Intrinsyc Unveils Open-Q 845 µSOM and Snapdragon 845 Mini-ITX Development Kit

Open-Q 845 µSOM Development Kit

Intrinsyc introduced the first Qualcomm Snapdragon 845 hardware development platform last year with its Open-Q 845 HDK designed for OEMs and device makers. But the company has now just announced a solution for embedded systems and Internet of Things (IoT) products with Open-Q 845 micro system-on-module (µSOM) powered by the Snapdragon 845 octa-core processor, as well as a complete development kit featuring the module and a Mini-ITX baseboard. Open-Q845 µSOM Specifications: SoC – Qualcomm Snapdragon SDA845 octa-core processor with 4x Kryo 385 Gold cores @ 2.649GHz + 4x Kryo 385 Silver low-power cores @ 1.766GHz cores, Hexagon  685 DSP, Adreno 630 GPU with OpenGL ES 3.2 + AEP (Android Extension Pack),  DX next, Vulkan 2, OpenCL 2.0 full profile System Memory – 4GB or 6GB dual-channel high-speed LPDDR4X SDRAM at 1866MHz Storage – 32GB or 64GB UFS Flash Storage Connectivity Wi-Fi 5 802.11a/b/g/n/ac 2.4/5Ghz 2×2 MU-MIMO (WCN3990) with 5 GHz external PA & U.FL antenna connector Bluetooth 5.x Audio & …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Tiny USB WiFi Camera Supports Motion and AI Human Detection

USB WiFi Camera

When I first saw U21 HD camera it reminded me of SOOCOO G1 is action camera with a flexible stick, since the camera also comes with a flexible hose which allows you to orient it as you please. But it’s a different bear, as U21 is a surveillance camera powered over USB and featuring WiFi connectivity. I can’t see any motion detection, so it may have some dose of “AI” since it claims to support motion and human detection so you only get relevant alerts. It is currently sold (pre-orders) on Banggood for $33.65 including shipping with order starting to be processed on October 30th. U21 USB WIFI camera key features and specifications: MCU / WiSoC – No information (yet) Storage – MicroSD card slot up to 128GB for up to one month of recording (8GB = 2 days); Cloud storage via third party (paid) Camera – 14mm lens, HD resolution Alerts – Motion detection, AI human detection (provided and …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Atomic Pi x86 SBC Meets Intel Neural Compute Stick 2 in $99 Neural Computing DevKit (Crowdfunding)

Atomic Pi Neural Computing Development Kit

IoT Team launched the $34 Atomic Pi SBC powered by an Intel Atom x5-Z8350 processor via a Kickstarter campaign last December. At the time, it only ships to the US, and looked too good to be true. But the thing is real coming from a failed robotics project, and the low-cost x86 board went back for sale via Amazon and other channels with worldwide availability last spring. The price has even gone a bit lower as you’ll find it for $32.95 on Amazon. Note that it requires some technical skills to get started and with 16GB eMMC flash it only supports Liux distributions such as Ubuntu 18.04, and installing Windows 10 is possible, but you’ll be seriously limited. Atomic Pi is back in the news, as IoT Team has now launched another Kickstarter campaign for the board, except it’s not sold standalone, but instead as part of a $99 neural computing development kit that combines Atomic Pi SBC with 2GB …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

AAEON BOXER-8310AI Rugged Fanless Mini PC Combines Apollo Lake Processor & Myriad X VPU for AI Edge Applications

AAEON BOXER-8310AI rugged fanless mini PC

We’ve covered several of AAEON rugged mini PCs part of BOXER-8100 family powered by an NVIDIA Tegra X2 processor and targetting AI Edge applications. The company has now introduced three new AI embedded computers for the same AI edge applications but using Intel processors together with Intel/Movidius Myriad X VPU (Vision Processing Unit) for AI acceleration. The three models are BOXER-8310AI, BOXER-8320AI, and the upcoming BOXER-8330AI based on respectively Intel Celeron/Pentium Apollo Lake processor, Intel Core i3 7th gen processor, and an Intel Core i3/77 or Xeon processor. I’ll focus on the Apollo Lake model in this post to introduce AAEON BOXER-8300AI family of rugged mini PCs. BOXER-8310AI specifications: SoC (one or the other) Intel Pentium N4200 quad-core Apollo Lake processor Intel® Celeron N3350 dual-core Apollo Lake processor System Memory –  1x DDR3L SODIMM slot supporting up to 8GB RAM @ 1867 MHz Storage Device – mSATA socket AI Module – AI Core X with Intel Movidius Myriad X VPU …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Samsung Exynos 9611 SoC Targets AI Powered Smartphones with a Pro-grade Camera

Samsung Exynos 9611

Silicon vendors are all launching new mobile processors with “advanced AI capabilities”, and Samsung has just announced another one of those processors with Exynos 9611 that upgrades on Exynos 9610 introduced last year. The company claims “the Exynos 9611 mobile processor brings intelligent performance for the next-generation experiences from artificial intelligent applications to pro-grade camera”, but I’m actually unable to find any differences between the two processors, except the Cortex-A53 cluster’s  maximum frequency has been boosted to 1.7 GHz instead of 1.6 GHz, and possibly support for 64MP single cameras. Exynos 9611 key features and specifications: CPU – Up to 2.3GHz quad-core Cortex-A73 cluster and up to 1.7GHz quad-core Cortex-A53 cluster. GPU – Mali-G72 MP3 Memory – LPDDR4x Storage – UFS 2.1, eMMC 5.1 Display – Up to WQXGA (2560×1600) Camera – 24MP single camera (up to 64MP),  16+16MP dual camera Video – 4K UHD 120fps encoding and decoding with HEVC(H.265) and H.264, and decoding with VP9 LTE Modem – …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

$118 BeagleBone-AI SBC is Made for AI Edge Applications

BeagleBone-AI

The BeagleBoard.org Foundation introduced BeagleBone-AI SBC at Embedded World 2019 last February. The board is specifically designed for artificial intelligence workloads at the edge thanks to Texas Instruments AM5729 dual-core Cortex-A15 processor that embeds a dual-core C66x DSP, and 4 EVE (Embedded Vision Engine) cores. The BeagleBone Black compatible board was not available at the time,  but the Foundation has now formally launched the board, and you can buy BeagleBone-AI for $118 and up with heatsink and antenna on sites such as Mouser, OKdo, or Newark. BeagleBone-AI full specifications have now been published: SoC – TI Sitara AM5729 with Dual-core Cortex-A15 processor @ 1.5 GHz 2x dual-core PRUs 2x Cortex-M4 real-time cores dual core C66x VLIW DSP 4x EVEs 2.5MB of on-chip L3 RAM VA-HD subsystem with support for 4K at 15fps H.264 encode/decode and other codecs at 1080p60 Vivante GC320 2D graphics accelerator Dual-Core PowerVR SGX544 3D GPU System Memory – 1GB RAM Storage – 16GB on-board eMMC flash …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Camect is an Artificial Intelligence based Universal Camera Hub (Crowdfunding)

Camect Smart Camera Hub

Every day people are getting more concerned about the security of their homes, families, offices, properties, and other related belongings getting more people investing in products and services that helps boost that security. Although we have several products that can be used for home security, Cameras are arguably the most common and important one. Cameras are one the most used home security solutions, and they come in various variants. One of the challenges that come with cameras is that a camera platform from company A won’t mostly work with company’s B platform, thus constraining the user to one single expensive platform or be tempted to juggle around different platforms. Camect is a Camera Hub powered by Artifical Intelligence that intends to address this problem. Camect can aggregate video feeds from any security camera on your home network regardless of the brand.  Camect I believe is the OpenHAB for cameras. A smart camera hub for uniting different cameras from most …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Raspberry Pi CM3+ based EagleEye Smart Camera Works with OpenCV and LabVIEW NI Vision

Raspberry Pi CM3 Industrial Smart Camera

We previously covered Q-Wave Systems’ Melon S3 board combining a Xilinx Spartan 3E FPGA with ESP8266, but the Thai company is back is a completely different product: EagleEye Smart Camera. The board is powered by Raspberry Pi Compute Module 3+ (CM3+) with 16GB or 32GB flash, and equipped with a 5 MP camera for machine vision and robotics applications.  There are two version of the board Uno and Industrial with the latter adding 24V digital input and outputs, circuit protections and support for industrial temperature range. EagleEye smart camera key features & specifications: SoM – Raspberry Pi CM3+ with Broadcom BCM2837B0 quad core cortex-A53 processor, 1 GB RAM, and 16GB or 32 GB flash Camera – 5 MP OV5647 image sensor,  CS/M12 lens holder + 4mm CS lens Video Output – mini HDMI port Networking – 10/100M Ethernet USB – 1x USB 2.0 host port up to 1.2A Expansion Uno – 4x 3.3V digital input; 4x 3.3V digital output; both …

Support CNX Software – Donate via PayPal or become a Patron on Patreon