Special Issues
Table of Content

Intelligent IoT for Smart Cities and Sustainable Energy Systems

Submission Deadline: 31 August 2026 View: 2112 Submit to Special Issue

Guest Editor(s)

Assoc. Prof. Mahmoud Elsisi

Email: mahmoudelsisi@nkust.edu.tw

Affiliation: Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, 80543, Taiwan

Homepage:

Research Interests: Power systems control, artificial intelligence techniques, machine learning, internet of things


Mr. Chou-Mo Yang

Email: i113154108@nkust.edu.tw

Affiliation: Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, 80543, Taiwan

Homepage:

Research Interests: Artificial Intelligence, reinforcement learning, applied machine learning, cybersecurity, power systems.


Assist. Prof. Noorman Rinanto

Email: noorman.rinanto@ppns.ac.id

Affiliation: Marine Electrical Engineering Department, Shipbuilding Institute of Polytechnic Surabaya, Indonesia

Homepage:

Research Interests: Artificial intelligence, image and signal processing, machine learning, automation and robotic, IoT


Dr. Alvian Toto Wibisono

Email: alvian@its.ac.id

Affiliation: Department of Materials and Metallurgical Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia

Homepage:

Research Interests: Material, metallurgy, selective laser melting


Dr. Muhammad Qomaruz Zaman

Email: muhammad.zaman@its.ac.id

Affiliation: Electrical Engineering Departement, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia

Homepage:

Research Interests: Mechatronics, robotics, fuzzy logic control


Summary

The integration of the Internet of Things (IoT) with advanced data analytics, machine learning, and optimization techniques is revolutionizing the development of smart cities and sustainable energy systems. IoT technologies enable real-time monitoring, predictive control, and intelligent decision-making across various urban domains, including transportation, energy management, waste reduction, and environmental monitoring.


This Special Issue focuses on recent advancements and innovative applications of IoT in creating intelligent, energy-efficient, and sustainable urban ecosystems. It welcomes original research, reviews, and case studies that explore IoT architectures, optimization algorithms, AI/ML models, and secure communication protocols tailored for smart city and energy applications. Special attention is given to how IoT and intelligent computing can enhance the efficiency, resilience, and sustainability of modern infrastructures.


By bridging IoT technologies with artificial intelligence and sustainable energy innovation, this issue aims to present interdisciplinary insights that contribute to the realization of smarter, greener, and more connected cities for the future.

Suggested Themes:
· IoT Applications in Smart Cities and Sustainable Energy Systems
· Machine Learning and Optimization for IoT-Based Decision-Making
· Energy Management, Smart Grids, and Renewable Integration
· Edge and Cloud Computing for IoT in Urban Environments
· IoT Security, Privacy, and Reliability
· AI/ML-Driven Sustainable Infrastructure


Keywords

IoT, Smart Cities, Machine Learning, Optimization, Sustainable Energy, Smart Grids, Edge Computing, AI, Security, Urban Systems

Published Papers


  • Open Access

    ARTICLE

    An Intelligent IoT-Enabled Real-Time Space Monitoring System for Urban Parking and Smart Manufacturing Logistics

    Isam Bahaa Aldallal, Saadaldeen Rashid Ahmed, Abdullahi Abdu Ibrahim, Oguz Bayat, Abu Saleh Musa Miah, Fahmid Al Farid, Md. Hezerul Abdul Karim
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2026.078742
    (This article belongs to the Special Issue: Intelligent IoT for Smart Cities and Sustainable Energy Systems)
    Abstract Urban parking problems worsen traffic jams, gas use, and pollution. Old parking systems often lack up-to-date space information, which annoys drivers and wastes their time. This research presents a smart IoT-enabled real-time space monitoring and booking system applicable to both urban parking management and Smart Manufacturing logistics environments, including loading bay coordination and Automated Guided Vehicle (AGV) docking station management. The system employs ultrasonic and IR sensors, managed by an Arduino UNO, to identify vehicles and track space availability. A servo-motor regulates entry. Slot data is presented on a Liquid Crystal Display screen and accessible More >

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