This repository contains various guides and demos that utilize the /IOTCONNECT Python Lite SDK to connect devices to the Avnet /IOTCONNECT platform and showcase telemetry reporting and cloud-to-device command functionality. The Python Lite SDK may be used to enable /IOTCONNECT on a wide variety of development boards/platforms. Avnet has completed this work for a subset of boards as outlined in the following section.
The following development boards are pre-enabled with /IOTCONNECT in this repository:
- Arduino Uno Q - (Purchase Link)
- Microchip Curiosity PIC64GX1000 Kit - (Purchase Link)
- Microchip PolarFire SoC Discovery Kit - (Purchase Link)
- Microchip ATSAMA5D27-SOM1 - (Purchase Link)
- Microchip SAMA7D65 Curiosity Kit - (Purchase Link)
- NVIDIA Jetson Orin NX - (Purchase Link)
- NXP FRDM-IMX93 - (Purchase Link)
- NXP GoldBox 3 Vehicle Networking Development Platform - (Purchase Link)
- Raspberry Pi - (Purchase Link)
- Renesas RZ/G3E Evaluation Board Kit - (Purchase Link)
- ST STM32MP135F-DK Discovery Kit - (Purchase Link)
- ST STM32MP157F-DK2 Discovery Kit - (Purchase Link)
- ST STM32MP215F-DK Discovery Kit - (Purchase Link)
- ST STM32MP257F-DK Evaluation Board - (Purchase Link)
- ST STM32MP257F-EV1 Evaluation Board - (Purchase Link)
- Tria MaaXBoard 8M - (Purchase Link)
- Tria MaaXBoard 8ULP - (Purchase Link)
- Tria MaaXBoard OSM93 - (Purchase Link)
- Tria Vision AI-KIT 6490 - (Purchase Link)
- Tria ZUBOARD-1CG - (Purchase Link)
To get started connecting your board to /IOTCONNECT, first follow the Quickstart Guide within your board's specific directory in this repository. This guide will help you flash any required images, get access to your device's console, and set up basic /IOTCONNECT onboarding for your device.
To explore setting up AWS Greengrass Lite on some of these same devices and deploying Python demos through pre-built or custom components, check out the /IOTCONNECT Python Greengrass Demos repo.
If you want to modify or add onto the basic /IOTCONNECT starter application, you can do so by sending a software package to your device.
Within the common directory is a starter-demo directory with instructions on how to do this.
Some devices also include directories for pre-built expansion demos such as the EIQ Vision AI Driver Monitoring System (DMS) Demo for the NXP FRDM i.MX 93. Inside of the directories for those demos you will find instructions on how to use a software package to deliver and install the pre-built demo.
AWS Kinesis Video Streams (KVS) is an AWS service for streaming video from devices to the cloud. The /IOTCONNECT platform integrates with KVS to enable live and recorded video directly from your device's dashboard. KVS expansion demos are available for a subset of the boards in this repository and are delivered as OTA software packages that patch on top of the basic /IOTCONNECT starter demo.
There are two types of KVS streaming, each suited to different use cases:
PutMedia streams video from the device to a KVS stream where it is stored and can be played back through the /IOTCONNECT dashboard. Because video is stored as fragments on AWS before playback begins, there is typically 5–15 seconds of end-to-end latency, but the footage is retained and can be reviewed after the fact. PutMedia is well-suited for security camera and recording use cases.
Supported on:
- NVIDIA Jetson Orin NX
- NXP FRDM-IMX93
- ST STM32MP135F-DK Discovery Kit
- ST STM32MP157F-DK2 Discovery Kit
- ST STM32MP257F-DK Evaluation Board
- ST STM32MP257F-EV1 Evaluation Board
- Tria Vision AI-KIT 6490
WebRTC establishes a direct peer-to-peer connection between the device and the viewer's browser, brokered through a KVS signaling channel. This delivers sub-second latency, making it suitable for real-time monitoring. Unlike PutMedia, WebRTC video is not stored — it is only viewable while actively streaming.
Supported on:
- NXP FRDM-IMX93
- ST STM32MP135F-DK Discovery Kit
- ST STM32MP157F-DK2 Discovery Kit
- ST STM32MP257F-DK Evaluation Board
- ST STM32MP257F-EV1 Evaluation Board
- Tria Vision AI-KIT 6490
This library is distributed under the MIT License.