An Internet of Things and Fuzzy Markup Language Based Approach to Prevent the Risk of Falling Object Accidents in the Execution Phase of Construction Projects
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AutorMartínez Rojas, María; Gacto, María José; Vitiello, Autilia; Acampora, Giovanni; Soto Hidalgo, José Manuel
Construction projectExecution phaseSafetyFalling objectsInternet of Things (IoT)Fuzzy markup language
Martínez-Rojas, M.; Gacto, M.J.; Vitiello, A.; Acampora, G.; Soto-Hidalgo, J.M. An Internet of Things and Fuzzy Markup Language Based Approach to Prevent the Risk of Falling Object Accidents in the Execution Phase of Construction Projects. Sensors 2021, 21, 6461. https://doi.org/10.3390/s21196461
PatrocinadorThis research was funded by University of Naples Federico II through the Finanziamento della Ricerca di Ateneo (FRA) 2020 (CUP: E69C20000380005) and has been partially supported by the ”Programa de ayuda para Estancias Breves en Centros de Investigación de Calidad” of the University of Málaga and the research project BIA2016-79270-P, the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund-ERDF (Fondo Europeo de Desarrollo Regional-FEDER) under project PGC2018-096156-B-I00 Recuperación y Descripción de Imágenes mediante Lenguaje Natural usando Técnicas de Aprendizaje Profundo y Computación Flexible and the Andalusian Government under Grant P18-RT-2248.
The Internet of Things (IoT) paradigm is establishing itself as a technology to improve data acquisition and information management in the construction field. It is consolidating as an emerging technology in all phases of the life cycle of projects and specifically in the execution phase of a construction project. One of the fundamental tasks in this phase is related to Health and Safety Management since the accident rate in this sector is very high compared to other phases or even sectors. For example, one of the most critical risks is falling objects due to the peculiarities of the construction process. Therefore, the integration of both technology and safety expert knowledge in this task is a key issue including ubiquitous computing, real-time decision capacity and expert knowledge management from risks with imprecise data. Starting from this vision, the goal of this paper is to introduce an IoT infrastructure integrated with JFML, an open-source library for Fuzzy Logic Systems according to the IEEE Std 1855-2016, to support imprecise experts’ decision making in facing the risk of falling objects. The system advises the worker of the risk level of accidents in real-time employing a smart wristband. The proposed IoT infrastructure has been tested in three different scenarios involving habitual working situations and characterized by different levels of falling objects risk. As assessed by an expert panel, the proposed system shows suitable results.