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

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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Identifiers

ORCID for Stefano Modafferi: orcid.org/0000-0003-0428-3194

ORCID for Zoheir Sabeur: orcid.org/0000-0003-4325-4871

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