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Introduction to intelligent sensors

Introduction to intelligent sensors
Okay, we have two more. The first one, optic related (sensors). Basically these use principle of optic operatings so we can measure the images based on the reflection of the optic signal. And also we can use the reflections to measure depths, similar to the distance of the sensor. The last one is biosignal related (sensors). That means we can measure the bio-vital signals of the human beings. For example, we can measure the temperature and also we can measure the heart rate sensors. There are two example we illustrated here. Okay, if we look at the last one, heart rate sensors. The sensors operation in this way is quite simple. We quickly look at the principle here.
You see we have a so-called light source. In general, it’s infrared. Okay, high frequency light source and make it through to the fingers or whatever you touched. Then based on the heart rate you see the blood flooding in your fingers so we can receive different signals. So we have a light source, and we have light detectors. Based on the strengths and the frequencies, we count of the devices. We can get the heart rate. That’s why whenever we measure the heart rate, we have touch on something else. Okay this is because the operation is based on this. We have one question is, if it depends on one single individual sensors to operate. Probably not enough for practical.
It means in most case we like to measure lots of signals. Different informations simultaneously. It will be called for smart, integrated, or even intelligent sensors. Okay so here we have different kind of evaluations for individual sensors. The first one we called integrated or hybrid. Integrated means we have different kinds of sensors integrated together into small pieces. That’s why we can put them into a small devices like cellular phone. Okay, hybrid means we can combine those different functionality sensors together. And signals can be measured on its original form. That means we have two sensors. One measures the biosignal. one measures the environmental signal like C02. They will not be messed up together. It’s what we mean “smart sensors.”
But they can combine into one body, one sensor body. Okay, the second one is so called the “sensor system.” We take auto-parking sensor system as an example. What you can see to the right, it figures we have auto parking. Tells you how to park your cars automatically. It will give you some correct informations or even the visions for the drivers to know how to park or for the machines, for the car how to make a park without the operation of the drivers. So we need lots of sensors. We need a camera to take the image to the analysis.
We need the infrared distance sensors to know how close our car is to the…maybe the wall or somewhere, or the car nearby. Okay and so forth. So we have lots of sensors in case we are going to bump into the nearby cars. We need some buzzers to alarm and to notify the drivers. So a lots of sensors are integrated together but they are not put into one devices. They operate individually but they connected together through the central control unit. This is what we mean sensors systems. Another one is called the sensor array. Basically, sensor array is composed of lots of sensors. For example, we have pressure sensor array.
This is one of the figures, you see lots of dots we form a plane. Basically a black dot represents a pressure sensor itself. And we have these connected together, transmit signals back to the circuitries for processing. We can use pressure sensors and make it like a blanket, put it on the bed, so that we can know the movement, know the sleep conditions of the patients or anybody else. These are pressure sensors.
Okay, we look at the sensors. As we say it. We combine the sensors at the upper layer. The application togethers. One we can explain more about the operation. The operation of sensor. And also we can look at the application of the sensors. How the system can post. So we cannot see the wood without the trees. So this is the example one. We look at some wearable devices. So to the left of the slides, you see lots of wearable sensors. Here, I have one here. I can take it off for demonstrations. This is the wearable watch. It’s okay, basically the wrist. So we can measure the blood pressure and also we can measure the heartbeat rate.
This is the wearable devices, one of the example. The example we show on the slide here is the vest. So in the middle, upper figure, represents vests. It looks like a normal vest but look at the inside we have lots of electricity, electronic circuit, sensors, put them together to measure your bio signals. This is the vest. Basically, the wearable vest has to be commercialized. You can buy it from the market. It costs maybe four or five thousand NT dollars. Okay, to the right, we show the processing flow of the whole wearable devices. So we can have lots of sensors equipped. We have a gyrometer, accelerometer, and magnetometer. So we can measure the magnet fields.
We can measure how fast the guy is moving and we can also see if the guy is keep balanced or not. So if we have these sensing signals coming into together, we integrate them together, we need to process it. We have a micro-control, a small chips, to process application signals and pack them into specific formats for communication, for transmitting back to the application layer for processing. Okay so we need to communication interface. It depends on what kind of communication technology you applied. For example, you may apply popular cellular phone, like 3G or 4G, and also you can use WiFi and so forth. So that’s why we have a communicate interface here.
Okay, down below there will be a propagation of signals back to the internet, back to the applications and so forth. This is the first one we see the wearable device. The second one we can look at the application of telemedicine. So here is an example. From this example we will see the expansion of the sensor and also the IOT. Here we have kids playing somewhere. So we have some sensors to measure the bio information. It is probably not a good example for this application, but basically telemedicine can be applied to chronic disease patients. There will be better all to the elders. Last one we apply to the kids, but anyways, this is an example.
Basically, we have sensors measure temperature, blood pressure, blood sugar, heart rate, and so forth. Based on these bio signals, we can analyze the health conditions of the guys being monitored. Okay, so you see… since we have lots of sensors, or maybe we have also the environmental informations to be collected, so you see the green dot all represents a different kind of sensors. These sensors have to be propagated to the backend for processing. Since the backend will be collect the data, analyze the data, and generate the useful information for human beings. So you can see lots of sensors has to be connected together, so these sensors has to be possess another capability, which is play a role of data forwarding.
So each sensor not only propagate the data, it generated (data) itself. It has also to process, to forward the data from the nodes, the sensor node nearby. So here is an example we have seen the dotted line represents the propagation of the data from different sensors. All the data has to go to a sink or gateways, to collect the data. Then through the internet, send back to the backend system for post-processing. Okay, so if we realize there are some dangerous situation happens, then we can sense the help and the risks immediately. It’s is the secondary example of telemedicine.

IOT is not that easy. After knowing the basic types of sensors, researchers have to combine different kinds of sensors in order to make “smart” sensors.

In this video, Prof. Ke will talk about wearable devices and telemedicine as applications of intelligent sensors.

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