## 3 IoT-JFML to FFH Proposal  
The aim of the proposed system is to prevent FFH suffered by construction workers. The system considers data obtained by different sensors distributed in construction place areas. Data collected by the sensors were associated with significant variables in FFH accidents. Communication between sensors and the rest of the system is based on wireless capabilities. The most relevant factors in FFH were identified and monitored in the present proposal.  
* Use of the harnesses. The appropriate use of PFAS is a key factor in FFH that is widely identified in the literature [8; 38].
* Altitude. Workplace height is an important variable in FFH. The consequences of FFH accidents are influenced by the altitude of the fall [61].
* Distance to the edge of the fall. A worker placed near to an edge at height is more likely to fall than another located far from the edge in the same workplace. In addition, when workers are placed on elevated surfaces heights, the related changes in their visual field, affect their body balance. There exists a direct relationship between fear of FFH and the actions performed for human postural control [62].
* Wind. Weather conditions are not possible to change in construction sites due to the majority of them being outdoor projects [63]. High wind velocity could impact negatively on construction sites [7].  
In order to manage the previously detailed variables, the following sensors and devices were included in the monitoring system.  
* BLE receiver (\(R\));
* Harness (\(H\)) with BLE integrated for attachment detection (\(B_{0}\));
* Virtual barrier (\(VB\)) of \(n\) BLE beacons (\(B_{1}\), \(B_{2}\),..., \(B_{n}\));
* Altimeter (\(Alt\));
* Anemometer (\(Anm\)).  
The BLE receiver was designed for IoT systems (\(R\)). It provided RSSI values of power for the beacon messages received during the scan phase. According to the RSSI values, the system can calculate the distance between the receivers and beacons [19]. Similarly, a virtual barrier \(VB\) with a set of BLE beacons (\(B_{1}\), \(B_{2}\),..., \(B_{n}\)) is used in the proposal [64]. Additionally, the altitude of the workplace was detected by an altitude sensor (\(Alt\)) attached to the worker. Moreover, the wind velocity at the workplace is collected by an anemometer (\(Anm\)). In Table 3, the information and the working range of the sensors are summarized [65].  
According to the sensors and collected information, many working conditions can be evaluated and the risk levels of the tasks performed can be valuated. For instance, the BLE beacon (\(B_{0}\)) joined to the lifeline, combined with a receiver BLE (\(R\)), can monitor the connection of the worker connected to the lifeline. Receiver (\(R\)) estimates the distance of the worker to the harness anchorage, based on an RSSI signal [19]. When the estimated gap between the worker (\(R\)) and the lifeline (\(B_{0}\)) is smaller than a given distance, the harness can be considered connected to the worker.  
Considering habitual scenarios, sensors are placed on different working places according to the recommendations of the construction safety experts. Then, the real time information about the worker and their safety conditions are collected and used as input data in the system IOT-JFML. Figure 1 depicts construction workplace with distributed sensors.