Reinforcing conceptual engineering design with a hybrid computer vision, machine learning and knowledge based system framework

We propose a novel system that aids engineers in the conceptual stage of design. Our system's goal is to support the engineer without limiting his creative role; thus, our proposed method does not produce ready study solutions but rather actively monitors the design procedure, verifying design...

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Bibliographic Details
Published in2011 IEEE International Conference on Systems, Man, and Cybernetics pp. 3242 - 3249
Main Authors Kaloskampis, I., Hicks, Y. A., Marshall, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2011
Subjects
behaviour analysis
Bridges
cognitive activities
Computer vision
design engineering
graphical model
Hidden Markov models
Monitoring
Radio frequency
random forest
Sections
Vegetation
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Summary:We propose a novel system that aids engineers in the conceptual stage of design. Our system's goal is to support the engineer without limiting his creative role; thus, our proposed method does not produce ready study solutions but rather actively monitors the design procedure, verifying design stages and pointing out potential mistakes. This is achieved with a hybrid computer vision, machine learning and knowledge based system framework. Design stage identification is performed with a novel algorithm which comprises a classification stage based on Random Forests and examination of the temporal relationships between the engineer's actions with the aid of statistical graphical models. Experimental results captured in a complex, real life scenario demonstrate our system's ability to efficiently support the engineer's decisions during the conceptual stage of design.
ISBN:9781457706523
1457706520
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2011.6084169