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Robot for saving victims in a fire
Group members
Name |
Student number
|
Email
|
Study
|
Dimitrios Adaos |
1712926
|
d.adaos@student.tue.nl
|
Computer Science and Engineering
|
Wiliam Dokov
|
1666037
|
w.w.dokov@student.tue.nl
|
Computer Science and Engineering
|
Kwan Wa Lam
|
1608681
|
k.w.lam@student.tue.nl
|
Psychology and Technology
|
Kamiel Muller
|
1825941
|
k.a.muller@student.tue.nl
|
Chemical Engineering and Chemistry
|
Georgi Nihrizov
|
1693395
|
g.nihrizov@student.tue.nl
|
Computer Science and Engineering
|
Twan Verhagen
|
1832735
|
t.verhagen@student.tue.nl
|
Computer Science and Engineering
|
Research papers
- A Victims Detection Approach for Burning Building Sites Using Convolutional Neural Networks https://ieeexplore.ieee.org/abstract/document/9031275
Title
|
Summary
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Link
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A Victims Detection Approach for Burning Building Sites Using Convolutional Neural Networks
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They trained a convolutional neural network to detect people and pets in thermal IR, images. They gathered their own dataset to train the network. The network results were pretty accurate.
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https://ieeexplore.ieee.org/abstract/document/9031275
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Early Warning Embedded System of Dangerous Temperature Using Single exponential smoothing for Firefighters Safety
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Proposes to add a temperature sensor to a firefighter's suit which will warn firefighters that they are in a very hot place > 200 C.
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https://shorturl.at/bcGJ2
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A method to accelerate the rescue of fire-stricken victims
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https://www.sciencedirect.com/science/article/pii/S095741742302688X
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The role of robots in firefighting
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https://www.emerald.com/insight/content/doi/10.1108/IR-10-2020-0222/full/html
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Firefighting robot with deep learning and machine vision
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An autonomous firefighting robot
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Real Time Victim Detection in Smoky Environments with Mobile Robot and Multi-sensor Unit Using Deep Learning
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Thermal, Multispectral, and RGB Vision Systems Analysis for Victim Detection in SAR Robotics
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Sensor fusion based seek-and-find fire algorithm for intelligent firefighting robot
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Appendix
Appendix 1; Logbook
Logbook
Week
|
Name
|
Hours spent
|
Total hours
|
1
|
Dimitrios Adaos
|
Meeting (1h), Brainstorm (0.5h)
|
|
Wiliam Dokov
|
Meeting (1h), Brainstorm (0.5h)
|
|
Kwan Wa Lam
|
Meeting (1h), Brainstorm (0.5h)
|
|
Kamiel Muller
|
Meeting (1h), Brainstorm (0.5h)
|
|
Georgi Nihrizov
|
Meeting (1h), Brainstorm (0.5h)
|
|
Twan Verhagen
|
Meeting (1h), Brainstorm (0.5h)
|
|
2
|
Dimitrios Adaos
|
|
|
Wiliam Dokov
|
|
|
Kwan Wa Lam
|
|
|
Kamiel Muller
|
|
|
Georgi Nihrizov
|
|
|
Twan Verhagen
|
|
|
3
|
Dimitrios Adaos
|
|
|
Wiliam Dokov
|
|
|
Kwan Wa Lam
|
|
|
Kamiel Muller
|
|
|
Georgi Nihrizov
|
|
|
Twan Verhagen
|
|
|
4
|
Dimitrios Adaos
|
|
|
Wiliam Dokov
|
|
|
Kwan Wa Lam
|
|
|
Kamiel Muller
|
|
|
Georgi Nihrizov
|
|
|
Twan Verhagen
|
|
|