Towards the Empathic Building – Detection and recognition of well-being of individuals and groups

This paper reviews the current state of science and technology on the detection and recognition of well-being of individuals and groups of people. It turns out that most of the current research projects refer merely to partial areas of this problem. Some concentrate on single values like temperature, ventilation or lighting separately. However, the results are often encouraging, suggesting that recognition of general well-being could in principle be possible. Based on these results we propose a new approach to measure and detect complacency in order to enable smart buildings to react to the needs of the inhabitants and users accordingly. Datasets composed of personal data from portable sensors and wearables or from questionnaires, data from sensor of the building and additional information like the current utilization of the room result in a clustering problem which can be solved using methods and algorithms of supervised learning.