Edge computing enhances automation process and improves efficiency by sharing workloads at the edge. ARBOR’s edge system can reduce data traffic and speed up automation process. With the specially designed graphics adapter support, it allows high level AI inferencing and deep learning applications. It can operate 24 hours a day to enhance quality assurance to its highest level and to remain focused on the job without irrespective of external factors.
ARBOR’s Edge Computing Solutions are powered by Intel’s 10th generation comet-lake platforms with support of power efficient, embedded Core i9/i7/i5/i3, and Xeon processors, which offers up to high performance 10 Core and 20 Thread processor on 35w and 65w configurations.
FPC-9107 offers unparallel flexibility on rich I/Os and expansion support, powered by Intel’s 10th Generation Core i3/i5/i7/i9 processor. Especially its GPU expansion with high performance thermal design, FPC-9107 supports two NVIDIA Tesla T4 GPUs or a (up to) 250W video card to enhance your AI and Edge Computing applications.
High performance graphic cards can generate a lot of heat inside the enclosure, ARBOR’s engineers strategically placed cooling vent and intake cooling fan can effectively reduce overall temperature inside the enclosure.
FPC-9107 integrated with Advanced Dynamic Smart-Fan utility, GPU cooling fan and system fan speed would change according to internal GPU temperature curve, to reduce overall noise
ARBOR’s Edge Computing Solutions are suitable for factory safety. As part of the preventive maintenance, sensor data from motors and other key components are collected. FPC-9107 can process tens and hundreds of sensor data to determine optimal maintenance time to prevent system failures. The data can also be used to enhance efficiency to improve factory productivity.
To compensate e-Tag technology with plate recognition solution, the traffic camera takes photo of oncoming traffic with a lidar trigger. The image data is sent to FPC-810X as edge computing system to process the image for license plate recognition, then sending the information to management system.