Currently, emergency response agencies use simplified “one-size-fits-all” procedures to decide what quantity and type of resources to dispatch to each fire threat. These procedures are based on principles established decades ago, and are generally static in nature. They then rely on the judgment of the experienced officer who has arrived on-scene to make a dynamic evaluation and request additional units if appropriate. In this thesis, we propose a fuzzy expert system to enhance the assessment procedures. iFAST is shown to reduce the dispatch time (usually between eight to sixteen minutes) to less than 30 seconds; hence saving lives while reducing costs and property loss. The intent of the proposed system is to allow the emergency response agencies to perform the majority of the “initial-size-up” analysis in less than thirty seconds after a fire emergency report. Our system will outline the decisions in regards to the adequate resources required to be sent to the incident at the given time, as opposed to having to wait until the first experienced officer has arrived on-scene.