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PRONTO

Financiado

Cerrado

Event Recognition for Intelligent Resource Management

PRONTO emphasizes the role of event recognition in intelligent resource management (IRM) and proposes a methodology for fusing data from various sources, analysing it to extract useful information in the form of events and deliver... ver más

29/02/2012

Fraunhofer

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANG... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 7 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2012-02-29 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

7 Participantes

Fraunhofer

0.00€ | Lider

UPB

N.D. | Participante

"NCSR ""D"""

N.D. | Participante

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Líder del proyecto

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANG... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto PRONTO emphasizes the role of event recognition in intelligent resource management (IRM) and proposes a methodology for fusing data from various sources, analysing it to extract useful information in the form of events and delivering the resulting knowledge for decision making, through a user-friendly IRM application. In order to achieve this objective, PRONTO draws methods and expertise from the fields of data fusion, information extraction, temporal representation and reasoning, machine learning, and knowledge management systems. PRONTO derives its motivation from the fact that today's organizations collect data in various structured and unstructured formats, but are not able to fully utilize these data to support and improve their resource management process. Therefore, it is evident that the analysis and interpretation of the collected data needs to be automated and transformed into operational knowledge. Events are particularly important pieces of knowledge for resource management. PRONTO proposes the aforementioned synergy of techniques to facilitate the recognition of events from the collected raw data, that remain underutilized with current technologies. The PRONTO methodology to IRM comprises five main steps: (a) Aggregation of data from various sensors and communication between actors, e.g. fire-brigade officers. (b) Analysis of the data and extraction of 'low-level' events. (c) Recognition of 'high-level' events, using Dynamic fine-tuning of event models, using machine learning. The novelty of PRONTO lies in the difficult task of real-time, accurate recognition of complex events given multiple sources of information, including various types of sensor and modes of actor interaction. The usability and acceptance of the derived methods and tools in real-world environments will signal the success of the project. Progress will be measured by real end-users, participating actively, as consortium partners, in all stages of the development of the project.

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