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Industrial platform Edge AI based on NVIDIA Jetson Thor
Up to 2070 TFLOPS (FP4) - performance for AI and robotics
Jetson T5000 (Blackwell + Tensor Cores 5th gen.)
Service 8 GMSL2 (FAKRA) cameras - advanced vision
QSFP28 (4×25GbE) - high-performance communications
CANbus, I2C, LTE, WiFi - industrial systems integration
Platform for robotics, autonomy and video analytics
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Free shipping from €300
Promocja cenowa na model HDR-15-5
Product intended for professional use onlyJetson Thor is not just a more powerful embedded platform. It is an architecture prepared for systems that need to simultaneously analyse images, combine data from multiple sensors and make decisions locally.
With performance of up to 2070 TFLOPS (FP4) the platform can handle complex AI models, perception pipelines and control algorithms without moving computation to the cloud.
MIC-742-AT is built around applications where AI needs to work on multiple inputs simultaneously: cameras, control interfaces and industrial or mobile sensor data.
Supports 8 channels of GMSL2.0 from the mini FAKRA allows the construction of advanced 360° perception, inspection and real-time video analysis systems.
The QSFP28 (4 x 25GbE) interface enables the transfer of large volumes of data, integration with network infrastructure and the construction of distributed edge AI systems.
CANbus, I2C, 5GbE, USB 3.2, WiFi and LTE facilitate integration with robots, sensors, controllers and mobile devices.
If you are looking for an edge AI computer based on NVIDIA Jetson Thor that combines very high computational performance with interfaces for cameras, sensors and control systems, the Advantech MIC-742-AT is the platform designed for exactly such implementations. It is the solution for modern applications in the areas of robotics, autonomous systems, sensor fusion, image analysis and edge computing.
| Process | |
|---|---|
| Model | NVIDIA Jetson T5000 |
| CPU | 14 core Arm Neoverse V3AE (64-bit) SMP CPU architecture |
| L1 / L2 / L3 Cache | L1 (I, D) per core: 64KB + 64KB, L2 1MB, L3 16MB |
| GPU | 2560 NVIDIA CUDA cores, 96 5th Gen Tensor cores, MAXN: 1.57 GHz |
| Memory | 128GB LPDDR5X |
| Ethernet | |
| RJ45 | 1 x 10/100/1000/2500/5000 Mbps Ethernet |
| QSFP28 | 4 x 25GbE |
| I/O | |
| Display | HDMI (Max. resolution 3840x2160 @ 60Hz) |
| USB | 4 x USB 3.2 Gen 2 |
| OTG USB | 1 x Micro USB |
| Console | 1 x microUSB console for debug (UART to USB) |
| Audio | 1 x audio speaker out, MIC in on board |
| CANbus | 4 x CAN FD |
| GMSL (optional) | 4 x MIPI 4 lanes (Support 8-ch GMSL2.0 with mini FAKRA connectors) |
| I2C | 1 x I2C |
| SIM card | 1 x Nano SIM on side of board |
| Expansion | |
| M.2 E-key | 1 x 2230 E-key (Signal: PCIe x1 + USB2.0) |
| M.2 B-key | 1 x 3052/3042 B-key (Signal: USB3.0 + USB2.0) |
| SATA | 2 x SATA connector |
| TPM | 1 x TPM (onboard) |
| Storage | |
| M.2 M-key | 1 x 2280 M-key NVMe (PCIe x4) |
| Pre-installed SSD | 1TB SSD |
| Power | |
| Power Supply | Power input: 19–36V |
| Power Type | Terminal Block 2 Pin |
| Internal pin header | 3 x SMART FAN |
| Environment | |
| Operational Temperature | -10 ~ 60 °C with 0.7 m/s air flow |
| Operating Humidity | 95% @ 40 °C (non-condensing) |
| Vibration | 3 Grms @ 5 ~ 500 Hz, random, 1 hr/axis |
| Mechanical | |
| Dimensions (W x D x H) | 217 x 76.4 x 184.5 mm |
| Weight | 3kg |
| Installation | Wall mount |
| Software & Certifications | |
| Operating System | NVIDIA Jetpack 7.0 |
| Certifications | CE/FCC/CCC/KC/KCC/BSMI/UL (No RED certification) |
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