A Fall from Height prevention proposal for construction sites based on Fuzzy Markup Language, JFML and IoT solutions

With the increasing complexity of problems in the construction sector, fall from height is one of the most worrying in this sector. An appropriate use of a harness can be the difference between an incident or a critical accident. Traditionally, safety training, safety communication and onsite inspections are the habitual tools to manage the adequate use of harness. Despite on the availability of some technological solutions to monitor workers safety, their use are not frequent because some construction conditions. For this reason, the integration of technology and security expert knowledge in this task are a key issue. Different technological solutions, mainly based on computer vision approaches, have been proposed in this context. Nevertheless, these solutions lack ubiquitous computing, real time decisions capacity and expert knowledge management being crucial in this sector. In this context, Internet of Things (IoT) and Fuzzy Logic Systems (FLS) can provide several advantages: acquired data from sensors and real time decisions based on FLS. In this paper, the definition and use of an IoT infrastructure integrated with JFML, an open source library to FLS according to the IEEE std 1855, to support experts' decision making in fall from height are presented.