Artificial Intelligence-Driven Decision Support Systems for Sustainable Energy Management in Smart Cities

被引:0
|
作者
Ma, Ning [1 ]
机构
[1] Shanxi Vocat Univ Engn Sci & Technol, Jinzhong 030619, Peoples R China
关键词
Smart cities; artificial intelligence; decision support systems; sustainable energy management; urban resilience; interdisciplinary collaboration;
D O I
10.14569/IJACSA.2024.0150953
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Due to the ongoing urbanization trend, smart cities are critical to designing a sustainable future. Urban sustainability involves action-oriented approaches for optimizing resource usage, ecological impact reduction, and overall efficiency enhancement. Energy management is one of the main concerns in urban, residential, and building planning. Artificial Intelligence (AI) uses data analytics and machine learning to instigate business automation and deal with intelligent tasks involved in numerous industries. Thus, AI needs to be considered in the strategic plan, especially in the long-term strategy of smart city planning. Decision Support Systems (DSS) are integrated with human- machine interaction methods like the Internet of Things (IoT). Along with their growth in size and complexity, the communications of IoT smart devices, industrial equipment, sensors, and mobile applications present an increasing challenge in meeting Service Level Agreements (SLAs) in diverse cloud data centers and user requests. This challenge would be further compounded if the energy consumption of industrial IoT networks also increased tremendously. Thus, DSS models are necessary for automated decision-making in crucial IoT settings like intelligent industrial systems and smart cities. The present study examines how AI can be integrated into DSS to tackle the intricate difficulties of sustainable energy management in smart cities. The study examines the evolution of DSSs and elucidates how AI enhances their functionalities. The study explores several AI methods, such as machine learning algorithms and predictive analytics that aid in predicting, optimizing, and making real-time decisions inside urban energy systems. Furthermore, real-world instances from different smart cities highlight the practical applications, benefits, and interdisciplinary collaboration necessary to successfully implement AI-driven DSS in sustainable energy management.
引用
收藏
页码:523 / 529
页数:7
相关论文
共 50 条
  • [21] Development of Decision Support Systems for Smart Cities
    Maitakov, Fedor Georgievich
    Merkulov, Alexander Alekseevich
    Petrenko, Evgeny Vladimirovich
    Yafasov, Abdurashid Yarullaevich
    ELECTRONIC GOVERNANCE AND OPEN SOCIETY: CHALLENGES IN EURASIA, EGOSE 2018, 2019, 947 : 52 - 63
  • [22] Artificial Intelligence-Driven Multi-Energy Optimization: Promoting Green Transition of Rural Energy Planning and Sustainable Energy Economy
    Peng, Xiaoyan
    Guan, Xin
    Zeng, Yanzhao
    Zhang, Jiali
    SUSTAINABILITY, 2024, 16 (10)
  • [23] Designing Sustainable Smart Cities: Cooperative Energy Management Systems and Applications
    Fujimoto, Yu
    Ishii, Hideo
    Hayashi, Yasuhiro
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2020, 15 (09) : 1256 - 1270
  • [24] Artificial Intelligence-driven regional energy transition:Evidence from China
    Zhao, Zuoxiang
    Zhao, Qiuyun
    Li, Siqi
    Yan, Jiajia
    ECONOMIC ANALYSIS AND POLICY, 2025, 85 : 48 - 60
  • [25] Artificial intelligence for waste management in smart cities: a review
    Bingbing Fang
    Jiacheng Yu
    Zhonghao Chen
    Ahmed I. Osman
    Mohamed Farghali
    Ikko Ihara
    Essam H. Hamza
    David W. Rooney
    Pow-Seng Yap
    Environmental Chemistry Letters, 2023, 21 : 1959 - 1989
  • [26] Artificial intelligence for waste management in smart cities: a review
    Fang, Bingbing
    Yu, Jiacheng
    Chen, Zhonghao
    Osman, Ahmed I. I.
    Farghali, Mohamed
    Ihara, Ikko
    Hamza, Essam H. H.
    Rooney, David W. W.
    Yap, Pow-Seng
    ENVIRONMENTAL CHEMISTRY LETTERS, 2023, 21 (04) : 1959 - 1989
  • [27] Preface to the special issue on "Artificial Intelligence-driven Decision Making in Health and Medicine"
    La Torre, Davide
    Bertossi, Leopoldo
    Kunze, Herb
    Poulin, Marc
    INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2025, 32 (04) : 2087 - 2088
  • [28] AI-Driven Decision Support System for Green and Sustainable Urban Planning in Smart Cities
    Xu C.
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [29] AN ARTIFICIAL-INTELLIGENCE APPROACH TO MODEL MANAGEMENT IN DECISION SUPPORT SYSTEMS
    DUTTA, A
    BASU, A
    COMPUTER, 1984, 17 (09) : 89 - 97
  • [30] Artificial Intelligence-Driven Biomedical Imaging Systems for Precision Diagnostic Applications
    Kumar, Vijay
    Singh, Amit Kumar
    Damasevicius, Robertas
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2024, 28 (03) : 1158 - 1160