# CAN-DAQ: An open-source, cost-effective data capture device and software for automotive research

**Authors:** Anuj Verma, Chandram Millon Dutta, Aritra Ghosh, Sakshin M. Kanchibail, Sneha Harish, Rishvanth S.K., Shaurya Chandra, Siddharth Das, Selvakumar K.

PMC · DOI: 10.1016/j.ohx.2026.e00743 · 2026-02-02

## TL;DR

CAN-DAQ is an affordable, open-source tool for capturing and analyzing CAN bus data, offering features comparable to expensive commercial systems.

## Contribution

The novel contribution is a low-cost, open-source hardware-software platform for CAN data capture with real-time visualization and SQL backend.

## Key findings

- CAN-DAQ supports all classic CAN baud rates and captures up to 1000 frames per second.
- The system was validated to perform reliably against commercial-grade automotive CAN interfaces.
- It provides a flexible Python-based SDK for custom real-time data analytics applications.

## Abstract

Modern systems, from vehicles to industrial testbenches, generate vast amounts of CAN bus data, yet researchers and developers lack affordable, open-source tools for its capture and analysis. While commercial tools are cost-prohibitive and existing open-source options often lack integrated hardware or mature software, acquiring this data is essential for subsystem validation (such as powertrains, safety systems, and sensors), ECU development, and network security analysis, with real-time graphing providing immediate insight. We present CAN-DAQ, a complete hardware–software platform that bridges this gap, matching the core features of commercial systems at a fraction of the cost. It combines an ESP32-based hardware interface with a flexible Python-based software and SDK, featuring high-resolution real-time visualization and a robust SQL backend. CAN-DAQ supports all classic CAN baud rates from 25 kbps to 1 Mbps and achieves a maximum sampling frequency of 1 kHz, reliably capturing 1000 CAN frames per second. As a fully open-source solution, it provides a foundation for users to build custom real-time data analytics applications. The system’s effectiveness was validated through comprehensive testing of its data reception, transmission, and sampling capabilities, demonstrating reliable operation against commercial-grade automotive CAN interfaces.

Graphical abstract Image 1

## Figures

24 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12906070/full.md

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Source: https://tomesphere.com/paper/PMC12906070