then I massaged the dataset and processed it for my machine learning model. Once data was properly organized, the next job was to research out the most fitting and applicable models. After several weeks of rigorous study, I identified 3 most eligible models for this type of data science problems.
The next job was to study the internals of these 3 models and understand the implication of several hyper-parameters that I need to tune-in for accurate outcome from the model.
Once I fully studied all the hyperparameters, it was time to train these models. My dataset is enough heterogenous and encompass all major soil composition in the world. I carried out extensive research pulling data to feed my models. The final stage of the project is testing. This is the time that proves how much of my 6 month effort paid off.
Though the backend of the project is very technically advance and computationally intensive, every effort has been made to abstract out these details from the end-user. The goal was to keep the end-users i.e., farmers as much abstract and seamless as possible in their user-journey with the application. As a result, a very intuitive mobile app was developed. This app works on both platforms i.e., iOS and Android and usable by any farmer by simply signing up and uploading their farming land's soil composition report obtained by any certified laboratory.
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