Key Points
• Vision systems at the edge need a careful
combination of ISP hardware, high-speed
memory, and reliable storage.
• Create, reuse, or customize AI models
using the Arduino App Lab's integration
with Edge Impulse platform.
• Validating logic in the prototyping phase
enables engineering teams to refine
system behavior and control stability
before committing to specific models.
• Hybrid architectures offer a clear division of
labor where the microprocessor manages
high-level logic, and the microcontroller
handles time-sensitive tasks.
• UNO Q provides the necessary RAM,
storage, and processing power required to
run AI at the edge.
C h a p t e r 2 | T h i n k
Uno Q 4 Gb
14
From Blink to Think: How Arduino UNO Q Helps Designers Go from Idea to Intelligent Product
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