بهره‌گیری از توسعه‌ی مدل‌رانده برای ارزیابی شاخص‌های کلیدی عملکرد در شهر هوشمند

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی کامپیوتر، دانشکده فنی، دانشگاه شهرکرد، شهرکرد، ایران

چکیده

رشد سریع شهرنشینی، به‌ویژه در کلان‌شهرها، چالش‌های پیچیده‌ای در مدیریت ترافیک، مصرف انرژی و کیفیت زندگی ایجاد کرده است. استفاده از شاخص‌های کلیدی عملکرد ابزار مهمی برای ارزیابی سیستم‌های شهری است، اما محاسبه‌ی دقیق آن‌ها به دلیل حجم بالای داده‌ها و پیچیدگی محاسبات، چالشی اساسی محسوب می‌شود. این پژوهش یک رویکرد نوین مبتنی بر مهندسی مدل‌رانده ارائه می‌دهد که با طراحی یک زبان مدل‌سازی خاص دامنه و ویرایشگر گرافیکی کاربرپسند، محاسبه‌ی خودکار شاخص‌ها را ممکن می‌سازد. این رویکرد ضمن کاهش پیچیدگی‌های محاسباتی، فرآیند ارزیابی را تسهیل و دسترسی سریع‌تر و دقیق‌تر به اطلاعات را برای مدیران شهری فراهم می‌کند. ارزیابی زبان مدل‌سازی پیشنهادی بر اساس معیارهای قابلیت نگهداری، درک‌پذیری و توسعه‌پذیری، نشان‌دهنده‌ی برتری آن نسبت به روش‌های مشابه است. نتایج پژوهش حاکی از بهبود قابل توجه در دقت و کارایی ارزیابی شاخص‌ها بوده و این امکان را فراهم می‌کند که تصمیمات مدیریتی دقیق‌تر و کارآمدتری اتخاذ شود. ویژگی‌های زبان پیشنهادی، شامل فرامدل ساختاریافته و دسته‌بندی‌های تخصصی، به کاهش زمان مدل‌سازی، کاهش خطاهای انسانی و افزایش دقت محاسبات کمک شایانی می‌کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

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

نویسندگان [English]

  • Seyed Masoud Hoseini
  • Leila Samimi-Dehkordi
  • Abbas Horri
Computer Engineering Department, Faculty of Engineering, Shahrekord University, Shahrekord, Iran
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Key Performance Indicator
  • Smart City
  • Model-Driven Engineering
  • Domain-Specific Modeling Language

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