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Edge AI PC with RTX 2060S mounted on a BOX PC using CFL-R S CPU【RCO-6000-CFL-2N-2060S】
The 【RCO-6000-CFL-2N-2060S】 adds a hot-swappable NVMe SSD canister to the base RCO-6000-CFL, allowing for the installation of up to four lockable 2.5" U.2 NVMe SSDs. Additionally, it features an added PCIe expansion slot equipped with an NVIDIA GeForce RTX 2060 Super GPU for inference acceleration.
Robust edge computer equipped with Intel CFL-R S processor, achieving high performance and ample storage expandability.
The 【RCO-6000-CFL-4NH】 features ultra-fast NVMe storage and adopts 2.5-inch U.2 15mm form factor NVMe SSD storage media to support larger capacities. This system is equipped with four lockable and hot-swappable NVMe SSDs that can be configured with RAID options 0, 1, 5, and 10.
Edge AI PC with RTX 2060S mounted on CML S CPU equipped BOX PC【RCO-6000-CML-20-2060S】
The RCO-6000-CML series is a fanless embedded system equipped with exceptionally integrated functionality, outstanding system performance, versatile I/O connectivity, and robust reliability. It offers dramatically improved CPU and graphics performance, a wide range of power and functional scalability, advanced features, modularized expansion I/O, abundant connectivity interfaces, a wide range (9-48V) DC power input, and 12-48VDC for GPU/card expansion, providing high reliability even in extreme temperature environments (-25°C to 60°C). Featuring a completely cable-free design, high functionality, integrated chassis design, and vibration-resistant design, it is a robust system that operates in harsh environments and is easy to install and maintain. It includes built-in over-voltage protection (OVP), over-current protection (OCP), reverse polarity protection, and wide-range DC power input, making it a safe system suitable for all industrial applications.
Simultaneous processing of multiple types of AI learning models.
■Equipped with two 'Hailo-8 AI processors' in a single fanless chassis■ The 'AT-IPCFG004' is an industrial computer with excellent environmental performance, featuring two high-performance AI chips designed for industrial applications. It can simultaneously apply different learning models, such as area recognition and object recognition, as well as object recognition and pose estimation, to input sources, thereby expanding AI inference capabilities. ■Equipped with two high-performance AI chips from Hailo, supporting multi-AI algorithms■ In AI deep learning, depending on the 'types of data sources' being handled, such as images, audio, and time series, as well as the 'analysis purposes' for what you want to learn from that data source, suitable algorithms are selected and applied accordingly for tasks like classification, depth estimation, object recognition, face detection, and pose estimation. Generally, in edge inference, one learning model is executed for one image source. With the AT-IPCFG004, by incorporating multiple Hailo-8 processors, it has become possible to 'simultaneously apply multiple algorithms to the source.'
