AGRICULTURE DATA MONITORING

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DEVELOPING A SYSTEM FOR AGRICULTURE DATA MONITORING

Monitoring crop yield is central to addressing decisions on the product’s inventory strategy, revenues, and pricing. In this project, we developed a scalable system to predict crop yield using a combination of historical data, remote sensing data and advanced machine learning modelling.

The system helped the client monitoring and precisely evaluate the effects of their quality certificate programs for farmers all-over Indonesia.

The evaluation approach is passed on a Regression Discontinuity Design in which variations in the quality and levels of production of a given crop are compared just before and after the introduction of the certificate program in a given area.

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Complex relations and complex models

SUMMARY  By carefully checking the assumptions of our modelling approach and the structure of our data, we can pick a better modelling

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