1.1
1
xml
info:srw/schema/1/dc-v1.1
Autonomous accident monitoring using cellular network data
Olof Görnerup
Per Kreuger
Daniel Gillblad
T. Comes, F.F., S. Fortier, J. Geldermann and T. Müller
Mobile communication networks constitute large-scale sensor networks that generate huge amounts of data that can be refined into collective mobility patterns. In this paper we propose a method for using these patterns to autonomously monitor and detect accidents and other critical events. The approach is to identify a measure that is approximately time-invariant on short time-scales under regular conditions, estimate the short and long-term dynamics of this measure using Bayesian inference, and identify sudden shifts in mobility patterns by monitoring the divergence between the short and long-term estimates. By estimating long-term dynamics, the method is also able to adapt to long-term trends in data. As a proof-of-concept, we apply this approach in a vehicular traffic scenario, where we demonstrate that the method can detect traffic accidents and distinguish these from regular events, such as traffic congestions.
urn:ISBN:9783923704804
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Autonomous%20accident%20monitoring%20using%20cellular%20network%20data&stitle=ISCRAM%202013&issn=2411-3387&isbn=9783923704804&date=2013&spage=638&epage=646&aulast=Olof%20G%F6rnerup&au=Per%20Kreuger&au=Daniel%20Gillblad&pub=Karlsruher%20Institut%20fur%20Technologie&place=KIT%3B%20Baden-Baden&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=537
citekey:OlofGoernerup_etal2013
citation:Olof Görnerup, Per Kreuger, & Daniel Gillblad. (2013). Autonomous accident monitoring using cellular network data. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 638-646). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
2013
ConferencePaper
text
Bayesian networks
Carrier mobility
Inference engines
Information systems
Sensor networks
Traffic congestion
Anomaly detection
Bayesian inference
Cellular network
Crisis management
Emergency response
Large scale sensor network
Mobile communication networks
Vehicular traffic scenarios
Accidents
file:http://idl.iscram.org/files/goernerup/2013/537_Goernerup_etal2013.pdf
Karlsruher Institut fur Technologie
English
2411-3387
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management
2013
638
646
1