Skip to Main content Skip to Navigation
Journal articles

A semantic plug&play based framework for ambient assisted living

Abstract : The large scale deployment of ambient assisted living systems raises challenges related to the heterogeneity of the environments in which sensors, devices and services will be deployed, as well as the diversity of patients' needs and profiles. In these environments, each patient has a specific profile that influences the choice of interaction devices and requires particular services. The selection of required context-aware services affects the decision on the set of sensors that need to be installed. Moreover, even in one specific environment, new sensors, devices and services may need to be added due to the evolution of patient's needs. Therefore, a generic framework that is able to adapt to such dynamic environments and to integrate new sensors, devices and services at runtime is required. In this paper, we present a dynamic framework for ambient assisted living able to adapt to the non-uniformity of the deployment environments. The main contribution consists of a semantically driven plug&play mechanism integrated seamlessly with the reasoning engine so that all the entities present in the environment can be plugged and integrated in the reasoning process without interrupting the framework functionality. Our solution is based on the OSGi framework with the use of the DPWS standard and the semantic web.
Document type :
Journal articles
Complete list of metadata

https://hal.sorbonne-universite.fr/hal-00728911
Contributor : Hamdi Aloulou <>
Submitted on : Friday, September 7, 2012 - 4:52:26 AM
Last modification on : Wednesday, November 4, 2020 - 3:38:31 PM

Identifiers

  • HAL Id : hal-00728911, version 1

Citation

Hamdi Aloulou, Mounir Mokhtari, Thibaut Tiberghien, Jit Biswas, Kenneth Lin Jin Hong. A semantic plug&play based framework for ambient assisted living. International Conference on Smart Homes and Health Telematics (ICOST), 2012, 7251, pp.165-172. ⟨hal-00728911⟩

Share

Metrics

Record views

148