Impulse Embedded, a leading provider of industrial computing systems and solutions, can now supply the RSC100, ARM-based Edge embedded PC featuring the Hailo-8 AI accelerator. This is a streamlined processing unit for AI applications that can offer up to 26 TOPs of int-8 performance in a cost-effective, power-efficient unit. The Edge system combined with Hailo-8 is suited for a wide range of uses including public safety, smart factory, agriculture and intelligent transportation.
The system chassis is made up of aluminium and heavy-duty steel with an IP40 rating and supports a wide operating temperature of -20°C to +70°C, ideal for use in harsh, industrial environments where the temperatures can vary throughout operation. Being an Edge device the RSC100 is kitted out with dual Gigabit Ethernet ports, an M.2 3052 B-key slot which can be used to install a 5G module and two full-size miniPCIe slots for expansion. The RSC100 also has seven SMA antenna breakout holes to meet the wireless comms requirements of your application.
The 8-core ARM processor is backed up with 4GB of LPDDR4 system memory and has 16GB of eMMC storage onboard as standard as well as an M.2 2280 M-key SSD slot with PCIe x4 NVMe support and a MicroSD card slot for additional storage. Further I/O includes a built-in HDMI 2.0 port with 4K resolution support, two serial ports supporting RS-232/422/485, two CANbus ports, two USB2.0 ports and 8-channels of digital I/O, (4-DI/4-DO). Embedded operating system support comes in the shape of Yocto Linux 3.0.
All of this I/O, software and connectivity combined with an AI focused microprocessor that uses just 2.5W whilst achieving 26TOPs of INT-8 performance, means the RSC100 can process complex deep learning neural networks out at the Edge in a wide range of smart embedded applications.
As with all of their embedded computing range, Impulse can fully configure the RSC100 to customer’s exact specifications in their UK-based engineering facility with a wide choice of storage, peripheral cards, operating system, and neural network.