STATS

About the project

The overall well-being of the military personnel has been put forward as one of the main focus points in the strategic agenda of the Ministry of Defence. It has been shown however, that attrition in recruits, burnout, general fatigue, injuries and diseases are common in military personnel worldwide and as such threaten the efficiency and functioning of the Belgian Armed Forces. However, the timely detection of problematic situations and preventive actions are not easy and a clustered monitoring of the determining factors is currently very complex.

STATS will investigate how objectively measured sensor data and specific military performance assessments can ease/facilitate the early detection of suboptimal function in 4 important pillars (physical fitness and recovery, mental readiness, health, nutrition and hydration) that might put the overall well-being of the military personnel at risk. The fully automated continuous collection of data with wearables and a data transmission system with an AI-based platform for “blended coaching” must guarantee that this approach is applicable for large numbers of individuals. In the blended coaching system, the professional experts in the different pillars are supported by AI-algorithms, though it is the expert who takes the decisions and who is in the driving seat.

Overall, STATS is a real-time monitoring and management system to get Ready To Perform Soldiers. This compares to top sports where athletes must be ready to perform every day – a domain where several of the project partners are already active for years.

STATS Schematic

IDLab role

An important aspect of STATS will be to make the sensors and WCN platform ready-to-implement in a military setting. This will be the main task/focus for IDLab. In the different project phases we will iteratively decrease the workload for staff/soldiers by:

  • easing the process to capture/collect data,
  • limiting the amount of wearables/devices (end goal: all-in-one),
  • providing one central platform with data of the 4 pillars,
  • making the visualisations/results easy to interpret.

Contact the involved IDLab Researchers

Main researcher
ing. Robbe Decorte
Assisting researcher
dr. ir. Maarten Slembrouck