Special Issues
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Innovative Computational Models for Smart Cities

Submission Deadline: 31 January 2026 View: 1857 Submit to Special Issue

Guest Editors

Professor Luis Hernández-Callejo, Universidad de Valladolid, Spain
Professor Pedro Moreno-Bernal, Universidad Autónoma del Estado de Morelos, Mexico
Professor Sergio Nesmachnow, Universidad de la República, Uruguay


Summary

Cities are transforming, and this process requires intervention from various areas. One of the significant changes involves developing and implementing innovative computational models, to be applied for problem solving in diverse areas. Cities must integrate new computational models and applications to enhance infrastructure and services, develop smart and sustainable mobility, integrate IoT and sensor technologies, develop smart communications, improve energy systems and water management, improve citizen participation and governance, among others.

 

This special issue is open for research and development contributions based on the main topics related to developing and applying new computational models. Among the related topics are (but not exclusive to):

- Innovative computing solutions for smart cities

- Computing models for smart energy, energy efficiency, and sustainability

- Computing models for smart infrastructures and the environment

- Artificial intelligence for smart cities

- Computing models for smart mobility, IoT, sensor networks, and communications

- Computing models for smart public services

- Computing models for intelligent urban environments

 

The special issue welcomes submissions of original surveys, research articles, and case studies that have the potential to inspire individuals interested in the advancement of smart cities. Submitted articles are expected to provide valuable insights and contribute to the overall well-being and progress of smart cities.


Keywords

● Innovative computational models
● Computational intelligence for smart cities
● Renewable energies and storage
● Smart grid and Energy efficiency
● Cybersecurity and Artificial Intelligence
● Smart infrastructures
● Smart mobility, IoT, communication networks
● Smart public services
● Governance and citizenship

Published Papers


  • Open Access

    ARTICLE

    Forecasting Performance Indicators of a Single-Channel Solar Chimney Using Artificial Neural Networks

    Carlos Torres-Aguilar, Pedro Moreno, Diego Rossit, Sergio Nesmachnow, Karla M. Aguilar-Castro, Edgar V. Macias-Melo, Luis Hernández-Callejo
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.069996
    (This article belongs to the Special Issue: Innovative Computational Models for Smart Cities)
    Abstract Solar chimneys are renewable energy systems designed to enhance natural ventilation, improving thermal comfort in buildings. As passive systems, solar chimneys contribute to energy efficiency in a sustainable and environmentally friendly way. The effectiveness of a solar chimney depends on its design and orientation relative to the cardinal directions, both of which are critical for optimal performance. This article presents a supervised learning approach using artificial neural networks to forecast the performance indicators of solar chimneys. The dataset includes information from 2784 solar chimney configurations, which encompasses various factors such as chimney height, channel thickness, More >

    Graphic Abstract

    Forecasting Performance Indicators of a Single-Channel Solar Chimney Using Artificial Neural Networks

  • Open Access

    REVIEW

    AI-Powered Digital Twin Frameworks for Smart Grid Optimization and Real-Time Energy Management in Smart Buildings: A Survey

    Saeed Asadi, Hajar Kazemi Naeini, Delaram Hassanlou, Abolhassan Pishahang, Saeid Aghasoleymani Najafabadi, Abbas Sharifi, Mohsen Ahmadi
    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1259-1301, 2025, DOI:10.32604/cmes.2025.070528
    (This article belongs to the Special Issue: Innovative Computational Models for Smart Cities)
    Abstract The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solutions are needed to improve efficiency, resilience, and environmental performance. This paper reviews the integration of Digital Twin (DT) technologies and Machine Learning (ML) for optimizing energy management in smart buildings connected to smart grids. A key enabler of this integration is the Internet of Things (IoT), which provides the sensor networks and real-time data streams that fee/d DT–ML frameworks, enabling accurate monitoring, forecasting, and adaptive control.… More >

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