Cognitive Village will deliver socio-technical innovation in the field of ambient assisted living and ambient intelligence. A challenge of the project is to identify potentials for support and provide technological compensation for physical decline as well as tools to foster wellbeing in older age. Based on a deep understanding of the needs of elderly users in different fields, the project will deliver a technical platform for measuring and analysing user behavior in a wide range of contexts, as well as components for making this data accessible to users in comprehensive ways that allow for self-reflection as well as optimized care.
Adaptive, learning systems for supporting the everyday life of elderly
Cognitive Village is a collaborative project co-funded by the German Ministry of Research and Education (BMBF). The project aims at developing an adaptive, learning system for supporting the everyday life of elderly in their homes and neighborhoods, both in urban as well as rural areas. The system will serve as a hub connecting various sensors and actuators via a real-time middleware. A machine learning component will analyse the behavior of the user in order to find patterns and adapt intelligently to his/her routines and individual needs.
In the project, innovation is facilitated through a collaborative process with strong user engagement. The role of FIT is to create legitimate spaces for co-design, enabling users and designers to find a common language and understanding of the system.
Cognitive Village aims at supporting elderly users in staying in their homes as long as possible. The field we are working in comprises of three different neighbourhoods all administered by the same housing agency. For bridging different perspectives, FIT engages in development of user interfaces for the system, translating user needs into design, and evaluating novel design concepts especially with regard to their usability and accessability for elderly users. Our approach combines several empiric methods ranging from ethnographical observations, semi-structured interviews, and various form of participatory design workshops.