IoT Plug and Play is now in public preview (https://aka.ms/IoTShow/IoTpnp).

In this episode of the IoT Show, you will see the new Azure IoT Central experience with native support for IoT Plug and Play.

Azure IoT Central has drastically simplified the task of building IoT solutions by eliminating the need for any cloud side development.

With IoT Plug and Play solution builders can explore a range of Azure IoT Certified Plug and Play devices; pick the devices that best fit their solution needs and build a production grade solution within days without having to write a single line of embedded code, drastically cutting down the time to market and costs.

After watching this short episode of the IoT Show and if you want to learn more, tune in (or watch on demand) the IoT Show Deep Dive episode: https://aka.ms/iotshow/deepdive/006

In this episode, Deb and Dani talk with entrepreneur and founder of MachineQ, Alex Khorram. 

MachineQ, a division of Comcast Corporation, is helping their customers transform by providing Low Power Network (LPN) based solutions to customers looking to embrace the power of IoT.  

Hear how his team approaches the market to democratize IoT for all users, not just developers and provides industry solutions to accelerate digital transformation.

Press the play button below to listen here or visit the show page.

Did you know that you can now train machine learning models with Azure ML once and deploy them in the Cloud (AKS/ACI) and on the edge (Azure IoT Edge) seamlessly thanks to ONNX Runtime inference engine.

In this new episode of the IoT Show, learn about the ONNX Runtime, the Microsoft built inference engine for ONNX models – its cross platform, cross training frameworks and op-par or better performance than existing inference engines.
From the description:
We will show how to train and containerize a machine learning model using Azure Machine Learning then deploy the trained model to a container service in the cloud and to an Azure IoT Edge device with IoT Edge across different HW platform – Intel, NVIDIA and Qualcomm.

In this episode of IoT Transformers, listen to Chris Palmer, manager of advanced technology services at PCL Construction to see how IoT will change construction.
In the past few years, PCL has taken the construction industry by storm with groundbreaking disruption in the “least transformed” industry.  Learn about their journey, the keys to their success and how they are continuing to grow their offerings and opportunities leveraging IoT.

Press the play button below to listen here or visit the show page.

BBC Click features the future of food in their latest episode: producing food with less environmental impact, how 5G helps salmon farms in the Orkney Islands, and a taste of new lab grown foods.

Azure Security Center for IoT can help you monitor and manage your IoT security posture.

Organizations can now easily protect their IoT deployments using hundreds of built-in security assessments drawn from the industry best practices, or create custom rules in a central dashboard. With newly added IoT security capabilities, you can now reduce attack surface for your Azure IoT solution and remediate issues before they can be exploited.

In this episode of the IoT Show, IoT Security experts show how to onboard to Azure Security Center for IoT and demo some of the many security values you will get.

For more details, visit Azure Security Center for IoT documentation at:

Enterprises nowadays are looking for ways to become more efficient by utilizing IoT to minimize safety incidents and maximize the lifespan of their assets. In this episode of the IoT Show, explore a real-life scenario from process manufacturing.

aka.ms/IoTShow/process-manufacturing

Read about IoT in Process Manufacturing: https://azure.microsoft.com/en-us/overview/iot/industry/process-manufacturing/
Experiment with the Azure IoT Edge LoRaWAN starter kit: https://github.com/Azure/iotedge-lorawan-starterkit
Learn about Azure Stream Analytics: https://azure.microsoft.com/en-us/services/stream-analytics/

AI has become a major driver of edge computing adoption. The edge computing layer was originally only meant to deliver lower compute, storage and processing capabilities to IoT deployments. As well as for  sensitive data that could not be sent to the cloud for analysis and processing is also handled at the edge.

Here’s an overview of the players and the state of the edge computing art.

Three AI accelerators present on the market today are NVIDIA Jetson, Intel Movidius and Myriad Chips, and finally the Google Edge Tensor Processing Units. All three are highly optimized for edge pipeline workflow and will see an increase in usage over the coming years. As AI continues to become a key driver of the edge, the combination of hardware accelerators and software platforms is becoming important to run the models for inferencing. By accelerating AI inferencing, the edge will become an even more valuable tool and change the ML pipeline as we know it.