Edinburgh Napier University

  Ongoing device miniaturization makes it possible to manufacture very small devices; therefore more of them can be embedded in one space. Pervasive computing concepts, envisioning computers distributed in a space and hidden from users' sight, presented by Weiser in 1991 are becoming more realistic and feasible to implement.
A technology supporting pervasive computing and Ambient Intelligence also needs to follow miniaturization. The Ambient Intelligence domain was mainly focused on supercomputers with large computation power and it is now moving towards smaller devices, with limited computation power, and takes inspiration from distributed systems, ad-hoc networks and emergent computing. The ability to process knowledge, understand network protocols, adapt and learn is becoming a required capability from fairly small and energy-frugal devices. This research project consists of two main parts. The first part of the project has created a context aware generic knowledgebase interpretation engine that enables autonomous devices to pervasively manage smart spaces using Communicating Sequential Processes as the underlying design methodology. In the second part a knowledgebase containing all the information that is needed for a device to cooperate, make decisions and react was designed and constructed. The interpretation engine is designed to be suitable for devices from different vendors, as it enables semantic interoperability based on the use of ontologies. The knowledge, that the engine interprets, is drawn from an ontology and the model of the chosen ontology is fixed in the engine. This project has investigated, designed and built a prototype of the knowledge base interpretation engine.
Functional testing was performed using a simulation implemented in JCSP.
The implementation simulates many autonomous devices running in parallel, communicating using a broadcast-based protocol, self-organizing into sub-networks and reacting to users' requests.
The main goal of the project was to design and investigate the knowledge interpretation engine, determine the number of functions that the engine performs, to enable hardware realisation, and investigate the knowledgebase represented with use of RDF triples and chosen ontology model.
This project was undertaken in collaboration with NXP Semiconductor Research Eindhoven, The Netherlands.