Lone workers are, as a rule, more isolated and subject to a higher risk. In 2015, in the EU-28 there were about 4,000 fatal accidents involving lone workers. Although communication systems already exist for this type of worker, FhP-AICOS and the French company Neogivie, of the ICOM France group, have come together to develop a more advanced and intelligent technology which, by using artificial intelligence techniques, allows defining patterns and predicting risk situations. SAIFFER is the project funded by the European program EUREKA! Eurostars and should be on the market in 2023.
In addition to location integration (outside and inside buildings) and movement analysis that allows the sending of alerts when the worker remains immobile for a long time or loses the connectivity signal, SAIFFER will integrate innovative features that seek to increase and guarantee the safety of lone workers. The technology will make it possible to continuously monitor the worker and detect falls (which can occur, for example, in the event of a third party attack, health problems, adverse floor conditions, etc.), in addition to including a module for predicting unexpected situations, that is, through the analysis of mobility patterns it will be possible to infer and predict risky situations. Let us imagine for example that, in a prison, a group of people runs in the same direction, this can mean the existence of an irregular or risky situation in a certain place. Through the algorithms and software to be developed by the FhP-AICOS’ team of experts, this forecast will be possible.
“Lone workers” means employees who work alone on the premises of a company or factory and who are often out of sight and reach of colleagues. Often unable to be rescued immediately in the event of an emergency or accident, they are often equipped with communication devices or monitored by protection systems. Although communication systems already exist for this type of worker, the truth is that they are all based on reaction, that is, alerts or warnings sent after an occurrence or incident. SAIFFER's innovation is based precisely on the fact that the system is proactive and warns of situations of imminent danger.