![](bg6.png)
Table 2: Frame rates attained for different image sizes and different devices.
Frames per second (fps)
Image size in pixels
1024 × 128 1024 × 256 1024 × 512 1024 × 1024
Desktop
CPU: i7-2600 23 20.1 16.1 11.5
GPU: GTX 560 Ti 60 60 60 26.8
GPU: GTX 480 60 60 60 40.3
Laptop
CPU: 620M 16 8.5 4.6 2.4
GPU: 3100M 60 32.6 16 7.8
the frame rates are capped at the screen refresh rate
(60 Hz). It is not a limitation incurred by the utilized
algorithms.
In summary, it was shown that using our fuzzy algo-
rithm is beneficial for detecting viruses in PAMONO
data: It increases positive agreement of the detection
results to synthetic ground-truth data. The algorithm,
along with the remainder of the processing pipeline,
achieves real-time performance on a portable device.
The utilization of GPGPU techniques is mandatory
because state-of-the art CPUs do not provide suffi-
cient processing power to satisfy the real-time con-
straint. Using the GPU furthermore saves energy.
5 DISCUSSION
With the increasing global spread of human viral in-
fections and the emergence of highly virulent norovi-
ral strains, the availability of fast, reliable and inex-
pensive methods for virus detection is urgently nec-
essary for screening at e.g. airports or in crisis ar-
eas. The proposed “Portable PAMONO Unit” ful-
fills these requirements. The unit consists of a small
case containing the novel PAMONO biosensor and of
an off-the-shelf laptop computer running specialized
signal analysis software. Besides allowing for ubiqui-
tous availability of virus detection, it accelerates diag-
noses because results are produced in real-time while
viruses attach to the sensor surface.
Future research aims at a further miniaturization
of the “Portable PAMONO Unit” and at running real-
time data analysis on tablet computers and smart
phones. Due to their low cost, a deployment of a large
number of cooperating “Portable PAMONO Units” is
conceivable. A network of such units allows for draw-
ing conclusions about the large-scale propagative be-
havior of pathogens in the human environment.
ACKNOWLEDGEMENTS
Part of the work on this paper has been supported
by Deutsche Forschungsgemeinschaft (DFG) within
the Collaborative Research Center SFB 876 “Provid-
ing Information by Resource-Constrained Analysis”,
project B2. URL: http://sfb876.tu-dortmund.de
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