## 9 Artificial Intelligence (AI)
### Challenges of Deploying AI for Smart Cities  
Due to several issues, implementing AI technology in smart cities is not an easy task. The main limitations of deploying AI for smart cities are summarized as follows [96; 97; 98]: \begin{table}
\begin{tabular}{c c} \hline \hline
**Dataset** & **Description** \\ \hline \multirow{6}{*}{Chicago traffic tracker dataset [103]} & - & This dataset provides real-time traffic information for various modes of transportation in Chicago. \\  & - & It includes traffic speed, congestion, and travel times data, which can be used for traffic management and optimization. \\ \hline \multirow{6}{*}{Land and Transport Singapore (LTSG) datasets [104]} & - & Datasets on public transportation, road traffic, and vehicle ownership. These datasets are used for traffic management, urban planning, and public transport optimization. \\  & - & It contains the following: \\  & \(\bullet\) & 8672 points of interest (with attributes: number of Google ratings, types, and street address). \\  & \(\bullet\) & 12,442 housing and development board buildings (with attributes: block number, street address, zip code, construction year, dwelling units, and functionality). \\  & \(\bullet\) & 5049 bus stations (with routing information). \\  & \(\bullet\) & 5018 bus stations (with passenger volume information). \\  & \(\bullet\) & 166 subway stations (with routing information). \\ \hline \multirow{6}{*}{Los Angeles GeoHub datasets [105]} & - & Datasets related to the city’s infrastructure, environment, and services. \\  & - & These datasets are used for urban planning, environmental monitoring, and public service optimization. \\ \hline \multirow{6}{*}{Los Angeles crime dataset [106]} & - & A comprehensive dataset of colony and misdemeanor crimes in Los Angeles from 2000 to 2018. \\  & - & Useful for crime pattern analysis and predictive policing applications. \\ \hline \multirow{6}{*}{City of Chicago crime dataset [107]} & - & This dataset contains information about reported crimes in Chicago, including location, type of crime, and time of occurrence. \\  & - & It is used for crime prediction, hotspot analysis, and law enforcement strategies. \\ \hline \multirow{6}{*}{Open traffic [108]} & - & Traffic data from several cities, including speed, traffic volume, and incident reports. \\  & - & Useful for traffic prediction and management. \\  & - & Linked to OpenStreetMap. \\ \hline \multirow{6}{*}{Citi bike trip dataset [109]} & - & It is a bike-sharing program in New York City, and its trip data include information about bike trips, locations, and timestamps. \\  & - & It is used for studying urban mobility patterns and optimizing \\  & - & bike-sharing services. \\ \hline \multirow{6}{*}{London bike sharing dataset [110]} & - & Details about bike journeys from the Santander Cycles bike sharing scheme in London. \\  & - & Includes trip duration, start/end stations, member types, and more. \\  & - & Useful for bike infrastructure planning. \\ \hline \multirow{6}{*}{Beijing air quality dataset [111]} & - & This dataset contains historical air quality measurements in Beijing, including pollutants, e.g., PM2.5, PM10, and ozone levels. \\  & - & It is used for analyzing air quality trends and predicting pollution levels. \\ \hline \multirow{6}{*}{Smart data hub [112]} & - & This dataset includes information from multiple domains for various cities, such as transportation, environment, energy, and demographics. \\  & - & It is used for multidisciplinary smart city research and analysis. \\ \hline \hline \end{tabular}
\end{table} 
Table 14: _Cont._* Infrastructure and cost: AI systems need powerful hardware, databases, and energy to function, raising the overall cost. * Privacy concerns: people might feel offended and worried about their privacy and personal space. * Risk of socialization: When developing such cities, inclusive urbanization, which addresses the growing vulnerability of the slums and poor population, must be prioritized.