Neousys Technology, an industry-leading provider of rugged embedded systems, releases one of the world’s first IP67-rated waterproof fanless GPU (graphics processing unit) computers, the SEMIL-1700GC.
Powered by an NVIDIA Tesla T4 or Quadro P2200, they are ideal accelerators to enhance AI (artificial intelligence) applications.
The system is designed to go beyond traditional embedded boundaries and is ideal for in-vehicle applications operating in all-terrain or extreme environmental conditions such as autonomous mining truck fleets.
SEMIL-1700GC is a waterproof and dustproof inference system with a pre-installed NVIDIA Tesla T4 or Quadro P2200 for the most demanding environments.
It can operate under 100 per cent load up to 62 degrees celsius ambient without the GPU throttling.
On top of its waterproof capability, the system is enclosed in a stainless steel and aluminum chassis for better corrosion resistance.
Backed by actual field implementation experiences in the mining industry and with SEMIL 1700GC’s tested and proven designs that thrive in extreme environmental conditions, it can bring modern AI inference technology to mining truck fleets with efficient route planning to reduce stop-and-go instances and improve operating efficiency, intelligent autonomy with object detection/ avoidance, advanced robotic controls to auto load/ unload and real-time remote monitoring to boost safety, and more.
Offering a variety of I/O (input/output) connectivity, including 802.3at Gigabit PoE+, VGA, USB, COM ports and optional 10G ethernet, all use robust and reliable M12 connectors for users to utilise cost-effective cable solutions that can be obtained off-the-shelf.
Additionally, SEMIL-1700GC features M.2 for NVMe SSD, two internal 2.5 inch SATA storage accommodations, 8-48V wide-range DC (direct current) input with ignition power control and complies with MIL-STD-810G and EN 50155 to ensure reliable system operation in shock and vibration conditions.
To contact Neousys Technology, please visit: https://www.neousys-tech.com/en/