PRE2019 3 Group5

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Group members

Name Student ID Department
Ana Maria Risnoveanu 1230444 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

User

With either the increase in the awareness of environment protection or relative regulations, people are paying more attention to rubbish sorting nowadays. However, not everyone has the correct knowledge of sorting, expecially in the countryside and some developing countries. Moreover, most people only have trash bins for domestic wastes in their homes. They have to mannually separate other watstes like glass and papers. All these problems could be solved with an automatic sorting trash bin. People no longer need to know or to think about what type of wastes they are throwing away, becaused the trash bin will do it for them. It will not only save space and time, but also will increased the efficiency at recycling centers, since the trash would already be sorted before they are transported.

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.

Approach, milestones and deliverables

Task distribution

Week1

Name[total hours of work] Tasks and hours
Ana Maria Risnoveanu [8h] learn wikitext[1h], Material sensors [5h], Approach-Milestones-Deliverables [1h], look over internet for other ideas [1h]
Stacey Elshove[10.5h] learn wikitext[2h], Reasons why[1][2]and summary[4h], What already exists[3][1][4] and summary[4.5h]
Petru Radulescu[6h] Leran wikitext[2h]; Objectives[1h]; Problem statement[1h]; Sorting systems[2h]...
Yiqin Hou[13h] Papers about X-ray imaging[5][6][7][8]/Object recognition[9] searched and studied[7h]; summary[2h]; Learn wikitext and make template for the group wiki[3.5h]; User aspect[0.5h]
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, [1] 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[2]. 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[3] . 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[1], which informs the collectors when it is full. The bin uses Ultrasonic sensors to determine how full the bin is.


[4]

Detection

X-ray

Inspired by security machines, X-ray imaging could be a usefull tool in detcting the type of rubbish. X-ray imaging [7]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[8]. With such techiniques and some morden X-ray imaging detectors [6], 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[5], 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

An alternative could be object recognition, by simply mounting a camera in the container and train an AI system to recognize different types of wastes. With the technique of using discriminative parts[9], the system could be even more precise. For example, it can distinguish the words on the package of the waste. Computer vison could be implemented together with other techniuqes like infrared spectroscopy, to increase overall effectiveness.


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. [10] NIR spectroscopy can also be used for different kinds of waste, such as construction debris [11]. 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. [12] 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. [13] FTIR spectrometers are simple enough devices that handheld versions with sensitivities good enough to separate materials exist. [14].

Available sensors

There are several sensors available on the market: electro-mechanical, pneumatic, magnetic, inductive, capacitive, photoelectric, ultrasonic. The electromechanical sensor only shows how resistive an object is, which might be important but not sufficient here since two different objects could output the same value [15]. The same is the case with a pneumatic sensor, which just differs in the way it is built [16]. The magnetic sensors are of no use since there is no magnetic field created by rubbish [17]. On the other hand, although it also uses an induced magnetic field, the inductive sensor (also known as inductive proximity sensors) may prove successful in the detection of metallic materials. Unfortunately, domestic trash mostly includes other types of materials and aluminium cans, for instance, are usually recycled in waste. Then, there is little difference between the applications of inductive and capacitive sensors [18] and spending time in choosing between them will only be useful if the team decides on the categories of rubbish. A photoelectric sensor is another proximity sensor, which can only be used to check the absence of an object which leads to the last option on the list: ultrasonic sensors. Although these sensors cannot detect different types of materials, they do offer more information: the distance to an object or the speed of the object; they are reliable and can be used in many applications Cite error: Closing </ref> missing for <ref> tag, such as a roller cylinder system that moves to create the right path to the corresponding bin for the trash.

Approach

Solving one of the recycling problem aspects has a difficult set of objectives: first, the team must evaluate if a smart trash can is a suitable solution or if there are easier ways; the implementation is next in line. Our goal is to first design the bin with: all the necessary instructions, design of the smaller components, draw the circuits, write the code; everything necessary to build the smart bin if we had the resources.

Milestones

A certain milestone of the problem is finding a suitable way, preferably non-contact, to detect the trash that is put inside the bin; choosing the method depends on dividing the type of trash in the right categories, setting certain features of trash that the bin must detect. Next, the method must ensure it takes little time such that the bin can cope with high demand. Another milestone would be to make the bin robust to deviations from the model (it can happen that 2 types of trash are scanned together or it can happen that the queue of trash to be sorted becomes too long). The biggest milestone of the project is to actually finish the development (on paper) at the end of the 2 months.

Deliverables

The output of the project should be a full description, including the methods (such as pseudocode) for implementing the idea. The description should ensure that anyone who will read it, follow the steps and buy the necessary parts can build the smart trash bin. This might change due to the complexity of the project to simply finding the right method to sort the trash by categories.

References

<references> [19] [16] [17] [20] [18] [21]

  1. ↑ 1.0 1.1 1.2 1.3 Sharma, N., Singha, N., & Dutta, T. (2015). "Smart Bin Implementation for Smart Cities". http://www.ijser.org. 5. Published: International Journal of Scientific & Engineering Research, 6(9).Date accessed: 2020-02-08.
  2. ↑ 2.0 2.1 Thomas, C., Slater, R., Leaman, J., & Downing, P. (n.d.)." What Makes People Recycle? An Evaluation of Attitudes and Behaviour in London Western Riverside. 11. Date accessed: 2020-02-09.
  3. ↑ 3.0 3.1 Roberts, F. (2017)."Smart bin from Polish start-up Bin-e set to sort UK recycling problems.https://internetofbusiness.com/smart-bin-bin-e-recycling/. Date accessed: 2020-02-05.
  4. ↑ 4.0 4.1 Ramson, S. R. J., & Moni, D. J. (2017)." Wireless sensor networks based smart bin.https://doi.org/10.1016/j.compeleceng.2016.11.030. 17: 337-353. Date accessed: 2020-02-08.
  5. ↑ 5.0 5.1 Peco-InspX. Detecting Plastics with X-Ray Inspection Systems. Date accessed: 2020-02-05. https://www.peco-inspx.com/blog/x-ray-detectable-plastics/
  6. ↑ 6.0 6.1 Sol M. Gruner.(2012). "X-ray imaging detectors" https://physicstoday.scitation.org/doi/10.1063/PT.3.1819 Pulisher: American Institute of Physics. Date accessed: 2020-02-06
  7. ↑ 7.0 7.1 Mary E.Coles. (1999). "8. X-Ray Imaging". https://doi.org/10.1016/S0076-695X(08)60419-6 . 35: 301-336. Date accessed: 2020-02-08.
  8. ↑ 8.0 8.1 Schroer, Christian G. (2011). "X-ray imaging: The chemistry inside". Nature. 476: 159-160. https://www-nature-com.dianus.libr.tue.nl/articles/476159a Date accessed: 2020-02-06
  9. ↑ 9.0 9.1 Liu, Ying-Ho; Lee, Anthony J.T.; Chang, Fu. (2012). "Object recognition using discriminative parts". Computer Vision and Image Understanding. 116: 854-867.
  10. ↑ D M Scott 1995 Meas. Sci. Technol. 6 156 ‘A two-colour near-infrared sensor for sorting recycled plastic waste’
  11. ↑ Iñigo Vegas, Kris Broos, Peter Nielsen, Oliver Lambertz, Amaia Lisbona, Upgrading the quality of mixed recycled aggregates from construction and demolition waste by using near-infrared sorting technology, Construction and Building Materials, Volume 75, 2015, Pages 121-128, ISSN 0950-0618, https://doi.org/10.1016/j.conbuildmat.2014.09.109.
  12. ↑ Offer Rozenstein, Eldon Puckrin, Jan Adamowski, Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry, Waste Management, Volume 68, 2017, Pages 38-44, ISSN 0956-053X, https://doi.org/10.1016/j.wasman.2017.07.023.
  13. ↑ A. C. Karaca, A. Ertürk, M. K. Güllü, M. Elmas and S. Ertürk, "Automatic waste sorting using shortwave infrared hyperspectral imaging system," 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Gainesville, FL, 2013, pp. 1-4. doi: 10.1109/WHISPERS.2013.8080744
  14. ↑ Masanori Kumagai, Hideto Suyama, Tomoaki Sato, Toshio Amano, and Nobuaki Ogawa, "Discrimination of Plastics Using a Portable near Infrared Spectrometer," J. Near Infrared Spectrosc. 10, 247-255 (2002)
  15. ↑ Cite error: Invalid <ref> tag; no text was provided for refs named electro-mechanical
  16. ↑ 16.0 16.1 Pneumatic Sensor fittings Datasheet, (Springer, 1999).
  17. ↑ 17.0 17.1 Y Shigeta, S Hayano, Y Saito, Magnetic sensor signal Analysis, (International Journal of Electromagnetics and Mechanics, 2001/2002).
  18. ↑ 18.0 18.1 Darran Kreit, Inductive verses Capacitive sensors, (Elsevier, 2013).
  19. ↑ Ilene J. Bush-Vishniac, Eletromechanical Sensors and Actuators, Date accesed: 2020-02-09 www.parker.com › LPCE › function-fittings .
  20. ↑ 5 reasons to choose Induction over Hall Effect sensors, Date accesed: 2020-02-09 https://www.gillsc.com/newsitem/45/5-reasons-choose-induction-over-hall-effect-sensors.
  21. ↑ K Nakamura, Ultrasonic transducers : materials and design for sensors, actuators and medical applications, Part 3,
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