The University of Southampton
University of Southampton Institutional Repository

Geospatial intelligence and visual classification of environmentally observed species in the future Internet

Geospatial intelligence and visual classification of environmentally observed species in the future Internet
Geospatial intelligence and visual classification of environmentally observed species in the future Internet
The rapid development of advanced smart communication tools with good quality and resolution video cameras,
audio and GPS devices in the last few years shall lead to profound impacts on the way future environmental
observations are conducted and accessed by communities. The resulting large scale interconnections of these
"Future Internet Things" form a large environmental sensing network which will generate large volumes of quality
environmental observations and at highly localised spatial scales. This enablement in environmental sensing at
local scales will be of great importance to contribute in the study of fauna and flora in the near future, particularly
on the effect of climate change on biodiversity in various regions of Europe and beyond. The Future Internet could
also potentially become the de facto information space to provide participative real-time sensing by communities
and improve our situation awarness of the effect of climate on local environments. In the ENVIROFI(2011-2013)
Usage Area project in the FP7 FI-PPP programme, a set of requirements for specific (and generic) enablers is
achieved with the potential establishement of participating community observatories of the future. In particular,
the specific enablement of interest concerns the building of future interoperable services for the management of
environmental data intelligently with tagged contextual geo-spatial information generated by multiple operators
in communities (Using smart phones). The classification of observed species in the resulting images is achieved
with structured data pre-processing, semantic enrichement using contextual geospatial information, and high level
fusion with controlled uncertainty estimations. The returned identification of species is further improved using
future ground truth corrections and learning by the specific enablers.
Arbab-Zavar, B.
40e175ea-6557-47c6-b759-318d7e24984b
Chakravarthy, A.
134cde0e-6d3e-4b05-9dd2-f456e9892312
Sabeur, Z.
74b55ff0-94cc-4624-84d5-bb816a7c9be6
Arbab-Zavar, B.
40e175ea-6557-47c6-b759-318d7e24984b
Chakravarthy, A.
134cde0e-6d3e-4b05-9dd2-f456e9892312
Sabeur, Z.
74b55ff0-94cc-4624-84d5-bb816a7c9be6

Arbab-Zavar, B., Chakravarthy, A. and Sabeur, Z. (2012) Geospatial intelligence and visual classification of environmentally observed species in the future Internet. European Geosciences Union General Assembly 2012 (EGU 2012), Austria. 22 - 27 Apr 2012.

Record type: Conference or Workshop Item (Other)

Abstract

The rapid development of advanced smart communication tools with good quality and resolution video cameras,
audio and GPS devices in the last few years shall lead to profound impacts on the way future environmental
observations are conducted and accessed by communities. The resulting large scale interconnections of these
"Future Internet Things" form a large environmental sensing network which will generate large volumes of quality
environmental observations and at highly localised spatial scales. This enablement in environmental sensing at
local scales will be of great importance to contribute in the study of fauna and flora in the near future, particularly
on the effect of climate change on biodiversity in various regions of Europe and beyond. The Future Internet could
also potentially become the de facto information space to provide participative real-time sensing by communities
and improve our situation awarness of the effect of climate on local environments. In the ENVIROFI(2011-2013)
Usage Area project in the FP7 FI-PPP programme, a set of requirements for specific (and generic) enablers is
achieved with the potential establishement of participating community observatories of the future. In particular,
the specific enablement of interest concerns the building of future interoperable services for the management of
environmental data intelligently with tagged contextual geo-spatial information generated by multiple operators
in communities (Using smart phones). The classification of observed species in the resulting images is achieved
with structured data pre-processing, semantic enrichement using contextual geospatial information, and high level
fusion with controlled uncertainty estimations. The returned identification of species is further improved using
future ground truth corrections and learning by the specific enablers.

PDF
339194-EGU2012-12902-1.pdf - Other
Download (38kB)

More information

e-pub ahead of print date: April 2012
Venue - Dates: European Geosciences Union General Assembly 2012 (EGU 2012), Austria, 2012-04-22 - 2012-04-27
Related URLs:
Organisations: Electronics & Computer Science, IT Innovation

Identifiers

Local EPrints ID: 339194
URI: https://eprints.soton.ac.uk/id/eprint/339194
PURE UUID: 6a27f6e6-3905-475a-8f2b-ea1657bd972b
ORCID for Z. Sabeur: ORCID iD orcid.org/0000-0003-4325-4871

Catalogue record

Date deposited: 24 May 2012 09:23
Last modified: 06 Jun 2018 12:34

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×