PRE2019 3 Group5: Difference between revisions

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==Problem Statement==
==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.         
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==
==Objectives==

Revision as of 22:35, 8 February 2020

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.
  • Utilize technologies like X-ray and image processing to achieve this.


USE Aspects

Approach, milestones and deliverables

Task distribution

Week1

Name[total hours of work] Tasks and hours
Ana Maria Risnoveanu ...
Stacey Elshove ...
Petru Radulescu Objectives ...
Yiqin Hou[?h] Papers about X-ray imaging[1][2][3][4]/Object recognition[5] searched and studied[?h]; summary[?h]; Learn wikitext and make template for the group wiki[4h]
Tobias Hilpert ...

SotA

Detection

X-ray

Inspired by security machines, X-ray imaging could be a usefull tool in detcting the type of rubbish. X-ray imaging [3]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[4]. With such techiniques and some morden X-ray imaging detectors [2], 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[1], 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 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 [5]

References

  1. 1.0 1.1 Peco-InspX. Detecting Plastics with X-Ray Inspection Systems. Date accessed: 2020-02-05. https://www.peco-inspx.com/blog/x-ray-detectable-plastics/
  2. 2.0 2.1 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
  3. 3.0 3.1 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.
  4. 4.0 4.1 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
  5. 5.0 5.1 Liu, Ying-Ho; Lee, Anthony J.T.; Chang, Fu. (2012). "Object recognition using discriminative parts". Computer Vision and Image Understanding. 116: 854-867.