PRE2020 Group 1 numbers: Difference between revisions

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|<!--Col1-->Time spent at measurement station per person
|<!--Col1-->Measurement station cycle time
|<!--Col2-->4 minutes
|<!--Col2-->4 minutes
|<!--Col3-->1 minute testing + 2 minutes disinfecting + 1 spare minute
|<!--Col3-->1 minute testing + 2 minutes disinfecting + 1 spare minute
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|<!--Col1-->Estimate of cost of the total system
|<!--Col1-->Estimated cost of the total system
|<!--Col2-->€10950,-
|<!--Col2-->€10950
|<!--Col3-->: €5500 for thermal camera, €1000 for microphones, €100 for microphone in cabin, €400 for camera on pole, €750 for camera pole, €3000 for booth including computer, software, screens, and interfaces, €200 for UV light
|<!--Col3-->€5500 for thermal camera, €1000 for microphones, €100 for microphone in cabin, €400 for camera on pole, €750 for camera pole, €3000 for booth including computer, software, screens, and interfaces, €200 for UV light
|<!--Col4-->Various webshops
|<!--Col4-->Various webshops



Latest revision as of 10:10, 15 October 2020

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Name Value Explanation Source
Microphone array range 10x10 meter Range provided by manufacturer [1]
Microphone mounting height 2.5 meters Minimum mounting height provided by manufacturer [1]
Distance between detection device and measurement station 2 meters Preferred value
Percentage of infected people 0.1% This is the amount of people currently tested positive for COVID-19. Some of these people are in the hospital and do not count, also the people tested positive will be a lot more careful coming into contact with others. However there are also people that have COVID-19 that are not tested. This will even out and so the same percentage of infected people was taken. [2]
Chance of detecting a cough with camera and microphone 87% Chance obtained by Korean researchers using a similar system [3]
Measurement station cycle time 4 minutes 1 minute testing + 2 minutes disinfecting + 1 spare minute
Expected false positive rate in measurement station 7% Study of similar cough classification algorithm achieved 96.6% accuracy. In this specific case this becomes higher than only the cough test since only 1 test needs to be positive to refuse access [4]
Expected false negative rate in measurement station 7% Study of similar cough classification algorithm achieved 96.6% accuracy. In this specific case this becomes higher than only the cough test since only 1 test needs to be positive to refuse access [4]
Frequency of random person getting picked out After every 2 coughing persons detected, 1 person is picked out randomly, if there is no queue This will ensure random people are not picked too often/not often enough and also random persons will not have to wait in a queue
Chance a healthy person coughs when in range of the microhpone 0.08% Based on average cough time and walking speed [5]
Estimated cost of the total system €10950 €5500 for thermal camera, €1000 for microphones, €100 for microphone in cabin, €400 for camera on pole, €750 for camera pole, €3000 for booth including computer, software, screens, and interfaces, €200 for UV light Various webshops
Salary of medical personnel €25 per hour Obtained from dad of group member who is a salary administrator
Dutch reproduction rate of COVID-19 3 [6]
Number of people in half an hour entering Heuvel Galerie during a quiet hour at a quiet entrance 24 Counted by group members
Number of people in half an hour entering Heuvel Galerie during a quiet hour at a busy entrance 61 Counted by group members
Number of people in half an hour entering Heuvel Galerie during a medium busy hour at a quiet entrance 117 Counted by group members
Number of people in half an hour entering Heuvel Galerie during a medium busy hour at a busy entrance 194 Counted by group members
Number of people in half an hour entering Heuvel Galerie during a busy hour at a quiet entrance 233 Counted by group members
Number of people in half an hour entering Heuvel Galerie during a busy hour at a busy entrance 756 Counted by group members


  1. 1.0 1.1 [1] Sorama. Sorama Smart City Listener.
  2. [2] RIVM. Actuele informatie over het nieuwe coronavirus.
  3. [3] Center for Noise and Vibration Control KAIST (2020). Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time​.
  4. 4.0 4.1 [4] Imran, A., Posokhova, I., Qureshi, H. N., Masood, U., Riaz, S., Ali, K., John, C. N., Hussain, I., & Nabeel, M. (2020). AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app. Informatics in Medicine Unlocked, 20, 100378.
  5. [5] Encyclopedia of Children's Health. Cough​.
  6. [6] RIVM. Verspreiding COVID-19.