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Abstract
Hazards are present in all workplaces and can result in serious injuries, short and long-term illnesses, or death. In this context, management of safety is essential to ensure the occupational health of workers. Aiming to assist the safety management process, especially in industrial environments, a Cognitive Vision Platform for Hazard Control (CVP-HC) is proposed. This platform is a Cyber Physical system, capable of identifying critical safety behaviors overcoming the limitations of current computer vision systems. In addition, the system stores experiential knowledge about safety events in an explicit and structured way. This knowledge can be easily accessed and shared and may be used to improve the user/company experience as well as to understand the company safety culture and to support a long term change process. The CVP-HC is a scalable yet adaptable system capable of working in a variety of video analysis scenarios whilst meeting specific safety requirements of companies by modifying its behavior accordingly. The proposed system is based on the Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA).
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Authors (3)
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Caterine De
- University of Newcastle, Australia School of Engineering
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Cesar Sanin
- University of Newcastle, Australia School of Engineering
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Details
- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Published in:
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Advances in Intelligent Systems and Computing
no. 853,
pages 266 - 275,
ISSN: 2194-5357 - Title of issue:
- Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018 strony 266 - 275
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- De C., Sanin C., Szczerbicki E..: Cognition and Decisional Experience to Support Safety Management in Workplaces, W: Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018, 2018, Elsevier,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-319-99996-8_24
- Verified by:
- Gdańsk University of Technology
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