Embedded World 2019 Best in Show Award Nominees: Artificial Intelligence
February 22, 2019
Embedded Computing Design's Best in Show Awards recognize innovative solutions for electronics engineers that will be showcased at Embedded World 2019. Here, we outline artificial intelligence.
Embedded Computing Design's Best in Show Awards recognize innovative solutions for embedded, IoT, and machine learning engineers that will be showcased at the Embedded World 2019 Exhibition & Conference. Here, we outline nominees for the 2019 Best in Show Award in the category of artificial intelligence (AI) and machine learning solutions.
- Aetina Corporation AX710
- Arrow Central Europe ICoMoX
- Diamond Systems Corp. ZiggyBox Miniature NVIDIA Jetson TX2 Computer
- Estone Technology EMB-2238
- Eurotech DynaCOR 50-35
- Intel Corp. Neural Compute Stick 2
- Supermicro SYS-1019D-FHN13TP
- Xilinx AI Platform
Aetina AX710 is a full-featured carrier board for NVIDIA Jetson AGX Xavier modules. At a size of 105 mm x 105mm, this carrier board perfectly fits applications with Xavier. Xavier, equipped with the NVIDIA Volta architecture, can enable revolutionary AI performance that achieves a 3x improvement over the previous GPU version. The AX710 liberates the entire power of Xavier, bringing a more thorough environment. The AX710 flexibly supports multiple cameras, with x8 FHD camera, x4 4K camera, and GMSL/FPD-LINK camera interfaces. An M.2 port helps integrate additional functionality with the Jetson platform, as does a 10G LAN board-to-board connector.
The Intelligent Condition Monitoring Box is an open development platform and a ready-to-use product for condition-based monitoring (CbM) of industrial equipment, assets, and structures. ICoMoX monitors operating conditions from the surface of the equipment to identify potential faults and reduce risks associated with equipment operation and maintenance. This extends the lifetime of the equipment, reduces downtime, cuts maintenance costs, and unlocks potential for energy savings.
ZiggyBox provides a compact, cost-effective solution for AI-at-the-edge and machine learning applications in an industrial environment. Based on the NVIDIA Jetson TX2/TX2i advanced computing module with NVIDIA Pascal family GPU technology, the ZiggyBox runs a complete Linux OS with NVIDIA extensions. With its ultra-compact size of 2.5" x 2.6" x 3.8" and tabletop or DIN rail mounting, ZiggyBox goes just about anywhere. In addition to Ethernet, USB 3.0/2.0/OTG ports, HDMI display, and two RS-232 interfaces, ZiggyBox adds real-world analog and digital I/O capabilities. Software support includes a programming library and a graphical control panel for real-time monitoring, control, and data logging.
The EMB-2238 is an industrial motherboard based on the NXP i.MX8M Arm application processor. It features a dual-core hardware DSP for voice control, noise suppression, and echo cancellation. It is designed to bring voice control and the power of edge computing to an industrial-quality board. It features a variety of high-quality digital audio inputs/outputs, and supports operating systems like Wayland, Amazon AVS (Alexa Voice Service) Device SDK, Sensory TrulyHandsfree Wake Word Engine, plus Android, Embedded Linux, and others.
Eurotech DynaCOR 50-35 is a rugged liquid-cooled high-performance embedded computing (HPEC) supercomputing platform. It comes in an extremely compact, fanless, and ventless format, and it carries the major needed certifications for automotive applications. The system is an in-vehicle deep learning enabler that allows both inference and training with TensorFlow, Caffe, and other deep learning frameworks, providing an ideal platform for autonomous driving and artificial intelligence (AI) applications. The DynaCOR 50-35 is designed to sustain massive workload capacities thanks to dual 14-core Intel Xeon CPUs and multiple high-performance accelerators, and networking cards, including several network interface controllers (NICs) that enable multiple interfaces up to 40/56 GbE. Storage is available through NVMe PCIe card modules.
Bringing computer vision and AI to your IoT and endpoint device prototypes is now easier than ever with the enhanced capabilities of the Intel Neural Compute Stick 2 (Intel NCS 2). Whether you're developing a smart camera, a drone with gesture-recognition capabilities, an industrial robot, or the next must-have smart home device, the Intel NCS 2 offers what you need to prototype smarter, faster, and more efficiently. What looks like a standard USB thumb drive hides much more inside. It's built on the latest Intel Movidius Myriad X VPU which features the neural compute engine – a dedicated hardware accelerator for deep neural network inferences. The Intel Distribution of OpenVINO toolkit streamlines development so you can innovate faster. The Intel NCS 2 accelerates inference up to 8x over the previous generation – exceptional performance per watt per dollar.
The SYS-1019D-FHN13TP is a 1U compact system with support for the latest Intel® Xeon® Scalable processor technologies and GPU support. It is a high-performance AIoT solution optimized for inference at the Edge.
The Xilinx AI Platform is the industry's first dual hardware and software optimizer. The comprehensive software environment directly compiles and quantizes trained neural network models in standard frameworks such as Caffe, TensorFlow, and MxNet, and optimizes them for implementation on Xilinx SoCs and FPGAs. The platform's network pruning technology reduces AI computation requirements up to 93 percent with accuracy loss of less than 1 percent. Additionally, for optimal performance, it customizes hardware IP and memory hierarchy for AI inference based on the network structure.
For more information on any of this year's Best in Show product nominations for the Embedded World 2019 Conference & Exhibition, contact Rich Nass, Executive Vice President and Brand Director, Embedded Computing Design.
For more information on the Best in Show Awards, visit bestinshow.embedded-computing.com.
For more information on the Embedded World 2019 Exhibition & Conference, visit www.embedded-world.de/en.