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An Ontology-based Context-aware System for Smart Homes: E-care@home
This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. Expand
The basic idea is to integrate the simulation of a sensorised apartment with human behaviour modelling based on constraint-based planning that produces a sequence of daily activities that exhibits the same relevant properties as data from a comparable real-world apartment. Expand
Seeking Prevention of Cognitive Decline in Elders via Activity Suggestion by A Virtual Caregiver
It is shown how the user experience can be enriched with an adaptive configuration encouraging socialization and cognitive training in an autonomous agent residing in the cloud and generating interventions based on users' data. Expand
Open-Source Data Collection and Data Sets for Activity Recognition in Smart Homes
A collection of software modules for data collection, labeling, and various reasoning tasks such as activity recognition, person counting, and configuration planning, and a series of data sets that were collected using the E-care@home system. Expand
The MOVECARE Project: Home-based Monitoring of Frailty
Here, it is described how home-based monitoring of frailty is addressed within MoveCare, specifically for the five Fried criteria. Expand
Towards a Synergy of Qualitative Spatio-Temporal Reasoning and Smart Environments for Assisting the Elderly at Home∗
Applications of smart environments are ever-increasing due to their possibilities of contributing towards an independent and active lifestyle for different user groups. An example of such anExpand
Context Recognition in Multiple Occupants Situations: Detecting the Number of Agents in a Smart Home Environment with Simple Sensors
Context-recognition and activity recognition systems in multi-user environments such as smart homes, usually assume to know the number of occupants in the environment. However, being able to count ...
Distributed Decision-Theoretic Active Perception for Multi-robot Active Information Gathering
This paper proposes a distributed decision process where a robot maintains a belief matrix representing its beliefs and beliefs about the beliefs of the other robots to access the relevance of their beliefs and the divergence with each other. Expand
Contribution to multiagent planning for active information gathering. (Contribution à la planification multiagent pour la perception active)
A new fully decentralized model of multiagent planning for information gathering, called MAPING (Multi-Agent Planning for INformation Gathering), the agents use an extended belief state that contains not only their own beliefs but also approximations of other agents’ beliefs. Expand
A decision-theoretic planning approach for multi-robot exploration and event search
A distributed decision-theoretic model called MAPING (Multi-Agent Planning for INformation Gathering), in which each agent computes a communication and an exploration strategy by assessing the relevance of an observation for another agent, and includes a forgetting mechanism to ensure that the event-exploration remains open-ended. Expand