This paper presents the development of a decision support system for run-time safety management in Smart Work Environments (SWEs). Our approach consists of four main phases: (i) definition of the basic steps of a methodology for run-time safety management; (ii) development of an ontological knowledge-base of safety in work environments; (iii) definition of constraints on the ontology based on organizations’ safety protocols; (iv) communication of relevant information to each actor in the safety management team. We propose a generic ontological model of safety expertise, based on Occupational Safety and Health Regulations (OSHA), that is employed as Knowledge required in our safety management methodology based on the MAPE-K (Monitor–Analyze–Plan–Execute and Knowledge) loop. We present the RAMIRES (Risk-Adaptive Management in Resilient Environments with Security) tool, implementing this methodology. RAMIRES is developed as a dashboard, supporting the safety management team in understanding the risk and its consequences, and to support decision making in risk treatment. RAMIRES interacts with the SWE and the safety management team (actors) in order to: (i) communicate the risks and preventive strategies to actors; (ii) obtain more data about the observed areas to understand the risk and its consequences; and (iii) execute the automatic preventive strategies and support actors in the execution of human-operated preventive strategies. In this paper, we show the details on concepts designed in the safety ontology and illustrate how these concepts can be extended to provide an abstract model of a specific use case. Furthermore, we propose the definition of constraints on the ontology using logic-based rules. Finally, we discuss the advantages and limitations of the proposed methodology regarding the resilience of the environment.
['Mahsa Teimourikia', 'Mariagrazia Fugini']
Ontology development for run-time safety management methodology in Smart Work Environments using ambient knowledge