<![CDATA[The concept of a smart city represents an innovative approach to urban development, aiming to enhance residents' quality of life by making cities more adaptable and efficient through the integration of advanced technologies. In recent years, the Internet of Things (IoT) has been widely applied in various smart city domains, including communication, healthcare, and transportation. However, localization has emerged as one of the key challenges in IoT implementation. Localization plays a crucial role in smart city development, as it is essential for effective urban planning, traffic management, and optimizing public transportation routes. Accurate location data enable personalized services for citizens, such as activity recommendations and real-time alerts about local events. Furthermore, by optimizing travel and improving resource management, localization contributes to urban sustainability by reducing waste and enhancing overall efficiency. This research makes several contributions. First, it examines the significance of localization in smart cities and highlights the associated challenges. Next, it explores various indoor and outdoor localization technologies, analyzing their advantages and disadvantages while providing a comparative assessment. The manuscript also classifies communication networks within smart cities, detailing their characteristics. Additionally, it discusses various machine-learning algorithms used to address localization challenges. Finally, it reviews related works in the field, providing insights into existing solutions and future research directions.]]>
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