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Multi-level data fusion of environmental data in future internet applications

Multi-level data fusion of environmental data in future internet applications
Multi-level data fusion of environmental data in future internet applications
The rapid increase in environmental observations which are conducted by SMEs, communities and volunteers using affordable in situ sensors at various scales, together with the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing rates. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached greater imminence. It is now highly critical to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources.

The early stages of aggregation of data enable the preprocessing of data generated from multiple sources with the reconciliation between temporal gaps in observation time series, and alignment of their respective asynchronicities. As a result, multi-level processes of fusion need to be implemented and made accessible to large communities of users using future internet services.

This paper presents the process and the preliminary results using RBF networks methods for the spatial fusion of water quality observations and measurements from asynchronous space-borne, in situ and validated models simulation data sources in the Irish Sea.
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Chakravarthy, Ajay
d5f40fb2-e262-49e1-9fcc-e1368e764d03
Sabeur, Zoheir
74b55ff0-94cc-4624-84d5-bb816a7c9be6
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Chakravarthy, Ajay
d5f40fb2-e262-49e1-9fcc-e1368e764d03
Sabeur, Zoheir
74b55ff0-94cc-4624-84d5-bb816a7c9be6

Modafferi, Stefano, Chakravarthy, Ajay and Sabeur, Zoheir (2013) Multi-level data fusion of environmental data in future internet applications. 21st Italian Symposium on Advanced Database Systems SEBD, Italy. 30 Jun - 03 Jul 2013.

Record type: Conference or Workshop Item (Paper)

Abstract

The rapid increase in environmental observations which are conducted by SMEs, communities and volunteers using affordable in situ sensors at various scales, together with the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing rates. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached greater imminence. It is now highly critical to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources.

The early stages of aggregation of data enable the preprocessing of data generated from multiple sources with the reconciliation between temporal gaps in observation time series, and alignment of their respective asynchronicities. As a result, multi-level processes of fusion need to be implemented and made accessible to large communities of users using future internet services.

This paper presents the process and the preliminary results using RBF networks methods for the spatial fusion of water quality observations and measurements from asynchronous space-borne, in situ and validated models simulation data sources in the Irish Sea.

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More information

Published date: June 2013
Venue - Dates: 21st Italian Symposium on Advanced Database Systems SEBD, Italy, 2013-06-30 - 2013-07-03
Organisations: IT Innovation

Identifiers

Local EPrints ID: 370579
URI: http://eprints.soton.ac.uk/id/eprint/370579
PURE UUID: 10fcb44f-033b-486a-b7a7-1a245a887a39
ORCID for Zoheir Sabeur: ORCID iD orcid.org/0000-0003-4325-4871

Catalogue record

Date deposited: 03 Nov 2014 11:56
Last modified: 19 Jul 2019 20:59

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Contributors

Author: Stefano Modafferi
Author: Ajay Chakravarthy
Author: Zoheir Sabeur ORCID iD

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