Recent advances in wireless networking technologies and the growing success of mobile computing devices are enabling new classes of applications. Distributed applications running in a mobile environment are often subject to varying qualities of service from the underlying infrastructure. The objective of the work outlined in this research is the development of an Ambient Middleware framework for Context-awareness (AMiCA) which will offer new opportunities for application developers and end users. Context-awareness has been a central issue in Ambient Intelligent research for the last decade. Context-awareness has emerged as an important idea for achieving automatic behaviours in pervasive systems. For example, a system or device that can sense a user’s context (e.g., location and physical actions, time, etc) and reacts to it provides convenience for the user and acts as an invisible interface for driving the system’s behaviour.
Ambient Intelligent systems and applications represent extremely complex and heterogeneous distributed systems/devices, composed of hardware and software components. The need for middleware to seamlessly bind these components together is well recognised. A framework to provide the required context-aware sensing capabilities is the main objective of this PhD research project. Approaches taken from the social insect metaphor Swarm Intelligence and Bayesian Networking techniques will be investigated for their potential. To confirm the effectiveness of AMiCA, an ambient intelligent cloud computing based assistive healthcare application will be developed which will showcase the decentralised and intelligent properties required within context-aware Ambient Intelligence middleware.