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Toward Sensor-Based Context Aware Systems

Autor: Kouhei Takada, Marco Anisetti, Valerio Bellandi, Paolo Ceravolo, Ernesto Damiani, Setsuo Tsuruta, Yoshitaka Sakurai

Publikováno v: Sensors, Vol 12, Iss 1, Pp 632-649 (2012)

This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and l

Externí odkaz: https://doaj.org/article/3b01f92057b94c23b0a622e9dfbeb441

Learning to automatically detect features for mobile robots using second-order Hidden Markov Models

Autor: Richard Washington, Jean-François Mari, Olivier Aycard

Publikováno v: proceedings of the IJCAI'03-Workshop on Reasoning with Uncertainty in Robotics-IJCAI-RUR'03
proceedings of the IJCAI'03-Workshop on Reasoning with Uncertainty in Robotics-IJCAI-RUR'03, Aug 2003, Acapulco, Mexico, France. 8 p
[Research Report] RR-4659, INRIA. 2002, pp.32
International Journal of Advanced Robotic Systems
International Journal of Advanced Robotic Systems, 2004, 1, 1 (4), pp.231--245
International Journal of Advanced Robotic Systems, Vol 1 (2004)
International Journal of Advanced Robotic Systems, InTech, 2004, 1, 1 (4), pp.231--245
International Journal of Advanced Robotic Systems, Vol 1, Iss 4 (2008)

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, espec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dea4dd84860ecec2e3e8c493c778e869
https://inria.hal.science/inria-00099809

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Using measurements to reduce model uncertainty for better predictions

Autor: Pasquier, Romain, Smith, Ian F. C.

Accurate models of real behaviour that are determined through measurements help engineers avoid expensive interventions and structural replacement. Model calibration by “curve-fitting” measurements to predictions is not appropriate for full-scale

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______185::86ff655dc6a2f8871fc1d4a88b6b4007
https://infoscience.epfl.ch/record/212711