This time we approached the workshop as a training and did not give the participants a breathing space. The presentation covered the MS AzureCloud platform in IoT and the potential of machine learning. We wanted to show the concept of AAEON's industrial devices.
Our supplier of embedded systems is AAEON and thus we brought single-board computers PICO-APL1-A10-N3350-KIT and PICO-APL3-A10-N4200-KIT with RAM and SSD from Apacer to our workshop. Single-board computers communicated via Wi-Fi with the Espressif ESP32 development module, to which humidity sensors (SHT-31), CO2 concentration (SCD30) and aerosol particle concentration (SPS30) from Sensirion were connected via the i2C interface.
Before the workshop, participants had to install the VisualStudioCode, Docker, and .net Core SDK that we worked with during the workshop. After a short introduction, we went into the practical part led by Szabolcs Baranyi.
Szabolcs gave us an overview of the Azure IoT platform, the machine learning capabilities, and the benefits of deploying AI on the Edge on industrial devices, such as the one used in a workshop.
The practical part focused on the development of IoT application for PICO-APL, powered by operating system Windows 10 IoT Enterprise LTSC 2019, leveraging the VisualStudioCodeCrossPlatform development tool. The application running on PICO-APL read the sensor data via Wi-Fi and sent it to Azure. In the cloud, we saw how easy it is to analyze these IoT data leveraging the IoT central service. We also explained the concept of device provisioning and showed how vendors can pre-install ID´s into a device and automatically connect to Azure backed.
For those who would like to get back to the information, or would like to try them, we have a GitHub.
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