Ontologia de aplicação para avaliação de riscos na interação humano-máquina
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Data
2022-03-02
Autores
Oliveira Neto, Marcílio Francisco de
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
A área de Segurança e Saúde Ocupacional evolui ao passo que as tecnologias aplicadas nas indústrias evoluem devido aos avanços da Indústria 4.0. Dessa forma, dentro do cenário industrial, com a Interação Humano-Máquina (IHM) presente, novos cenários de riscos são apresentados. Sendo assim, a demanda de análise e identificação desses riscos em ambientes compartilhados, os quais envolvem seres humanos e máquinas, aumentou e, com isso, identificar, classificar e monitorar novos riscos passou a demandar abordagens que utilizam sistemas computacionais com tecnologias avançadas de sistemas de informação, compartilhamento de dados, web semântica e ontologias, garantindo melhor cooperação e exploração das capacidades das máquinas em conjunto com os seres humanos, e portanto, um ambiente mais seguro. Porém, abordagens que utilizam ontologias para descrever o contexto de riscos não englobam a descrição do contexto de IHM, sendo que a recíproca também é válida. Além disso, a avaliação de riscos no contexto de IHM não utiliza, em sua maioria, tecnologias semânticas. Desse modo, com o intuito de propor uma ontologia capaz de descrever o contexto de análise de riscos em ambientes de IHM, o presente trabalho propõe a ontologia OAR-IHM, bem como uma aplicação semântica para validar a ontologia em cenários de IHM simulados, através do uso de simulador CoppeliaSim. A ontologia OAR-IHM reutiliza uma ontologia do contexto de riscos, a Hazardous Situation, e uma ontologia do contexto de máquinas e sensores, a Semantic Sensor Network, bem como demais requisitos que visam a segurança do colaborador em um cenário de IHM, para oferecer descrição suficiente desse contexto a fim de possibilitar a avaliação do risco presente em diferentes cenários simulados de IHM. Dessa forma, uma vez criada a ontologia, ela é utilizada para definir um modelo conceitual inicial do contexto presente no cenário simulador, o qual é criado no simulador CoppeliaSim. Sendo assim, com o modelo conceitual inicial criado e a simulação confeccionada, tais etapas servem como entrada para uma aplicação semântica, a qual é capaz de, em tempo de execução, instanciar todos os individuos presentes no cenário de IHM simulado, bem como todas as suas respectivas relações, possibilitando a consulta do potencial risco presente no cenário, baseado na distância entre colaborador e maquinários presentes no ambiente. Com isso, foram confeccionados quatro diferentes cenários simulados de IHM, e, através da ontologia OAR-IHM e da aplicação semântica, a proposta se mostrou suficiente na descrição dos contextos apresentados nesses cenários, bem como ofereceu formas de avaliar o risco presente nos cenários, levando em consideração a distância entre colaboradores e maquinários.
The Occupational Safety and Health area evolves while the technologies applied in the industries evolve due to the advances of Industry 4.0. Thus, within the industrial scenario, with Human-Machine Interaction (HMI) present, new risk scenarios are presented. Thus, the demand for analysis and identification of these risks in collaborative environments, which involve humans and machines, has increased and, with that, identifying, classifying, and monitoring new risks has started to demand approaches that use computer systems with advanced technologies of systems of information, data sharing, semantic web, and ontologies, ensuring better cooperation and exploitation of the capabilities of machines together with humans, and therefore, a safer environment. However, approaches that use ontologies to describe the risk context do not encompass the description of the HMI context, and the converse is also valid. In addition, risk assessment in the context of HMI does not use, for the most part, semantic technologies. Thus, to propose an ontology capable of describing the context of risk analysis in HMI environments, the present work proposes the OAR-HMI ontology, as well as a semantic application to validate the ontology in simulated HMI scenarios, through using CoppeliaSim simulator. The OAR-IHM ontology reuses a risk context ontology, the Hazardous Situation, and a machine and sensor context ontology, the Semantic Sensor Network, as well as other requirements aimed at employee safety in an HMI scenario, to offer sufficient description of this context to make it possible to assess the risk present in different simulated HMI scenarios. Thus, once the ontology is created, it is used to define an initial conceptual model of the context present in the simulator scenario, which is created in the CoppeliaSim simulator. Thus, with the initial conceptual model created and the simulation made, these steps serve as input to a semantic application, which is capable, at runtime, of instantiating all the individuals present in the simulated HMI scenario, as well as all their respective relationships, making it possible to consult the potential risk present in the scenario, based on the distance between the employee and machinery present in the environment. With this, four different simulated HMI scenarios were created, and, through the OAR-IHM ontology and the semantic application, the proposal proved to be sufficient in the description of the contexts presented in these scenarios, as well as offering ways to assess the risk present in the scenarios, considering the distance between employees and machinery.
The Occupational Safety and Health area evolves while the technologies applied in the industries evolve due to the advances of Industry 4.0. Thus, within the industrial scenario, with Human-Machine Interaction (HMI) present, new risk scenarios are presented. Thus, the demand for analysis and identification of these risks in collaborative environments, which involve humans and machines, has increased and, with that, identifying, classifying, and monitoring new risks has started to demand approaches that use computer systems with advanced technologies of systems of information, data sharing, semantic web, and ontologies, ensuring better cooperation and exploitation of the capabilities of machines together with humans, and therefore, a safer environment. However, approaches that use ontologies to describe the risk context do not encompass the description of the HMI context, and the converse is also valid. In addition, risk assessment in the context of HMI does not use, for the most part, semantic technologies. Thus, to propose an ontology capable of describing the context of risk analysis in HMI environments, the present work proposes the OAR-HMI ontology, as well as a semantic application to validate the ontology in simulated HMI scenarios, through using CoppeliaSim simulator. The OAR-IHM ontology reuses a risk context ontology, the Hazardous Situation, and a machine and sensor context ontology, the Semantic Sensor Network, as well as other requirements aimed at employee safety in an HMI scenario, to offer sufficient description of this context to make it possible to assess the risk present in different simulated HMI scenarios. Thus, once the ontology is created, it is used to define an initial conceptual model of the context present in the simulator scenario, which is created in the CoppeliaSim simulator. Thus, with the initial conceptual model created and the simulation made, these steps serve as input to a semantic application, which is capable, at runtime, of instantiating all the individuals present in the simulated HMI scenario, as well as all their respective relationships, making it possible to consult the potential risk present in the scenario, based on the distance between the employee and machinery present in the environment. With this, four different simulated HMI scenarios were created, and, through the OAR-IHM ontology and the semantic application, the proposal proved to be sufficient in the description of the contexts presented in these scenarios, as well as offering ways to assess the risk present in the scenarios, considering the distance between employees and machinery.
Descrição
Palavras-chave
Ontologia, Avaliação de riscos, Interação humano-máquina, Segurança e saúde ocupacional, Ontology, Risk evaluation, Human-machine interaction, Occupational health and safety