Hydrometeorologic Social Network With CBR Prediction

Abstract

Human activities are contributing to more frequent natural extremes and climate change, which also come from the atmosphere, water or the Earths crust. With the increasing development of infrastructure, the impacts of these changes and extremes leave more perceivable damage and increasing loss of lives and property. With the use of modern resources and technology we are able to minimize the impact of these extreme phenomena. There are in fact two main approaches-professional and nonprofessional-both meant from the aspect of data collection and information processing itself. The advantages of social networks have been increasingly utilized during the natural disasters as a way of communicating important information. This article describes the aim of our research-to create a hybrid system which would both enable the collection of data from the professional and non-professional public as well as communicate with other types of systems, to utilize and then process the data and use the data to predict new dangers. The principle is based on collecting data (knowledge, experience, etc.) from both main approaches to disaster management (professional and nonprofessional) and then applying this information to achieve new solutions. The practical application of a DIP system shows that it can be used for describing the risk of future natural disasters and enables us to deduce the threat imposed by them. Analyzing this data can help create new solutions in the fight to minimize the damage incurred by these disasters.