NiSIS Nature-inspired Smart Information System

NiSIS is a European Project under the Co-ordinated Action (CA) scheme with the following overall mission aims:Encourage cross-disciplinary team-based thinking to cross-fertilise engineering and life science understanding into advanced inter-operable systems. Progress the theme of adaptivity beyond curiosity and basic earlier engineering concepts and theory, via the spur of naturally-occurring phenomena and self-emergent systems.Elaborate the themes of hierarchy, modularity, redundancy, learning capacity etc in pursuit of greater robustness and reliability against uncertainties, time-variations and fault conditions for large information systems.Incorporate the large body of knowledge on systems dynamics, modelling and identification/estimation into hybrid structures based on intelligent paradigms. Develop a Taxonomy and Strategic Roadmap to describe the state-of-the-art knowledge in the different disciplines about intelligent systems and to signpost a future for integration of deeper nature-inspired concepts into smart devices and systems. This aims to prepare for long term goals leading beyond FP6. Provide training and education across the relevant disciplines via workshops, symposia, Best Practice Guidelines etc., Foster Technology Transfer via competitive team-based feasibility Workshops on realistic benchmarking problems. Encourage promising young researchers in the field, spin-off ventures and SME via interchange of students and researchers using Web-based material and short Schools providing expertise transfer.

NiSIS is a European Project under the Co-ordinated Action (CA) scheme with the following overall mission aims. Encourage cross-disciplinary team-based thinking to cross-fertilise engineering and life science understanding into advanced inter-operable systems. Progress the theme of adaptivity beyond curiosity and basic earlier engineering concepts and theory, via the spur of naturally-occurring phenomena and self-emergent systems. Elaborate the themes of hierarchy, modularity, redundancy, learning capacity etc in pursuit of greater robustness and reliability against uncertainties, time-variations and fault conditions for large information systems. Incorporate the large body of knowledge on systems dynamics, modelling and identification/estimation into hybrid structures based on intelligent paradigms. Develop a Taxonomy and Strategic Roadmap to describe the state-of-the-art knowledge in the different disciplines about intelligent systems and to signpost a future for integration of deeper nature-inspired concepts into smart devices and systems. Provide training and education across the relevant disciplines via workshops, symposia, Best Practice Guidelines etc. and foster Technology Transfer via competitive team-based feasibility Workshops on realistic benchmarking problems.