• KanwalAalijah

Urban planning plays a very important role in development modern cities. It effects the economic growth, quality of life, and environmental sustainability. Modern cities face challenges in managing traffic congestion. These challenges arise to due to rapid urbanization. In this study we will explore how AI can be used to understand the traffic and mobility related issues and its effects on the resident’s sentiment. The approach combines real-time traffic data with geo-located sentiment analysis, offering a comprehensive and dynamic approach to urban mobility planning. AI models and exploratory data analysis was used to predict traffic congestion patterns, analyze commuter behaviors, and identify congestion hotspots and dissatisfaction zones. The findings offer actionable recommendations for optimizing traffic flow, enhancing commuter experiences, and addressing city-specific mobility challenges in the Middle East and beyond.

Urban Mobility, Artificial Intelligence, Traffic Optimization, Sentiment Analysis, Geo-located Data, Dubai, Riyadh, Smart Cities, Sustainable Transportation, Commuter Behavior, Urban Planning.

"Traffic and Mobility Optimization Using AI: Comparative Study between Dubai and Riyadh ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.a499-a506, March-2025, Available :http://www.jetir.org/papers/JETIR2503067.pdf

"Traffic and Mobility Optimization Using AI: Comparative Study between Dubai and Riyadh ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppa499-a506, March-2025, Available at : http://www.jetir.org/papers/JETIR2503067.pdf