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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Sensor Observation Service for Environmental Monitoring Data

Mokhtary, Mandana January 2012 (has links)
The Swedish Environmental Protection Agency (Naturvårdsverket) is the public agency in Sweden with responsibility to overview the conditions of the environment and the policies related to the environmental monitoring data. Nowadays, observation data are stored in several different data models in this organization, leading to difficulties in finding, understanding and consequently using data in terms of analysis and management of environmental issues. One common model that uniformly structures observation data could largely make it easier for decision makers to find the required information. The aim of this study is to build an interoperable data model for environmental monitoring observation in Naturvårdsverket based on OGC-SWE standard formats. The proposed solution relies on Sensor Web architecture, which is the set of data model definitions andweb service specifications. Also, this methodology is based on open source components; therefore it is cost-effective for the users. The Service Oriented Architecture (SOA) is used to create a uniform model by using communication protocols such as Extensible Markup Language (XML) and Simple Object Access Protocol (SOAP). The primary findings of the thesis is that when the observation is encoded into the standard format from the beginning, then it is easier to parse these documents and find the required information for the end users without knowing how these information are gathered and stored. The client scan send a request to the Sensor Observation Service (SOS) and receive the observation that is structured based on Observation and Measurements (O&M).

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