PRE2019 3 Group5

Group members

Name	Student ID	Department
Ana Maria Risnoveanu	0000000	Electrical Engineering
Stacey Elshove	1279998	Psychology and Technology
Petru Radulescu	1371320	Psychology and Technology
Yiqin Hou	1281135	Electrical Engineering
Tobias Hilpert	1281070	Chemical Engineering

Problem Statement

Today the technology for recycling already exists and is put to use in most first world countries, but at times it can be inefficient because of mistakes made by all of us when throwing the trash, either unwillingly or because of our ignorance. So to mitigate this and help create a better planet for the future generation, we have come up with the idea of a smart trash can, that will use a huge array of sensors and cameras to determine whether the waste should go in the glass, plastic or paper bin. This product will be small enough to fit in our homes and, in the future, it could be upscaled to service a full residence, like a block of flats.

Objectives

• Design an affordable smart trashcan that fits into our homes.

• Use machine learning and AI to sort the trash into their corresponding compartment.

• Find suitable technologies to achieve this.

USE Aspects

Society

Automatizing recycling will shift the topic from a widely recognized theme to an issue to be solved by experts. Recycling campaigns will likely get far less attention than they do now and did in the recent past. This might slightly counteract the intended effect of increasing recycling. These effects seem unlikely to outweigh the advantages gained in the efficiency of sorting, however. There will also be a shift of who holds the responsibility for recycling. This responsibility is currently largely held by the consumer who is expected to throw garbage into the designated bins. If this process is largely automated the responsibility will either be carried by a few enterprises or, shared among society as a whole if the adoption of smart cans is facilitated through government owned utilities.

Enterprise

Recycling firms are struggling to be profitable in large part due to expensive and inefficient separation of waste feed-streams. An automated bin will judge much more accurately which products are likely to be recyclable than the average consumer. This improved recycling prior to waste collection would drastically lower the cost of recycling and increase profitability of these plants, therefore encouraging new investments into such businesses. The increase of separated waste arriving at recycling plants rather than landfills will also allow for these plants to invoke the economics of scaling up to further increase profitability, making such businesses even more attractive. It thus likely that widely accessible smart bins will grow the recycling industry.

Task distribution

Week1

Name[total hours of work]	Tasks and hours
Ana Maria Risnoveanu	...
Stacey Elshove	learn wikitext[2h], Reasons whyand summary[4h], What already exists and summary[3h]
Petru Radulescu	Objectives; Problem statement; ...
Yiqin Hou[?h]	Papers about X-ray imaging/Object recognition searched and studied[?h]; summary[?h]; Learn wikitext and make template for the group wiki[4h]
Tobias Hilpert[14h]	Literature study into waste sorting[4h], Research into Infrared spectroscopy[8h], Learned wikitext[2h], Wrote Enterprise and Society aspect[]

SotA

Reasons why

Too much rubbish

Nowadays there is an over load in rubbish in cities and in rubbish dumps, he main reason for this is that there are many recyclable materials that just get throw away in the normal rubbish. Having smart bins will help reduce this waste and the resources we use to make produces. Sharma and Singha, found that the pile up of rubbish is leading to many diseases and came up up with a solution about a Smart Bin that will alert the collector when the bin is full and they will come a collect it. This will prevent rubbish over load for example, rubbish falling out of bins or piling up next to them because they are full. However this is just a start to our problem as this still does not solve the recycling issue, this is dealt with in the next section.

Easy to recycle

The best way to get people to do things is to make it easy for them to do it. When it is easy to do something people are more inclined to do it than when they would have to put lots of effort in for example to have to take their separate plastics bag to the supermarket to recycle it when they could just add it to the normal rubbish.

Lack of knowledge

Thomas etal, found that many people are unaware of what happens after they throw something away, or the benefits of recycling. Creating more awareness will cause people to understand what their actions will lead to and hopefully impact the way they behave.

Fun to recycle

When something is fun to do as when it easy to do people are more inclined to do it. This can be seen in the Efteling in the Netherlands, they have paper bins which are shaped like people who have their mouth open. People can through paper into their mouths and then they are thanked for recycling (feeding them). This make people more inclined to recycle as now it is fun to throw the paper into his mouth and they also receive positive feedback.

What already exists

Bin e is a smart bin that sorts anything you throw away . It sorts the items into plastic, glass, paper and metal. This bin is only for recyclable materials thus people still have to put some thought into whether they can recycle it or not.

As mentioned above the Smart bin, which informs the collectors when it is full.

Detection

X-ray

Inspired by security machines, X-ray imaging could be a usefull tool in detcting the type of rubbish. X-ray imaging makes use of the property of X-ray that it attenuates differently accorss difderent materials. For example metal atoms and ions attenuate more X-ray than normal organic tissue, such as fat and protein. Some new X-ray imaging techniques could even determine the chemical structures that form within the materials. With such techiniques and some morden X-ray imaging detectors , the bin can distinguish materials much more accurate than using normal X-ray imaging. It is also possible to distinguish different types of plastics with X-ray imaging, which further increases the recycling sorting process.

Despite its reliable performance in detecting metal and different kinds of organic materials, an X-ray imaging system is too expensive to implement in a household trash bin. Even the cheapest X-ray tubes cost $100 to $500 each, let alone the detectors, power supply and other systems.

Computer vision and image processing

Object recognition

Infrared Spectroscopy

Infrared spectroscopy can be classified into different categories based on the wavelengths used. This detection method is both cheap and fast enough for practical applications in waste sorting. Near Infrared (NIR, wavelength 1-1.7µm) Spectroscopy is already deployed for uses in plastic separation. NIR has the ability to excite overtones of molecular vibrations and therefore can give information on the chemical composition of the sample. NIR spectroscopy can also be used for different kinds of waste, such as construction debris . There are clear limitations when analysing black and coloured samples though, as their reflectivity in the NIR spectrum is too low to allow for signal-to-noise ratios high enough for proper identification. To overcome this difficulty NIR spectroscopy can be enhanced with longer wavelengths. It has been shown that combining NIR with Midwave Infrared (MWIR, wavelength 3-12µm) significantly improves the performance of detectors for black and opaque products. This can be extended to multiple spectra in hyperspectral imaging techniques, which probe a wide range of wavelengths even in the visible spectrum for material identification. These systems have also been shown to work at the speeds which would be needed for practical applications. FTIR spectrometers are simple enough devices that handheld versions with sensitivities good enough to separate materials exist. .