An Experimental Platform for Quantified Crowdiwanicki/projects/... · An Experimental Platform for...
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An Experimental Platformfor Quantified Crowd
M. Grabowski, M. Marschall, W. Sirko,M. Debski, M. Ziombski, P. Horban,
S. Acedanski, M. Peczarski, D. Batorski,K. Iwanicki
University of Warsaw
WiMAN 2015, Las Vegas, NV, USA, August 6th, 2015
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Quantified Self
= Self knowledge through numbers
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You can't manage what you don't measure
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Quantified Crowd
The enabling factors:
● Further device miniaturization;
● Low-power wireless inter-device communication.
The core ideas:
● Collaborative sensing of collocated people.
● Online and (partially) in-network data analysis.
● Coordinated feedback for groups of people.
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Quantified Crowd
Crowd management:● Detecting patterns of
coordinated behavior in a crowd.
● Automaticly recognizing and predicting problematic situations.
● Notifying people and the autorities about danger.
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You can't manage whatyou don't measure
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Quantified Crowd
Maximizing event experience:● Detecting interpersonal
interactions.
● Recognizing communities.
● Navigation through crowds.
● Contact and content suggesting.
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Problem Statement
Prior research has been conducted with:● Smartphones, or● Custom devices.
We are not aware of a common platform thatwould allow for innovating at various levels
of quantified crowd.
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Experimental Platform
Goal:● experimentation in as many scenarios as possible.
Components:● Hardware
● Software
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Hardware
Design goals:● On its own should enable experimentation in
many scenarios.● It should be possible to extended with external
devices.
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Hardware
Based on ARM Cortex-M0+.
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Hardware
Local sensors:● Accelerometer
● Magnetometer
● Gyroscope
● Microphone
● Barometer (altimeter)
● Light sensor
● Thermometer
● Hygrometer
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Hardware
Crowd texture sensors:● Low-power 868MHz radio
● Infra-red transceiver
● Bluetooth Low Energy chip
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Hardware
I/O interfaces:● 400x300 e-paper display
● Buttons
● LEDs
● Buzzer
● External flash memory
● SD card
● USB socket
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Software
● Badge software – written in NesC.● External software – mostly Java.
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Evaluation
● Conducted on a small scale.● We are in the process of manufacturing a
large batch of badges.
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Evaluation
Power consumptionComponent Standby [μA] Active [mA]MCU 1.7 6.1RF transceiver 0.2 16.9 (RX), 34.2 (TX @ 12 dBm)Infrared transceiver 0 0.9 (RX), 72 (TX @ power level 3)BLE module 0.4 25 (RX), 36 (TX)E-compass 2 0.44Gyroscope 1 5Barometer 0.5 0.025Light sensor 4 0.13Microphone 0 1.8External flash 100 20SD card 0 depends on a card (e.g., 100)E-paper display 0 8
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Evaluation
Proximity detection with RF
Dist. [m]Radio TX power [dBm]
-30.2 -27.7 -20.5 -15.7 -11.0 -5.0 -0.3 3.71 74.8 85.3 99.0 99.7 99.4 99.3 99.7 99.62 14.0 65.7 99.7 99.2 99.0 99.6 99.3 98.43 2.0 0.0 98.7 98.9 99.3 99.6 99.2 99.35 14.9 0.0 99.4 99.1 99.6 99.4 97.9 99.3
10 0.0 0.0 36.0 96.0 99.7 99.9 99.0 99.320 0.0 0.0 0.0 14.9 98.3 99.9 99.3 99.530 0.0 0.0 0.0 0.0 23.6 35.0 99.0 99.140 0.0 0.0 0.0 0.0 20.0 22.0 68.5 99.550 0.0 0.0 0.0 0.0 0.0 1.0 11.0 98.860 0.0 0.0 0.0 0.0 0.0 0.0 23.4 98.170 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
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Evaluation
Proximity detection with IR
0 1 2 31 100.0 99.0 93.0 88.02 74.0 67.0 99.0 88.03 0.0 55.0 33.0 51.04 0.0 0.0 50.0 53.05 0.0 0.0 0.0 30.06 0.0 0.0 0.0 0.0
Dist. [m]IR TX power [level]
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Evaluation
Mutual orientation detection with IR
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Evaluation
Real-world situation detection
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Conclusion
● Our platform has the potential to serve on its own in various experimental scenarios for quantified crowd.
● It can be extended with off-the-shelf mobile devices, which further broadens its applicability.
● We are in the process of manufacturing 100 pieces of the badges.
● We hope that the platform will be used by other groups.
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Thank You
Questions?
Supported by the (Polish) National Science Centre (NCN) withinthe SONATA programme under grant no. DEC-2012/05/D/ST6/03582.K. Iwanicki was additionally supported by a scholarship from the (Polish)Ministry of Science and Higher Education for outstanding youngscientists.