## 6 Conclusions  
The scope of the current paper is to emerge and highlight the functions, the applicability, and the advantages of a new software application developed for the rapid seismic damage assessment of RC buildings. The developed software is intended to instantly provide assessment results and is used for both pre-and post-earthquake assessments. Whereas the required seismic data can be instantly available either from strong-motion databases or in real-time after a seismic event, the level of availability of the structural data (parameters) is low due to the limited time and limited resources. The selected ANN-based method for the seismic damage assessment of RC buildings is a method based on the definition and the solution of pattern recognition (PR) problems. More specifically, by formulating the structures' seismic damage assessment problem (compatible with \"first stage simplified methodologies\") in terms of PR problems and of ANNs' function, the software application extracts predictions regarding the seismic damage state (DS) of RC buildings in real-time. This DS is quantified considering three seismic damage classes (SDC) defined using specific threshold values of a seismic damage index (SDI). In the current paper, the maximum interstory drift ratio (MIDR), which is extensively used in research studies, was selected as SDI. The selection of three DSs was in line with the DS proposed in RVIs, in order to be directly applicable. The seismic and structural parameters were selected as input parameters for the ANNs in the current version of the  
Figure 17: CMs correspond to the classifications extracted by the used MFPNNs considering input vectors with assumed values for the unknown structural parameters: (**a**) for BB, (**b**) for FIB, and (**c**) PB. proposed application; however, they can be easily changed in future versions due to the flexibility of the source code developed. The current version of the developed software application was evaluated by predicting the DS of two general categories of RC buildings, namely buildings with reliable known values of the selected structural parameters and buildings with unknown (or no-reliable known) values of the selected structural parameters. In both cases, the effectiveness of the proposed application regarding its capability to extract reliable results in real-time was highlighted. However, it must be noted that the accuracy of the results extracted by the application depends on the effectiveness of the ANNs used. The latter is not the subject of the present paper since already trained ANNs were used. In line with the above, the usage of user-defined ANNs trained with different databases is also possible. In any case, the capability for direct (in real-time) and reliable estimation of the DS of a building or building inventories in the pre-earthquake phase or after a strong earthquake, avoiding time-consuming modeling and analyses, without exclusively requiring detailed RVI input data (implementing parametric analyses), renders the software developed a valuable calculational tool available to the authorities either for retrofit prioritization in the pre-earthquake phase or emergency planning after a strong earthquake event. Conceptualization, K.M. ; methodology, K.M. and S.S.; software, K.M. and O.M. ; validation, S.S. and O.M. ; investigation, K.M., S.S. and O.M. ; writing--original draft preparation, K.M. ; writing--review and editing, S.S. and O.M. ; project administration, K.M. ; funding acquisition, S.S. and O.M. All authors have read and agreed to the published version of the manuscript. This research was funded by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH CREATE INNOVATE--Second Round (project code: T2 EDK-03412). Not applicable. Data Availability Statement: Data are only available after contacting the authors. The authors declare no conflict of interest.