García González, JorgeFernández Andrés, JavierAliane, NourdineSánchez Soriano, Javier2026-02-072026-02-072025García-González, J., Fernández-Andrés, J., Aliane, N., & Sánchez-Soriano, J. (2025). Big data and i2x communication infrastructure for traffic optimization and accident prevention on automated roads. IEEE Access, 13, 133497-133509. https://doi.org/10.1109/ACCESS.2025.35923102169-3536https://hdl.handle.net/11268/16802This paper presents a scalable big data infrastructure designed to support traffic optimization and accident prevention in automated and connected road environments. The proposed system integrates real-time data acquisition from heterogeneous sources, including multichannel roadside camera gantries and IoT-enabled vehicle telemetry. The architecture is built upon technologies such as Apache Kafka, Apache Beam, and MongoDB, enabling high-throughput data ingestion, processing, and storage. To validate its performance, two experimental use-cases were developed: one for large-scale image ingestion and another for vehicle telemetry data streaming. The system successfully handled over 48 GB of image data and more than 3.4 million telemetry messages under real-time constraints. Results show that applying data compression techniques—such as resolution reduction and transmission throttling—reduced image upload durations by up to 77%, improving ingestion efficiency without compromising system robustness. These findings demonstrate the feasibility of deploying the proposed infrastructure as a foundational layer for future intelligent traffic anagement systems.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal article10.1109/ACCESS.2025.3592310open accessAnálisis de datosIngeniería del transporteInfraestructura de transportesGoal 3: Ensure healthy lives and promote well-being for all at all agesGoal 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation