AAEON BOXER-8224AI is a thin and lightweight AI edge embedded system solution based on NVIDIA Jetson Nano system-on-module and designed for drones, or other space-constrained applications such as robotics. AAEON BOXER products are usually Embedded Box PCs with an enclosure, but the BOXER-8224AI is quite different as it’s a compact and 22mm thin board with MIPI CSI interfaces designed to add computer vision capability to unmanned areal vehicles (UAV), as well as several wafers for dual GbE, USB, and other I/Os. BOXER-8224AI specifications: AI Accelerator – NVIDIA Jetson Nano CPU – Arm Cortex-A57 quad-core processor System Memory – 4GB LPDDR4 Storage Device – 16GB eMMC 5.1 flash Dimensions – 70 x 45 mm Storage – microSD slot Display Interface – 1x Mini HDMI 2.0 port Camera interface – 2x MIPI CSI connectors Networking 2x Gigabit Ethernet via wafer connector (1x NVIDIA, 1x Intel i210) Optional WiFi, Bluetooth, and/or cellular connectivity […]
Sony IMX500-based smart camera works with AITRIOS software
Raspberry Pi recently received a strategic investment from Sony (Semiconductor Solutions Corporation) in order to provide a development platform for the company’s edge AI devices leveraging the AITRIOS platform. We don’t have many details about the upcoming Raspberry Pi / Sony device, so instead, I decided to look into the AITRIOS platform, and currently, there’s a single hardware platform, LUCID Vision Labs SENSAiZ SZP123S-001 smart camera based on Sony IMX500 intelligent vision sensor, designed to work with Sony AITRIOS software. LUCID SENSAiZ Smart camera SENSAiZ SZP123S-001 specifications: Imaging sensor – 12.33MP Sony IMX500 progressive scan CMOS sensor with rolling shutter, built-in DSP and dedicated on-chip SRAM to enable high-speed edge AI processing. Focal Length – 4.35 mm Camera Sensor Format – 1/2.3″ Pixels (H x V) – 4,056 x 3,040 Pixel Size, H x V – 1.55 x 1.55 μm Networking – 10/100M RJ45 port Power Supply – PoE+ via […]
IP67-rated CM4 AI camera uses Raspberry Pi Compute Module 4 for computer vision applications
EDATEC ED-AIC2020 is an IP67-rated, Raspberry Pi CM4-based industrial AI camera equipped with a fixed or liquid lens and LED illumination that leverages the Raspberry Pi Compute Module 4 to run computer vision applications using OpenCV, Python, And Qt. We’ve previously written about Raspberry Pi Compute Module-based smart cameras such as the Q-Wave Systems EagleEye camera (CM3+) working with OpenCV and LabVIEW NI Vision and the StereoPi v2 (CM4) with stereo vision. But the EDATEC ED-AIC2000 is the first ready-to-deploy Raspberry Pi CM4 AI camera we’ve covered so far. EDATEC “CM4 AI camera” (ED-AIC2020) specifications: SoM – Raspberry Pi Compute Module 4 up to 8GB RAM, up to 32GB eMMC flash Camera 2.0MP global shutter or 5.0MP rolling shutter Acquisition rate – Up to 70 FPS Aiming point – Red cross laser Built-in LED illumination (optional) Scanning field Electronic liquid lens Fixed focal length lens Networking Gigabit Ethernet M12 port Communication protocols – Ethernet/IP, PROFINET, Modbus […]
SOPHON BM1684/BM1684X Edge AI computer delivers up to 32 TOPS, decodes up to 32 Full HD videos simultaneously
Firefly EC-A1684JD4 FD and EC-A1684XJD4 FD are nearly identical Edge AI embedded computers based on respectively SOPHON BM1684 and BM1684X Arm AI SoC delivering up to 32 TOPS of AI inference, and capable of decoding up to 32 H.265/H.264 Full HD videos simultaneously for video analytics applications. The BM1684(X) SoCs are equipped with eight Cortex-A53 cores clocked at 2.3 GHz to run Linux, and the systems come with up to 16GB RAM, 128GB flash, two Gigabit Ethernet ports to receive the video streams, one HDMI output up to 1080p30 for monitoring, as well as RS232 and RS485 DB9 connectors, and a few USB ports. Firefly EC-A1684JD4 FD and EC-A1684XJD4 FD specifications: SoC – SOPHGO SOPHON BM1684/BM1684X CPU – Octa-core Arm Cortex-A53 processor @ up to 2.3GHz TPU BM1684 64 NPU arithmetic units with each NPU containing 16 EU arithmetic units, or 1,024 EU in total Up to 17.6 TOPS (INT8), […]
conga-STDA4 SMARC 2.1 module features TI TDA4VM/DRA829J Jacinto 7 processor
congatec conga-STDA4 is a SMARC Computer-on-Module (CoM) based on Texas Instruments TDA4VM or DRA829J Jacinto 7 processor with two Cortex-A72 cores, six real-time Cortex-R5 cores for functional safety, accelerated vision and AI processing capabilities, and plenty of interfaces. The first Texas Instruments-powered CoM from the company is designed for industrial mobile machinery requiring near-field analytics, such as automated guided vehicles and autonomous mobile robots, construction and agricultural machinery, as well as any industrial or medical solutions requiring energy-efficient computer vision at the edge. conga-STDA4 specifications: SoC – Texas Instruments Jacinto 7 TDA4VM/DRA829J with Dual-core Arm Cortex-A72 up to 2.0 GHz 6x Arm Cortex-R5F cores @ 1.0 GHz up to 8 MB of on-chip L3 RAM 1x C7x DSP up to 80 GFLOPs 2x C66 DSPs up to 40 GFLOPs Up to 8 TOPS MMA AI accelerator PowerVR Rogue 8XE GE8430 3D GPU with support for OpenGL ES 3.1, OpenVX, OpenCL […]
MIPI CSI camera works with Intel Atom x7000, Processor, and Core i3 Alder Lake-N processors
Most Intel processors do not come with a MIPI CSI camera, but some Alder Lake-N processors do, and Leopard Imaging has designed the LI-ADL-ADP-IMX415-MIPI-081H MIPI CSI camera module that is compatible with the Intel ADL-N CRB (Alder Lake-N Customer Reference Board) and custom Alder Lake-N boards equipped with a compatible MIPI CSI connector. The 13MP camera supports resolutions up to 3864 x 2176 and works with boards and embedded systems based on Intel Atom processors x7000E Series, Intel Core i3-N processors, and Intel Processors N-Series processors. LI-ADL-ADP-IMX415-MIPI-081H specifications: Sony IMX415 CMOS image sensor Diagonal – 6.43 mm (Type 1/2.8) Active Pixels – 3864 (H) x 2176 (V) Pixel Size: 1.45 x 1.45 μm Optical Format: 1/2.8″ Effective Focal Length – 4.063 mm Aperture, F/#2.29 ± 5% IR Filter – 650 nm IR cut filter Field of View (FOV) – 81.7˚ horizontal, 44.7˚ vertical; 95.1˚ diagonal Lens Mount – M12 x […]
$499 NVIDIA Jetson Orin Nano Developer Kit delivers up to 80x Jetson Nano Devkit performance
NVIDIA Jetson Orin Nano Developer Kit is an upgrade to the popular Jetson Nano Developer Kit that delivers 80 times the performance, up to 50 times the performance per watt, and gives the developers the ability to design entry-level AI-powered robots, smart drones, intelligent vision systems, and more. The Jetson Orin Nano has a similar form factor as the original Jetson Nano, but is fitted with a Jetson Orin Nano 8GB module with up to 40 TOPS AI performance, and is equipped with a DisplayPort video output, USB 3.2 Gen 2 ports, two M.2 Key M sockets for SSDs, Gigabit Ethernet, a pre-installed Wi-Fi module, and connectors for cameras. NVIDIA Jetson Orin Nano Developer Kit specifications (compared to Jetson Nano Developer Kit-B01) The new developer kit is supported by the Ubuntu 20.04-based NVIDIA JetPack 5.1.1 SDK, as well as application-specific frameworks such as NVIDIA Isaac ROS and DeepStream, which are […]
Texas Instruments unveils AM62A, AM68A and AM69A Arm Cortex Vision processors and devkits
Texas Instruments AM62A, AM8, and AM69A Arm Cortex-A53 or Cortex-A72 Vision processors come with 2 to 8 CPU cores and deep learning accelerators delivering from 1 TOPS to 32 TOPS for low-power vision and artificial intelligence (AI) processing in applications such as video doorbells, machine vision, and autonomous mobile robots. Three families and a total of 6 parts are available: AM62A3, AM62A3-Q1, AM62A7, and AM62A7-Q1 single to quad-core Cortex-A53 processors support one to two cameras at less than 2W in applications such as video doorbells and smart retail systems. Equipped with a 1TOPS vision processor, the AM62A3 is the cheapest model of the family going for US$12 in 1,000-unit quantities. AM68A dual-core Cortex-A72 processor can handle one to eight cameras in applications like machine vision, with up to 8 TOPS of AI processing for video analytics. AM69A octa-core Cortex-A72 SoC supports up to 12 cameras and achieves up to 32 […]