Dynamic extraction of holiday data for use in a predictive model for workplace accidents

This work has been supported by FCT—Funda¸c˜ao para a Ciˆencia e Tecnologia within the Project Scope UIDB/05757/2020 and NORTE-01-0247-FEDER-072598 iSafety: Intelligent system for occupational safety and well-being in the retail sector.
Workplace accidents are a concern for companies nowadays and can occur due to internal and external factors of the company. Thereby, several strategies are developed to predict and minimize the hazards in this environment. Companies resort to intelligent solutions, such as predictive analytics, aiming to increase productivity while ensuring safety in the work environment. In terms of accident prediction analysis, different input data are needed to ensure the accuracy of a predictive model. Therefore, this study aims to automatic collect and pre-process data from holidays for subsequent implementation in an accident-oriented predictive model to demonstrate its relevance in predicting accidents in the workplace.

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