European Union Projects

European Union Projects

16040 PHEW (Personal-Health-Empowerment)

Rising costs of healthcare due to the ageing population and related increase of non-communicative diseases urges for finding ways to save expenses by diminishing the need for care and making the current care more efficient. Current care provision is reactive, and process driven, treating patients according to predefined pathways with limited possibilities to take into account the individual needs or abilities. Health authorities and care providers are finally noticing the one resource that had remained unused – the person or patient him/herself! By starting with the primary need of the person – to be healthy – and including him/her into the process in an active role, new paradigms for care become possible. Significant cost reductions can be achieved by preventive solutions to help the person adopt a healthy lifestyle – thus reducing the number of patients – and by providing the person with tools to actively participate in the treatment when diseases do arise – thus decreasing the burden on care personnel. The main goal of this proposal is to empower people to monitor and improve their health using personal data and technology assisted coaching.

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17039 XIVT (Excellence In Variant Testing)

Within the XIVT (pronounced “shift”) project, a method and toolchain will be defined for testing highly configurable, variant-rich embedded systems in the automotive, rail, industrial production and telecommunication domains. This enables a highly effective, cost-efficient quality assurance, allowing the shift to autonomous, flexible and adaptive applications in these domains. Base of the method is a knowledge-based analysis of requirements formulated in natural language, and a model-based test generation on the product-line level. The XIVT project will result in modules and open-source packets for the enhancement of existing domain-specific testing tools, a reference implementation of the resulting method and toolchain, and an ecosystem of services around the proposed methodology.

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17020 POLDER (Urban Data Policy Lab: POLicy & Data Exploitation & Re-use)

Recent advances in technology, from wireless sensor networks to big data processing and analysis, are radically changing our cities, by introducing new services for the citizens, and improving existing ones both in terms of efficiency and reduced costs. Urban policy making is a fundamental aspect of such transformation and can benefit from such emerging technologies with new supporting tools and optimized processes. Currently though, policy-making is not benefiting from these developments. This will be addressed in the POLDER project.

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18032 FoodFriend (Autonomous and easy-to-use tool for monitoring of personal food intake and personalised feedback)

What and how much we eat has an important impact on our health. Diet-related diseases are a major public health concern and continue to endanger our population health and the sustainability of our healthcare systems. Unbalanced food intake (relating to both what and how much we eat) can result in metabolic disturbances, malnutrition, overweight, poor mental performance and other medical risk factors like hypertension, and osteoporosis. This can further lead to cardiovascular diseases, type 2 diabetes, hip fractures, liver pathologies, Alzheimer’s disease and cancer. [1] It is evident that these issues are found both in free living as well as hospital/nursing home settings. Therefore, the newly developed Food Friend technology as presented in this proposal will be oriented towards (1) Prevention of malnutrition in nursing homes and in patients using tube feeding and (2) Nutritional trans-mural care of chronic diseases (obesity, type 2 diabetes)

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18003 APE: Automatic Privacy Explorer

Since 2018, every company dealing with European citizen personal data has to build its GDPR registry. Listing all personal data managed every day by the company can be an easy task because processes are well defined and documented, but finding all other data rarely used and stored internally can be a real challenge.

All companies often have some contact details or resumes about Human Resources candidates, documents containing personal data received by email, contact details from meeting attendees, … the list can be very long and varied. Finding all these personal data, checking if they have to appear in the GDPR registry or be deleted is a really big challenge for companies.

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19038 DOMONOID Domotics for Independent Living

Independent living for the aging population is a major challenge in healthcare, with many caregivers and care organizations in Europe becoming more and more overburdened with the increasing amount and complexity of health complaints, especially among the elderly population. Technical solutions have been proposed to mitigate some of these burdens, but current domotics solutions often only address a small part of the problem. There is a growing need for technology which integrates various smart home devices and software to be able to learn from the data each device collects, create a holistic image of the occupant, and is easy to use for the elderly resident, taking into account the various health problems they might have. The goal of DOMONOID is to create such an infrastructure, which unites domotics, interfaces, sensor technology, and the user to support independent living.

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9020 e-INDEX Electrombility-Intelligent iNtegrated Demand-side Energy-management eXchange

Electrical power systems represent complex and dynamic systems, consisting of a large number of interconnected subsystems for supply, demand, and distribution, including smart electric meters, consumers, electrical grids, transformers, power-plants, and decentralized generators to name a few. These subsystems are nowadays strained by the rapid growth of electric mobility, like cars and trains, and the increasing demand for high power and fast charging. Moreover, the transition to renewable energy sources and the decommissioning of conventional power plants creates supply-stability problems. Both the increase in demand and instability in the supply pose a major challenge that requires innovative solutions to regain the balance in this value chain. From a business perspective, this problem is vital to electricity providers as their core business is changing. Since the technology to generate and store electricity at one’s home is becoming more affordable, more people are adopting it and the value proposition for being connected to the grid is no longer be about energy, but about service reliability and power quality that the grid can provide. Such a situation creates a new business value where electricity providers can charge for the service offered not the energy. For example, they charge customers’ batteries when wholesale prices are low, or discharging them when prices are high; schedule energy intensive devices and/or operations at times when demand is low; and finally, support local grids when they are stressed. The new business model should revolve around managing the behind-the-meter assets, not managing the generation assets. Demand Side Management (DSM) enables the adjustment of the loads in the grid to ensure a balanced operation, while simultaneously optimizing the utilization of the resources in the electrical power system. It also provides an opportunity for energy consumers to function as providers, energy storage buffers, and demand pattern regulators. Today’s DSM systems are limited to local energy grids, and the load-balancing solutions within the local grid itself does not fully utilize planning and machine learning methods.

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19027 AIToC Artificial Intelligence supported Tool Chain in Manufacturing

Modern approaches for manufacturing engineering rely heavily on software tools for planning, simulation and automation. While these tools are highly sophisticated in their area of application, interoperability is lacking, due to missing standards and incompatibilities between tools, methods and formats. While some companies have developed internal standards and methods, there is no industry-wide standard. Engineering software tools therefore must be adapted to each company’s needs, with large efforts. Furthermore, overall optimization of the design of production systems is still largely done in an iterative process by experienced engineers, and usually not well supported by computer tools. This is due to the fact that the number of variants and combinations in which a production system can be built, is huge. The combinations of alternatives for manufacturing methods, operations planning, choice of resources and tooling, and the factory layout makes it difficult to do advanced simulations and evaluations of even a small set of alternatives.

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