Abstract:
Maritime accidents occur due to the accumulation of various contributing factors that happened in the sequence. The nature of these tributary factors can be either latent or active. The maritime accident ought to be investigated and evaluated based on some accident causation model. Approximately 80% of maritime accidents are attributed to factors that are associated with humans. Either the chain of erroneous events that eventually leads to an accident or some contributing step is factually initiated by human operator. The statistics by International Maritime Organization (IMO) depicts that the major contributing factors are either negligence of operators or violation of the standard operating procedures, thus, the study of the factors having maximum contribution will serve the principal purpose. Hence, for the elimination of these factors to avoid such misfortune events, operator vigilance for gross violations is deemed necessary. Breaches of rules by the human operator are a frequent cause of accidents, as accident evaluations show. Until now, there exists no framework for operator vigilance and cognition in their active environment. In this study, based on the fact that the primary cause of accidents in the maritime, chemical, and aviation industry is the erroneous human behavior, we have designed an AI-based Human-centered design IoOT (Internet of Operator Thing) Larch for continuous monitoring and surveillance. Various sensors constitute the Larch, which extracted the activities data and fed to the system where activities are successfully recognized and classified as either valid or invalid. An alarm will trigger by the continuous occurrence of mischievous activities by a specific human operator. Besides the rectification of malpractices by validating activities, the system also develops the profile of operator activities by creating separate log account, which can be further manipulate for behavioral and policy management in the long run.
