Arduino UNO Q with Qualcomm AI Chip: Enabling Next-Generation Edge Intelligence for Embedded AI Prototyping
DOI:
https://doi.org/10.70112/ajes-2025.14.2.4279Keywords:
Dual-Processor Architecture, AI Inference, Benchmark Analysis, Memory Bandwidth Real-Time ControlAbstract
The Arduino UNO Q introduces a novel dual-processor heterogeneous architecture, combining a Qualcomm Dragonwing QRB2210 microprocessor with a real-time STM32U585 microcontroller. The QRB2210 features a quad-core 64-bit Arm Cortex-A53 CPU (2.0 GHz) with an Adreno 702 GPU (845 MHz), delivering significant computational improvements over legacy Arduino platforms. Benchmark analysis reveals that the UNO Q achieves a 12.5× throughput improvement over the Arduino UNO R3 (16 MHz) and a 4.2× improvement over the UNO R4 WiFi (48 MHz). The memory architecture shows a 1,048,576× increase in SRAM relative to the UNO R3, with 2 GB of LPDDR4X enabling complex AI inference. Peak memory bandwidth reaches 2.4 MB/ns, compared to 0.32 MB/ns on the UNO R3. The dual-brain architecture enables real-time deterministic control via the STM32U585 subsystem, while leveraging GPU acceleration for TensorFlow Lite inference with sub-100ms latency. This work examines the architectural innovations and practical implications for edge AI, IoT, and robotics, which require both high-performance computing and real-time response guarantees in resource-constrained environments.
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