Why send all vehicle data to the cloud when intelligence can live at the edge? Kvaser’s new platform enables real-time diagnostics, remote monitoring, and smarter data processing inside the vehicle itself. Kvaser experts Freddy Dahlberg, Nisarg Nirmalkumar, and Tobias Stalfors share the vision with EFY’s Akanksha Sondhi Gaur.
Q. Could you begin with an overview of the company and the role it plays in the automotive development ecosystem today?
A. Founded more than 40 years ago, Kvaser built its reputation on reliable controller area network (CAN) interfaces used in automotive and industrial machine-to-machine communications. As vehicle networks evolved to include technologies such as local interconnect network (LIN) and automotive Ethernet, the company expanded beyond CAN connectivity. Today, Kvaser provides hardware interfaces, software platforms, application programming interfaces (APIs), drivers, and development tools that enable engineers to connect to, monitor, test, and diagnose vehicle systems. The company is now extending its focus to advanced connectivity and edge computing solutions that support modern vehicle development workflows.
Q. How would you define the company’s role today in automotive research and development (R&D)?
A. Our core business remains enabling engineers to access and interact with vehicle networks throughout the development lifecycle. Our solutions support activities ranging from development and validation to diagnostics and aftermarket applications. With the introduction of edge computing platforms and expanded connectivity capabilities, we are evolving from a hardware interface provider into a broader technology partner that helps engineers manage and analyse vehicle data more efficiently.
Q. How does your software partner ecosystem work?
A. We focus on providing the foundational software layers, including APIs, drivers, and development frameworks, that simplify access to our hardware. More specialised capabilities such as advanced diagnostics, analytics, and flashing tools are typically delivered through software partners. For example, companies such as RA Consulting build advanced applications on top of our hardware and software platform. This approach allows customers to choose from a range of solutions while giving software partners the flexibility to innovate within an open ecosystem.
Q. Do you also act as a system integrator for complete development or testing solutions?
A. Depending on customer requirements, we can provide complete solutions that combine hardware, software, and support services. In other cases, we work alongside software partners that contribute specialised tools. This flexibility allows customers to either build their own toolchains or adopt integrated solutions.
Q. What motivated the development of the new edge computing platform?
A. The platform originated from customer demand for more efficient access to vehicle data. Traditionally, CAN data loggers stored information locally on secure digital (SD) cards, requiring engineers to physically retrieve data.
As vehicles began generating larger volumes of data, customers increasingly wanted remote access and automated data transfer to cloud or server-based systems. What started as an advanced data logging project evolved into a full edge computing platform capable of local processing, analytics, diagnostics, and remote monitoring.
Q. What were the core architectural goals behind developing the edge platform?
A. The objective was to combine our traditional strengths in reliability and ease of use with significantly greater computing capability. The platform needed to be robust enough for demanding automotive and industrial environments while remaining simple to deploy and manage. A key design feature is its secure, sandboxed operating system architecture, which isolates applications from the underlying hardware. This allows developers to focus on application development while the platform manages hardware resources, security, and system stability.
Q. How does this edge platform differ from traditional CAN-to-PC interfaces used in vehicle communication?
A. Traditional CAN interfaces primarily connect vehicle networks to external computers. The edge platform combines connectivity and computing within a single device, allowing applications to run directly on the hardware without requiring a connected laptop. Its sandboxed architecture also improves security and reliability by isolating applications and preventing software faults from affecting the underlying system. In effect, the platform brings data processing and analytics closer to the vehicle itself. So basically, we bring data processing closer to the vehicle edge.
Q. Could you describe the hardware architecture of the platform?
A. The platform is built around an NXP Semiconductors system-on-chip (SoC) featuring a quad-core advanced RISC machines (ARM) processor running Linux. It also incorporates a neural processing unit for future machine-learning applications based on TensorFlow Lite. Vehicle network connectivity is provided through a field-programmable gate array (FPGA)-based CAN controller connected via peripheral component interconnect express (PCI Express), supporting up to eight CAN channels and potentially additional protocols such as LIN. The architecture is highly modular, enabling integration of cellular connectivity, Wi-Fi, Bluetooth, and sensors including Inertial Measurement Units (IMUs).
Q. How does the Linux-based operating system ensure reliability and security?
A. The platform uses Linux containers to isolate applications from one another and from the core operating system. Hardware access is controlled through secure management layers, ensuring that faults or vulnerabilities within one application cannot compromise the rest of the system.
This architecture provides a stable and secure environment for deploying custom applications while maintaining overall system integrity.
Q. How does it enable efficient data processing and filtering at the edge?
A. Modern vehicles generate vast amounts of telemetry data, much of which may not need to be transmitted or stored. The platform allows developers to process, filter, and analyse data locally before forwarding only relevant information to backend systems. Applications can be developed in languages such as Python or C and can combine CAN data with inputs from Ethernet devices, cameras, and sensors. Processed information can then be sent to cloud services such as Amazon Web Services (AWS), Microsoft Azure, private servers, or partner platforms.
Q. How does it support remote diagnostics and monitoring?
A. The platform enables engineers to access vehicle data remotely, reducing the need to travel to test tracks, climate chambers, or other development locations. Using Wi-Fi, long-term evolution (LTE), or other communication links, engineers can monitor logs, run diagnostics, update software, and in some cases perform electronic control unit (ECU) flashing remotely. This significantly improves development efficiency and responsiveness.
Q. What role do sensors such as global positioning system (GPS) receivers and IMUs play in the platform?
A. The platform supports multiple satellite positioning systems, including GPS, Galileo, and global navigation satellite system (GLONASS), delivering location accuracy of approximately 1.5 metres. Combined with an integrated IMU containing accelerometers and gyroscopes, the system can correlate vehicle behaviour with operating conditions. This helps engineers understand whether specific events occurred during braking, acceleration, cornering, or other vehicle manoeuvres, providing valuable insight during testing and validation.
Q. What cybersecurity features are built into the platform?
A. The platform incorporates a hardware secure element that protects cryptographic keys and sensitive information, establishing a hardware root of trust. In addition, application isolation and secure operating system controls prevent compromised software from affecting critical system functions. The platform is designed to align with requirements of the Cyber Resilience Act and International Electrotechnical Commission (IEC) 62443 cybersecurity standards.
Q. How does the open partner ecosystem benefit customers?
A. The open ecosystem gives customers flexibility in choosing software solutions rather than locking them into a single proprietary environment. They can use partner applications or develop their own tools using our APIs and software development kits (SDKs). This approach allows organisations to tailor workflows for logging, diagnostics, analytics, and simulation while maintaining compatibility across different development teams.
Q. How important is the Indian market to your global strategy?
A. India is an increasingly important market due to its growing role as both an automotive manufacturing hub and a centre for engineering and development activities. The expansion of vehicle production and automotive R&D is creating strong demand for connectivity, testing, and development tools. Although we do not have a direct presence in India, partners such as Skillicon Technologies provide local support, customer engagement, and market development activities.
Q. What role will edge computing play in the future of automotive development?
A. As vehicles become increasingly software-defined, edge computing will play a larger role in enabling real-time data processing, diagnostics, and decision-making closer to the vehicle. Rather than replacing traditional development tools, edge computing will complement them by supporting remote diagnostics, distributed analytics, and local processing. It adds a new layer of capability that helps engineers manage growing data volumes and increasingly complex vehicle architectures more effectively.
