The project: Ishango.ai Fellows Bright Aboh and Aimable Ishimwe Manzi worked alongside the data science team at Philip Morris International (PMI) on a project to remotely identify tobacco fields using satellite imagery data. The aim of the project was to extract key information that could be used to improve the socio-economic wellbeing of the farmers by suggesting best practices.
The outcome: Bright and Aimable built a model that could identify tobacco leaves and therefore tobacco farms and also measure the land surface which the crop was being grown on. The ambitious pair went even further and began to explore how else the model could be applied. Realising that the model had wider potential applications, they explored and eventually created an application that can be used to analyze any geographical region around the world and classify other types of land surfaces, for example, an urban area or a body of water.
Watch below to hear the pair describe their solution and click here to read more about their application.
“It’s been a great success, It’s added value. The students proved they were extremely skillful. They were really capable of pursuing data science projects with limited supervision. And there were no communication or time difference issues. They really helped our team.”Krzysztof Stec, Lead Data Scientist at Philip Morris International
Having delivered impressive results during their Fellowship, Aimable and Bright received a contract offer from Philip Morris International to enable them to continue exploring their technology.
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