Leveraging Model-Driven Development to Evaluate Key Performance Indicators for Smart City

Document Type : Original Article

Authors

Computer Engineering Department, Faculty of Engineering, Shahrekord University, Shahrekord, Iran

Abstract

Rapid urbanization, particularly in megacities, poses complex challenges for traffic management, energy consumption, and quality of life. Key Performance Indicators (KPIs) are crucial for evaluating urban systems, but their accurate calculation is challenging due to the large volume of data and computational complexity involved. This research presents a novel model-driven engineering approach that automates KPI calculation through a domain-specific modeling language (DSML) and a user-friendly graphical editor. This approach simplifies the evaluation process by reducing computational complexity, providing city managers with faster and more accurate access to information. An evaluation of the proposed DSML, based on maintainability, understandability, and extensibility, demonstrates its advantages over existing methods. The results show a significant improvement in the accuracy and efficiency of KPI evaluation, enabling more informed and effective management decisions. The features of DSML, including a structured metamodel and specialized classifications, significantly reduce modeling time, minimize human error, and enhance computational accuracy.

Keywords

Main Subjects

References

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