BIM-4-CARE
Research and development of a building model based on artificial intelligence for the care-orientated redesign of domestic living environments using modern automation technologies
| Brief description |
| BIM-4-CARE uses digital technologies to improve the living environment of people in need of care. It aims to help them avoid or delay a transfer from their own home to a care home for as long as possible. For the first time, BIM-4-CARE uses modern technologies such as helmet camera systems, a robot dog and artificial intelligence to record the living environment and the condition of the person concerned. This data then provides the basis for a care living space model that can plan and organise individual care better and more easily. In addition, it promotes a higher level of independence and quality of life for people in need of care. |
Challenge and innovation
The care sector represents both a cost-intensive and major socio-political challenge for Germany. The number of people in need of care is expected to rise to 6.5 million by 2050, with the percentage of home care continuing to increase. Home care generally requires structural remodelling measures. In order to meet the requirements of the care situation, all those involved in care, construction planning, and system installation should work together during the planning phase. For example, services based on smart living technologies and the resulting customer benefits depend very much on the cooperation of several players (care, trades, consultants, planners). The networking of stakeholders is currently insufficiently covered. This leads to unnecessary and contradictory surveys when recording care needs.
This is where the BIM-4-CARE project comes in: It aims to digitalise the planning of measures in order to improve living space for people in need of care. To this end, BIM-4-CARE is developing an AI-supported application solution that records and harmonises the knowledge gained from care experience with the expertise of relevant players in the field of home redesign. It can be integrated into the smart living ecosystem via interfaces. BIM-4-CARE enables, for example, the automatic recording of image data relating to the living environment and the enrichment of care-related requirements. This is used to create a care living space model that is suitable for simulating different development scenarios of the patient's condition. The simulations are visualised on an interactive room map. At the same time, improvement measures, such as structural changes and the use of smart living technologies, are generated. In particular, the mapping of the data within the ForeSightNEXT digital twin, which is provided via the Gaia-X-compliant ForeSightNext dataspace, is essential. The available data (e.g. patient data, information on living environments) is exchanged in a Gaia-X-compliant manner. Data can be provided by users both as private data and for sharing in the ecosystem.
Application and benefits
The use cases address specific applications for the care environment:
- Measures to improve the living environment: In this use case, the information from the platform is further processed to enable a precise definition of the requirements for care support and automation within the living space of the person concerned. Existing standards, care requirements from experts and individual wishes are taken into account in order to propose customised solution concepts and modification measures. These proposals will be used to generate care-related funding applications and tenders for necessary construction measures.
- Interactive room map: This use case processes the generated information for the user and visualises potential problem areas such as insufficient door widths, tripping hazards or lack of accessibility. Interactive planning of care requirements in conjunction with equipment features and structural measures allows various scenarios of the course of the illness to be simulated in order to take care requirements into account and plan accordingly.
Project partners
Architekturbüro Leinhäupl + Neuber GmbH, pricura GmbH, Hochschule Darmstadt, Forschungsgruppe „Assisted Working and Automation“ am Fachbereich Elektrotechnik und Informationstechnik
Consortium leader
Open Experience GmbH
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