IDEAL-CITIES aims to develop, demonstrate and evaluate an open modular platform for building adaptive Internet-of-Things and Participatory Sensing (IoTPS) based Smart City applications, supported by Big Data analytics and Cloud services. IDEAL-CITIES outcomes will increase urban life quality, safety and inclusivity by enabling citizens and authorities to produce and exchange contextualised distributed intelligence and information in real-time, in a trustworthy and sustainable manner. The IDEAL-CITIES platform will foster the development and uptake of novel IoTPS-based Smart City applications and enhance the associated market base, by demonstrating new feasible ways for providing IoTPS applications and services which can contribute to urban citizen’s well-being and the cities’ circular economy. The IDEAL-CITIES platform will be demonstrated in the context of two fully-fledged IoTPS Applications, with a focus on mobility for the impaired and on citizen safety, in close cooperation with involved communities (a non-profit organisation for the blind and partially-sighted and four municipalities, respectively), validating the utility of the proposed platform and approach.

The abundance of tracking sensors in recent years has led to the generation of high-frequency and high-volume streams of data, including vessels, vehicles' tracking data, smartwatches, cameras, and earth observation sensors. However, there are cases where the trajectory of a moving object has gaps, errors, or is unavailable. However, a vast pool of tracking data is available but remains unexplored or underutilized and has the potential to reveal important information. The MUlti-Sensor Inferred Trajectories (MUSIT) project aims at exploring and fusing data from all heterogeneous sources to provide detailed information about a moving object’s whereabouts and behavior, reduce gaps, and produce a refined and inferred trajectory with minimal errors. The fusion of multi-sensor data is required to fill in the trajectory gaps of moving objects and attach useful semantics to the trajectory and its components. AI algorithms and spatio-temporal methodologies that can fuse information and infer the “missing knowledge” are crucial to the implementation of MUSIT. Furthermore, different representation models from multiple domains within the ICT sector will also be explored. Datasets will be made available in cases where it was previously thought impossible, and infer knowledge thus improving the overall surveillance. Therefore, the MUSIT project will tackle the aforementioned issues in a process that can be categorized into three parts: i) data collection and creation, ii) exploitation and utilization of cross-domain representation models within the ICT sector for trajectories, and iii) analysis and processing of outcomes to produce information-rich results related to vessel monitoring and urban mobility.

SYNAPSE aims to design, develop & deliver an Integrated Cyber Security Risk & Resilience Management Platform, with holistic Situational Awareness, Incident Response & Preparedness capabilities. The proposed platform will encompass: (i) Incident Response through process automation and orchestration mechanisms, also covering organisational/business aspects (e.g., business continuity processes); (ii) AI-enhanced Situational Awareness, encompassing extraction & analytics of actionable and pertinent Cyber Threat Intelligence (CTI), along with attack early warning & threat hunting systems; (iii) Preparedness through cybersecurity, privacy & business continuity training, covering different training delivery means, allowing it to tailor the delivery method to the content; (iv) Technical & economic risk management, integrating outputs of (i)-(iii) above and supporting risk-benefit analyses (including what-if scenarios) to inform decision-making and enable risk transfer schemes with Smart Contract-enabled cybersecurity insurance; (v) Continuous feedback between (i)-(iv) above, along with standards-based sharing, alerting & reporting (intra- & inter- Member State), based on outputs of (i)-(iii) above, thus enabling the establishment of shared situational awareness, coordinated response and joint preparedness

CONSENTIS is geared to alleviate the challenges posed by personal data sharing towards the implementation of EU regulations and strategic initiatives like eIDAS, EU Data Spaces and GDPR. It introduces a novel framework which offers Self-Sovereign Identity and user-centric consent management solutions that enables users to (a) have full control over their personal data collection and usage and (b) provide informed consent through user-friendly interfaces and notifications. The proposed framework is agnostic to existing services and formats and guarantees high levels of protection avoiding potential legal uncertainty, through a continuous assessment mechanism for security, risk and legal aspects. CONSENTIS is an industry-oriented project, with SMEs and large companies covering more than 80% of the consortium and is built on a collaboration of 12 organisations from 9 EU member states and associated countries. The Consortium includes: 2 academic institutions, 8 SMEs and 2 large industry partners that bear strong interest and relevance to the project objectives and are highly committed in the delivery of scientific excellence and innovation in the fields of identity management and SSI, consent management, blockchain and smart contracts, user interfaces/user experience, cybersecurity and PETs, business and market impact and EU laws, policies and regulations for human rights and technology.

PHOENi²X aims to design, develop, and deliver a Cyber Resilience Framework providing Artificial Intelligence (AI) - assisted orchestration, automation & response capabilities for business continuity and recovery, incident response, and information exchange, tailored to the needs of Operators of Essential Services (OES) and of the EU Member State (MS) National Authorities entrusted with cybersecurity. Through the deployment PHOENi²X Cyber Resilience Centres (PHOENi²X CRCs), OES will gain: (i) enhanced Situational Awareness with AI-assisted Prediction, Prevention, Detection & Response capabilities, and business risk impact assessment-based prioritisation; (ii) proactive and reactive Resilience Automation, Orchestration, and Response (ROAR) mechanisms, providing Business Continuity, Recover and Cyber & Physical Incident Response; (iii) Increased Preparedness through relevant Serious Games and realistic Resilience Cyber Range (RCR) Assessment & Training; (iv) timely and actionable Information Exchange between OES, National Authorities and EU actors, leveraging interoperable and standardised alerting and reporting mechanisms and processes.