AI-at-Home – Artificial Intelligence at Home

Project Duration: 01.12.2020 - 30.11.2022

The aim of the present project is to develop a self-learning system for the area of age-appropriate living that will be able to predict the individual probability of incidents – in particular dangerous situations – by means of Algorithms of Artificial Intelligence (AI Algorithms). These incidents include dementia or depression, increased risk of falling and acute complaints. For this purpose, thanks to data mining, predictors can be identified that will make individual predictions of incidents possible with help of adaptive models. That in turn will enable elderly people or their relatives to be warned at an early stage. This self-learning system will be optimised with the help of 75-100 participants, preferably recruited from the district areas of the project partners Pflegewerk and AOK. Both project partners hope to achieve potential savings from the prevention of emergency interventions and inpatient treatment. Furthermore, the quality of life of the participants and their relatives will increase and positive effects on the service system as well as on the work of the care providers will be achieved.

With over 50 years of experience in the market, the iso-Institute contributes to the AI-at-Home project with its social science competences. Our work tasks focus mainly on identifying the needs within the target group of older and particularly vulnerable people. By this, we will collect socio-demographic data, support the recruitment of test persons and we will analyse the acceptance of the system among the users and among the service providers involved in the project. Moreover, we will examine how the technology used affects the interaction of the test persons with the service providers in the care setting and how socio-technical systems must be designed in order to be accepted in everyday life and in work routines.

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Project Duration:

01.12.2020 – 30.11.2022

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Funded by:

Bundesministerium für Wirtschaft und Energie

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Project Staff:

Dr. Sabine Kirchen-Peters, Kathleen Schwarz

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