LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Answer set programming for stream reasoning
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
Proceedings of the 10th SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software
Smart solutions for risk prevention through analysis of people movements
GPC'11 Proceedings of the 6th international conference on Grid and Pervasive Computing
A rule-based contextual reasoning platform for ambient intelligence environments
RuleML'13 Proceedings of the 7th international conference on Theory, Practice, and Applications of Rules on the Web
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This paper describes an intelligent home healthcare system characterized by a wireless sensor network (WSN) and a reasoning component. The aim of the system is to allow constant and unobtrusive monitoring of a patient in order to enhance autonomy and increase quality of life. Data collected by the sensor network are used to support a reasoning component, which is based on answer set programming (ASP), in performing three main reasoning tasks: (i) continuous contextualization of the physical, mental and social state of a patient, (ii) prediction of possibly risky situations and (iii) identification of plausible causes for the worsening of a patient's health. Starting from different data sources (sensor data, test results, inference results) the reasoning component applies expressive logic rules aimed at correct interpretation of incomplete or inconsistent contextual information, and evaluates correlation rules expressed by clinicians. The expressive power of ASP allows efficient enough reasoning to support prevention, while declarativity simplifies rule-specification and allows automatic encoding of knowledge. Preliminary evaluations show that the combination of an ASP-based reasoning component and a WSN is a good solution for creating a home-based healthcare system.