Abstract
This thesis studied improvements in the timely delivery
of relevant near real-time environmental information to
support decision making in dynamic environments.
Especially, the focus was on orchestration of the data
processing tasks, presentation of the information to
end-users, and data collection from the field where the
users are operating. It was found that three system
design principles can be used to improve the information
delivery: 1) organizing the synergies in data access and
information processing as a component called Data
operator, 2) including automatic analyses of the
situation to support the interpretation of the
information, and 3) harnessing of end-users and end-user
devices as opportunistic and participatory sensors to
collect data from the local conditions in order to
complement other data sources.
The research was conducted by studying two application
cases: ice navigation and water quality monitoring. In
the ice navigation case, we developed a system to deliver
in-situ and remote sensing data as well as forecasts by
computational models about the meteorological,
oceanographic and ice conditions to ice-going ships, a
route optimisation method to support the decision making
and information presentation, and a method for using
ships and ship radars as a sensor network. In the water
quality monitoring case, citizens were harnessed as
observers of water turbidity and the algae situation in
order to complement other data sources, and citizen
observations were compared with expert observations.
Open data and open interfaces are important elements for
accessing data, but they are not adequate to guarantee
the optimal use of environmental data in near real-time
applications. The whole processing chain from data
sources to end-user awareness should be considered in
order to take full advantage of the data. It is concluded
that the three design principles are not limited to the
application cases of this study, but are applicable to
other domains of environmental monitoring as well, for
example air quality, disaster and built environment
monitoring. The amount of environmental data is growing
exponentially, and new methods are needed to include
these data in decision making in society.
| Original language | English |
|---|---|
| Qualification | Doctor Degree |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 10 Dec 2016 |
| Place of Publication | Espoo |
| Publisher | |
| Print ISBNs | 978-952-60-7168-8, 978-951-38-8480-2 |
| Electronic ISBNs | 978-952-60-7167-1, 978-951-38-8479-6 |
| Publication status | Published - 2016 |
| MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- environmental monitoring
- environmental informatics
- computer science
- remote sensing
- participatory sensing
- ice navigation
- route optimisation
- water quality monitoring
