TerraMaster F2-425 Plus NAS review – Part 2: Configuration, benchmarks, and AI-enhanced media storage

I received the TerraMaster F2-425 Plus 3+2 Hybrid NAS for review last month, and after checking out the hardware in the first part of the review, I've finally had time to test the Intel N150 NAS. After installing two 4TB SATA drives and an M.2 NVMe SSD, I'll report my experience setting up the system with the TNAS Android app, before running some benchmarks, and testing features like photo backup with AI search capabilities. Hard drive installation I already had an old, but little-used, 4TB HGST SATA drive, and I bought a "new" 4TB SATA drive online for a pretty good deal (2979 THB or a little over $90 US). It turns out the HPE MB4000GVY2K drive I got was refurbished, having been manufactured in 2017. However, it's an enterprise-grade drive, and the TNAS app reports it has been used "only" for 2,517 hours, so I don't feel too bad

CNX Software - Embedded Systems News

DURABOOK Z14I-HG brings serious AI power to a rugged laptop

https://fed.brid.gy/r/https://nerds.xyz/2026/03/durabook-z14i-hg-ai-rugged-workstation/

RuView project leverages ESP32 nodes for WiFi-based presence detection, pose estimation, and breathing/heart rate monitoring

https://fed.brid.gy/r/https://www.cnx-software.com/2026/03/26/ruview-project-leverages-esp32-nodes-for-presence-detection-pose-estimation-and-breathing-heart-rate-monitoring/

RuView project leverages ESP32 nodes for WiFi-based presence detection, pose estimation, and breathing/heart rate monitoring

RuView is an open-source "WiFi DensePose" implementation leveraging multiple ESP32 nodes to turn WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection without relying on video cameras. WiFi DensePose is a sensing technique, first explored in academic research, that leverages WiFi signals to reconstruct human pose. RuView implements this technique in Rust or Python, and relies on your WiFi router and several ESP32 nodes to track body pose, detect breathing rate, and measure heart rate even through walls. As we'll discuss below, this project has its own controversy, as some claim it's fake. The solution relies on Channel State Information (CSI) disturbances caused by human movement to reconstruct body position, breathing rate, heart rate, and presence in real time using "physics-based signal processing and machine learning". That obviously means you need CSI-capable hardware, and not all consumer WiFi nodes implement it. The project description lists various

CNX Software - Embedded Systems News

LooperRobotics Insight 9 standalone spatial AI camera features D-Robotics RDK X5 SoC, supports ROS 2 (Crowdfunding)

https://fed.brid.gy/r/https://www.cnx-software.com/2026/03/25/looperrobotics-insight-9-standalone-spatial-ai-camera-features-d-robotics-rdk-x5-soc-supports-ros-2/

LooperRobotics Insight 9 standalone spatial AI camera features D-Robotics RDK X5 SoC, supports ROS 2 (Crowdfunding)

LooperRobotics Insight 9 is an autonomous plug-and-play spatial AI camera designed for embodied intelligence, quadruped robots, and dynamic mobile platforms. Compared to typical USB depth cameras like Intel RealSense D435i or Luxonis OAK-D, which rely on a host PC for processing, the Insight 9 integrates a D-Robotics RDK X5 octa-core Cortex-A55 processor with a 10 TOPS AI accelerator, allowing it to run Visual SLAM (V-SLAM) and depth mapping entirely on-device. The camera features a "Tri-Eye Perception Matrix," which includes an 8.4MP Sony Starvis IMX415 RGB sensor with an ultra-wide 188° field of view, and two SmartSens SG0132 global shutter sensors for stereoscopic depth. Encased in a passively cooled CNC aluminum chassis, it is also equipped with an automotive-grade Bosch BMI088 IMU capable of 24g high-G tracking, making it suitable for the heavy vibrations of legged locomotion. LooperRobotics Insight 9 specifications: SoC – D-Robotics RDK X5 octa-core Arm Cortex-A55 processor @ 1.5 GHz;

CNX Software - Embedded Systems News
Quixant IQON 3 and Air 3 AMD Ryzen Embedded 8000 systems target casino and arcade gaming

Quixant IQON 3 and IQON Air 3 are two new Ryzen Embedded 8000-based industrial systems designed specifically for casinos, sports betting, and arcade gaming machines. Built around AMD Ryzen 5 and Ryzen 7 PRO R8000 Series SoCs, they support four independent 4K displays and feature game-specific hardware, including 4MB of battery-free MRAM for instant state saving, eleven physical intrusion-detection monitors, dedicated LED controllers, and casino-standard serial interfaces such as ccTalk, JCM ID003, and SAS. Both systems are very similar in hardware specifications, but the IQON 3 is a passively cooled, fanless system, whereas the IQON Air 3 comes with a cooling fan enabling a higher TDP (ranging from 15W to 54W) for graphics-intensive workloads. Quixant IQON 3 and IQON Air 3 specifications: SoC – AMD Ryzen 5 or 7 PRO R8000 Embedded Series SoCs with Zen 4 cores, AMD Radeon 7x0M graphics (RDNA 3), and AMD XDNA NPU System Memory

CNX Software - Embedded Systems News
Optimising edge AI hardware for industrial IoT deployments

Industrial IoT deployments demand edge AI hardware capable of processing complex data on the factory floor.

Internet of Things News

Hugging Face’s Reachy Mini is an open-source AI robot for your computer or Raspberry Pi CM4

https://fed.brid.gy/r/https://www.cnx-software.com/2026/03/24/hugging-face-reachy-mini-open-source-ai-robot-computer-raspberry-pi-cm4/

Hugging Face’s Reachy Mini is an open-source AI robot for your computer or Raspberry Pi CM4

Better known for its artificial intelligence software solutions, Hugging Face unveiled the Reachy Mini open-source desktop robot last year. It is designed to deploy AI applications that interface with the physical world. The robot features a camera, four microphones, and a speaker, and can move its 6 DoF (degrees of freedom) head, rotate its body, or wave its antennas thanks to nine servo motors. Two versions are available: the Reachy Mini Lite designed for computers running Mac, Linux, and Windows, and the Reachy Mini Wireless autonomous robot, powered by a Raspberry Pi CM4, adding WiFi and Bluetooth connectivity, an accelerometer, and battery support. Both models share most of the same specifications: Reachy Mini's SDK can be found on GitHub. It's based on Python, but also supports JavaScript and Web apps, and can integrate with LLMs to easily build apps and publish them to Hugging Face. The SDK also features several

CNX Software - Embedded Systems News

[오픈소스 협력 강화|ArmSoM Sige5, 2026 임베디드 월드에서 Collabora와 함께 선보여

ArmSoM의 Sige5 개발보드가 2026 Embedded World에서 Collabora와 협력하여 전시되었으며, 메인라인 Linux 지원 기능을 시연했습니다. 양사는 향후 협력을 확대할 계획이며, Sige5는 6TOPS NPU를 탑재한 임베디드 및 엣지AI 최적화 제품입니다.

https://news.hada.io/topic?id=27805

#embeddedworld #opensource #linux #edgeai #collaboration

오픈소스 협력 강화|ArmSoM Sige5, 2026 임베디드 월드에서 Collabora와 함께 선보여

<p>2026년 3월 10~12일 독일 뉘른베르크에서 개최된 Embedded World 2026에서 ArmSoM의 Sige5(RK3576) 개발보드가 Collabora 부스에 전시되었으며,...

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Flying from Albuquerque right to the #EdgeAI conference. I’m missing the first day…better late than never!
CIX ClawCore Armv9.2 CPU family targets OpenClaw deployments

OpenClaw was just introduced a few months ago, but we've already seen several low-footprint implementations, and some companies even ship mini PCs preloaded with OpenClaw. But today, I was just informed that CIX had gone further, and introduced the ClawCore Armv9.2 CPU family specifically designed/optimized for OpenClaw. The family will be comprised of three main SKUs: ClawCore-P (勁螯芯  "Powerful Claw") - High-performance model with 12-core CPU @ 3.2GHz, Immortalis-G720 GPU, 45 TOPS AI compute, and support for up to 64GB LPDDR5 RAM. Aimed at high-parallelism, large-capacity scenarios. Shipping starts now in March 2026. ClawCore-A (智螯芯  "AI/Smart Claw") - Octa-core CPU @ 3.0GHz, 80 TOPS AI compute (expandable to 200 TOPS via PCIe AI card), up to 64GB LPDDR5. It's designed for 24/7 use, supports full-chain ECC, hardware security (encryption/key management), and enables up to 50% reduction in model token costs via local inference. In practise, 80 to 90% of requests

CNX Software - Embedded Systems News