Sense Your Fruits
Sense Your Fruits
The food that we consume on a daily basis are more often than not are not familiar to us for it's stories, origin and culture. We eat, digest and excrete. How can the cosumers be made more aware of the food's journey from the land where it first originated.
Machine learning aided by computer vision was used to identify the fruits when picked from basket while folklore music is played in the background and country of origin of the fruit is shown on the wall. In order to recognise the fruits, they were first trained and a model was created.
Multi-culturism and globalisation have found their leg in the world. These phenomena have contributed hugely to the availability of produce which was unimaginable to be found in some places a few decades ago. A huge variety of goods are readily available as a consequence of these phenomena and we have forgotten to give credit where it is due. The food that we eat today is resourced from various parts of the world, of which we don’t know much about. My team wanted to explore the idea of making consumers aware of the fruits that they ate and something about the culture of the country where they came from.
Sense Your Fruit is a one-day machine learning project which aims to encourage people to look and interact with something they know with familiarity in a new light. What would it be like to experience a new dimension to something as simple and refreshing as a piece of fruit? When it comes to fruits, we have associations of taste, emotion and texture, but rarely do we visualise the places they come from and the cultural sounds of that region.
The focal point of the project is a fruit bowl that is placed on a bare table. When a person picks up a specific fruit, they hear music from the country that the fruit as imported from to Denmark. In front of them, simultaneously, they see a map visualisation of the country that the fruit comes from. The experience encourages the participant to think about the journey of the fruit from its origin to the person’s hand, spark curiosity in guessing where the music might originate from, and keep picking up different fruits so they can enjoy different musical experiences.
The project was completed using Wekinator to train various classifications of the fruits so that the machine could recognise each fruit and provide a corresponding visual and audio output.
Team: Fahmida Azad
Instructors: Andreas Refsgaard and Gene Kogan
Duration: 3 days
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