Building trustworthy smart cities: The system definition of the Smart Metrology Campus data infrastructure

Abstract

This article highlights the critical role of robust data infrastructure in enabling data-driven smart cities, emphasizing metrology and systems engineering to ensure reliability and interoperability. The Smart Metrology Campus (SMC) aims to facilitate reliable data science in smart cities by integrating sensor and meter data with metrology-based metadata. Prior research has established systems engineering as the optimal strategic framework for guiding such data engineering processes. Additionally, the subsequent concept phase has been demonstrated to align with the data engineering requirements for electricity data collection. Building on this, the present study extends the methodology by defining a data quality framework focused on trust in electricity meter data. The article further elaborates on the systems definition phase, utilizing outcomes from the concept definition, such as requirements and general architecture, to develop a detailed system architecture, including technology selection for subsystems. It explores methods and tools for efficient system definition, combining established techniques like requirements tables and criteria catalogs with software engineering approaches like entity-relationship models and mockups. These methods, alongside the data quality framework, are applied in a case study of the SMC, culminating in a fully specified system architecture with detailed subsystem descriptions to support implementation.