End-to-end IoT Development with Zephyr

Developing IoT with Zephyr is a journey from hardware all the way to application. It involves multiple teams and expertise, from hardware to cloud and application development. This talk will cover the options for getting a Zephyr app connected (WiFi, Ethernet, Cellular), selecting the right data encoding (JSON/CBOR), securing the data transfer (DTLS/TLS), and choosing a protocol (HTTP/MQTT/COAP). But that’s not the end of the story, the cloud needs to manage devices allowed to connect, consume the data being received, open up options for using that data, and be aware of the continued state of the hardware. And once you have the data you need to build a user-facing application on top of it. Understanding this lifecycle will help us as developers to make good choices on what Zephyr provides, helping ensure successful IoT projects.

June 8, 2022 · Zephyr Developer Summit 2022 · Computer History Museam - Mountain View, CA · 🗣· 🎙· 🎥

Using GitHub Actions and Golioth to Automatically Deploy IoT Firmware

What if your IoT firmware deployments happened automatically just by typing ‘git push’? Lead Engineer Alvaro Viebrantz talks about a sample project that compiles and delivers firmware to eligible devices automatically using Golioth and GitHub Actions.

April 7, 2022 · 🎥

Output Streams are the firehose of data to your chosen platform

In this video, Alvaro shows the new Golioth Labs CircuitPython SDK, which allows rapid prototyping using the popular program language designed for microcontrollers.

February 17, 2022 · 🎥

Click “save” to stream IoT device data to the cloud -- Golioth introduces CircuitPython SDK

In this video, Alvaro shows the new Golioth Labs CircuitPython SDK, which allows rapid prototyping using the popular program language designed for microcontrollers.

January 25, 2022 · 🎥

Trying out Golioth with PlatformIO and Arduino Core

In this video and associated post, we’re talking about interfacing hardware to Golioth using popular tools like PlatformIO and Arduino Core (API). Alvaro shows how to use an ESP32 board from Adafruit with the Arduino Core on PlatformIO to talk to the Golioth MQTT endpoint. Golioth has a range of tools and resources for hardware and firmware engineers to get their devices talking to the cloud.

December 9, 2021 · 🎥

Provisioning IoT Devices with Zephyr, MCUmgr, and Golioth

Every IoT project needs to provision devices that are going to be available in the field. Leveraging open standards, Golioth cuts down on the required time and hassle for IoT development teams.

October 28, 2021 · 🎥

Device firmware update (DFU) using Golioth

Update your firmware over the network using the Golioth platform. Bundle multiple artifacts (binaries) together into a release and easily deploy firmware packages to specific devices in your fleet. In this video Alvaro shows how to update the firmware of an nRF52 over Ethernet using a Featherwing board using Golioth’s DFU capabilities.

October 14, 2021 · 🎥

Using Grafana To Visualize Golioth's LightDB Stream

Alvaro shows how to map LightDB Stream data, which allows for instant, continuous data output from your IoT devices on the Golioth network. Stream data back from a sensor, a device measurement, or anything else you can think of. Grafana allows for charting and slicing of data in a local instance, for fast diagnosis of problems, and longer term trend charting.

September 3, 2021 · 🎥

Introduction to Golioth Tags

Device tags are a key part of Golioth. Managing device deployments—large or small—gets easier when you start grouping devices together. Adding “tags” on the Golioth platform allows you to notate an individual device belongs to a broader group. If you’re developing something like smart light bulb and you have devices tagged “kitchen”, you can send an update over LightDB to the “kitchen” tagged devices and turn all the bulbs on or off. You can also group devices by hardware type, by end customer, by firmware deployment test group anything you can think of!

August 4, 2021 · 🎥

TinyML - IoT e Machine Learning na prática

A junção das áreas de Machine Learning em ambiente embarcado/IoT tem crescido bastante, sendo atualmente chamada de TinyML. Já temos modelos robustos e pequenos o suficientes para rodar até mesmo em micro controladores com 16kb de memória. Nessa palestra vou mostrar as diferentes formas de se trazer modelos de Machine Learning para ambiente embarcado usando o ecossistema do Tensorflow.

February 20, 2021 · Tensorflow Everywhere - Edição Brasil · Online · 🗣· 🎙· 🎥