PRE2018 4 Group7

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Group members:

Name	Student ID	Email	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/
7) https://www.researchgate.net/publication/267387412_APPROPRIATE_TECHNOLOGY_FOR_AUTOMATIC_PASSENGER_COUNTING_ON_PUBLIC_TRANSPORT_VEHICLES_IN_SOUTH_AFRICA <br\> 8) https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=9&cad=rja&uact=8&ved=2ahUKEwiR9p2Uw4HiAhWNZ1AKHUeuBI4QFjAIegQIAhAC&url=http%3A%2F%2Fwww.movetec.fi%2Fimages%2Fpdf%2FTapeswitch-tuntoreunat.pdf&usg=AOvVaw0I2j-QILXPBH48Jq9N8T_d <br\> 9) http://www.instantcounting.com/technology.html

Categorize:
Counting people:
2,4,5,7
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 that can be placed underneath the padding of the seat. The Voltage is converted from a real output to a binary output which is created by Arduino. The application can read the amount of 0's and 1's and can convert that into images. The used pressure pad detects weight from 20 kg and higher.<br\> 7: <br\> Next to PIR, infrared beams could be used that detect when interrupted. Can be either active or passive: Passive sensors sense IRradiation and with that can find moveing direction, active sensors actually can locate the person. Ultrasonic sensor works approxiametly the same way. Test in South Africa: 28000 Rand (1866 euros) per bus with 1 sensor per door. This gives an accuracy level of 95%, while 3 sensors per door give 99%. Other methods are also given in this article, giving treadle mats, IR again, load cell and normal camera.<br\> 8: <br\> Tapeswitch is a company that produces copyright public transport equipment. Among those also belongs the treadle mat which already are in use at Amtrak trains, Copenhagen and melbourne. These mats commenly are produced with multiple zones, such that they can count passengers. <br\> 9: <br\> Instant counting is a company that provided treadle mats with the provided software. This software is capable of detecting the movement of a person when boarding/deboarding. It is possible to link 90 of these mats to eachother in one system. An interface shows the amount of people entering and the amount of people exiting.