Third generation telecare involves a customised sensor network, able to detect a person's movements and use of furniture and household items, coupled with a sophisticated fuzzy data analysis process able to answer high level queries such as "is the person eating regularly". Soft computing techniques are needed due to the high degree of uncertainty in the inference process. We describe a trial system, which has been installed in two homes. Results indicate that fuzzy analysis enables us to summarise the data in a manner which is useful to the care providers without them needing to be experts in data analysis.

Tele-care systems aim to carry out intelligent analyses of a person's wellbeing using data about their daily activities. This is a very challenging task because the massive dataset is likely to be erroneous, possibly with misleading sections due to noise or missing values. Furthermore, the interpretation of the data is highly sensitive to the lifestyle of the monitored person and the environment in which they interact. In our tele-care project, sensor-network domain knowledge is used to overcome the difficulties of monitoring long-term wellbeing with an imperfect data source. In addition, a fuzzy association analysis is leveraged to implement a dynamic and flexible analysis over individual- and environment-dependent data.