congatec COMs based on NXP i.MX8 processor series
conga-QMX8-Plus
- NXP i.MX 8M Plus processor
- Integrated Neural Processing Unit (NPU)
- Quadcore Arm® Cortex®-A53 / M7
- Up to 3 independent display outputs
- Industrial temperature support
conga-SMX8-Plus
- NXP i.MX 8M Plus application processor
- Integrated Neural Processing Unit (NPU)
- Quadcore Arm® Cortex®-A53 / M7
- Up to 3 independent display outputs
- Industrial temperature support
conga-SMX8-Mini
- NXP i.MX 8M Mini application processor
- Up to quadcore Arm® Cortex®-A35
- 1x Arm® Cortex®-M4F for real-time processing
- GC NanoUltra 3D graphics
- Industrial temperature support
conga-SMX8X
- NXP MX8-X application processor
- Ultra-low power design (2-5 W)
- Up to quadcore Arm® Cortex®-A35
- 1x Arm® Cortex®-M4F for real-time processing
- Industrial temperature support
Videos
Low-power AI accelerated embedded applications with i.MX 8M Plus SMARC
AI for shopping carts based on congatec i.MX8 SMARC module
Do you want to learn more about congatec i.MX8 COMs?
Join our congatec Design-In training to learn all about ARM based Computer-on-Modules including the following topics:
- Introduction ARM vs. x86
- ARM Architecture / Types incl. Roadmap Update
- Bootloader Introduction | Boot Sequence | U-boot | Boot Container
- Kernel Introduction | Structure | Booting Parameters | Configuration
- BSPs Introduction | Yocto Project | Android
- Hands-On Training (e. g. Hardware Setup, Booting Sample Image, Set up BSP, …)
- Design-In Support incl. TSC Services
SMARC modules with NXP i.MX 8M Plus Processor
congatec is expanding its SMARC platform with a new module with an NXP i.MX 8M Plus processor especially for embedded AI applications. Thanks to the extensive ecosystem with application-ready 3.5-inch carrier board, Basler cameras, and AI software stack, fast proof of concept is possible.
Mit einer NPU ans Patientenwohl denken
Die Art der Embedded-Integration entscheidet über den Erfolg von KI-basierten Systemen für Medizintechnik – egal, ob bei Diagnose, Defibrillator oder Livebildern einer minimalinvasiven Operation. Damit Entwickler schneller zu spezifischen Lösungen für medizinische Anwendungen kommen, bieten sich vorkonfigurierte Embedded-Baukästen an.
