We know that the focus of this course on the business applications of Industrial Internet of Things technology. But in order to further understand the business context and how it's applied, I think it is important for us to have some understanding about the technology, and the technical concepts behind how these applications are created. You need to understand, you need to build awareness about the building blocks that actually lead to these capabilities, and more importantly, the players, the different companies that come together and play different roles in developing and delivering these applications. Let's first start with the basic requirements. You should never think about any IoT or IIoT applications, unless you have your infrastructure right, in terms of your hardware, your communication technology. Because just remember that all these applications that we talked about, some examples, we used the all rely on a good communication network that is high speed, that has got good latency, and so if you have problems with that, I think these applications are going to fall apart. It's important to have the right hardware and the good communication network, and more important to that is the cybersecurity. We'll come and talk about service security is a big risk. You have to protect these applications, because on one hand the advantage is that you get real-time data access and you're able to make fast decisions, but at the same time, now the data is in the network, so you have to make sure that you have all the cybersecurity steps taken for you to launch any of these applications. Then on top of that, what I call, they're all IIoT platforms , they're available commercially. We have MindSphere from Siemens, this is one of them, which allows for the gathering and organizing of the data and the logic and the different pieces that actually pull together these applications. There are multiple platform that are available in the market, and it is important to understand what the variety of platforms are and what are their pros and cons. On top of that, then you have these platforms actually also connect with the enterprise software such as the ERP or your PLM software, the product life cycle management in software that actually runs the manufacturing process. These platforms connect with those software products, and also in a manufacturing context, you may have multiple devices, you have a lot machines, and then a lot of these machines themselves are intelligent, and we talked about programmable logic controllers and machines, because the machines have ability to be programmed and they have logic in them. Those machines will have operating systems, or software that controls those machines. We call it device operating system, any device just like our phones has got an operating system, does it not? We call this Apple's phone operating system or Android. These are operating system, these are software that control the device. Just like our phone, we have other devices that are used in the manufacturing contact. They will have their own operating system , so these platforms, they actually connect with those operating systems software, and so with all these capabilities on top of that, what you build is the IIoT applications. In other words, any of these say preventive maintenance application that I was referring to earlier, so that particular application, then will connect with the device operating system of that particular machine. It will connect with the IIoT platform that you've chosen, so that how you're organizing the data and the logic, where you're storing it in, and which Cloud architecture and things like that. Then it'll also that particular software IIoT application sometimes may also connect with your enterprise software, so that set of connectivity that I talked about with this platform and the device operating system, that is what leads to the IIoT application. Of course, this entire application is sitting on high-speed communication network that you've architected, and we're also all productive with the cybersecurity software layer that actually protects these vital information. Of course, more recently what has happened is the entire IIoT platform, they've been moved to the hyperscale in Cloud architecture. Because now with companies like Amazon AWS or Microsoft Azure or Google Cloud, they all offer what is called as hyperscaling because their ability to scale is enormous in terms of they can take a manufacturing company from one single plan. They will connect the same application, give access to the application across multiple clients globally, so they can scale it the way they want in terms of both global axis and also in terms of computing power. That's why you'd find that most of these IIoT applications are now rendered from this hyperscaling Cloud platforms, and these IIoT platforms are in fact hosted in the Cloud architectures. It is also important for us to understand who are some of the major companies that actually are playing roles in various layers, as I've shown in the diagram here. You certainly have appliance and hardware manufacturers. Siemens is actually both a hardware manufacturer and also a software manufacturer because eventually they provide both. In fact, they are very well known for their platform minefield that actually connects all different IIoT applications and also more complex applications using their IIoT capabilities. You have companies like ADLINK that actually connects to the balancing the Cloud and Edge intelligence distribution that we talked about earlier. We have specialist companies like Fastly which actually provide this Edge computing platform. We have NVIDIA, which is actually a chip company, which has a very dedicated GPUs, graphic processing units or high powered, very fast chips that are dedicated for particular applications so that you can put that in a specific Edge application. They're a chip company that are playing here. They're system integrators like Accenture, IBM or Tata Consultancy Services, Deloitte, all these are what we call them as system integrators in the sense they work with multiple platforms, and they actually bring together all these different parties and they take ownership working with their clients to deliver this IoT application in the context of that particular manufacturing company. Some of these systems more recently, they also have their own platform like TCS, Tata Consultancy Services, they have their platform. IBM has its own platform, so that when you're developing applications, sometimes they also can bring their platform. Of course, the hyperscalable platform that we talked about earlier, Amazon's AWS and IBM's platform for IoT, was also rendered from Cloud and Azure. These are some of the examples of how different companies come together. The reason I'm actually sharing this is when you are learning about these Industrial Internet of Things applications, it is important for you to know what goes behind the screen and then how these all come together, because for rolling out or thinking about new applications, it is important to understand who are the players? Who are the partners? Then how do you make use of these partners to build a viable and scalable solution for you.
