e-SENSE Missione-SENSE provides heterogeneous wireless sensor network solutions to enable Context Capture for Ambient Intelligence, in particular for mobile and wireless systems beyond 3G; thus enabling truly multi-sensory and personal mobile applications and services, as well as assisting mobile communications through sensor information. |
Ambient Intelligence is a key component in the next epoch of mobile and wireless communication systems. Much of the work in Ambient Intelligence has been progressed during the initial stages of several IST funded projects, e.g. the IST-MOBILIFE project, as well as other national and international projects (see Useful Links). However, the enabling technology that provides systems with information to allow for Ambient Intelligence has been neglected and currently consists of many independent modes of input, mainly relying on active user interactions or specialised sensor systems gathering information.
Therefore e-SENSE proposes a context capturing framework that enables the convergence of many input modalities, mainly focussing on energy efficient wireless sensor networks that are multi-sensory in their composition, heterogeneous in their networking, either mobile (e.g. Body Sensor Network) or integrated in the environment (e.g. small to large scale sensor networks, e.g. from single sensors (e.g. camera) to thousands or millions of sensors collecting information about the environment, a person or an object).
This framework will be able to supply ambient intelligent systems with information in a transparent way hiding underlying technologies thus enabling simple integration.
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The e-SENSE project is split into the following technology oriented research areas:
- Energy and Bandwidth Efficient, wireless sensor communications
- Scalable and Reconfigurable Transport of Data (air-intefaces up to the transport layer in a cross functional optimised approach), and
- Distributed Processing Middleware (preparation of data to be presented to upper layers, management of resources and pre-processing of data (e.g. synchronisation)); situation aware applications and services (e.g. positioning)
Further, e-SENSE takes into account the socio-economic and psychological impact such a system can have. This is linked with scenario building, user testing (in the form of visual and simulated scenarios to be presented to users) and specification of top level requirements (current and future sensor payloads, characterisation of situation and context, classification of information).
Information will flow into an innovation sink that will convrge and steer these work areas, thus develop a common architecture and e-SENSE framework.
The main outputs are formulated through extensive, bandwidth efficiency and scalability of the system as well as further proof of concept of the value and feasibility of a generic framework for Ambient Intelligent Systems.
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