Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DASC: Towards A Road Damage-Aware Social-Media-Driven Car Sensing
  Framework for Disaster Response Applications   While vehicular sensor networks (VSNs) have earned the stature of a mobile
sensing paradigm utilizing sensors built into cars, they have limited sensing
scopes since car drivers only opportunistically discover new events.
Conversely, social sensing is emerging as a new sensing paradigm where
measurements about the physical world are collected from humans. In contrast to
VSNs, social sensing is more pervasive, but one of its key limitations lies in
its inconsistent reliability stemming from the data contributed by unreliable
human sensors. In this paper, we present DASC, a road Damage-Aware
Social-media-driven Car sensing framework that exploits the collective power of
social sensing and VSNs for reliable disaster response applications. However,
integrating VSNs with social sensing introduces a new set of challenges: i) How
to leverage noisy and unreliable social signals to route the vehicles to
accurate regions of interest? ii) How to tackle the inconsistent availability
(e.g., churns) caused by car drivers being rational actors? iii) How to
efficiently guide the cars to the event locations with little prior knowledge
of the road damage caused by the disaster, while also handling the dynamics of
the physical world and social media? The DASC framework addresses the above
challenges by establishing a novel hybrid social-car sensing system that
employs techniques from game theory, feedback control, and Markov Decision
Process (MDP). In particular, DASC distills signals emitted from social media
and discovers the road damages to effectively drive cars to target areas for
verifying emergency events. We implement and evaluate DASC in a reputed vehicle
simulator that can emulate real-world disaster response scenarios. The results
of a real-world application demonstrate the superiority of DASC over current
VSNs-based solutions in detection accuracy and efficiency.

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The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
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The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
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The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph