/IOTCONNECT is EBV’s cloud-based solution accelerator to enable our customers fast-forward, lean and secure evaluation of IoT and cloud-based products. It is based on our productive environment based on either AWS or MS Azure Infrastructure.
This page summarizes our global and local Webinar and seminar activities, currently focused on tutorials and walk-through demo enablement webinars. We take ready demo boards with the available EgdeAI models from our Suppliers and show in these webinars, how to get them running for first evaluation purpose, making use of /IOTCONNECT as Dashboard for interaction and visualization.
Available webinars and courses:
NXP i.MX93 - Webinar
EdgeAI models discussed: Driver Safety, Object Monitoring, Eyes Open, Yawning Detection
Processor characteristics: MPU (Linux-based) with NPU as AI-Accelerator
Webinar (61min): Register to watch on-demand Webinar
Hardware used: FRDM-IMX93
Step by Step Guide on GitHub
ST STM32N6 Webinar
EdgeAI models discussed: People Counting, Object Recognition, People Tracking and Gesture Recognition
Processor characteristics: MCU with Neural-ART Accelerator specifically for AI applications
Webinar (51min): Register to watch on-demand Webinar
Hardware used: STM32N6570-DK | DA16600EVZ | DA16200MEVZ | Jumper Wire Kit
Step by Step Guide on GitHub
Renesas RZBoard V2L
EdgeAI models discussed: Pose Estimate, Object Detection, Image Classifier, MultiPerson Pose
Processor characteristics: MPU (Linux-based) with DRP as AI-Accelerator
Webinar (59min): Register to watch on-demand Webinar
Video (3:22 min): Vision AI Use case Examples
Hardware used: RZBoard V2L - Tria
Step by Step Guide on GitHub
ST STM32MP257F-EV1
EdgeAI models discussed: Image Classification
Processor characteristics: MPU (Linux-based) only dual core Arm® Cortex®-A35 and Arm® Cortex®-M33 based
Webinar (49min): Register to watch on-demand Webinar
Hardware used: STM32MP257F-EV1
Step by Step Guide on GitHub
Infineon PSOC™ 6 AI
EdgeAI models discussed: Sound Classification (Baby cry), Accelerometer based Evaluation
Processor characteristics: MCU only Arm® Cortex®-M4 and Arm® Cortex®-M0+ based
Webinar (51min): Register to watch on-demand Webinar
Hardware used: CY8CKIT-062S2-A
Step by Step Guide on GitHub
Other model: IMU Based Human Activity Detection
Step by Step Guide on GitHub
