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 |
| Toby | 0000000 | ... |
Problem Statement
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] |
| Toby | ... |
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
- ↑ 1.0 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/
- ↑ 2.0 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
- ↑ 3.0 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.
- ↑ 4.0 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
- ↑ 5.0 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.