Increasing concerns about new threats related to a possible major accident on a nuclear power plant or a tactical nuclear explosion, linked with the war in Ukraine, impose to EU Countries to improve their current capabilities to prepare for and respond to these possible large-scale accidents. The need for advanced technologies, interoperable risk assessment tools, and comprehensive emergency coordination strategies has never been more critical. GUARDIANS will deliver advanced, cost-effective technologies, and strategies to improve disaster emergency management in Europe. The project will enable the development of advanced radiological technologies (radioactive gas sensor, active dosimeter network), innovative and scalable strategies for triage (video analyses, digital triage), decontamination, and medical countermeasures (hydrogel, new strategy for stable iodine distribution). Autonomous means such as drones and robots equipped for radiological measurements and enhanced observation capabilities will increase overall responsiveness. A central web-platform GUARDNET, built upon existing operational tools, will facilitate real-time information processing, synthesis, mission management, and simulation services, to support decision-making. The active participation of first responders/receivers and decision-makers, along with the execution of two field tests and the assessment of the alignment between population needs and authorities' response strategies will ensure that GUARDIANS produces a new and enhanced operational capability to respond effectively to a radiological or nuclear emergency. GUARDIANS will significantly enhance European Member States' ability by providing stakeholders with state-of-the-art capabilities, innovative technologies, and effective coordination strategies. This will accelerate the decision-making process, reduce intervention times, and mitigate human and environmental impacts through improved protection of populations and infrastructures.

Border authorities and Law Enforcement Agencies (LEAs) across Europe face important challenges in how they patrol and protect the borders. Their work becomes more problematic considering the heterogeneity of threats, the wideness of the surveyed area, the adverse weather conditions and the wide range of terrains. Although there are several research tools and works targeting these areas independently for border surveillance, nowadays border authorities do not have access to an intelligent holistic solution providing all aforementioned functionalities. Towards delivering such a solution, ROBORDER aims at developing and demonstrating a fully-functional autonomous border surveillance system with unmanned mobile robots including aerial, water surface, underwater and ground vehicles, capable of functioning both as standalone and in swarms, which will incorporate multimodal sensors as part of an interoperable network. The system will be equipped with adaptable sensing and robotic technologies that can operate in a wide range of operational and environmental settings. To provide a complete and detailed situational awareness picture that supports highly efficient operations, the network of sensors will include static networked sensors such as border surveillance radars, as well as mobile sensors customised and installed on board unmanned vehicles. To succeed implementing an operational solution, a number of supplementary technologies will also be applied that will enable the establishment of robust communication links between the command and control unit and the heterogeneous robots. On top of this, detection capabilities for early identification of criminal activities and hazardous incidents will be developed. This information will be forwarded to the command and control unit that will enable the integration of large volumes of heterogeneous sensor data and the provision of a quick overview of the situation at a glance to the operators, supporting them in their decisions.

The aim of our project is to train police officers’ on the procedure, through gamification technologies in a safe and controlled virtual environment. Essential tasks during the creation of LAW-GAME serious game are to virtualise and accurately recreate the real world. We will introduce an attractive approach to the development of core competencies required for performing intelligence analysis, through a series of AI-assisted procedures for crime analysis and prediction of illegal acts, within the LAW-GAME game realm. Building upon an in-depth analysis of police officers’ learning needs, we will develop an advanced learning experience, embedded into 3 comprehensive “gaming modes” dedicated to train police officers and measure their proficiency in: 1. conducting forensic examination, through a one-player or multi-player cooperative gaming scenario, played through the role of a forensics expert. Developed AI tools for evidence recognition and CSI and car accident analysis, will provide guidance to the trainee. 2. effective questioning, threatening, cajoling, persuasion, or negotiation. The trainee will be exposed to the challenges of the police interview tactics and trained to increase her emotional intelligence by interviewing a highly-realistic 3D digital character, advanced with conversational AI. 3. recognizing and mitigating potential terrorist attacks. The trainees will impersonate an intelligence analyst tasked with preventing an impending terrorist attack under a didactic and exciting “bad and good” multiplayer and AI-assisted game experience. The proposed learning experience focuses on the development of the key competences needed for successfully operating in diverse and distributed teams, as required by several cross-organisational and international cooperation situations. The learning methodology developed by the LAW-GAME consortium will be extensively validated by European end-users, in Greece, Lithuania, Romania, Moldavia and Estonia.