Simulation-Based Training with Gamified Components for Augmented Border Protection

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Abstract:

ARESIBO, an EU H2020 funded project, aims to improve the efficiency of border surveillance systems by providing the operational teams and the tactical command and control levels with accurate and comprehensive information by means of augmented reality (AR). This article describes the training system, with gamified modules, that was designed and developed within the project to deliver training on the AR applications developed to operators in border security missions. The ARESIBO Training System is fed by a set of interoperable, distributed simulators (Simulation Engine) comprised of detailed landscapes, realistic assets, and end-user vetted border control scenarios. By generating virtual incidents and situations, the Training System creates realistic operational conditions in which to train and employ the ARESIBO AR devices. It also includes the front-end tools and interfaces for the trainer to setup and execute the training sessions, such as the Trainer Editor GUI. Additional gamified modules were developed to investigate the effectiveness of serious gaming for training; these modules work both on- and off-line and independently of each other to maximize the autonomy of the trainer. This work concludes with a description of the training scenario and training events.