TY - GEN
T1 - Location intelligence for augmented smart cities integrating sensor web and spatial data infrastructure (SmaCiSENS)
AU - Bhattacharya, Devanjan
AU - Painho, Marco
N1 - Funding Information:
D. Bhattacharya has been funded by the European Commission through the GEO-C project H2020-MSCA-ITN-2014, Grant Agreement number 642332, http://www.geo-c.eu/.
Publisher Copyright:
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2018/12/31
Y1 - 2018/12/31
N2 - Spatio-temporal aspects of data lead to critical information. Sensors capture data at all scales continually so it is imperative that useful information be extracted ubiquitously and regularly. Location plays a vital part by helping understand relations between datasets. It is crucial to link developmental works with spatial attributes and current challenge is to create an open platform that manages real-time sensor data and provides critical spatial analytics atop expert domain knowledge provided in the system. That is a two-faced problem where the solution tackles not only data from multiple sources but also runs data management platform, a spatial data infrastructure(SDI) as backbone framework able to harness sensor web(SW). The paper proposes development of such a globally shared open spatial expert system(ES), SmaCiSENS, a first of a kind geo-enabled knowledge based(KB) ES for multiple fields, smarter cities to climate modeling. SmaCiSENS is integration of SW and SDI with domain KB on data and problems, ready to infer solutions. The paper describes an architecture for semantic enablement for SW, SDI; connect interfaces, functions of SDI and SW, and sensor data application program interfaces (APIs) to better manage climate modeling, geohazard, global changes, and other vital areas of attention and action.
AB - Spatio-temporal aspects of data lead to critical information. Sensors capture data at all scales continually so it is imperative that useful information be extracted ubiquitously and regularly. Location plays a vital part by helping understand relations between datasets. It is crucial to link developmental works with spatial attributes and current challenge is to create an open platform that manages real-time sensor data and provides critical spatial analytics atop expert domain knowledge provided in the system. That is a two-faced problem where the solution tackles not only data from multiple sources but also runs data management platform, a spatial data infrastructure(SDI) as backbone framework able to harness sensor web(SW). The paper proposes development of such a globally shared open spatial expert system(ES), SmaCiSENS, a first of a kind geo-enabled knowledge based(KB) ES for multiple fields, smarter cities to climate modeling. SmaCiSENS is integration of SW and SDI with domain KB on data and problems, ready to infer solutions. The paper describes an architecture for semantic enablement for SW, SDI; connect interfaces, functions of SDI and SW, and sensor data application program interfaces (APIs) to better manage climate modeling, geohazard, global changes, and other vital areas of attention and action.
KW - expert system
KW - Geographical Information System
KW - Knowledge Based System
KW - sensor web
KW - smart cities
KW - Spatial Data Infrastructure
KW - spatial technologies
UR - http://www.scopus.com/inward/record.url?scp=85051995299&partnerID=8YFLogxK
U2 - 10.5220/0006786102820289
DO - 10.5220/0006786102820289
M3 - Conference contribution
AN - SCOPUS:85051995299
T3 - GISTAM 2018 - Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management
SP - 282
EP - 289
BT - GISTAM 2018 - Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management
A2 - Grueau, Cedric
A2 - Laurini, Robert
A2 - Ragia, Lemonia
PB - SCITEPRESS
T2 - 4th International Conference on Geographical Information Systems Theory, Applications and Management, GISTAM 2018
Y2 - 17 March 2018 through 19 March 2018
ER -