In a world accelerating toward intelligent automation, edge analytics, and real‑time industrial response, hardware must do more - faster, smarter, and securely. PHYTEC’s phyCORE‑i.MX 8M Plus System‑on‑Module rises to this challenge, redefining what’s possible at the edge.
Built on the powerful NXP i.MX 8M Plus SoC, this System On Module integrates a robust ARM architecture, on‑chip AI acceleration, advanced multimedia interfaces, and industrial‑grade connectivity — all within an ultra‑compact 40 mm × 37 mm footprint. It’s engineered to help developers bring cutting-edge embedded products to life quickly, reliably, and cost‑efficiently.
Why the phyCORE‑i.MX 8M Plus Is a Game-Changer
PHYTEC didn’t just build another System on Module — they built a scalable, intelligent processing platform optimized for AI, vision, Industry 4.0, and IoT edge computing applications.
- AI at the Edge
Equipped with a Neural Processing Unit (NPU) delivering up to 2.3 TOPS, the SOM enables on-device machine learning with minimal CPU load. Ideal for real‑time decision-making, computer vision, predictive maintenance, and more.
- Advanced Multimedia & Vision Processing
The module includes:
Dual MIPI‑CSI camera interfaces
On‑chip Image Signal Processor (ISP) supporting up to 12MP/375MP/s
Display options including HDMI, LVDS, and MIPI‑DSI
- Industrial‑Grade Connectivity
With dual Gigabit Ethernet (TSN‑capable), USB 3.0, PCIe, CAN FD, and extensive I/O options, the SOM meets the demands of modern industrial systems — precise timing, secure communications, and robust integration.
- Designed for Low Power, High Reliability
Using NXP’s 14LPC FinFET technology, LPDDR4 memory, and a sophisticated PMIC, the SOM excels in thermally constrained and battery‑sensitive environments.
- Flexible Prototyping & Cost‑Optimized Production
Choose between:
Connectorized variant for rapid prototyping
Solder‑down version for mass‑production cost reduction
Top Use Cases Powered by phyCORE‑i.MX 8M Plus
Whether you're building compact devices or industrial-grade automation, the module’s versatility shines:
✔ Smart Home / Smart City
(e.g., traffic monitoring, home automation)
✔ Industry 4.0 & Robotics
(e.g., HMI panels, robotic control, machine vision)
✔ Edge Computing / IIoT Gateways
(e.g., predictive analytics, secure edge nodes)
✔ Multimedia & Imaging Systems
(e.g., industrial cameras, vision‑based automation)
Why Engineers Choose PHYTEC SOMs
Developers prefer PHYTEC modules because they offer:
Industrial reliability
Long-term availability
Custom hardware support
Optimized BSP software
Fast product development cycles
The phyCORE-i.MX 8M Plus continues this tradition by delivering powerful Edge AI capabilities in a compact and scalable form factor.
Get Ready for Embedded World 2026 — March 10–12
PHYTEC invites you to experience the future of Edge AI, Custom BSPs, and Industrial Embedded Innovation — live!
Live Demonstrations Include
Driver Monitoring System (DMS) — detects drowsiness, distraction, phone usage, and even smoking
Drone‑Based Parking (ROS 2) — vehicle detection, OCR, brand ID & occupancy analytics
Celebrity Face Match — ultra‑fast identity matching using INT8 ResNet50
Industrial Digital Twin — Wi‑SUN mesh‑powered motor monitoring with secure MQTT
Scalable & Secure Wi‑SUN Mesh Network
Custom BSP Highlights
Zephyr BSP — sensor nodes, OTA, networking & more
Embedded Linux (Yocto) — NPU delegate, video pipeline, secure OTA updates
Meet PHYTEC at Embedded World 2026
Visit us at Booth: 3‑641
Event Date: 10–12 March 2026
Location: Nuremberg, Germany
Book Your Slot For
Private demo walkthroughs
Technical consultations
Business & partnership discussions
Starter kits & early BSP release access
👉 Book Your Appointment Now
FAQ – phyCORE-i.MX 8M Plus SOM
What is the phyCORE-i.MX 8M Plus SOM?
It is a compact System-on-Module based on the NXP i.MX 8M Plus processor, designed for AI edge computing, industrial IoT, and embedded vision applications.
What makes the i.MX 8M Plus suitable for Edge AI?
The processor integrates a Neural Processing Unit capable of 2.3 TOPS, enabling real-time machine learning inference directly on the device.
What applications can use this SOM?
Typical applications include:
Industrial automation
Smart cameras
Robotics
Edge AI gateways
Smart city infrastructure
Does the module support Embedded Linux?
Yes. The SOM supports Embedded Linux through Yocto-based BSPs, making it easy for developers to build custom embedded solutions.
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