The ASCLEPIOS project will research novel cryptographic approaches for cloud-based e-health systems and will develop mechanisms for protecting sensitive data in healthcare. The vision of ASCLEPIOS is to maximize and fortify the trust of users on cloud-based healthcare services by developing mechanisms for protecting both corporate and personal sensitive data. While researchers have developed many theoretical models that could enhance the security level of healthcare services, only a rudimentary set of techniques are currently in use. ASCLEPIOS is exploiting this gap by using by utilizing several modern cryptographic approaches to build a cloud-based eHealth framework that protects users’ privacy and prevents both internal and external attacks.
PREVENTOMICS builds a new paradigm in preventive personalised nutrition based on the potential of omics, especially metabolomics, accessible for everyone. The novelty relies on a new integration of genetic, nutritional and psychological factors and the application of state of the art metabolomics technologies and computational modelling of the metabolome, to assess the real incidence of disease-inducing factors on the organism, translating this information into personalized dietetic advice for the user, levering on ICT technologies. The main outcome from PREVENTOMICS is a novel mFood Platform, a unique-in-its-kind service, interoperable with current existing Apps for monitoring health status and with personalized nutrition software, thus opening the door to the personalization of any type of health treatment where combinations of genetic, biological, nutritional and psychological factors are important.
UPTIME aims to design a unified predictive maintenance framework and an associated unified information system in order to enable the predictive maintenance strategy implementation in manufacturing industries. The UPTIME predictive maintenance system extends and unifies the new digital, e-maintenance services and tools and incorporates information from heterogeneous data sources, e.g. sensors, to more accurately estimate the process performances. The UPTIME Platform has been designed according to Systems Engineering principles to address both generic and specific user needs & technical requirements. The UPTIME Platform is deployed and validated against three industrial use cases: (1)production and logistics systems in the aviation sector, (2) white goods production line and (3) cold rolling line for steel straps.
With the projected growth in transport demand, the current modus operandi in transport supply is deemed unsustainable and generates the need for innovative services that could support seamless mobility and a shift from car ownership to usership. Αgainst this background the main goal of MaaS4EU is to provide quantifiable evidence, frameworks and tools, to remove the barriers and enable a cooperative and interconnected EU single transport market for Mobility-as-a-Service (MaaS), a user-centric, intelligent mobility distribution model, in which users' needs are met via a single platform and are offered by a service provider, the mobility operator. This will be achieved by addressing challenges at the level of business, end-users, technology and policy, including the definition of sustainable business models that support the cooperation across transport stakeholders, the understanding of user needs and choices, the implementation of the required technological infrastructure (a MaaS mobility hub) and the identification of the enabling policy and regulatory frameworks.
Journalism is an important economic sector with a strong influence on the society and politics. In an era of information overload, journalists struggle to develop fresh, innovative and creative stories challenged by time pressure, huge amount of information to process and lack of funds. INJECT aims to help journalists to develop stories in a more efficient and creative way. To accomplish this goal, INJECT is developing digital services that will help journalists throughout the whole process of developing a news story. INJECT digital services implement creative search algorithms that provide inspirational resources for new articles, effectively providing information resources in a more efficient way, making search and information collection easier and helping journalists save time by facilitating story creation. We want journalists to get the most out of technology so INJECT will also help SMEs to integrate these services into the platforms they already use and give them the training to use the services.
The goal of PrEstoCloud is to make substantial research contributions in the Cloud computing and real-time Big Data technologies in order to provide a dynamic, distributed architecture for proactive cloud resource management reaching the extreme edge of the network for efficient big data processing and to reply and validate it in three challenging, complimentary and commercially promising use cases. Three use cases will demonstrate pro-activeness, self-adaptation, orchestration of distributed processing nodes and processing on the edge: (a) A vehicle/fleet management processes real-time information and alerts – based on data streams from GPS, on-board diagnostics, tire sensors and others (b) A media prosumer platform offers personalized and flexible consumption of real-time stories by combining freelance reporting, traditional broadcasting and social media streams. (c) A surveillance solution combines real-time data streams from cameras and pre-processing results from groups of unmanned aerial vehicles. You can follow PrEstoCloud on Twitter and like the Facebook page. Read more at the project's the web site
MELODIC will enable data-intensive applications to run within defined security, cost, and performance boundaries seamlessly on geographically distributed and federated cloud infrastructures. Serving the user’s needs and constraints, MELODIC will realise the potential of Cloud computing for big data and data-intensive applications by transparently taking advantage of distinct characteristics of available private and public clouds, dynamically optimise resource utilisation, consider data locality, conform to the user’s privacy needs and service requirements, and counter vendor lock-in. These benefits are achieved by integrating and extending the results and the open source platforms available from three major European Cloud projects with the Hadoop and Spark big data frameworks. The integrated MELODIC platform will be tested in several demanding real world applications: scalable Customer Relationship Management, real-time optimised traffic routing, and fast and scalable processing of genomic data.
The transportation sector is undergoing a considerable transformation as it enters a new landscape where connectivity is seamless and mobility options as well as related business models are constantly increasing. Our vision is to provide the required interoperability, adaptability and dynamicity in modern transport systems for a proactive and problem-free transportation system. OPTIMUM will establish a largely scalable, distributed architecture for the management and processing of multisource big-data, enabling continuous monitoring of the transportation systems needs and proposing corresponding proactive decisions and actions in an (semi-) automatic way. The project follows a cognitive approach based on the Observe, Orient, Decide, Act loop of the big data supply chain for continuous situational awareness. The proposed solution will be deployed in real-life pilots in order to realize a set of challenging use cases in the domains of multi-modal transportation, adaptive toll pricing and Car2X integration.
The valuable transformation of organizations that adopt cloud computing is indisputably accompanied by a number of security threats that should be considered. PaaSword introduces a novel holistic, data privacy and security by design, framework that aspires to alleviate them. The envisaged framework intends to maximize and fortify the trust of individual, professional and corporate users to cloud services. Specifically, PaaSword involves a context-aware security model, the necessary policies enforcement and governance mechanisms along with a physical distribution, encryption and query middleware, aimed at facilitating the implementation of secure and transparent cloud-based applications. PaaSword will provide storage protection mechanisms, which will improve confidentiality and integrity protection of users’ data in the cloud while it will not affect the data access functionality.
In the European Union, around 5 million people suffer from psychotic disorders, being schizophrenia one of the most widely-known. Around 30-50% patients are considered treatment-resistant and present persistent symptoms, requiring long periods of hospital care and being at greater risk of mortality and multi morbidity. During the 3 years of the project, a model of analysis will be implemented, in order to move forward in understanding resistant schizophrenia.
m-Resist project aims to develop an innovative disease management system, m-RESIST, a mobile ICT system addressed to empower patients suffering from resistant schizophrenia, which will involve them to actively participate in the therapeutic process and will enable them to self-manage their condition. m-RESIST will become a step forward in improving and optimizing the clinical decision process.