The GAUSS project aims fast and thorough achievement of acceptable levels in terms of performance, safety and security for both, current RPAS and future UTM operations. UTM helps control, manage and integrate all RPAS in the VLL airspace to ensure the security and efficiency of UAS operations. The key element within GAUSS is the integration and exploitation of Galileo-EGNOS exceptional features for precise and secure positioning. These features will enable not only safe, timely and efficient operations but also coordination among a higher number of RPAS with appropriate levels of security, as it provides anti-jamming and anti-spoofing capabilities. Multi-frequency and multi-constellation solutions will be exploited with this purpose. GAUSS will increase resilience in UTM operations and, at the same time, ensure UTM coordination capabilities to increase the number of platforms that can share the same airspace. Precise coordination among UAS in the air, together with individual high precision and secure positioning are key for the safety of the operations and therefore for the success of UTM. The UTM infrastructure will also benefit from the GAUSS Galileo-EGNOS based ADS-B solution and encrypted air-ground communications. GAUSS includes the definition, negotiation and execution of safe trajectories both in normal operation and in case security or safety is compromised. The GAUSS systems will be validated with two field trials (in-land and sea) with the operation of 4 UTM coordinated RPAS with different types (fixed and rotary wing) and EASA operational categories. The outcome of the project will consist of Galileo-EGNOS based technological solutions to enhance safety and security levels in current RPAS operations and future UTM based operations. Increased levels of efficiency, reliability, safety and security in RPAS operations are key enabling features to foster the European RPAS regulation and market development and their full acceptance by the European society.

HERON aims to develop an integrated automated system to perform maintenance and upgrading roadworks, such as sealing cracks, patching potholes, asphalt rejuvenation, autonomous replacement of CUD elements and painting markings, but also supporting the pre/post-intervention phase including visual inspections and dispensing and removing traffic cones in an automated and controlled manner. The HERON system consists of: i) autonomous ground robotic vehicle that will be supported by autonomous drones to coordinate maintenance works and the pre-/post- intervention phase; ii) various robotic equipment, including sensors and actuators (e.g., tools for cut and fill, surface material placement and compaction, modular components installation, laser scanners for 3D mapping) placed on the main vehicle; iii) sensing interface installed both to the robotic platform and to the Road Infrastructures (RI) to allow improved monitoring (situational awareness) of the structural, functional and RI’s and markings’ conditions; iv) the control software that interconnects the sensing interface with the actuating robotic equipment; v) Augmented Reality (AR) visualization tools that enable the robotic system to see in detail surface defects and markings under survey; vi) Artificial Intelligence/AI-based toolkits that will act as the middleware of a twofold role for: a) optimally coordinating the road maintenance/upgrading workflows and b) intelligent processing of distributed data coming from the vehicle and the infrastructure sensors for safe operations and not disruption of other routine operations or traffic flows; and vii) integrate all data in an enhanced visualisation user interface supporting decisions and viii) communication modules to allow for Vehicle-to-Infrastructure/-Everything (V2I/X) data exchange for predictive maintenance and increase users safety. HERON aims to reduce fatal accidents, maintenance costs, traffic disruptions, thus increasing the network capacity and efficiency.

In the recent years, there are plenty of metrics that try to evaluate the maturity of products/systems/processes when identifying their deployment readiness. Even though, an excessive effort has been made to integrate widely used frameworks, methodologies and indicators in the products/systems/processes, this leads to a limited usage from the EU funded security R&I projects. As a result, a robust scaling framework is more than of utmost importance. The proposed MultiRATE scaling framework will rely on the existing established readiness level approaches and will formally combine them into one acceptable and reliable framework. MultiRATE will be able to evaluate and apply the readiness of all aspects of products/systems/processes. It will make a thorough research on the existing methodologies and will develop a well-established scale taking into consideration several areas of knowledge such as Technology Readiness Level (TRL) scale, Integration Readiness Level (IRL), Commercialisation Readiness Level (CRL), Manufacturing Readiness Levels (MRL), Security, Privacy and Ethics Readiness Level (SPRL) and Societal Readiness Level (SRL). These RLs will set the basis for the creation of the holistic MultiRATE framework that will evaluate the readiness of all aspects of a product/system/process. The experience gained from previously proposed and ongoing maturity evaluation solutions developed and will be proposed under EU-funded projects will lead to the MultiRATE robust holistic framework solution. Of great importance will be the establishment of a network of projects and organisations that will support the design of the appropriate evaluation methodologies adding also their knowledge and expertise on the calibration and testing of both individual RLs and the holistic one. This network will be built based on the partner’s involvement on existing networks and EU funded projects.

Maritime Domain Awareness is the combination of activities, events and threats in the maritime environment that could have impact on marine activities and EU territory. During the past decades, advances in Information and Communication Technologies have provided better means to monitor and analyse vessel activity. Today private and public source of data such the Automatic Identification System or space related data can be combined with Vessel Traffic Services, Vessel Traffic Management Systems and Vessel Traffic Monitoring & Information Systems data enabling the development of value added information resulted by the combination of such data. European waters are navigated daily by some 12,000 vessels, which share their positions to avoid collisions, generating a huge number of positional messages every month. It is important that this overabundance of information will not overwhelm the marine operator in charge for decision-making. The challenge is twofold: on one side encourage the exchange of heterogeneous data among administration valorising the CISE network currently in place, on the other exploit at the best these datasets by means of automated processing in a way to minimise false alert that might results by an incorrect processing or interpretation of the results. PROMENADE will improve solutions for the vessel tracking, behaviour analysis and automatic anomaly detection by means of the application Artificial Intelligence (AI) and Big Data (BD) technologies, and to promote collaborative exchange of information between maritime surveillance authorities, shortening the time to market and assuring the compliance with legal and ethical regulations. An open, service-based toolkit implementing “state of art” AI / BD techniques also benefiting of HPC (High Performance Computing) platform is the core activity of the project. The project’s developments will be demonstrated and evaluated in 3 operational scenarios and 1 simulated defined by Border Guards Authorities.

CONNECTOR’s vision is to contribute to the European Integrated Border Management (EIBM) and to the EU Customs Action Plan by addressing the need of close cooperation between Customs, Border and Coast Guard Authorities within the current and upcoming challenging and demanding environment of borders’ control by further involving Customs to the Common Information Sharing Environment (CISE) network and Enhanced Common Information Sharing Environment (e-CISE) through the proposed Customs Extended Common Information Sharing Environment (CE-CISE). CONNECTOR aims for the first time to suggest an integrated, common and shared risk assessment approach for all Border Management Authorities, considering the pan-EU common risk indicators per end user group (Customs, Border and Coast Guards Authorities including FRONTEX), to ensure external EU border and secure EU citizens from cross-border crime and/or secure the seamless flow of travellers, as recommended in the multiannual strategic policy document . Thus, in this sense, CONNECTOR proposal, will design and develop the CONNECTOR system as an interoperable technical environment, ensuring close and practical cooperation and information exchange at all levels. The design and the development of the CONNECTOR system will be based on the analysis of current policy initiatives in EU level (directives, policy and staff documents, guidelines etc.) along with needs, gaps and future views of the end-user groups going beyond previous initiatives (ANDROMEDA, MARISA, EFFECTOR, etc.), complying with the Societal, Ethical and Legal (SoEL) requirements and regulations, following the SoEL-by-design principle. The CONNECTOR system will be validated in real operational environment, based on well-defined National, Cross-border and Transnational use cases defined commonly by Customs and Border and Coast Guards authorities, during three (3) long lasting trials (Demonstration and Testing) under standardised methodology.