International Conference on Transportation Analytics using Big Data (ICTABD - 27)

This track focuses on the application of predictive analytics techniques to enhance decision-making in transportation systems. Participants will explore methodologies for forecasting traffic patterns, demand, and operational efficiency using big data.

This session will delve into the integration of machine learning algorithms within intelligent transport systems. Researchers will present innovative approaches to improve traffic management, safety, and user experience through data-driven insights.

This track examines the role of artificial intelligence in integrating diverse transportation data sources for comprehensive analytics. Discussions will highlight techniques for enhancing data quality and accessibility to support informed decision-making.

Focusing on real-time analytics, this session will explore methodologies for monitoring and managing traffic conditions dynamically. Participants will discuss the impact of real-time data on congestion mitigation and resource allocation.

This track emphasizes the importance of data visualization in interpreting complex transportation datasets. Presenters will showcase innovative visualization tools and techniques that facilitate better understanding and communication of analytical findings.

This session will explore optimization strategies in logistics through the lens of big data analytics. Researchers will present case studies demonstrating how data-driven approaches can enhance supply chain efficiency and reduce operational costs.