*This episode of the Industrial IoT Spotlight Podcast is sponsored by the Industrial Internet Consortium

How to think about building an IIoT solution to provide business value? How to communicate IIoT solutions to corporations who want to implement some “IoT stuff”? What is the role of organizations and associations in accelerating adoption of IIoT solutions? 

Mitch gives us an overview of the manufacturing quality management testbed at IIC in conjunction with Huawei and Haier. He also gives advice on the process of conceptualizing an IoT product, and how to best go to market with it.

Mitch is a managing member of Tseng InfoServ, and a distinguished consultant to Huawei at the IIC. He is also the co-chair of the IIC Innovation and Edge Computing task groups. 

Erik: Welcome back to the industrial IoT spotlight. I am joined today by Mitch Tseng. Mitch is managing member of Tseng InfoServ. He's also a distinguished consultant to Huawei at the IIC, the Industrial Internet consortium. At the IIC, Mitch is the co-chair of the innovation task group and also the co-chair of the edge computing task group. Mitch also has a deep background in some of the fundamental technologies behind the industrial Internet. So he's involved with ISO, the International Organization for Standardization. He's a chair at the TIA engineering committee for vehicle telematics.

So, Mitch is a perfect person to be speaking with today about how we are taking some of the fundamental technologies that have been developed in the past decade or so and now putting them into very practical use cases that traditional businesses that don't have deep IT departments can start to implement. Mitch, thank you so much for joining us today.

Mitch: Thank you, Erik. Thank you for having me.

Erik: Mitch, you've got an interesting background. You also have a PhD, I should mention that. So you, you are very much a technologist. How did you end up first, setting up Tseng InfoServ, and then representing Huawei at the IIC?

Mitch: Several years back, I was actually focused on the telecommunications for many years, my PhD is actually working on a digital signal processing. And then I got into the digital vocoder design, and eventually cut into wireless communications. And I have to say, I'm fortunate enough to ride on the tide of the growth of the wireless communications. And after working in the industry, with those major player like Nortel Networks and Nokia, I found that the world is changing and then all the communication bases form a very good foundation for the future work.

So after I left Nokia in 2009, I decided, okay, I'm going to start looking for the next step. And I found a new love, which is a machine-to-machine communications, M-to-M. And that's the time that people are talking about there’s small machines and the system on chips. And then eventually try to get into this how do we use sensors and networks to help our industry and to boost our life, and even quality.

And then later on, of course, end-to-end become the IoT, Internet of Things. So I started looking into that part and try to leverage my background in the communications. And I'm also very interested in the business models because there was a time actually I was assigned to Beijing by Nokia, focusing on the smartphone platform marketing. So I've been trying to combine them together and I found that IoT or is not actually just something that the technical people should focus on. But also like a success of this IoT business actually is a combination of technology plus business.

So I formed Tseng InfoServ as a consulting firm and start talking to people, start learning that and eventually pry myself as IoT evangelist for this hut. Then of course, in the process I receive attention from the organization and also some companies and eventually I end up landing a contract with Huawei Technologies. has been a years now.

Erik: And Huawei is really one of the more interesting companies out in the market. Certainly, I think, a lot of people know them from their consumer business. But they are maybe the number one player, maybe number two in the enterprise market or the connectivity infrastructure. Are they now the number one player in the market globally?

Mitch: Arguably, yes. Their total sales in the infrastructure side, I think they surpass the others and become the number one in the world. And, of course, their fundamental business is actually access. There’s a radio access and the wire access. And eventually, they branch into enterprise networks. And, of course, when you talk about SS, this divided into two parts. One is the terminal side, which is handset and the other one is a network. I've been working with the research wings terminal and also now working with the network side.

Erik: The testbed that we're going to be discussing today is manufacturing quality management. So, interesting that a connectivity company like Huawei would be taking the lead. What's the background story? Why did Huawei become interested in this topic and decide among all the potential topics that could be the focus of a testbed to focus on manufacturing quality management?

Mitch: Erik, you know well, that in our industry in this IoT or IIoT, it's actually a combination of the IT and OT people. Then Huawei with a very strong presence and also a build out a lot of experience by connecting terminals devices, and actually pretty much just to support the whole communication community with the best access technologies. So, yes, Huawei is very strong on the IT side.

On the other hand, Huawei recognize that the communication business with the traditional telecom operators is actually continue to grow, but then the pace may be slowing down. And then they need to figure out what would be the best way to revive their technologies for the future. When IoT becomes practical, and of course, one size that you can connect, for example, like wearable devices, those will be like a more like a commercial related access.

But then they also really recognize that there is a one territory that nobody in the IT community has been really fully addressed. That is in the operational technology domain, the OT domain. For example, a lot of factories, they have automations. But automation, they are using those controllers, and they also be using those limiters to make sure that the process can be automatically produced. And of course, the objective for those factories is that it makes sure that in the production line, the product can be produced without any glitches, and then the quality will be good and also the quality of the great so that they will meet their market needs. And in that case, they are very contented data with whatever they have today. Because as long as the production line is not breaking down, then you can expect the whole business is booming and the revenue is coming.

But now, with this the IIoT, which is IoT focus on industrial domain, then that people from the IT domain figured there are so many things that we can help, for example, the quality of sensors getting better and better. And also this the computing power and memory chips or the hardwares, the price of those hardwares are driving down through the years and also the power of each chip, either is the computing power or the memory size actually growing exponentially over the past few years.

So we figured that well, with the conventional, those the PLC, the controllers, then we can probably do much better with our new virgin devices and new technologies. And of course, there's something that will in the OT domain, they're pretty contented with whatever they have today. So we need to figure out a way that we can actually knock on the doors and then introduce what we have over there, and to make sure that we bring in all the goodness, the greatest of IT and then to show that by connecting both parties together, we can actually create a much better view for the future.

And of course, about three years ago, there were some movements going on in the world, in Germany there’s industry 4.0. And then in China, they have a corresponding movements are the quarter Made in China 2025. So in that case, both sides, they all based on like I say, you join the IT and OT together, and hopefully, number one, you produce a much better product in the future; number two is streamline the process, make it more efficient; number three, you drive fully automation. And there are maybe other benefits for that. But these three will be something that the whole industry is looking at. And Huawei being the leader of this excess technology in the telecommunication domain, they figure that they need to also get involved in that area and that's how they get started and then they join IIC.

Erik: So just for the listeners here, a couple of the other the other stakeholders in this testbed are Hire Group which is one of the larger white goods manufacturers in the world, the China Academy for Information and Communications Technology and China Telecom. And one of the strategic priorities, in China right now is to improve the quality of manufacturing. So obviously, China is very efficient on quantity and cost quality in some cases is already excellent; in other cases, there's still a lot of room for improvement.

What I see as the goal on the testbed website is that using the MQM, the Manufacturing Quality Management analytics engine to drop the false detection rate by 95%. For Hire, hire is the end user here, so they're the ones who are providing their facility and reporting on the benefits as they realize. What's the business case behind this for Hire or for another manufacturer that might be using this solution in the future?

Mitch: The original design for the MQM testbed is actually we try to renovate older existing factories, or we should say we should develop a very systematic way to renovate those existing manufacturing facilities in China, get them suited up so that they can fit into the future like a modern production. And at that time, Huawei and the Hire as team up together, and that's mainly because Hire is actually focused on the appliance manufacturing. So, they actually use a perfect partner choices for the OT.

And at that time, we came up with Hire, and then because at that time we turn that Hire has some facilities in the [inaudible 19:02] China and then they focus on this air conditioning manufacturing. When we first got it, we say okay, we heard that they had some problem with their welding section because inside a key component of the air conditioning is this heat exchange tubes or the heat exchange tubes, it's actually rely on that as a welding process so they makes sure that there's no leak and they join those tubes together.

And we heard that there are some issues with that production because some of the false detection rate, just like what I mean forced detection means the machine actually has failed, but then somehow you pass the QC test. And of course, when the product was shipped to the customer and the customer use it in a short time, they decided they want to return it and this costs a lot of hustle for the logistics. For example, they need to bring it back to the store and then do start RMA process internally.

So they have been reporting there are some issues on that one. So, at that time, what we're thinking is that okay, then can we do something to control the manufacturing quality to help Hire on this part? So we got to remember so CICT and China Telecom, we get them together, and then we try to discuss what we may be able to do to improve the process. And then, as an engineer, we always think that, okay, we need to zoom in the problem right away. So immediately we room into this welding section.

And when we first started, we found that is not very straightforward that we can do it. And then later on, we come back and then try to evaluate what we should do. And finally, we change the value a little bit and just focus on the QC stations. And with that, in a short time, we actually turn the whole thing around, and we improve the pass-pass detection rate from 95%-99%. Actually, pretty much everything that's a passed will be passed.

And then the one that the false detection rate, originally, it was like 50%, is pretty much like you flip a coin on that one. But actually, we have new method in place that we improve the success rate from 50%-95%. And of course, this actually greatly impressed the management., and they eventually return into this quality control station, and how he changes.

Erik: So I guess one of the big challenges is how to cost efficiently integrate new technologies into a brownfield factory. And that's going to include, I suppose, in this case, some hardware, some software. Please do first walk us through the evolution of this project from focus initially on welding towards a broader focus.

Mitch: Right. We are all experienced engineers, so almost like firefighters, when we see that, okay, there's something wrong with that welding session, then we immediately jump into their part. Because when we talk about is IIoT, normally, we follow this IIC three tier architecture, which is that you have this edge tier which contains a lot of sensors. Then you get those data and then you pass to the second here, which is called a platform here. The platform would do all the analytics to analyzing it to make sure that you can come up with a meaningful analysis, then they can go back to help you fix the problem in the front.

And of course, the third tier is a management here, they actually oversees the whole process, and make sure the process run smoothly. So as an engineer, and normally, when the team reach the Hire factory, they actually just had to zoom into this welding section right away. And then we found that there's a potential problem there because the welding section is actually a “very dirty environment” from electronic signals viewpoint, because you have all this OS coming out, you get high voltage arcs running around. And worst of all, that robots has been there for some time.

So after a few trials, we recognize that it is almost impossible for us to stick a new sensor in the retrofitting process. So we've been bugged by this for some time, and then eventually, we came to IIC and then there are some partners, some members actually come in to help. For example, they have this company called Fujifilm, and then Olympus, they both have divisions handling the welding factories. And then we actually consult with them and then found out that most of the welding process, the people, they don't do a real time check. What they do is that they do the post analysis. For example, like Fujifilm, they have this X-ray film-based system. For example, these mobile phones, after you weld it, they can take a picture of that. And if there's any crack, they can actually see it from the optical viewpoint.

And then Olympus, the technology is actually most based on ultrasound. They will run the whole material through with the ultrasonic sensors, and ultrasonic source, then based on the response, they can detect a crack. A crack in the welding means a failure over there. So, we found that, alright, there's no real time process we're going to do, so what can we do to help this process? So that's why we sit back a little bit and then say, alright, let's reevaluate the whole thing, because remember we are focusing on the quality control system, not just one station. So maybe at that time, we jump into this welding session too early.

On your second visit of the Hire factory, we recognize that the way the quality control was made at that time at the end of the production line, they actually installed three experienced listener, they turn on the machine and then get the listener to listen to the noise of the machine. But then, of course, the whole success rate is rely on how experienced those listeners are. Of course, you can tell that people have good days and bad days. So maybe some good days, everything will be fine, and the bad day, then some of these reporting products, we got them slip into the shipping line.

So we come back to the lab and then agree redesign the whole thing. And then finally, we say, okay, can we focus on this analytical engine part, just in the platform side? Can we get some something that we can use to help this acoustic noise detection process? And of course, I actually had some expertise on the voice before. So I know there's something just like with some training data, that we can have some machine, we can train it, so that they can do it online automatically.

And fortunately, at that time, Huawei, they have this artificial intelligence AI engine, originally was designed for the project. But we were fortunate to borrow it. And then by asking Hire to provide a lot of test data, and we actually can train the AI engine. We use this as a deep learning or machine learning. And pretty soon that we found that the machine actually pick it up the detection process in a reasonable fashion in lab, then one of the challenges that does the we don't have too much of this false data.

Because the production actually is in pretty good shape, like 90%-95% of the success rate, so they don't have a whole lot of value of happen. But we manage the ask Hire to provide those data. And eventually, the first time we went to the field test, the machine actually is at least maintain a PAR was the human listening. Then we don't come back again to analyze why there is still cannot do better than human. We also pick up a lot of this ambient noise. So we just take a couple of days and we do this small just noise proof chamber with padding inside and can greatly reduce ambient noise. And then we put the microphone inside and then listen to the machine and then pump the data to this AI engine. And even the first file, just like I say we reach almost 100% accuracy. So that's actually very, very impressive at a time.

The best part is that the Hire management, originally, they’re skeptical about what we're doing. Because a lot of people have been talking to them about this IoT stuff, but they never have a good feeling about how this stuff can help them. So what we did is that we just use this IRA architecture just to have sensor platform and management, and try to map what they have in the production line. So the first step is that we gain the management from the production mind agree with us, so that we can actually operate on that one. And then eventually, when we showed them the great result, they are fully convinced.

And actually went silent on this one is that originally the testbed we only plan to have one production, ion air conditioning. But just because the success rate is so great, the management actually approved the second line on the kitchen bench shortly.

Erik: I was in a conversation yesterday with a partner and she mentioned that she's working with a lot of Chinese manufacturers who say they want to know what technology they can use to improve their facilities, and they want somebody to tell them install these or purchase these set of hardware and software and you'll become more profitable and so forth, you'll become “an Industry 4.0 ready facility”.

So I think the process that you just outlined here, very much a learning process where your initial hypotheses didn't really pan out because you found out that the operating environment was too noisy, it was too uncontrolled in order to install new sensors accurately collect data and have a result there. And then you try to deploy the analytics engine or the algorithm in the existing situation that the human is operating in and found out, likewise if there's too much ambient noise for this to be an efficient solution.

And so is this iterative process where you change scope somewhat and you had to properly understand the problem and then develop the solution around that. So it needs to be kind of a learning process, discovery of where in the process can we actually use technology to create a result and then what's technology suite might that be.

Where are you in the testbed today? It sounds like you've had a great success Hire is open to expanding the scope. Is this now a solution where you say it's more or less ready to bring to market or are you working with Hire or other partners to deploy it in different environments and continue to refine the approach of modifying retrofitting a brownfield environment and then deploying this solution? Is it already a standardized enough that you feel it's commercial ready?

Mitch: The process right now actually to a point that I will be trying to wrap up all the lessons we learned through this process and then try to publish the final report in the MQM testbed in IIC. And there'll be a starting point, kind of like a draw on this one. And meanwhile, we are seeking through IIC and their members, see if anybody else is interested in reapplying these methodologies to their process.

And actually, I have to say one great thing that we learned from the whole thing, we actually kind of expose one of the great mystery, people has been talking about IoT for many years, then why the deployment has always been slow down? And you can see on the internet, there are a lot of hypes talking about the new devices and new solutions. Then one fundamental question that people try to address is that why this IoT is not taking off as people have predicted.

And of course, there are some success deployments in the several fields. But in the process when we do the review session, we found that maybe because we are trying to say understand the problem and work with the client first, then we're looking for solutions. And they’re maybe the one that leads us to a better result in at the end. Because we have observed, there are so many companies and entities, they produce a lot of wonderful products. But normally is a group of engineers. They sit in their labs and they work real hard, and come up with something that they can see that that's the best product.

But in our process, we found that the product may be great, but the product actually may not fit our client's needs. And then most often you’ll find the sales persons, they bring their product and then they talk to potential clients. Then no matter how great the product is, when the client asks, how soon can I get it, you'll find more so often that this product is not ready. And unfortunately, the need from the client side is always now or even yesterday.

In this process, we learned that we can do better, then by listening to the client first and then we define the problem. And then we're not afraid of refining the process to make sure that we achieve what the client really wants. And the most important finding out of the whole thing is that we actually listen to the clients and then we produce immediate tangible value for the client.

And of course, right now, we are using the IIC as a platform and we try to encourage their members. And then if there are some people who are interested in reviewing the whole process, and then they're willing to actually discuss with us, then we are certainly welcome to that. Because right now Huawei is not making business on this site yet because IoT is definitely the focus. But right now there’s no entity talking about MQM manufacturing or whatever right away. So if you want to get involved in this or maybe have a feeling about his MQL testbed, I think the best bet is still going through the IIC channel for now.

Erik: If I can just kind of reiterate or synthesize that, I would say if you're industrial IoT technology company, especially a younger company, emphasis needs to be placed from the beginning on building partnerships. But typically, these companies have a great product that fits into a much larger solution that is going to require a lot of customization. And that means that they need to figure out how does my product fit into this solution or this range of solutions? And how does this solution have to be customized?

And typically, the technology company, there are some engineers sitting somewhere in the world, maybe in a place like Silicon Valley, where they're very disconnected from actual manufacturers and figuring out how they're going to get to market and how they're going to put their specific technology into the right system and configure that system for the needs of real client. Certainly, the Siemens’s and the GE’s can potentially do that, although I think they also are seeing more value in partners. But for most companies, they are going to need to get some system integrators involved, they're going to need to get some other companies that maybe sensor manufacturers and so forth, that have really unique vertical expertise, a lot of understanding of specific problems, and collaborate with them on getting that product out to market.

I think companies are starting to take more of this ecosystem approach. Because even a large company like Huawei, end of the day, it's providing one set of technologies into a much broader system, and they don't have the vertical expertise. So they certainly need to collaborate together. I think that's a big strength of the IICs testbed program.

When I'm reading through the MQM brief here, I see it broken down into the cognitive computing platform that Huawei has developed into data acquisition, data preparation, cognitive analysis, and then testing. What were the sets of technologies that were developed during this process? What are the technologies that were already off the shelf either at Huawei or partners that you integrated? Can you give us break down what the actual technology suite looks like and then what was needed to develop specifically for this solution and which technologies did you use that were readily available on the market?

Mitch: Those are softwares actually. Some of them actually, they’re off-the-shelf products, they’re actually Huawei adopted. Then, of course, like Huawei, we also have this precaution and lab is like corporate level research labs. They actually have an AI team is over there and then they focus on all the new software on the field. And I have to say, I don't know much about the details on their part. But then the good thing is that they provide us support to get those software's involved.

Of course, this machine learning engine and also the deep Learning engine, those actually require some development internally. If you are thinking about more details about that, I can actually hook you up with designers over there. Unfortunately, I couldn't give you too much detail on that.

Erik: What about the engagement of China Telecom? So I see they're one of the member participants. I mean, certainly, connectivity is required here. Was it more or less standard connectivity solution that they provided or did they also have some strategic or R&D support in this testbed?

Mitch: In our original design, China Telecom will be the provider for if we want to do the remote connectivity for the testbed, for example. The AI engine right now is actually in Hire’s factory. That's the phase one. Then what we want to do is that in the phase two, and phase three, what we can do is a number one, we beef up this network in the factory. So we provide a better connectivity so that makes sure that all the data can be connected, not just in this quality management session.

Then eventually, in our original proposal, we will have at least a center in Beijing, either in CICT or Huawei; actually, they can have like a mirror system set up over there. Whatever effect happens in the factory, then they will have a copy on site. So that means like, if there is something wrong with the analytical engine, they can actually do the reconfiguration or software upload through the network. And that will be Huawei lab and work with CICT and the China Telecom will provide all the necessary connections.

Erik: And then as you continue to identify the right solution for this problem, was it the case that that was just not necessary for the solution that you developed or is that a hypothetical next stage? It sounds almost like a digital twin type solution if I'm capturing the concept right?

Mitch: That's correct. But then the thing is that we have original proposal that we try to finish this phase one project in two years. And then at that time, the main focus is actually we want to go into the field to understand the customer's needs and to come up with a workable solution and provide a tangible result.

Then the decision at that point is that, yes, the AI engine, originally, we think about maybe just poor network on that. But then in the initial phase, it turn out that this work may be too cumbersome. So what we're actually doing is that we actually shift the whole computer to the production line. And then, right now, a lot of people may think this is overkill, if you just want to do this acoustic detection with so many competing powers in it. But for us, this is actually more than just a proof of concept because we also use this to demonstrate to OT partners. So what do we mean by this analytic engine?

So when they see something like that in the premise, and they can see it, they can feel it, and they can see how it works, this is actually really helpful as well. Then of course, that the other part like a digital twin, that's actually in the plan.

Erik: And then of course, company like Hire has dozens, if not hundreds of factories around China. So I could see the value, especially for a large organization to have a central control center, where they're able to monitor the different production lines and different stages on those production lines remotely. That's certainly, I think, hypothetically, much more cost effective than having troubleshooting teams in every facility because there's just so much talent to go around.

Mitch: Exactly. Actually, when we heard that from our partners, that is the Hire manager was so impressed with this project. They actually are former internal team just tried to focus on how do they retrofit all the different production lines on this part. So they may not actually jump into digital trim right away, but then I think they're on the way to there.

Erik: Mitch, what do you think is the next step for you? Are you going to be taking this through to a next stage? Or do you see potentially another testbed that might be on the horizon for Huawei?

Mitch: Well, actually, a Huawei has multiple testbeds that’s actually in the queue right now. To name a few, we had this time testbed that focus on the digital metro that's like the metro line subway system. They are actually in a review process right now. And also, there's another one proposed that a user this elevator. They want to connect all the elevators to form this elevator networks. Then you can do a lot of interesting things like where you connect all the elevators together, ranging from stabilities to all the analysis you can have.

Advertisement is one of the major applications on that. Like a predictive maintenance, for example, you can make sure that the maintenance team, they only do the maintenance on the elevator when it's needed and of course, will improve the efficiency on their part. Then there are several other testbeds actually cooking internally that I'm not able to say. But Huawei, I think that there are a lot of people inside, they’re seeing this testbed was a good way to showcase what they have, and also to join as partners for the future. And then they can actually turn this connected world much better with the Huawei access technologies.

And personally, will probably be number one just to continue to be the spokesperson for the MQM. And then also, if there are some interests in this part, then I can certainly try to connect them with interested parties, then also I’ll probably be the lead for some of the testbeds in the future as well.

Erik: Based on your experience with MQM, what advice would you give to companies that are either an IIC member and haven't gotten involved in testbeds or maybe not an IIC member, but a company that's trying to figure out how to do cost effective development of industrial IoT solutions, whether it's joining the IIC or just figuring out how to run programs with multiple other stakeholders with multiple partners? I think that's something that a lot of companies just haven't had much experience with in the past. It's either been internal or it's been bilateral. So what advice would you give to companies that are exploring this concept in order to help them maybe take the first steps and minimize the risk of failure?

Mitch: I've been working on the MQM IoT domain since 2009-2010 era. It never surprised me that so many people are interested in it. And then every day, when I look around the world, there are new products pop up and then there are some companies, some will people think that they can turn rich overnight just because they have a new product.

But the truth is, after so many years, I finally realized that when we talk about this IoT or IIoT, is actually an end-to-end business. You cannot just say, okay, I've become part of that and I've become very successful. For example, when you build a device, rather than just how powerful these devices, you need to picture that how this piece of device will be fit into the much bigger system picture. When you have a sensor, then you need to know how much information you can get and how much power you can consume and how secure it is because all the characteristics will affect the overall end to end service. We actually talk about IoT service. If you're just thinking about IoT without thinking about IoT service, you're going to run into trouble in the future.

Now, when we try to talk about this end-to-end, what as the testbed is that you try to test a service based or maybe you test a technology or you try to test some new sensors, everything can be done like that. But the problem that you try to solve is that you want to make sure that you have is end-to-end service built up because without an end-to-end service, you don't provide a value to your clients. And IIC testbed, you need to plan from the sensor side, which is like we call the edge tier and then when you go to the analytic power, which is an engine, they need to process those data, you connect it. And then of course, on the management side, you want to make sure that how you convey these messages to your customer, to your client, and also to your end users on the part.

And now we have more than 28 testbeds in IIC. And I can tell you that every single one of them is almost like I say just slap the business model on the top of that, it will be something you can try and run immediately. We have some testbed actually in China, they are talking about this water monitoring. The thing is that they actually work with the water systems in some counties in China. On one end, you have this reservoir, they will monitor how much water they pump. And then you also have this transmission line in between. And at the end, you have end users how you go into each household or you go to the water tank.

And of course, in the process, you monitor all the flows. So you know that when the assumption is much less than the pumping, then that means there is a leak in between. And how you diagnose it, and how you can test it, it started as a testbed, but you eventually turned into a successful business model for companies. And all the testbeds are working from that angle.

So for those people who want to be instant millionaire or who want to get rich fast, I would really suggest that say number one, when you talk about this IIoT domain, you always need to think about end-to-end perspective and then try to decide which part you fit in this end-to-end process. And of course, you know that you're just part of that, you know that you need to team up with somebody, how do you identify the supporting partners or the partner you can work with?

There are a couple of ways that we can do that. The number one is, of course, you can just join the association's affiliations and then we can actually just connect the people.

In IIC, we have members, actually that we call the IIC Connect in every meeting. That's like I say you're a member, you're welcome to join; if you're a nonmember, you're still welcome to join. All you need to do is just a register and then say you have some time slot, then you can have a one-on-one meeting with the other IIC members. Then you can jointly exploit what you can do.

And I think what we want to do is that we want to make sure that IoT business can be proliferated soon. Because I do believe, like I said, the volume actually matters. When we have more and more people engaging the IoT, when we will have more and more deployment in IoT, everything will be better, everything will be a lower cost and this actually will create a positive cycle for the whole business.

If I can be any help, you're welcome to reach me. Or if you want to contact IIC, I can help on their part as well. And actually, Erik, maybe you can post some links about IIC in this webcast, we can work from there.

Erik: I’ll certainly post the links to the testbed also how to get in touch with the IIC. Mitch, what would be the best way, if somebody did want to get in contact with you, do you prefer through LinkedIn or email? Or what would be the best way for people to reach out to you?

Mitch: I do have a LinkedIn account. And then email is probably the best way to reach me because I'm all over the places. And then I think email is most reliable to reach me.

Erik: So is it okay, if we put that in the show notes?

Mitch: Sure. No problem. Just put mitch@t-infoserve.com. That is my email address.

Erik: Alright. We'll put it there. Mitch, thanks so much for taking the time to talk to us, the testbed today.

Mitch: The pleasure is mine. Thank you, Erik.