01934nas a2200241   4500000000100000000000100001008004100002653002800043653002900071653002900100653003500129653001300164100002000177700001800197700001800215700001700233700002100250700001700271245008700288300001200375490000700387520129800394       2022                            d10aHigh Level Architecture10ainteroperable simulation10aModelling and Simulation10aserious games and gamification10atraining1 aAlberto Tremori1 aSasha Godfrey1 aLuca Berretta1 aArnau Viñas1 aPavlina Nikolova1 aIliyan Hutov00aSimulation-Based Training with Gamified Components for Augmented Border Protection  a255-2720 v533 a<p>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.</p>