 Hi, I'm Pietro Montino. Hi, I am Danilo Pau. So, at BlueIn we are providing engineering solutions in the domains of electronics, embedded software, connected devices, and cloud services. Last year I was looking for a link between high-level AI coding frameworks and embedded microcontroller tool chain. During my researches, I came across Danilo, who introduced me to STM32QBI. And it proved exactly to be what I was looking for. Embedded deep learning was enormously easy. So now our products can exploit their potential by managing and structuring data. The application Pietro has brought to embedded world is very innovative, as it classifies the audio Doppler effect of cars approaching and leaving the microphone of the sensor tile powered by the Ultralow Power STM32L4 microcontroller. So, here we have the Vivaldi Sound Recognition Embedded Suite, powered by STM32QBI technology. The platform extracts intelligent meaning from surrounding sounds and enables the system to take autonomous decision. It targets several sectors, intelligent cities, predictive maintenance for industrial machinery, keyword spotting in robotics, physical event recognition for home automation and safety systems. In this version, we can see the Vivaldi Suite deployed for intelligent city applications. The sensor tile detects moving cars and triggers the possibility of real-time traffic monitoring. So car flows can be optimized and environmental pollution can be reduced. The fact that this device is based on audio makes it a lot cheaper and easier to install than any other. Basically, the sensor tile performs three steps, audio acquisition, audio preprocessing and classification with a pre-train neural network. It's able to distinguish whether a car is approaching or leaving. So it's recognizing the Doppler effect of moving cars. And so the counter is increased when either the Doppler effect is perceived. The next steps will be to increase the number of classes and to introduce regression to calculate the CO2 emissions of the flowing vehicles, connecting different kinds of sensors along the roads, making them directional and making the neural network more robust for running harsh environments. The world of sound is full of meaningful information, so we urge to create breakthrough applications from it. Since January 3, 2019, STM32Cube.ai is available for everybody and can be downloaded from ST.com. As you can see from all our partner testimonials, people are really engaging with this tool and provide great usability feedbacks. So please check out the links to our and Blue Wind website as shown.