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28 May 2013GOOSE: semantic search on internet connected sensors
More and more sensors are getting Internet connected. Examples are cameras on cell phones, CCTV cameras for traffic
control as well as dedicated security and defense sensor systems. Due to the steadily increasing data volume, human
exploitation of all this sensor data is impossible for effective mission execution. Smart access to all sensor data acts as
enabler for questions such as “Is there a person behind this building” or “Alert me when a vehicle approaches”.
The GOOSE concept has the ambition to provide the capability to search semantically for any relevant information
within “all” (including imaging) sensor streams in the entire Internet of sensors. This is similar to the capability provided
by presently available Internet search engines which enable the retrieval of information on “all” web pages on the
Internet. In line with current Internet search engines any indexing services shall be utilized cross-domain. The two main
challenge for GOOSE is the Semantic Gap and Scalability.
The GOOSE architecture consists of five elements: (1) an online extraction of primitives on each sensor stream; (2) an
indexing and search mechanism for these primitives; (3) a ontology based semantic matching module; (4) a top-down
hypothesis verification mechanism and (5) a controlling man-machine interface.
This paper reports on the initial GOOSE demonstrator, which consists of the MES multimedia analysis platform and the
CORTEX action recognition module. It also provides an outlook into future GOOSE development.
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Klamer Schutte, Freek Bomhof, Gertjan Burghouts, Jurriaan van Diggelen, Peter Hiemstra, Jaap van 't Hof, Wessel Kraaij, Huib Pasman, Arthur Smith, Corne Versloot, Joost de Wit, "GOOSE: semantic search on internet connected sensors," Proc. SPIE 8758, Next-Generation Analyst, 875806 (28 May 2013); https://doi.org/10.1117/12.2018112