As we discuss the Internet of Things in the industrial context as IIoT, we talked about how we connect various kinds of devices to embed intelligence in the manufacturing products and processes. In fact, these devices play an important role in collecting information in these manufacturing processes and enabling actionable insights through this real time information. Now these insights that we get from these real time information, right, they come from a technology that is embedded in these devices. It's called the sensor technology. The sensor technology actually enables these devices to collect the information from the manufacturing process or the environment, whatever we are interested, and these technologies play a very important role in enabling industrial Internet of Things as a concept. You may also recall that in the introduction of this series, I talked about the important Hex attack trend, the six big tech trends and the emergence of smart sensor network was one of the technologies that I referred to. And it is important for us to understand the sensor technology a little bit more as we build our understanding around the industrial Internet of Things. So let us understand what is a sensor. We can take a black box view of sensors, something that takes an input and then can create one or more output. For example, we talked about thermostat. Thermostat takes the input is basically the current temperature in the room. It senses that information and then it could either display that as a one output or it could send that information back to the cloud. So those are a couple of outputs. Now your smoke detector in your room, another sensor that we always are used to, right? I mean, that's constantly sensing for smoke or something related that. And then if there is detection then it just beeps, okay? So that's another example of a sensor. It's just a black box taking some input and then giving one or more output. More complex sensors kind of can also take multiple inputs. For example, you could have the same sensor that actually both senses your temperature and also it maybe senses the moisture in the room. And it could also, sometimes in industrial applications you could have sensors that do multiple sensing, whether it is heat or there this moment there is pressure, all the stuff. So when you take multiple inputs and then you can convert that into multiple outputs, of course the sensors becomes a bit more complex. That black box inside the sensor now, instead of being just a simple logic, the logic in that could be a little bit more complex, right? And then that's what is captured in the microprocessor chip that actually where you program the logic of how that sensor should behave. We come across sensors in everyday life. In fact you can kind of understand sensors and the concept of a simple, what I would call as the consumer sensors that we kind of come across these sensors in our day to day life. When last time you went to the grocery store you will find that you're just kind of you're scanning your item that you're buying that there is a sensor there which is actually looking at the bar code then reading the information. It could be there could be multiple sensors as you're walking through the aisle in the grocery store. In some grocery stores, they also have smart cards which actually kind of digitally displays information if you actually scan a particular product you want to know the price or some information about that particular product you want to buy. In some companies, it's kind of quite prevalent now where they use sensors or identification devices in their personal identification cards. They can use that for gate pass, kind of open doors where censors recognize the identification of this particular card and then give the required access that is needed. Those are some of the examples I call consumer sensors because directly we use it as consumers, citizens. And there are also industrial sensors in the context of manufacturing like on the left hand side of the slide. We could have simple robots, the simple robots which actually kind of takes some input, they sense the moment of some other part. They sometimes will sense the movement of conveyor belt and they take an action, okay? There are multiple sensors inside the robots, and the more complex the robots use a computer vision and they call the eyes of the robot their sensors in some sense. And we also have complex, the PLC machines, we talked a little bit earlier in the introduction, these PLC, the programmable logical controllers. They are actually, in other words, they're also big sensors, right? I mean, complex sensors because it's complex logic and you can program them, pre-program them for how the machine should operate in the manufacturing context. So in other words, there are so many different types of sensors. I mean, here is a chart that actually lists some examples of sensors, kind of temperature sensor. We talked about pressure, could be position sensors, there could be sensors based on the lat long, where exactly the asset is positioned, it can actually track that. And it can sense for a chemical, it can sense for gas. There are so many applications. In fact, it will be interesting way to look at the application of what each of these sensors does and then look at how we can put this together to create useful applications in a manufacturing or industrial context. Now let's take one simple example of one of these sensors. It's often called as the RFID. You might have heard this term, RFID, just kind of the full form is the radio frequency identification time. These are simple, microprocessors with antenna kind of transponders, you can receive and send information in radio frequency. So they are used as just storing information sometimes just kind of for identification purposes. And there are simple RFIDs, and kind of there are also, just like I talked about how sensors can be very simple sensors to complex, the same applies to RFID. And you are seeing RFID being used in manufacturing context to track inventory. It's used in grocery stores. So sometimes you'll see people taking inventory, walking through the aisle, they will have a kind of a reader on their hand. The antennas scan to see how many milk bottles are left on this aisle or something like that. They just captured their information to track real time inventory information. Now the RFID, the way it works is there is a tag, there's a static tag that has got this information. There's a reader that actually kind of senses this tag and the briefs that information communicates with the tag and then collects this information. Just we talked about how devices in the IOT applications collect information and provide real time information and provide that access to decision makers so that they can now derive some actionable insights and make decisions to improve the manufacturing process. So in the case of grocery store, you'll see that as they are scanning these RFID tags walking through the aisles, I mean people in the back end they're kind of getting this real time information. They know exactly which particular product is moving fast or not moving so that they start getting this real time transparency, the supply chain movement of this inventory so that they can replenish it faster. So that's one example of how RFID is used in terms of tracking the location, getting information, and of course, also use some analytics to make some decisions.