FPGA powered Corazon-AI gateway supports up to 8 IP cameras for video analytics

corazon-ai

Earlier this year, we covered some video analytics solutions based on AAEON UP Xtreme Edge embedded computer combining an Intel Whiskey Lake processor with Intel Movidius Myriad X AI accelerator modules, as well as video management & analytics software solutions from Milestones & SAIMOS, or aotu.ai BrainFrame. iWave Systems has now introduced a similar solution with Corazon-AI gateway capable of handling up to 8 IP cameras in real-time,  but instead of relying on AI accelerators, the company leverages Xilinx Zynq Ultrascale+ Arm Cortex-A53/R5 FPGA MPSoC for AI inference. Corazon-AI gateway specifications: SoC – Xilinz Zynq Ultrascale+ ZU2, ZU3, ZU4 or ZU5 MPSoC Processing System (PS) Quad/Dual Arm Cortex-A53 @ 1.5GHz, dual Cortex-R5 @ 600MHz Arm Mali-400MP2 GPU @ 677MHz H.264/H.265 Video Encoder/Decoder Programming Logic (PL) Up to 256K Logic cells PL GTH Transceivers x 4 @ 12.5 Gbps System Memory 64bit, 2GB DDR4 with ECC for PS (upgradable) 32bit, 1GB DDR4 for PL (upgradable) Storage – 8GB eMMC Flash (upgradable), […]

Learn more about Hailo-8 AI accelerator and understanding AI benchmarks

Hailo 8 Development Kit

Last week we wrote about Hailo-8 M.2 card delivering up to 26 TOPS of AI performance, and comparing well against Google Edge TPU and Intel Movidius Myriad X  both in terms of footprint, performance, and efficiency. I’ve since then had a conference call with Liran Bar, VP of Business Development for Hailo, where we had time to discuss more about Hailo’s AI solutions, and how to interpret & understand AI benchmarks that may be misleading in many instances. Hailo-8 Architecture In the first post, we noted the chip managed to get the extra performance and efficiency thanks to a “proprietary novel structure-driven Data Flow architecture instead of the usual Von Neumann architecture”. But that’s a bit abstract, so Liran told me one of the key reasons for the performance improvement is that RAM is self-contained without the need for external DRAM like other solutions. This decreases latency a lot and reduces power consumption. Internally, the Hailo-8 chip is comprised of […]

Vizy AI camera runs Tensorflow, OpenCV, PyTorch on Raspberry Pi 4 (Crowdfunding)

Vizy AI Camera

We previously covered Charmed Labs PIXY2 computer vision camera based on an NXP LPC4330 microcontrollers that worked with Arduino, Raspberry Pi, and other development boards. The company is now back with a fully integrated more powerful solution with Vizy AI camera featuring a Raspberry Pi 4 SBC with up to 8GB RAM. Vizy AI camera key features and specifications: SBC – Raspberry Pi 4 with Broadcom BCM2711 quad-core Arm Cortex-72 processor, up to 8 GB RAM Camera – High-resolution camera based on Sony iMX477 12.3 MP sensor that can capture at over 300 frames/second and support both daytime and nighttime viewing; Both M12 and C/CS lenses are supported Video Output – 2x micro HDMI ports Audio – Analog stereo audio port Networking – Gigabit Ethernet, dual-band WiFi 5, and Bluetooth 5.0 USB – 2x USB 3.0 ports, 2x USB 2.0, 1x USB Type-C port from Raspberry Pi 4 (But not sure it’s actually used) Expansion – 8-pin terminal block for […]

VIA Pixetto Hi3518E V300 HD Camera Board Targets Artificial Intelligence and Machine Learning Education

VIA Pixetto HD Camera Board AI Education

VIA Technologies has launched the VIA Pixetto vision sensor aims to teach artificial intelligence (AI) and machine learning (ML) to students aged twelve and above. The Linux board features an Hisilicon Hi3518E V300 Cortex-A7 HD camera SoC combined with 64MB RAM, 128MB SPI flash, a MicroSD slot, as well as GalaxyCore GC2053 2M CMOS sensor offering 1920 x 1080 resolution and a 130° field of view. VIA Pixetto hardware specifications: SoC – Hisilicon Hi3518E V300 Cortex-A7 HD camera SoC @ 900 MHz with H.264, H.265, MJPEG/JPEG encoder System Memory – 64MB DDR, MicroSD card slot Storage – 128MB SPI flash Camera – GalaxyCore GC2053 2M CMOS sensor with 1920 x 1080 resolution,  130° FoV Audio – Microphone USB – 1x Micro USB 2.0 port Connectivity – WiFi 4 via Hisilicon Hi1131 low-power Wi-Fi chip  and ceramic antenna Expansion – Grove connector Misc – 3x LEDs (Power, OS boot, active status), 1x reset button Power Supply 5V/500mA via Micro USB port […]

QuickFeather Board is Powered by QuickLogic EOS S3 Cortex-M4F MCU with embedded FPGA (Crowdfunding)

QuickLogic EOS S3 Development Board

Yesterday, I wrote about what I felt what a pretty unique board: Evo M51 board following Adafruit Feather form factor, and equipped with an Atmel SAMD51 Cortex-M4F MCU and an Intel MAX 10 FPGA. But less than 24 hours later, I’ve come across another Adafruit Feather-sized Cortex-M4F board with FPGA fabric. But instead of using a two-chip solution, QuickLogic QuickFeather board leverages the company’s EOS S3 SoC with a low-power Cortex-M4F core and embedded FPGA fabric. QuickFeather board QuickFeather specifications: SoC – QuickLogic EOS S3 with Arm Cortex-M4F Microcontroller @ up to 80 MHz and 512 Kb SRAM, plus an embedded FPGA (eFPGA) with 2400 effective logic cells and 64Kb RAM Storage – 16Mbit SPI NOR flash USB – Micro USB  port with data signals tied to eFPGA programmable logic Sensors – Accelerometer, pressure sensor, built-in PDM microphone Expansion I/Os – Breadboard-compatible 0.1″ (2.54 mm) pitch headers including 20 Feather-defined GPIO + 13 additional GPIO with UART, I2C, I2S and […]

Boardcon RK1808 SBC Targets Smart Audio & Computer Vision Applications

RK1808 SBC

Rockchip RK1808 neural network processing unit was initially an IP Block inside RK3399Pro, but the company eventually launched RK1808 Cortex-A35 processor as a standalone solution now providing up to 3.0 TOPS for AI inferencing in modules, USB sticks, and development kits. Boardcon offers another option with EM1808, a Rockchip RK1808 SBC equipped with the processor. The board should be suitable for two main types of AI applications, namely smart audio applications thanks to four audio ports, speaker header, & an onboard 4-mic array, and computer vision with MIPI CSI & DSI interfaces. Boardcon EM1808 board is comprised of a baseboard and CPU module with the following overall specifications: SoC – Rockchip RK1808 dual Cortex-A35 processor up to 1.6GHz with 3.0 TOPS (for INT8) NPU, VPU supporting H.264 1080p60 decode, 1080p30 encode System Memory- 2GB LPDDR3 Storage – 8GB eMMC flash, MicroSD slot, M.2 NVMe SSD interface Display I/F – 26-pin MIPI DSI header Camera I/F – 26-pin MIPI CSI header […]

XMOS launches Xcore.AI, a scalable AI processor for the Edge

XMOS, known for its high-performance voice interfaces, is joining the AIoT bandwagon with the announcement of the Xcore.ai, a flexible and economical processor delivering high-performance AI, DSP, control, and I/O’s in a single device. IoT and AI have been one of the most trending topics and fields in the last decade. Both areas have seen large innovations in between them. Deep neural networks have become better, IoT deployment cost has also been greatly reduced, and most importantly, they both have a significant impact on multiple industries. An interesting trend recently is the emergence of applications merging AI and IoT together to form so-called AIoT applications. IoT will be the digital nervous system, while AI will become the brain that makes all the critical decisions which will control the whole system. AIoT has led to the development and deployment of what we call AI processors or AI modules that can be deployed to the edge for high-performance Edge computing applications. An […]

Arm Introduces Cortex-M55 MCU Core, Arm Ethos-U55 microNPU for Cortex-M Microcontrollers

Arm Cortex M55

Artificial Intelligence and the Internet of Things often go hand in hand with AIoT being a new buzz word that came up last year or so. But for AIoT to scale we need ultra-low-cost, low-power solutions capable of doing inference at the sensor node level, and this is only possible with microcontrollers. To achieve this goal, Arm has just unveiled the Arm Cortex-M55 microcontroller core optimized for artificial intelligence workloads that delivers up to a 15x uplift in ML performance and a 5x uplift in DSP performance with greater efficiency, as well as Ethos-U55 microNPU designed for Cortex-M microcontrollers that need even more AI performance (up to 480 times faster), while consuming as little power as possible. Arm Cortex-M55 Key features and specifications: Architecture – Armv8.1-M Bus interface – AMBA 5 AXI5 64-bit master (compatible to AXI4 IPs) Pipeline – 4-stage (for main integer pipeline) Security – Arm TrustZone technology (optional) DSP extension – 32-bit DSP/SIMD extension M-Profile Vector Extension […]