PRE2018 4 Group7: Difference between revisions
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pyro-electric infrared (PIR) sensor and a camera (2). Two possible ways: detection-based and map-based methods. Latter option more precise in counting (10,11). Differential PIR sensors used, since this is only possibility for differentiate between entry and exit of an environment and ordinary activities in that area by analyzing body movement. A couple of modules are used that consist of multiple PIR sensors. This data is collected and are input for a list of classifiers. Wavelet transform is used to create output signal. Using only camera yields ~ 80% efficiency, while integrating PIR has ~ 100% efficiency (Tutorial: https://www.youtube.com/watch?v=6Fdrr_1guok ) | pyro-electric infrared (PIR) sensor and a camera (2). Two possible ways: detection-based and map-based methods. Latter option more precise in counting (10,11). Differential PIR sensors used, since this is only possibility for differentiate between entry and exit of an environment and ordinary activities in that area by analyzing body movement. A couple of modules are used that consist of multiple PIR sensors. This data is collected and are input for a list of classifiers. Wavelet transform is used to create output signal. Using only camera yields ~ 80% efficiency, while integrating PIR has ~ 100% efficiency (Tutorial: https://www.youtube.com/watch?v=6Fdrr_1guok )<br\> | ||
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Also, a pressure sensor could be used. Pressure sensors behaves like a open-closed circuit which delivers voltage while closed. Binary output is created by Arduino, which is the input for the application. The used pressure pad detects weight from 20 kg and higher. | |||
Revision as of 12:19, 3 May 2019
Group members:
| Name | Student ID | Study | |
|---|---|---|---|
| Emiliyan Greshkov | 1281666 | e.greshkov@student.tue.nl | Insert |
| Thomas Janss | 1006697 | t.f.w.janss@student.tue.nl | Mechanical Engineering |
| Perry Kloet | 1236356 | p.a.j.kloet@student.tue.nl | Computer Science |
| Bram Schut | 1019001 | b.b.j.schut@student.tue.nl | Insert |
| Sem de Werdt | 1017882 | s.j.a.d.werdt@student.tue.nl | Insert |
Relevant scientific papers:
Research
1) https://www.alstom.com/our-solutions/digital-mobility/optimet-real-time-train-occupancy-smoother-passenger-flow-platforms
2) https://www.researchgate.net/publication/280735165_A_robust_system_for_counting_people_using_an_infrared_sensor_and_a_camera (currently doing (Thomas))
3) https://www.dilax.com/en/public-mobility/portfolio/seat-management/
4) https://www.researchgate.net/publication/323027620_Smart_Bus_An_Automated_Passenger_Counting_System
5) https://www.google.nl/url?sa=t&rct=j&q=&esrc=s&source=web&cd=21&cad=rja&uact=8&ved=2ahUKEwiCudCpgPbhAhUJr6QKHRJQBlM4ChAWMAp6BAgIEAI&url=https%3A%2F%2Fpdfs.semanticscholar.org%2F55a0%2F9a9adb1e7905f99607846f7a286e3f39bf17.pdf&usg=AOvVaw0ZK1-RYUZ15nYZshrA0cHs
6) https://www.usenix.org/legacy/events/hotos03/tech/full_papers/gruteser/gruteser_html/
Categorize:
Counting people:
2,4,5
Application itself:
4
2:
pyro-electric infrared (PIR) sensor and a camera (2). Two possible ways: detection-based and map-based methods. Latter option more precise in counting (10,11). Differential PIR sensors used, since this is only possibility for differentiate between entry and exit of an environment and ordinary activities in that area by analyzing body movement. A couple of modules are used that consist of multiple PIR sensors. This data is collected and are input for a list of classifiers. Wavelet transform is used to create output signal. Using only camera yields ~ 80% efficiency, while integrating PIR has ~ 100% efficiency (Tutorial: https://www.youtube.com/watch?v=6Fdrr_1guok )<br\>
4:
Also, a pressure sensor could be used. Pressure sensors behaves like a open-closed circuit which delivers voltage while closed. Binary output is created by Arduino, which is the input for the application. The used pressure pad detects weight from 20 kg and higher.