Avnet and its Newark distribution brand frame this booth tour around one goal: get engineers from “dev kit on the table” to a secure edge-to-cloud pipeline fast, using the /IOTCONNECT platform integrated with AWS IoT services. The pitch is less about a single board and more about repeatable onboarding: device provisioning, identity/cert handling, MQTT/HTTP telemetry, and a clean path to dashboards, rules, and APIs without spending days on glue code.
https://www.iotconnect.io/
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On the demo side, the interesting bit is how much inference stays on the device. A Linux edge box runs multiple computer-vision models in parallel (face, mouth, eyes) aimed at worker-safety analytics, while other “production ready” edge models focus on gesture detection and voice-assistant style interaction. The cloud link is used for fleet visibility and, critically, for capturing labeled data so models can be retrained and redeployed through a tighter MLOps loop in the cloud.
This segment was filmed at Embedded World North America 2025, and it’s basically a hands-on workshop format: attendees open a kit and, within about an hour, see a supplier board connected and reporting into the cloud. The lineup spans NXP microcontrollers (MCX) and MPU dev boards (i.MX93 class), plus connectivity paths that map to real deployments in the Americas, including Amazon Sidewalk and AWS IoT Core for LoRaWAN-style device onboarding in the field.
A lot of the flow is anchored in Ubuntu and containerized delivery: the /IOTCONNECT Snap on Snapcraft lets teams standardize install and updates across heterogeneous edge hardware. The booth also points to higher-end edge compute like Seeed Studio platforms with NVIDIA Jetson Xavier NX, and Avnet’s Tria Technologies modules, including Qualcomm Dragonwing QCS6490-based Vision AI kits (SMARC form factor) for multi-camera vision workloads with CPU/GPU/DSP/NPU acceleration at the edge.
Newark (Premier Farnell in Europe) sits in the practical middle layer: stocked dev boards and lab gear (Tektronix, Fluke, Keysight class tools), plus a bridge from prototype to volume via Avnet partners—illustrated here with drone telemetry and maker-style demos like Raspberry Pi 5 running YOLO on a vision camera and pushing counts upstream. The takeaway is an ecosystem play: edge AI on many silicon families, with a fast, consistent route into cloud operations and lifecycle management at scale.
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