Learn how edge AI modules process vision and sensor data in real time for robotics, automation, and smart infrastructure.
As edge AI adoption accelerates across robotics, industrial automation and smart infrastructure, system builders are seeking platforms that balance inference performance with power efficiency and deployment flexibility. Many applications require stable real time processing at the edge, without the cost, size or energy demands of data centre class hardware.
EDOM Technology has announced the introduction of the NVIDIA Jetson T4000 edge AI module, targeting system integrators, equipment manufacturers, and enterprise users looking to deploy practical physical AI at scale. The module is positioned for scenarios where compact design, low latency and consistent inference performance are critical.
Built on NVIDIA Blackwell architecture, the module supports Transformer Engine and Multi Instance GPU technologies. It integrates a 12 core Arm Neoverse V3AE CPU, three 25GbE network interfaces and a broad range of I/O options, enabling support for multi sensor and real time workloads. Dedicated hardware blocks include a third generation programmable vision accelerator, dual encoders and decoders and an optical flow accelerator to maintain stable inference under constrained power and compute budgets.
The platform is designed to support applications such as robotics, industrial equipment, machine vision, smart terminals, edge controllers and sensor data processing. For enterprises, edge based inference and pre-processing can reduce latency, lower cloud workloads, and improve operational efficiency across environments such as smart factories, retail and security systems.
Key features of the module include:
- Blackwell architecture based edge AI processing
- Support for Transformer Engine and Multi Instance GPU
- Integrated 12 core Arm Neoverse V3AE CPU
- Three 25GbE interfaces for high speed connectivity
- Dedicated vision, video and optical flow accelerators
- Compact form factor with low power operation
The module can help customers accelerate real world edge AI deployment by combining stable inference, flexible integration and support from a mature software and ecosystem framework.
