The authors wish to acknowledge the Italian Ministry of Environment who founded the Project 1.7 “Technologies for the efficient penetration of the electric vector in the final uses” within the “Electrical System Research” Programme Agreements 22-24 (PTR 22-24) and the European Union who founded the MULTICLIMACT project (Grant Agreement No. 101123538). In particular, the first project has supported the development of the “Smart City Platform Specification (SCPS) for Interoperability Layer” and its reference implementation (“Smart City Platform” SCP); the MULTICLIMACT project has supported both the customization of the existing SCPS and the deployment of a customized SCP instance for monitoring natural threats.@en

When dealing with seismic risk assessment at a large scale, the collection of relevant building data is still deemed a challenging task, often leading to limited building knowledge and, consequently, high uncertainties. Therefore, innovative yet standardized frameworks and adaptive tools are needed to support the seismic risk assessment of buildings. Towards this goal, this paper proposes a simplified multi-knowledge seismic assessment methodology involving the analytical-mechanical SLaMA (Simple Lateral Mechanism Analysis) method. An ad-hoc data collection form is first developed to identify the building vulnerabilities by merging and building on existing institutional forms at the international level and integrating new input data. The data are then used to implement the SLaMA-based methodology, at different building knowledge levels, to assess the seismic safety and the economic losses of buildings. The proposed data structure and approach is planned to be included in the “Seismic-Response” module for PELL (Public Energy Living Lab)-School platform, aiming to become a standardized and interoperable database for relevant data of Italian schools and a dashboard for allowing stakeholders to continuously monitor their energetic and static/seismic conditions. The paper discusses the potential and effectiveness of the proposed procedure for large-scale applications and its integration into platforms assessing the energy efficiency of buildings.

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