Machine learning engine to monitor human performance

The proposed solution will predict the level of human performance in a given scenario, on the basis of historical data, enabling replanning of operations, or real-time warning to operators. The use of machine learning (ML) algorithms has been explored in aviation to identify precursors of unsafe take-off or landing, warning pilots of potentially dangerous configurations of team, aircraft, weather status. As a complementary approach, the proponent has developed the use of quantitative and qualitative indicators – including behavioral, neuro-physiological indicators, online and post-session questionnaires – to monitor the different components of Human Performance, like workload, stress, decision making. The approach proposed here builds on these two experiences, with two major extensions: - Considering data from all the available data sources: human behavior, speech, brain activity, physiological measures, data from the equipment, or from external contextual conditions. - Use of the data for planning purposes and not only in real-time during operations. Human performance issues are often hard to monitor because it's complex to clearly define “what is a good performance” and because its outcomes may not immediately be measurable. However, human operators still remain the key system element for successful and safe operations. It is also multi-layered: what is observable (the results) is different than what drives the performance, i.e. individual factors, as well as equipment and contextual factors. The SME is already engaged in international collaboration and is able to sell its products mainly in Germany and Europe. The company is looking for a commercial agreement with technical assistance and marketing collaboration for opening new potential markets, to enlarge their business market with ad-hoc solutions to be integrated into the customer contests. Also, research cooperation agreements are envisaged. The preferred partners are: - companies (public and/or private) for marketing and commercial agreements with technical assistance mainly in Europe, but also in the USA and Nord America are sought.