Harnessing Big Data for Real-Time Traffic Forecasting and Urban Mobility Optimization
Introduction Urban mobility is a cornerstone of modern cities, yet traffic congestion remains a persistent challenge, costing billions in economic losses, increasing pollution, and reducing quality of life. Big data, with its ability to process vast, real-time datasets from diverse sources, offers transformative solutions for predicting and managing traffic patterns. By leveraging advanced analytics, machine learning, and real-time data from IoT devices, cities can optimize transportation systems, reduce congestion, and enhance urban mobility. This chapter explores how big data enables real-time traffic prediction, its applications in urban mobility, real-world case studies, challenges, and future trends shaping smarter cities. The Role of Big Data in Traffic Prediction Understanding Big Data in the Traffic Context Big data in traffic prediction involves collecting and analyzing large-scale, high-velocity datasets from various sources, including: IoT Sensors : Traffic cameras,...