PRE2022 3 Group3: Difference between revisions

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Luta Iulia Andreea 1671685, Sonia Roberta Maxim 1675656, Hakim Agni 1430149, Marie Spreen 1909983, Fenna Schipper 1625624, Dhruv Manohar (1568868),Lazgin Mamo (1502506)
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==Group members==
{| class="wikitable"
!Name!!Student id
!Major
|-
|Luta Iulia Andreea
|1671685
|BCS
|-
|Sonia Roberta Maxim  
|1675656
|BCS
|-
|Marie Spreen
|1909983
|
|-
|Fenna Schipper
|1625624
|
|-
|Hakim Agni
|1430149
|
|-
|Lazgin Mamo
|1502506
|
|-
|Dhruv Manohar
|1568868
|
|}





Revision as of 14:24, 13 February 2023


Group members

Name Student id Major
Luta Iulia Andreea 1671685 BCS
Sonia Roberta Maxim 1675656 BCS
Marie Spreen 1909983
Fenna Schipper 1625624
Hakim Agni 1430149
Lazgin Mamo 1502506
Dhruv Manohar 1568868


Brainstorming:

- Greenhouse robot

- Piano playing robot

- Drone that detect quality of snow in order to estimate risk of avalanches

- Drones that detect people stuck in places?

- Robot that helps elderly people with education

- Sorting robot for recycling

- Bed that closes in case of eg. earthquakes


Final Idea choice:

Sorting robot for recycling

- Targeting private homes (individual Trashcans with inbuilt sorting function)

-> using affordable materials

-> trash "compression"

- Targeting companys (Sorting arms, larger scale)

- ML approaches for Material classification

Paper about Material Classification with Machine Learning:

https://www.intechopen.com/chapters/75628

The literature review depicted the support vector machine (SVM) and artificial neural network (ANN) techniques as more effective than other ML techniques for material classification. The last section of this chapter includes a python-based ANN model for material classification. This ANN model has been tested for construction items (brick, wood, concrete block, and asphalt) for training and prediction. Moreover, the predictive ANN model results have been shared for the readers, along with the resources and open-source web links.

-> Maybe we can apply this to waste-materials


Game Plan:

Week 01:

- research different areas of Problem