Grant: Strategic Projects - Group

The challenges in prevention of disasters and effective risk management for livestock production, public health and rural communities are immensely important and extremely timely. As of today, we have been witnessing a wave of rapidly developing and highly unexpected outbreaks. Any efficient, well-orchestrated development aimed at the design of decision-support framework does call for a multidisciplinary approach in which holistic and unified data analysis becomes of paramount relevance. The essence of the holistic data analysis pertains to the collection, usage and processing of data coming from different sources, which offer an important and highly diversified insights into the complexity of the prevention tasks, allow managing risk in an effective way as well as strengthening public policies with this regard. With respect to the design of the decision-support system, the role of innovative information technologies, especially those emerging under the banner of Computational Intelligence (CI) and computerized decision support systems has been promising and already demonstrated their potential. It is clear that a reliable identification of possible outbreaks constitutes a necessary step to detect and characterize possible threats. The CI aspect of this proposal clearly satisfies those requirements. The effectiveness of the classification and quantification of risks links to risk assessment and reduction of vulnerability becomes important. The ultimate objective of this project is to develop a comprehensive, well-rounded methodology and a set of guidelines that can be directly used to strengthen the existing public policies or may lead to the development of new ones. It is important to underline here that such a challenge, even though being extremely timely and of significant practical relevance, has never been fully explored in the past. The originality of the proposed research project is indeed multifaceted and stems from the most essential features of the project including (1) holistic view at data coming from a variety of sources and a fusion of results for the purpose of effective risk assessment; and (2) taxonomy of risk scenarios along with the associated actions/recommendations. The originality of the undertaken research comes hand in hand with the tangible practical pursuits - within the framework of the project, we come up with a functionally complete and unique prototype whose usage will help collect and solidify extensive experimental evidence supporting and quantifying the methodological investigations and ensuing algorithms as well as identifying further refinements. The design experience could be readily available to support the development of similar systems at the national level.