ARTIFICIAL INTELLIGENCE TO
IMPROVE WASTE MANAGEMENT

Problem

We all travel, whether is for business or pleasure. During our journeys we read, we drink, we eat something, basically we produce trash. Each passenger on a standard flight produces an average of 1.4 kg of trash; if we think about all the flights that occur every year, and all the passengers on them, we are talking about a huge amount of trash. According to VOX, every year airplane companies produce more than 9K tons of plastic and enough aluminium to produce 58 new Boeing 747. This data, which already are impressive, are more frightening if we consider that most of this trash is not differentiated: on airplanes 75% of the produced trash is not sorted, and on trains it represents the 70%.

Do we know how much it costs not to differentiate?

A lot: in Italy manage a ton of undifferentiated trash is 32% more expensive than managing a ton of sorted waste. And do we know how much it costs us not to differentiate? A lot as well: it costs us more than 45% of CO2 emissions in the atmosphere every year. So, if bad waste sorting is so costly for companies, and so dangerous for the environment, why companies do that? Because there is no space on board to differentiate trash, since the design of both airplanes and trains has been done to maximise the number of passengers on board. This is why we developed a solution which is able to differentiate trash at its direct arrive at the airport or station.

According to the International Air Transport Association (IATA)

The average passenger generates 1.4 kg of waste per flight

SOLUTION

The innovation of Re Learn’s solution consists in having created a device with all the features proposed individually by our competitors. NANDO automatically recognize and sort several wastes that are inserted at the same time. Thanks to a machine learning software and a camera system, it recognizes waste. By using the Artificial Intelligence, the image recognition algorithms, NANDO recognizes the material of which the waste is composed and then with a mechanical system, grab and sort the waste into the correct container.

NANDO handles the transaction towards a waste sustainable management for the activities without huge investments. NANDO simplifies the circular economy chain by making logistics more efficient and reducing the level of contamination of waste thanks to a correct differentiation, thus allowing their reuse.

We want to use technology to turn waste into a resource

We want to use technology to turn waste into a resource

SOLUTION

The innovation of Re Learn's solution consists in having created a device with all the features proposed individually by our competitors. NANDO automatically recognize and sort several wastes that are inserted at the same time. Thanks to a machine learning software and a camera system, it recognizes waste. By using the Artificial Intelligence, the image recognition algorithms, NANDO recognizes the material of which the waste is composed and then with a mechanical system, grab and sort the waste into the correct container.

NANDO handles the transaction towards a waste sustainable management for the activities without huge investments. NANDO simplifies the circular economy chain by making logistics more efficient and reducing the level of contamination of waste thanks to a correct differentiation, thus allowing their reuse.

They support us in our mission