Smart Cities can promote economic growth, sustainable transport, environmental sustainability, and good governance among cities. These benefits can support cities in achieving the SDG-11 targets. Smart Cities entails the integration of smart technologies, including machine learning techniques, in cities. Among the machine learning techniques, Artificial Neural Network (ANN) is prominent. Literature revealed significant research interest on ANN for Smart Cities, resulting to several existing review works. Existing works revealed research interests on applications for structural monitoring, Internet of Things (IoT), transport systems, and cybersecurity among others. However there is a scarcity in understanding the implications of ANN for Smart Cities towards SDG-11. This work, therefore, reviews the research trends on ANN for Smart Cities towards SDG-11 through a systematic bibliometric methodology. This work utilizes a keyword-based search retrieving 743 documents for descriptive analysis and 131 documents for content analysis. The results reveal an exponential growth in research interest and cluster formation among pertinent themes. This work determined the prominent themes on Environmental Impact, on Transport Systems, and on Urbanization. This review highlights insights on research trends, on thematic prominence, and on specific SDG-11 themes.
