Rugged NVR from Premio (Model RCO-6000-CML-4NH-1E)

March 8, 2023
See it at ISC West 2023 Booth 3071

Greater Los Angeles, CALIFORNIA - Premio Inc., a global leader in rugged edge and embedded computing technology, today added a new model to its flagship line of RCO-6000-CML AI Edge Inference Computers powered by Intel® 10th Generation Core processors at the International Security Conference & Exposition 2023 (ISC West) at the Venetian Expo in Las Vegas, Nevada. 

The latest RCO-6000-CML-4NH-1E model provides high-performance edge AI processing, high-speed NVMe storage, modular I/O configurability, and wireless connectivity in a ruggedized enclosure. System integrators and OEMs can use this off-the-shelf computing solution for deployments that require real-time processing in the harshest and most challenging environments away from the cloud.    

“Video analytics for security and surveillance is a great example where edge computers continue to process and analyze data streams in real-time,” product marketing director, Dustin Seetoo said. “This specific model (RCO-6000-CML-4NH-1E) balances key technologies that enable powerful processing, data redundancy, and I/O connectivity for surveillance applications that use machine learning, intelligent automation and even IoT data telemetry.”

A key feature of the RCO-6000-CML-4NH-1E computer is its hot-swappable NVMe data brick that supports x4 u.2 NVMe SSDs (7mm) for high-speed storage. NVMe SSDs provides access to high-speed read/write performance for mission-critical data for local real-time processing. The NVMe data brick also includes the standard RCO-6000-CML series software development kit that provides programable logic to suspend all I/O transmissions and read/write operations in order to prevent the loss or corruption of data with a click of a button.  A hot-swappable exhaust fan is also positioned in the computer to ensure optimal thermal regulation of NVMe SSDs and expansion cards. The computer also comes bundled with a hardware RAID controller to maximize the storage performance and ensure data redundancy for the NVMe solid-state drives (SSD). Hardware RAID levels are made available with a Broadcomm MegaRAID 9560-8i PCIe add-in card and sits in one of the available PCIe x16 slots in the computer system.  The other available PCIe x16 slot can be populated for applications that require scalable network cards for even faster performance and bandwidth speeds in 10/25/50/100/200G.

Edge applications that require a variety of I/O connections to IoT sensors can also leverage Premio add-on modules for benefits. These add-in modules can be configured into the RCO-6000-CML-4NH-1E and support up to x8 additional LAN & PoE in wired RJ45/M12 connectors, x8 USB 3.1 gen 2 ports, x4 10GbE in RJ45 connectors, and even a 5G ready module for low-latency wireless connectivity. In terms of edge AI processing, the computing system supports up to x4 Hailo-8™ processors that provides up to 104 TOPS of performance and lower TDP for inference analysis and object detection in real time.

“As edge deployments continue to rely on performance-based hardware in the harshest remote and mobile settings, our engineers find creative ways to design the most transformative technologies for real-world applications,” Seetoo said. “With more than 30 years of hardware engineering and manufacturing of computing solutions, we enable our customers to ability to scale quickly with reliable, performance-based systems in the most innovative markets.”  

The RCO-6000-CML-4NH-1E computer uses an industrial-grade design to ensure better reliability in wider temperatures ( -25C to 70C), wider input voltages (9-48VDC), and even resistance to shock (50G) and vibrations (5GRMS).  These key environmental features allow the computer the ability to be reliable in environments that require better responses to situational data, low-latency data processing, and mission critical business insights based on actionable intelligence. 

To learn more about Premio’s AI Edge Inference Computers, please visit www.premioinc.com or contact our embedded computing experts at [email protected].

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