On the Home page & Keynote of the largest Microsoft event in Europe

I got selected to talk during a Keynote of the largest Microsoft event in Europe. I’ll be presenting Azure IoT Edge, AI (Azure Custom Vision with Object Detection, and also Custom AI based on OpenCV/TensorFlow) deployed on Drones for ALTAMETRIS, to inspect the SNCF infrastructure.

Microsoft Experiences : it’s 15000 people, 300000 users connected on Live-Streaming

On the home page:  https://experiences18.microsoft.fr/ 

!

In 3 days, I got over 2000 views and kind feedback

https://www.linkedin.com/feed/update/urn:li:activity:6461365896681222144/

Speaker au Sido “La révolution IoT Edge et AI temps réel : avant-goût avec un drone de reconnaissance”

I got the opportunity to be an exhibitor and speaker at the Sido (one of the largest IoT event in Europe : 10 000 visitors)

My talk : “The IoT Edge & real-time AI revolution : illustration with Drone”

(original title in French :  “La révolution IoT Edge et AI temps réel : avant-goût avec un drone de reconnaissance”)

The Sido hosts 450 exhibitors, and is organized every year in April.

In 2018, it was on the 4th and 5th April : https://www.sido-event.com/ 

We had the privilege to have been selected by Microsoft, and we were hosted on their Microsoft Village, as a consulting firm expert in IoT.

https://twitter.com/VISEOGroup/status/981441899188948992

https://twitter.com/VISEOGroup/status/981485560375148545
 

https://twitter.com/AbdulOtman/status/981818184180346886

I love those mobile meeting-individual rooms to work in peace !

Nano Technologies, with Nano (hence) invisible sensors, except the electronic parts :

Our partner Advantech :

Realtime DataScience on IoT Edge Computing with Azure–HOL–Hands On Lab introduction

ScottGu is coming to Paris!! Hurry up to prepare a great 2.5 hours Hands On Lab, on realtime DataScience on Azure IoT Edge!

Register here for the Labs : https://www.microsoftevents.com/profile/form/index.cfm?PKformID=0x3237525abcd 
Here for the entire event : https://experiences.microsoft.fr/evenements/technique/azure-red-shirt-dev-tour/#register 
Link to the HOL : https://github.com/azugfr/RedShirtTour-IoT-Edge-AI-Lab  (made by Artem SHEIKO and Taras CHIEN ; with the contributors : Vincent Thavonekham + Igor Leontiev)

The detailed of the HOL will be available at the end on Github.

Below is a v1 introduction for the HOL (will be updated iteratively).

1 Introduction and why this Hands On Lab ?

IoT has been around approximately since 2000, and prior to that M2M (Machine to Machine), with sometimes some industrial standards such as OPC and later OPC UA, and sometimes no standards at all and only proprietary protocols.

Before we had :

1. Simple Processing
• [Machine A] <=> [Machine B]
• [Machine A] <=> [Machine B] <=> [Machine C] <=> [Machine A] <=> etc…
2. Complex Processing

• [Machine A] <=> [Server/Cloud] <=> [Machine B]
  and [Machine C] <=> [Server/Cloud] <=> [Machine D]
  where the complex processing is handled by sending the telemetry the Server/Cloud, that will then analyze near-realtime + take decisions + send back actions via network

We notice that sending back and forth the data through the network is not efficient at all (ex. 3D X-Ray Scanners cannot send 2 TB of Data per second to the Cloud for processing).

But today, we are more interested to provide intelligence DIRECTLY into the sensors, on the so-called “Edge” side. Hence, “Edge Computing”

Source: https://www.openfogconsortium.org/

2 Architectural Overview: Let the Edge decide faster and avoid pyramidal decision structure

Sources : https://medium.com/@rshariffdeen/edge-computing-vs-fog-computing-5b23d6bb049d
         and https://www.supinfo.com/articles/single/5054-edge-computing-cloud-intermediaire

3 What Azure IoT offer in terms of Edge Computing in one sentence ?

To ease the understanding, one could define a vision statement of the “Azure IoT Edge Computing” Solution such as :

“Design intelligence from PC (manually with Python 2.7.x or using Cognitive Services as a Black Box), deploy THE SAME into the Cloud, and again THE SAME architecture on the Device side !”

4 Overview of the Azure IoT Edge computing

BEFORE starting the Hands on Lab / Tutorials, because the entire process is quite complicated, we will explain, as an overview the end-to-end high level scenario.

Source : https://www.technative.io/microsoft-brings-azure-stream-analytics-to-the-edge/ 

In the HOL, we will see that the extensibility allows us to replace the Module “Azure Stream Analytics on Edge device” by another on composed by your Module containing your own Python code, produced by your DataScientific.

4.1 On your PC (as a DataScientist)

1. When DataScientists algorithm: Code you Python algorithm on your PC using Azure Machine Learning Workbench, then sends that to Azure, via a Docker Container
• When using the ML model over and over, we will need to monitor and ensure that the model has not shifted beyond a given limit.
• He can perform basically 2 things:
• a Classification (probability to hit this mountain at this speed ?)
• or a prediction (according to the heat, the number of hours used, etc… the 4rth fan will be out of usage in 3 days). And beyond a threshold of 24 hours, send a purchase order of an identical fan and as soon as I got back an internet connection.
2. When AI / Cognitive Services : Pick and choose the Azure Cognitive Services you are interested in (then it is the same that is going to be deployed on the Edge Computing within the “IoT Lambda Architecture”)

4.2 On Azure Side

Use the Azure IoT Hub that your know, and locate the property Azure IoT Hub Edge.

Configure the reports (using Azure TimeSeries Insight)

4.3 On the Edge side

- Install and configure Module with Stream Analytics job for Edge Hub as a Source and Sink (see later explanation)

4.4 On “all sides”: The Fun part !

Now to glue all sides tightly we will start using concepts that can be made easy when compared to Geography for instance. For a second, imagine that you are the President of a country (or God if you prefer!) and you want to reshape entirely the towns/cities. You then have to take into account the following criteria:

1. Each city and town has its own specialty

2. The cities or Towns could be located around the Capital-area, or de-centralized on an island (i.e. far away with lots of time to travel from the capital to the de-centralized location)

3. The cities and towns are connected together through a mesh of roads, each of them has a sign-post telling where the road comes from and where it goes to

Now on Azure IoT Edge Computing, we have :

a. City or Town ó large or small modules with each of them having its specialty
(IoT Hub, near-realtime processing, Cold Storage,
Hot Storage, aggregation, Datascience computation, …)

b. Capital area vs. island ó the Azure IoT modules are located either in the Cloud

(Capital and Centralized decisions), or on the Edge
(de-centralized locations)

c. Mesh of roads with sign post ó Azure IoT Edge routes with a description of the
previous module and the next one

5 Conclusion in Azure IoT Edge

Easy yes ?
Let’s summarize with a different comparison. Let consider a human with a central brain that centralize the decisions: Complex decisions and Simple decisions.

When our leg gets burnt, the hurting information do not need to flow back to the brain. By reflex, the leg automatically moves away from the fire.

Indeed, it would have taken too much time for the leg to send the information to the brain, wait for a decision, and sends the conclusion back to the leg. Rather, the leg relies on local decision for “simple” actions to be taken.

That’s the entire idea of Azure IoT Edge: Have centralized and managed decision in the Cloud, and we rely on local devices that could take decisions, and report it back to the Cloud to carry on further complex decisions.

6 Deeper explanation

Now that you understood, let’s go deeper into the concepts:

• Each module is like a module is like Docker Container, hence we have the image and its “implementation” as “instance”, that is monitored be the Cloud Azure, thanks to a secured agent installed into the Edge
• Now because the complexity is handled mostly by the Cloud, then pushed to the Edge, we have a kind of duplicated information, or call it a “twin” notion.
• These Twins are separated into two types :
• the Module Twins
• and the Device Twins
• Those Twins are necessary and automatically managed by the Cloud behind the scene to hide the complexity of having a Drone working disconnected from the Internet/Cloud and when the Internet is Back, information are synchronized back :
• telemetry,
• status (On, Off, …)
• data (Edge contains a micro database)
• commands (upgrade Firmware, etc…)
• Now try coding that using the old fashion way with Assembler or C : How many months or years would that require ? and would that work and the code maintenable ??
  Next, I will carry on explaining why Azure IoT Edge is pseudo-complex, but the majority of the complexity is encapsulated behind Microsoft’s technology.
  
  

6.1 Why is it so complex ?

In the past, coding a real-time decision making on a Drone, we needed to know well the Intel Chipset and Assembly or C languages. It took a long time and was a tedious and error prone process. I can let you imagine that it was way more complex than the Azure IoT Edge solution. The later offers the following advantages :

- ease the entire ALM process, and perform DevOps with tools that every (good) one knows, such as VSTS-GIT (CB, CT, CD, …)

- secure on both Edge side and on Cloud side (authentication key, X509, SSO, …)

- allow “user friendly” yet powerful code such as Python to be developed an entire IoT+processing+ML system and deploy that (using Docker) all the way to the Edge, via the Cloud that supervises that all. Thus, Microsoft relies on opensource and cross platform technologies that could be ported to any other platform for reversibility needs.
Since we are using a regular Docker, we could extend the features by adding any additional ones.

6.2 What Next ?

• Imagine all this working … with No Internet AT ALL, and with medical regulation constraints, … and even worst … this should work in France with endless crazy regulation  ?? Would that be a dream and totally unfeasible ??
• Not so sure : With Azure Stack, we will be able to do that !! https://azure.microsoft.com/en-us/overview/azure-stack/ 
• Magic ??
• Now imagine, extend all this to SAP and Dynamics365 and with an IoT System without coding anything at all ?? Not possible ??
• It is possible with Azure IoT Central, as SaaS solution !! https://www.microsoft.com/en-us/iot-central 

7 FINAL CONCLUSION

• Azure IoT offers an entire ecosystem, very rich, open and extensible, from Edge to SaaS, that was build with security and DevOps in mind.

• Now it is important to pickup the proper options and design an IoT architecture that suites the needs : that’s the job of IoT & Cloud Enterprise Architects or Cloud Solution Architects.

COMME AND JOIN US :

https://experiences.microsoft.fr/evenements/technique/azure-red-shirt-dev-tour 

SOUVENIRS

https://x.com/ShelPF/status/955804078122168321?s=20 

https://x.com/vThavo/status/955806487988850688?s=20

Making Industrial IoT move in France with OPC UA Standards

I had the opportunity to work with the OPC Foundation with Thomas Burke, president of OPC Foundation worldwide, very open minded and accessible to talk on various topics.

We organized an OPC Convention in France (free event), in the Headquarter of Schneider Electric (an OPC member, where Jim Luth, Schneider-Electric, is Chief Technology Officer). The “hive” has reached its full capacity, with head of Industry4.0 from SAP, Renault and Schneider. With other VIP and CTO interested in security, blockchain, …

Behind this OPC convention, we had the opportunity to present our vision on stage (along with the head of SAP for Industry4.0, head of Schneider Electric for Industry4.0, head of Renault for Industry of the Future, creator of OpenOPCUA, the creator OPC UA nodeJS and book author, …).
During the convention, many insights of Industrial IoT got presented worldwide, concrete feedback of the massive Industrial project with Renault and OPC UA as key to its strategy, … The problem is that, now we see that France are so much behind Germany, and even behind China that has an innovative strategy enforced by the government on their Industrial products/goods and manufacturing processes !!
(report in French here)

Wake-up France !! Industrial IoT is a reality, when you’ll realize that, it’ll be too late ! I also presented the work we done for Renault regarding security and Blockchain (ePassport).

Finally, we got the chance to make thing move in France, with Thomas Burke (on the very right hand-side proposing great ideas). We’ve got a plan with few elements and let’s hope I’ll gather enough people and companies (and budget !!) to make things move nationwide : I might be Microsoft Regional Director and Azure MVP, which gives me access to those VIP people worldwide on one side, and on NDA roadmap for the next few years on the other hand, but if all the promises made to me are not in place rapidly, we could wait an extra 2 or 3 years to make things emerge into industrial reality…

Let’s hope France will not be “Industry of the Past !“ if the Government and other major actors are not moving fast enough !
OPC UA is totally independent from Microsoft ; but because Microsoft works on Industry4.0 and Industrial IoT connected to Azure Cloud, with Microsoft France, we are trying to join our forces with Microsoft Germany and Microsoft Corp.
And by that time, France we will be the bottom rank : It’s an industrial competition, we have to be proactive and move fast !!