 Hi everybody, my name is Mauro Scandiuso, Field Application Engineer for ST Microelectronic and I'm working on the MEMS sensor portion. What I'm going to show you today is this eval board, this development kit that is called EssenceSensorTile.box, this is the way that we sell the device, it's a compact IoT node Embedded you have several sensors such as accelerometer, gyro, magnetometer, pressure sensor, humidity, temperature, so you can leverage all these devices in one, communicate through Bluetooth, you have an SD card embedded and a big battery to do, let's say, data logging and let's say evaluation of our sensor in synergy with our STM32 microcontroller. If you want to find information you go to our website st.com, the number is stevellmksbox1v1, you have a lot of information like user manual, schematic, below material, layout and really you can you can see also how is implemented the inside. The main device that I would like to show you today is the 6-axis, the latest 6-axis is called LSM6DSO-X, with the X we put in place the let's say the best in terms of feature embedded on 6-axis IMU, in particular we have embedded feature for pedometer, tilt detection, double tap tap, but we have also FiniStayMachine that can work for gesture recognition and machine learning core for activity recognition, so basically you can design decision tree and you can design also Fini FiniStayMachine combined together and make your application smarter in an extremely low power domain, because we are talking for make decision at the sensor level, at sensor level we can go from 2 to 10 microamps instead of compute everything to the microcontroller, make a computation and decision on top of that. Let's go for the demo that we have thinking today, so you pair the device directly to our Android phone through Bluetooth, you have several tabs here, one is dedicated application for smartphone, one dedicated for wearable, another one for personal computer, another for automotive, another is more generic application. If you go for all of them we have a label here and tell you exactly which kind of portion you are using, if you are using the Excel data or the Excel plus gyro data and if you are using the machine learning core, the FiniStayMachine or the embedded feature, for example for activity recognition we are using Excel and just a machine learning core portion. For other we can use machine learning core, FiniStayMachine and also Excel and gyro in combination. Let's pick up for example this one, flip down, we upload the configuration on the six axes and now we flip down the device and it detects that it's flipping down. Let's go and check other, let's say for example feature that we have in the wearable section, the wearable section we have the wrist tilt, so assuming that this device will be your smartwatch and you want to wear it, I want to detect when I wrist my device in order to enable and turn on the display. Now I detect and I wrist tilt. Let's go back for example in the application generic application, here you have a monitor vibration, let's see how much is the vibration and I detect. So now I have a level one, so basically it's static, no vibration, I move a little bit and I detect two. I move fast and I detect three. This is another application and I can use let's say the data from accelerometer in combination with the machine learning core. In case then I want to build up my machine learning core and my FiniStayMachine using the graphical user interface called Unico available from our website, you can always upload your configuration file here and you can also have the possibility to log through the SD card your data to design also your FiniStayMachine and also your machine learning core using the selecting the full scale, selecting the operation condition for each device, Excel and Gyro and you also you can connect directly the sensor title box to your computer and using the let's say the configuration as a mass storage tool to move the data directly to from the SD card to your computer. Thanks for your attention today, I hope that was a useful demo and if you need more information please go to our website www.st.com. Thank you.