Ambient intelligence is a key component for future beyond 3G mobile and wireless communication systems and platforms with their respective service environment. The enabling technology that provides systems with information to allow for ambient intelligence requires the capturing of context that enables the convergence of information collected through many input modalities, rather than relying on the active user interactions or specialized sensor systems gathering only limited information about particular parts of a system. The richness of information that is required to fully capture the ambient intelligence demands a multitude of multisensory information. To obtain this information, potentially, a large variety in terms of their sensing capabilities as well as a large number of sensors is required. The sensors may communicate among themselves or via gateways with other systems and networks (e.g. other sensor networks, Cellular, WLAN, PAN, or the core network). The majority of the sensors in these areas will be wireless, mainly for the ease of deployment and convenience.
a proposed framework that enables the convergence of information and focusing on energy-efficient WSNs that are multisensory in their composition, heterogeneous in their networking, and either mobile or embedded in the environment. This encompasses any structure from single sensors to thousands of sensors collecting information about the environment, a person, or an object. The proposed framework is able to supply ambient intelligent systems with information in a transparent way hiding the underlying technologies, thus enabling simple integration of context sources and autonomous operation. The architectural vision towards ambient intelligence is shown in the illustration below.
Capturing, classifying, filtering, and sensing the situation and context through phenomena and signals from the physical environment will support and significantly enhance and enrich personal, family, and community focused mobile applications and services as well as enhance the wireless communication systems. A system concept and architecture has been developed to collaboratively capture a user’s context, and to pre-process rough data into meaningful data to be input into a user’s (individual, family, community) profile enabling context-enabled applications and services to a user at the right time. The integrity and sensitivity of such information demands a careful consideration on security, privacy, and trust of a user.
The key requirements for the architecture shown in the illustration above, are ultra-low power operation (in particular, for the communications but also for the local processing of the sensor information) and multidimensional scalability with respect to mobility, number of sensors, diversity of sensor classes, sensor network types, and sensor payload types. Also, presenting the captured information to ambient intelligent systems, achieving transparency with respect to the underlying sensor systems is of importance.
