Visual content representation and retrieval for Cognitive Cyber Physical Systems

Cognitive Cyber Physical Systems (C-CPS) have gained significant attention from academia and industry during the past few years. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes, which environmental conditions may vary, adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior like predicting possible events based on cognitive capabilities that are able to sense, analyze, and act based on their analysis results. However, perceiving the environment and translating it into knowledge to be useful for the decision making process, still remains a challenge for real time applications due to the complexity of such process. In this paper, we present a multi-domain knowledge structure based on experience, which can be used as a comprehensive embedded knowledge representation for C-CPS, addressing the representation of visual content issue and facilitating its reuse. The implementation of such representation has been tested in a Cognitive Vision Platform for Hazard Control (CVP-HC) which aims to manage of workers’ exposure to risks in industrial environments, facilitating knowledge engineering processes through a flexible and adaptable implementation.