Johan Stokking, CEO and Co-Founder of The Things Industries, joins Olivier on the IoT Show to walk us through the evolution of LoRaWAN in the industry over the last few years and what role it is playing in enabling the connection of physical environments with their digital twins in the Metaverse. Learn more about The Things Industries at www.thethingsindustries.com Learn more about LoRaWAN watching this video: aka.ms/WhatIsLoRaWAN - [0:00](#time=0m00s) Teaser - [0:33](#time=0m33s) Introductions - [1:15](#time=1m15s) Refresher: what is LoRaWAN? - [2:00](#time=2m00s) LoRaWAN's status in the industry - [3:47](#time=3m47s) Private vs. Public LoRaWAN network - [5:06](#time=5m06s) LoRaWAN ecosystem of plug and play sensors and Gateways - [5:57](#time=5m57s) Demo: 3D rendering of real time data from LoRaWAN sensors - [7:26](#time=7m26s) LoRaWAN's role in building the Industrial Metaverse - [8:33](#time=8m33s) Indoor usage - [9:31](#time=9m31s) LoRaWAN vs. 5G - [10:43](#time=10m43s) LoRaWAN and Edge Compute - [12:44](#time=12m44s) Wrap up and call to action

Anode is an end-to-end anomaly detection solution for Industrial applications by Codit. In this new episode of the IoT Show we discuss the importance and complexity of anomaly detection models as well as how Anode makes these accessible and easy to implement in production. Learn more at https://aka.ms/iotshow/Anode 0:00 - Teaser 0:52 - Introduction 3:25 - What is anomaly detection about and why is it hard? 8:54 - Introducing Anode 13:09 - Demo 19:05 - How can Codit help implementing anomaly detection solutions on Azure? 25:53 - Wrap up and call to action

Whether you are developing IoT devices solutions and wondering how you can integrate them into business application or you are agnostic of how IoT devices work but need them to trigger business workflows, this episode is for you. Eric Szymkowiak from Pilot Things joins Olivier to discuss Power IoT, a codeless solution that streamlines IoT integration into business applications and workflows. Learn more at https://aka.ms/IoTShow/PowerIoT - [0:00](#time=0m00s) Teaser - [0:31](#time=0m31s) Introductions - [1:40](#time=1m40s) What customer use cases and scenarios does PowerIoT address? - [4:10](#time=4m10s) Introducing PowerIoT - [6:55](#time=6m55s) How to get started with PowerIoT - [8:40](#time=8m40s) How LoRaWAN sensors data is converted and injected into Power Apps - [10:01](#time=10m01s) Demo: LoRaWAN sensors data used in Power Apps - [17:18](#time=17m18s) Call to action and wrap up

Device Update for IoT Hub is a comprehensive platform that you can use to publish, distribute, and manage over-the-air updates for everything from tiny sensors to gateway-level devices. This platform is now generally available in multiple regions. Why should you care? Keeping a network of IoT devices secure and up to date can be complex and costly, especially for organizations with limited technology staffing. Rather than take on the cost and work of building and maintaining custom update solutions, you can take advantage of a platform that is tailored for IoT devices and built on the experience Microsoft has developed through regularly updating hundreds of millions of Windows devices. - [0:00](#time=0m00s) Teaser - [0:33](#time=0m33s) Introductions - [1:35](#time=1m35s) What is Device Update for IoT Hub? - [2:27](#time=2m27s) Get started with Device Update in the Azure Portal - [3:23](#time=3m23s) The Device Update agent - [4:40](#time=4m40s) Prepare update deployment manifests and files - [6:47](#time=6m47s) Different types of updates supported (firmware or package based) - [7:41](#time=7m41s) New: Delta updates - [8:51](#time=8m51s) Configuring groups, scheduling, rollback - [12:55](#time=12m55s) Monitoring and troubleshooting updates - [15:08](#time=15m08s) Proxy updates - [17:00](#time=17m00s) Wrap up and call to action Learn more at https://aka.ms/iotshow/DeviceUpdate

Machine Learning is a key asset for Industrial IoT scenarios, but is a complex technology that presents many challenges. In this new episode of the IoT Show we will discuss the common Industrial IoT prediction patterns Machine Learning is used to implement and will demo resources and samples made available on GitHub to help you become familiar with Machine Learning for IIoT. - [0:00](#time=0m00s) Teaser - [0:30](#time=0m30s) Introductions - [1:30](#time=1m30s) What are the typical use cases for ML use in IoT solutions? - [3:30](#time=3m30s) What are the core steps for implementing Machine Learning? - [7:09](#time=7m09s) Demo: Exploration (problem definition, data acquisition, exploratory analysis) - [25:00](#time=25m00s) Demo: Experimentation (base line modeling, auto-ML, align Business and ML objectives, Model and data management, training pipeline) - [35:50](#time=35m50s) Demo: Operation (Business actions mapping, deployment and monitoring) - [38:12](#time=38m12s) Wrap up and call to action Learn more reading Jomit's blog post: https://aka.ms/iiot-ml Check out the samples repository: https://aka.ms/iiot-samples

Updating hundreds, thousands or even millions of microcontroller devices over the air is critical to secure IoT solutions. In this episode we discuss the challenges this presents and will demo how the Azure Device Update service allows to do this on ESP32 devices powered by FreeRTOS and a new middleware developed by our teams