Granular knowledge discovery framework for fire and rescue reporting system

Abstract

We present a proposition for an architecture of a platform for fire & rescue Incident Data Reporting System (IDRS). We propose to extend the current, simple functionality of such systems with knowledge that is a result of using semantic background of the analyzed phenomena. We discuss how to build and tune practically meaningful models of processes by means of granules, approximating their states and instances. We discuss how the incorporation of granular paradigm in the process of modelling and knowledge discovery from IDRS data may enrich the final outcome. of data preparation and transformation. We justify the need for proposed approach by presenting several case studies related to existing IDRS. We also discuss the complexity of available data sources that can be utilized to make the proposed approach more useful.