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ICTSEDM · Registering as Listener

International Conference on Transportation Systems Engineering and Data Mining

11th Jun – 12th Jun 2027 Kuwait City, Kuwait Standard / Physical Participation

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ConferenceICTSEDM

ModeStandard / Physical

ParticipationListener

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Benefits of Registering as Listener

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Conference Session Tracks

SDG-Aligned Research Themes

International Conference on Transportation Systems Engineering and Data Mining conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 9 - Industry, Innovation and Infrastructure

SDG 11 - Sustainable Cities and Communities

This track focuses on the latest methodologies and technologies in traffic analytics. Participants will explore data-driven approaches to understanding traffic patterns and behaviors.

This session will delve into predictive modeling techniques that enhance decision-making in transportation systems. Emphasis will be placed on the application of machine learning algorithms to forecast traffic conditions.

This track examines innovative smart mobility solutions that leverage data mining for improved urban transportation. Discussions will include the integration of IoT and big data in developing efficient mobility systems.

This session will highlight the role of sensor data in assessing and optimizing infrastructure performance. Participants will discuss techniques for analyzing real-time data to enhance transportation system reliability.

This track will explore advanced algorithms and frameworks for route optimization in various transportation contexts. The focus will be on minimizing travel time and maximizing efficiency through data-driven strategies.

This session addresses the integration of data mining techniques in transportation planning processes. Participants will share insights on how data can inform strategic planning and policy-making.

This track investigates the intersection of intelligent transportation systems and data mining. Discussions will center on how data analytics can enhance the functionality and effectiveness of ITS.

This session will focus on data-driven strategies for effective traffic management. Participants will explore case studies that demonstrate the impact of analytics on reducing congestion and improving safety.

This track highlights the application of machine learning techniques in various transportation-related challenges. Topics will include anomaly detection, classification, and regression in traffic data.

This session will explore the implications of big data on transportation engineering practices. Participants will discuss challenges and opportunities presented by large-scale data in transportation systems.

This track examines how data mining can contribute to sustainable transportation solutions. Discussions will focus on optimizing resource use and reducing environmental impacts through informed decision-making.