CAREFUL-EDGE-X
Cascaded edge computing applications with Gaia-X for patient care
| Short description |
| CAREFUL-EDGE-X implements an intelligent system network for care facilities, comprising decentralised data collection, AI-based processing of patients’ vital signs and the use of nursing robots. In this way, it frees up care staff from having to perform routine tasks, while complying with data protection regulations. |
CAREFUL-EDGE-X implements edge computing solutions for in-patient and out-patient care. The cornerstone of this project is the automated, contactless collection and intelligent processing of readings of important bodily functions of patients, i.e., their vital signs. The solutions enable monitoring of the patients’ health status and optimise their care. They also reduce workload for care staff. Situation-specific data processing is performed on hardware devices with the aid of a multi-level edge system that is developed within the project and compliant with Gaia-X. In future, this will enable integration of the CAREFUL-EDGE-X system into health-related Gaia-X data ecosystems and thus also integration of additional Gaia-X-based offerings and services from third-party providers. As part of the project, the system will, for example, be demonstrated and tested under realistic conditions in an intelligent nursing room as well as in the home as a “healthcare setting”.
Market perspectives and product claims
The target market of the edge system developed by the CAREFUL-EDGE-X project comprises organisations providing in-patient and out-patient care for senior citizens and persons with disabilities. As the system frees up care staff from performing routine tasks, it also contributes to solving the problem of skills shortages. In the long term, this will invigorate job profiles in the sector and improve the participation of people in need of care. The proposed system also helps meet the demand that exists in the health and care sectors for solutions capable of merging and analysing various data sources in compliance with data protection regulations.
CAREFUL-EDGE-X creates trust in the digitalisation of care, which is a patient-oriented and therefore particularly data-sensitive sector. In future, the solution will have the greatest application potential for those who require care but want to remain in their own homes for as long as possible. The system as a whole and its individual sub-components can be operated and sold as a complete package or as stand-alone solutions.
Challenge and innovation
At present, the only digital support for care staff is available in the form of limited siloed solutions. AI-based analysis of the data collected is rare and almost exclusively based on centralised cloud computing. The transfer of the large data volumes produced results in high energy and CO2 consumption. It also presents the healthcare sector with considerable challenges in relation to data security and data protection. This undermines the trust of participants in intelligent care applications and reduces their acceptance.
To overcome these challenges, CAREFUL-EDGE-X employs a multi-level concept intended to ensure that, in future, only as much data as is necessary will need to be transferred to central Gaia-X-compliant cloud platforms thanks to efficient, decentralised preprocessing of data close to the devices themselves and incorporating AI elements. This means that the edge devices can be integrated into the overall system to meet the individual requirements of the individual care situation. The project is developing and testing the concept using an intelligent patient room. It is based on a hardware network of service robots and a large number of sensors for measuring vital signs, as well as a “care data gateway” designed to ensure the Gaia-X-compliant transfer of individual, selected data records. A cloud interface that is also integrated into the system enables connection to a Gaia-X data platform.
To ensure that the processing of the data collected by the sensors can be adjusted to meet the needs of the individual situation, the project uses a multi-level concept for edge devices. At the first edge level, the sensor data is pre-processed in the immediate vicinity of the sensors using specialised hardware. This first-level “node” is then passed on to a second edge level, where the data is compared with the data of other first-level nodes and the data quality is improved by means of redundancy analyses. The second edge-level “room node” also ensures that the transfer of sensitive data to the cloud is limited to what is necessary, thereby complying with the principle of data minimisation.
Use cases
The CAREFUL-EDGE-X concept is being implemented as a demonstrator and is being evaluated in realistic scenarios. This includes, for example, the use of an intelligent seat cushion and an intelligent nursing bed. These sub-components are equipped with sensors that measure vital signs and enable contactless collection of data, including heart rate, breathing rate and lying position. The existing ManagingCare Digital (MCD) digitalisation platform from C&S Computer und Software GmbH
enables dynamic provisioning of the data for each edge level and its integration into the platform's care process planning function. In future, this is expected to contribute to greater planning efficiency.
Consortium
C&S Computer und Software GmbH (consortium leader), Fraunhofer IMS, Herrmann Bock GmbH, Visseiro GmbH, Medisana GmbH, Friedrich-Alexander University (FAU) of Erlangen-Nuremberg
Benefits
| Current situation | Future vision |
| Routine tasks represent a significant drain on resources. In out-patient care, this is compounded by long travel times. | Care staff are freed up from performing routine tasks. In out-patient care, less travel is required, resulting in more time for care and fewer emissions of greenhouse gases. |
| AI-based applications are only available via cloud services in the care sector. | Multi-level edge devices enable AI-based applications with local data processing – which produce savings on greenhouse gas emissions. |
| Lack of data sovereignty in relation to patient data due to centralised processing, usually via cloud services from suppliers outside of Europe. | Gaia-X implementation results in high levels of data sovereignty and security for data that is collected close to patients and analysed using AI methods. |
| Digital applications to support care staff consist of siloed solutions. | A scalable system solution comprising applications that can be customised to suit individual requirements. |
| Minimal use of Gaia-X by SMEs. | Gaia-X becomes established among SMEs that offer products and services in the care sector. |
