Bellotto, Nicola, Fernandez-Carmona, Manuel and Cosar, Serhan (2017) ENRICHME integration of ambient intelligence and robotics for AAL. In: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing (AAAI 2017 Spring Symposium), 27 - 29 March 2017, Stanford, CA.
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25362 Bellotto2017.pdf - Whole Document 3MB |
Item Type: | Conference or Workshop contribution (Presentation) |
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Item Status: | Live Archive |
Abstract
Technological advances and affordability of recent smart sensors, as well as the consolidation of common software platforms for the integration of the latter and robotic sensors, are enabling the creation of complex active and assisted living environments for improving the quality of life of the elderly and the less able people. One such example is the integrated system developed by the European project ENRICHME, the aim of which is to monitor and prolong the independent living of old people affected by mild cognitive impairments with a combination of smart-home, robotics and web technologies. This paper presents in particular the design and technological solutions adopted to integrate, process and store the information provided by a set of fixed smart sensors and mobile robot sensors in a domestic scenario, including presence and contact detectors, environmental sensors, and RFID-tagged objects, for long-term user monitoring and
Keywords: | AAL, assistive robotics, ambient intelligence, RFID, smart-home |
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Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence H Engineering > H671 Robotics G Mathematical and Computer Sciences > G740 Computer Vision |
Divisions: | College of Science > School of Computer Science |
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ID Code: | 25362 |
Deposited On: | 15 Dec 2016 20:24 |
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