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Smart Belt Design by Naïve Bayes Classifier for Standard Industrial Protection Equipment Integration

Sergio Márquez-Sánchez, Israel Campero-Jurado, Juan Quintanar-Gómez, Sara Rodríguez, Juan M. Corchado

Abstract



One of the main objectives of various companies between the industrial sector is the reduction of accidents, ranging from minor injuries to the death of workers. In order to prevent previously affected hazards, the fusion of Internet of Things and Industry 4.0 technologies has been chosen, being key tools for the detection and notification of personnel of anomalies detected in the environment, generating Industrial Protection Equipment (PPE) with the ability to predict, detect and report anomalies in the environment. This article proposes the design of a belt capable of being integrated into standard industrial protection equipment, this component being able to detect the operator’s condition from the presence of falls thereof, detection of noise levels, gas detection Toxic and notifications to the worker or nearby personnel of the anomaly detected. The information collected is processed by Artificial Intelligence (AI) techniques through Cloud Computing, highlighting during the investigation process the Naïv Bayes classifier to detect real risk situations in risk environments, alerting with 90% accuracy about different situations that can put the life of users at risk.

Keywords


OHS, Condition monitoring, Artificial Intelligence, Naïv Bayes, e-Health. Computing Classification System: Hardware Integrated circuits Interconnect Input / output circuits. Information systems Information systems applications Decision support systems Expert systems.

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