User Reporting–Based Semeiotic Assessment of Existing Building Stock at the Regional Scale

Abstract

The large-scale management and monitoring of existing buildings is a complex issue for the holders and administrators that are responsible for user safety. Decision support systems (DSS) can be used to simplify such operations and to detect the criticalities that can compromise human safety or building usability. This paper proposes a DSS designed for detecting building criticalities, which includes a software application (APP) implemented on mobile devices and a web service–based quality detection platform (QDP) that stores and processes data. The APP allows the building users to report criticality through photographic inspection and to answer a suitable questionnaire. The collected data are processed by the QDP, which quantifies critical issues through a set of key performance indices (KPIs). The KPI formulations are computed by an optimized analytic hierarchy process (O-AHP), which is a modified version of the AHP. The DSS allows monitoring buildings at the regional scale and provides a classification of the most damaged buildings, which is useful for civil protection aims and for the prioritization of interventions.