Many countries face the challenge of an aging population. Development of suitable technologies to support frail elderly living in care homes, sheltered housing or at home remains a concern. Technology evaluation in real-life conditions is often lacking, and randomized controlled trials of ‘pre-designed’ technologies are expensive and fail to deliver. A novel alternative would be ‘living labs’-real-life test and experimentation environments where users and producers co-create innovations and large-scale data can be collected.

The goal of the living labs and Data Driven Research and Innovation (DDRI) Programme is to use data driven analytics and insights to support technology development for independent living, healthy aging and more cost-effective care. This involves a cluster of long-term residential care facilities providing 24/7 living lab settings, linked to an embedded innovation hub. DDRI also encompasses private vehicles (e.g. sensors in cars) to enable elderly to drive safely for longer. Collaborations have been established with Universities in England, Scotland and Ireland and with international industry partners.

Several projects are underway: (i) develop machine learning algorithm from non-intrusive sensor data to build a well-being representation for individual residents/citizens; (ii) evaluate innovative interventions for good sleep environment and nutritional support; and (iii) establish ethics framework to ensure that needs of residents, families and staff are embedded in design, communication, and evaluation of future DDRI projects. In addition, fifteen interdisciplinary doctoral fellowships are in place, six universities are working closely with individual living lab settings, and an innovation hub has been established in one care home for horizon-scanning and strategic technology selection and implementation.

Over the next five years, a national network of 20 residential living labs with over 1,500 participants will be established. Generation of new user-led technologies, blueprints for capture of individual data at significant scale, and ethical and organizational guidelines will be developed. Intelligent mobility via data capture/feedback in vehicles will be established.