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Abstract
This paper proposes the integration of image processing techniques (such as image segmentation, feature extraction and selection) and a knowledge representation approach in a framework for the development of an automatic system able to identify, in real time, unsafe activities in industrial environments. In this framework, the visual information (feature extraction) acquired from video-camera images and other context based gathered data are represented as Set of Experience Knowledge Structure (SOEKS), a formal decision event for reasoning and risk evaluation. Then, grouped sets of decisions from the same category are stored as decisional experience Decisional DNA (DDNA) to support future decision making events in similar input images. Unlike the existing sensor and vision-based approaches, that required rewriting most of the code when a condition, situation or requirement changes, our platform is an adaptable system capable of working in a variety of video analysis scenarios. Depending on the safety requirements of each industrial environment, users can feed the system with flexible rules and in the end, the platform provides decision makers with hazard evaluations that reuse experience for event identification and correction.
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Authors (3)
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Caterine De
- University of Newcastle School of Engineering
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Cesar Sanin
- University of Newcastle School of Engineering
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- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Published in:
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Advances in Intelligent Systems and Computing
no. 657,
pages 243 - 252,
ISSN: 2194-5357 - Title of issue:
- Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 strony 243 - 252
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- De C., Sanin C., Szczerbicki E..: Hazard Control in Industrial Environments: A Knowledge-Vision-Based Approach, W: Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017, 2018, Springer,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-319-67223-6_23
- Verified by:
- Gdańsk University of Technology
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