 Hi everybody, my name is Maurius Candius of Field Application Engineering for ST Microelectronics and I'm here to cover the MEMS Sensor. What we're going to present today is the Sensor TIE, then probably you already know, it's a portable device with a lot of sensors, microcontroller and also Bluetooth and low energy and we will connect to our laptop Windows 8 or Windows 10 through Bluetooth and low energy and we're going to use the Uniqlo Graphical User Interface to connect and pair the device. First things to do, go to ST.com and in the search area type Uniqlo, the Graphical User Interface then we're going to use. Press the Uniqlo Graphical User Interface, scroll down and download, get the software. Obviously you need to have a username and password in ST.com, so after then you download the Graphical User Interface and you launch the installation, you need to pair the device. As you see, the sensor tile, the LED is blinking, so it's in advertised mode. Now you need to pair to your laptop, open the Bluetooth feature, add a Bluetooth device, scroll down. This particular device is AM1V310, you need to pair that. It requires a password from the C code, the password is 123456. Next, waiting then the pairing. Now that it's connected, I can launch my Graphical User Interface. I can select the proper connection, connect it, select the feature that I want. In this case I want to have everything, so environmental sensor, motion detection, activity, accelerometer event, battery, sensor fusion, activity recognition, carry position and gesture recognition. I start, the first thing that I see is the data logging here. And here on the vertical bar I have all the features, the data logging, the graph. Let's see the first things then let's say more peculiar for a wearable device. First of all, let's wear your watch. Let's look for the sensor fusion. Sensor fusion is a teapot, actually the teapot is represented exactly my wrist movement. And as you can see is exactly the kind of movement that I'm doing with my arm. Now assuming that I want to do some activity, let's see the activity recognition. So I'm doing a stationary condition, so it's detecting that I'm in a stationary. Now let's start from a walking condition. I'm walking and the algorithm embedded on the microcontroller will recognize that I'm walking. Assuming now that I'm joking and we recognize that I'm joking and now I go back in a stationary condition. And we recognize that I'm in a stationary condition. Let's assume that now I want to remove my wearable. I'm going to sleep, so I remove that. I put on my desk and we recognize that it is in my desk. At this point I take in my hand and we recognize that it is in my hand. Assuming then that potentially could be also a wearable. Now the algorithm will recognize that it is an wearable. Other things that I can do is data logging all the activity using the data log tab, select what I want between temperature, humidity, pressure, acceleration, angular rate, magnetometer, accelerometer, events, battery status, sensor fusion, e-compact, activity, carry position and just a recollection. The way that data logging is through a CSV file and I can elaborate using Excel, MATLAB, whatever I want. If you need more information please go to our website st.com slash sensor tile. Thank you for your attention.