NVIDIA’s Jetson AGX Xavier Industrial module is making it easy to deploy AI at the edge in harsh environments where safety and reliability are critical attributes.
Manufacturing, agriculture, construction, energy, government, and other industries are progressively using robotics and automation, and yet many organizations have failed to apply the benefits of Artificial Intelligence (AI) and deep learning in the most advanced environments.
NVIDIA’s Jetson AGX Xavier Industrial Module
The industrial module features a 512-core NVIDIA Volta GPU with 64 Tensor Cores, two NVIDIA deep learning accelerators, two vision accelerators, an eight-core NVIDIA Carmel Arm CPU, an encoder and decoder. Included in the new SCE at the heart of the module is the dual-core Arm Cortex-R5 processor. It can be used for integrated fault-detection methods, lock-step subsystems, and built-in system testing. Cortex-R5 can be utilized for safety and mistake correction operations because it is always on.
The design intent for Jetson AGX Xavier is mainly for embedded applications in harsh environments. The module features 50G shock and 340G vibration protection and a -40 to 85° C operating temperature. All thanks to components that have been tested to demand industry standards and have novel functional safety features. It has a small, power-saving design and can reliably give AI performance of up to 30 trillion operations per second (TOPS). Additionally, the other reliability characteristics include error correction codes, single and double error correction, and parity protection for RAM resilience, among others.
Furthermore, the supercomputing power of the Jetson AGX Xavier’s system-on-module can be combined. This improves reliability, availability, and serviceability features needed to deploy AI in harsh environments.
Use Cases of Jetson AGX Xavier Industrial Module
The Jetson AGX Xavier Industrial optimizes abnormality and failure estimates in the petroleum sector. By offering real-time insights based on pipelines, valves, equipment, and maintenance activities. The module’s increased reliability allows it to be used in applications such as safety, predictive maintenance, and compliance. In addition, it fits perfectly in situations where the equipment must remain on at all times despite changing environmental conditions.
A manufacturer producing more than 1,000 automobiles each day needs to inspect over 6 million welding sites on the fly in order to keep up with demand. The Jetson AGX Xavier Industrial can assess process and quality data straight from weld guns using AI and computer vision. Hence, this lowers the inspection time, improves quality prediction, and ultimately helps consumers get safer cars.
Construction sites, likewise, use heavy equipment that must function dependably in a variety of conditions. In addition to harvesting thousands of acres of crops on a variety of terrains. Tractors must be able to transport fertilizers and pesticide sprayers. When operating in difficult locations, unmanned aerial vehicles like drones can undergo tremendous stress and vibration. Patient monitoring and point-of-care ultrasounds require steady operation for lengthy periods of time.
Customers can simply maintain and upgrade ruggedized and safety-critical equipment in the field. This is possible by making use of cloud-native technologies for orchestration and management with Jetson AGX Xavier Industrial and JetPack.
The new Jetson AGX Xavier Industrial module is now available for pre-order , with delivery expected in late July. Developers can use the Jetson AGX Xavier Developer Kit to start designing the smartest embedded systems for their industrial applications right now, with complete documentation available on the NVIDIA Jetson site .
Jennifer James is a graduate student in Computer Science Engineering who is passionate about front-end development. She is a content-writer inquisitive about technology. A rising enthusiast in search for optimum knowledge through learning and experiences of the everyday fast-growing Digital Industry through organizational exposure.
