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AECC Introduces Data-First Architecture to Advance Scalable, Data-Driven Automotive Services

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New white paper outlines a distributed framework to manage the growing volume of vehicle data and support the next generation of intelligent, software-defined vehicles

The Automotive Edge Computing Consortium (AECC) today announced the release of its latest white paper, “Data-First Architecture for Data-Driven Automotive Service Development.” Developed by the AECC Data First Special Interest Group (SIG Data First), the paper presents a forward-looking framework for collecting, processing, and distributing automotive data at scale — a critical requirement as vehicles become increasingly software-driven and data-intensive.

As the industry transitions toward software-defined vehicles (SDVs) — vehicles in which key functions are controlled and updated through software rather than hardware — the volume of data generated by onboard systems is rising sharply. Modern vehicles now operate as intelligent edge devices, continuously producing sensor data and operational logs used to improve performance, enable new features, and train artificial intelligence models.

This rapid increase in data presents new challenges. Traditional internet-of-things (IoT) architectures are not optimized to handle the scale, cost, and bandwidth demands of automotive data, which can reach tens of gigabytes per vehicle per day.

To address these challenges, the AECC white paper introduces the data-first architecture — a communication and computing platform that places data at the center of the automotive ecosystem.

Rather than relying solely on centralized systems, the architecture uses a distributed, tiered model that processes and moves data across multiple layers:

  1. Peer-to-peer network layer: Enables direct communication between nearby vehicles, allowing them to exchange and aggregate data locally without relying on centralized infrastructure.
  2. Edge network layer: Uses localized computing resources — such as edge data centers (small-scale data processing facilities located closer to where data is generated) and Wi-Fi access points — to process and offload data traffic efficiently.
  3. Mobile and cloud network layer: Provides centralized coordination through cellular networks and cloud platforms, supporting large-scale data management and long-term storage.

This multi-layered approach allows data to be handled where it makes the most sense — improving energy efficiency, reducing network strain, and supporting real-time and non-real-time use cases alike.

“By combining diverse communication methods — including cellular, Wi-Fi, and inter-vehicle data transfer — with distributed computing across vehicles, edge infrastructure, and cloud platforms, the data-first architecture offers a practical path forward for managing automotive data at scale,” said Dr. Ryokichi Onishi, AECC Board Chairperson.

“This approach not only addresses current infrastructure limitations but also supports a broader shift toward data-driven development. As AI expands beyond driving systems into areas such as infotainment, voice assistants and personalized travel recommendations, access to high-quality, large-scale data will be essential.”

The AECC believes this architecture will play a central role in enabling more intelligent, efficient, and adaptive automotive services, while supporting the continued evolution of connected vehicles within a larger digital ecosystem.

Download “Data-First Architecture for Data-Driven Automotive Service Development” now.

About the AECC

The Automotive Edge Computing Consortium (AECC) is an association of cross-industry, global leaders working to explore the rapidly evolving and significant data and communications needs involved in instrumenting hundreds of millions of vehicles worldwide. The AECC’s goal is to promote best practices for communication and computing infrastructure to effectively utilize automotive big data, toward realizing an enriched mobility society. The AECC’s members are key players in the automotive, high-speed mobile network, edge computing, wireless technology, distributed computing and artificial intelligence markets. For more information about the AECC and its membership benefits, please visit https://aecc.org/.

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