A software system for the discovery of situations involving drivers in storms

Markus Stocker; Okko Kauhanen; Mikko Hiirsalmi; Janne Saarela; Pekka Rossi; Mauno Rönkkö; Harri Hytönen; Ville Kotovirta; Mikko Kolehmainen

doi:10.1007/978-3-319-15994-2_22

A software system for the discovery of situations involving drivers in storms

Markus Stocker, Okko Kauhanen, Mikko Hiirsalmi, Janne Saarela, Pekka Rossi, Mauno Rönkkö, Harri Hytönen, Ville Kotovirta, Mikko Kolehmainen

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

We present an environmental software system that obtains, integrates, and reasons over situational knowledge about natural phenomena and human activity. We focus on storms and driver directions. Radar data for rainfall intensity and Google Directions are used to extract situational knowledge about storms and driver locations along directions, respectively. Situational knowledge about the environment and about human activity is integrated in order to infer situations in which drivers are potentially at higher risk. Awareness of such situations is of obvious interest. We present a prototype user interface that supports adding scheduled driver directions and the visualization of situations in space-time, in particular also those in which drivers are potentially at higher risk. We think that the system supports the claim that the concept of situation is useful for the modelling of information about the environment, including human activity, obtained in environmental monitoring systems. Furthermore, the presented work shows that situational knowledge, represented by heterogeneous systems that share the concept of situation, is relatively straightforward to integrate.

Original language	English
Title of host publication	Environmental Software Systems
Subtitle of host publication	Infrastructures, Services and Applications
Publisher	Springer
Pages	226-234
ISBN (Electronic)	978-3-319-15994-2
ISBN (Print)	978-3-319-15993-5
DOIs	https://doi.org/10.1007/978-3-319-15994-2_22
Publication status	Published - 2015
MoE publication type	A4 Article in a conference publication
Event	11th IFIP WG 5.11 International Symposium, ISESS 2015 - Melbourne, Australia Duration: 25 Mar 2015 → 27 Mar 2015 Conference number: 11

Publication series

Series	IFIP Advances in Information and Communication Technology
Volume	448
ISSN	1868-4238

Conference

Conference	11th IFIP WG 5.11 International Symposium, ISESS 2015
Abbreviated title	ISESS 2015
Country/Territory	Australia
City	Melbourne
Period	25/03/15 → 27/03/15

Keywords

environmental knowledge systems
situation theory
ontology
knowledge representation
MMEA
Wavellite

Access to Document

10.1007/978-3-319-15994-2_22

Cite this

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title = "A software system for the discovery of situations involving drivers in storms",

abstract = "We present an environmental software system that obtains, integrates, and reasons over situational knowledge about natural phenomena and human activity. We focus on storms and driver directions. Radar data for rainfall intensity and Google Directions are used to extract situational knowledge about storms and driver locations along directions, respectively. Situational knowledge about the environment and about human activity is integrated in order to infer situations in which drivers are potentially at higher risk. Awareness of such situations is of obvious interest. We present a prototype user interface that supports adding scheduled driver directions and the visualization of situations in space-time, in particular also those in which drivers are potentially at higher risk. We think that the system supports the claim that the concept of situation is useful for the modelling of information about the environment, including human activity, obtained in environmental monitoring systems. Furthermore, the presented work shows that situational knowledge, represented by heterogeneous systems that share the concept of situation, is relatively straightforward to integrate.",

keywords = "environmental knowledge systems, situation theory, ontology, knowledge representation, MMEA, Wavellite",

author = "Markus Stocker and Okko Kauhanen and Mikko Hiirsalmi and Janne Saarela and Pekka Rossi and Mauno R{\"o}nkk{\"o} and Harri Hyt{\"o}nen and Ville Kotovirta and Mikko Kolehmainen",

year = "2015",

doi = "10.1007/978-3-319-15994-2_22",

language = "English",

isbn = "978-3-319-15993-5",

series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer",

pages = "226--234",

booktitle = "Environmental Software Systems",

address = "Germany",

note = "11th IFIP WG 5.11 International Symposium, ISESS 2015, ISESS 2015 ; Conference date: 25-03-2015 Through 27-03-2015",

}

Stocker, M, Kauhanen, O, Hiirsalmi, M, Saarela, J, Rossi, P, Rönkkö, M, Hytönen, H, Kotovirta, V & Kolehmainen, M 2015, A software system for the discovery of situations involving drivers in storms. in Environmental Software Systems: Infrastructures, Services and Applications. Springer, IFIP Advances in Information and Communication Technology, vol. 448, pp. 226-234, 11th IFIP WG 5.11 International Symposium, ISESS 2015, Melbourne, Victoria, Australia, 25/03/15. https://doi.org/10.1007/978-3-319-15994-2_22

A software system for the discovery of situations involving drivers in storms. / Stocker, Markus; Kauhanen, Okko; Hiirsalmi, Mikko et al.
Environmental Software Systems: Infrastructures, Services and Applications. Springer, 2015. p. 226-234 (IFIP Advances in Information and Communication Technology, Vol. 448).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Stocker, Markus

AU - Kauhanen, Okko

AU - Hiirsalmi, Mikko

AU - Saarela, Janne

AU - Rossi, Pekka

AU - Rönkkö, Mauno

AU - Hytönen, Harri

AU - Kotovirta, Ville

AU - Kolehmainen, Mikko

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N2 - We present an environmental software system that obtains, integrates, and reasons over situational knowledge about natural phenomena and human activity. We focus on storms and driver directions. Radar data for rainfall intensity and Google Directions are used to extract situational knowledge about storms and driver locations along directions, respectively. Situational knowledge about the environment and about human activity is integrated in order to infer situations in which drivers are potentially at higher risk. Awareness of such situations is of obvious interest. We present a prototype user interface that supports adding scheduled driver directions and the visualization of situations in space-time, in particular also those in which drivers are potentially at higher risk. We think that the system supports the claim that the concept of situation is useful for the modelling of information about the environment, including human activity, obtained in environmental monitoring systems. Furthermore, the presented work shows that situational knowledge, represented by heterogeneous systems that share the concept of situation, is relatively straightforward to integrate.

AB - We present an environmental software system that obtains, integrates, and reasons over situational knowledge about natural phenomena and human activity. We focus on storms and driver directions. Radar data for rainfall intensity and Google Directions are used to extract situational knowledge about storms and driver locations along directions, respectively. Situational knowledge about the environment and about human activity is integrated in order to infer situations in which drivers are potentially at higher risk. Awareness of such situations is of obvious interest. We present a prototype user interface that supports adding scheduled driver directions and the visualization of situations in space-time, in particular also those in which drivers are potentially at higher risk. We think that the system supports the claim that the concept of situation is useful for the modelling of information about the environment, including human activity, obtained in environmental monitoring systems. Furthermore, the presented work shows that situational knowledge, represented by heterogeneous systems that share the concept of situation, is relatively straightforward to integrate.

KW - environmental knowledge systems

KW - situation theory

KW - ontology

KW - knowledge representation

KW - MMEA

KW - Wavellite

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M3 - Conference article in proceedings

SN - 978-3-319-15993-5

T3 - IFIP Advances in Information and Communication Technology

SP - 226

EP - 234

BT - Environmental Software Systems

PB - Springer

T2 - 11th IFIP WG 5.11 International Symposium, ISESS 2015

Y2 - 25 March 2015 through 27 March 2015

ER -

A software system for the discovery of situations involving drivers in storms

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Keywords

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