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.
The SYMPHONY project develops an innovative platform for supporting policy-making, including the following key components: i) An agent based macroeconomic model and simulator for policy making, able to take into account disequilibrium dynamics and including credit and financial markets ii) An integrated system of social media mining and information markets, able to collect citizens’ economic expectations in order to inform policy makers and to calibrate the expectations of artificial agents in the agent-based model iii) A game interface for the agent-based model, in order to allow researchers, policy makers, stakeholders and citizens to access and interact with the model iv) A set of customized information markets in order to monitor and collect dynamically the expectation of the users on the simulated artificial economy. This allows for a dynamic feedback between policy and expectations. These components are designed to provide policy makers with a groundbreaking set of instruments able to involve citizens in the policy formation process and to increase their awareness about the various economic scenarios.
A new class of enterprise systems, proactive enterprises, that will be continuously aware of that what "might happen" in the relevant business context and optimize their behavior to achieve that what "should be the best action", are emerging nowadays. ProaSense's core goal in this context is to pave the way for an efficient transmission from Sensing into Proactive enterprises systems, a new class of systems that will be in essence of a world where it is possible to prevent problems or capitalize on opportunities before they even occur. This will be achieved through the adoption of the Observe-Orient-Decide-Act (OODA) loop of situational awareness and development of corresponding technologies supporting a scalable, distributed architecture for the management and processing of big-data that will eventually enable continuous monitoring and the need for service adaptation and propose corresponding changes in an (semi-) automatic way.
As enterprises increasingly adopt the model of cloud computing, the enterprise IT environment is progressively transformed into a matrix of interwoven infrastructure, platform and application services which are delivered from diverse service providers. To help enterprises deal with the overwhelming complexity of consuming large numbers of cloud services from diverse providers, future enterprise cloud service delivery platforms will need to implement a wide array of sophisticated brokerage-enabling capabilities, which will give rise to services that go far beyond anything currently offered by today’s cloud intermediaries. The challenge, to which the Broker@Cloud project commits, is to research and to develop solutions with respect to some of the most valuable and technically demanding types of brokerage capabilities foreseen for future enterprise cloud service brokers.