The automated care and monitoring of vulnerable people is becoming a reality with the rapid development and improvement of networked sensor technologies. Many researchers have shown considerable success in determining immediate causes for concern in well-being, such as detecting falls in the home. To date however, little emphasis has been placed on monitoring well-being in a long-term sense, known as third generation telecare. The system described in this paper 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 infer activities that the monitored client is undertaking and thus answer high level queries such as “is the person eating regularly”. The system also detects abnormal patterns of behaviour and provides tools for long-term trend analysis such that gradual and subtle changes in behaviour can be clearly understood. Soft computing techniques are needed due to the high degree of uncertainty in the inference process. We also describe a trial of the system, which was 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.
|Translated title of the contribution||A Third-Generation Telecare System using Fuzzy Ambient Intelligence|
|Title of host publication||Computational Intelligence for Agent-based Systems|
|Publisher||Springer Berlin Heidelberg|
|Pages||155 - 175|
|Number of pages||20|
|Publication status||Published - 2007|