Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Gumstix AutoBSP Automatically Generates Device Tree Files for Hardware Designed with Geppetto

Gumstix AutoBSP Automatically Generates Device Tree Files for Hardware Designed with Geppetto

Gumstix launched Geppetto Design-To-Order (D2O) system back in 2013, and at the time you could design complete baseboard for their Overo CoMs right in your Chrome or Firefox web browser, and once complete, order the board from the website. The system is meant to save you time, and “design” here does not mean drawing schematics, and laying out PCBs, but instead selecting board size, and adding ports as needed. Since then, the company has added support for more modules, and you can now easily build you own baseboard for Raspberry Pi Compute Module, Technexion PICO-IMX6 module, Toradex Colibri SoM, 96Boards Mezzanine, and they even have Beaglebone Black and 96Board CE or IoT connectors, among others. Support for Qualcomm DragonBoard 410c, Atmel (Arduino) , and STMicro platforms is also being worked on. Their latest feature – AutoBSP – automatically generates device tree files for your custom boards, so you can simply copy it to your favorite image and get started as …

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Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Getting Started with OpenCV for Tegra on NVIDIA Tegra K1, CPU vs GPU Computer Vision Comparison

Getting Started with OpenCV for Tegra on NVIDIA Tegra K1, CPU vs GPU Computer Vision Comparison

This is a guest post by Leonardo Graboski Veiga, Field Application Engineer, Toradex Brasil Introduction Computer vision (CV) is everywhere – from cars to surveillance and production lines, the need for efficient, low power consumption yet powerful embedded systems is nowadays one of the bleeding edge scenarios of technology development. Since this is a very computationally intensive task, running computer vision algorithms in an embedded system CPU might not be enough for some applications. Developers and scientists have noticed that the use of dedicated hardware, such as co-processors and GPUs – the latter traditionally employed for graphics rendering – can greatly improve CV algorithms performance. In the embedded scenario, things usually are not as simple as they look. Embedded GPUs tend to be different from desktop GPUs, thus requiring many workarounds to get extra performance from them. A good example of a drawback from embedded GPUs is that they are hardly supported by OpenCV – the de facto standard libraries …

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Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on Christmann RECS|Box Atlas Quad Apalis Microserver Evaluation Kit Supports Four Toradex Apalis SoM

Christmann RECS|Box Atlas Quad Apalis Microserver Evaluation Kit Supports Four Toradex Apalis SoM

System-on-modules are normally used in low volume embedded systems, but they can also be used in microservers, for example to upgrade capacity as needed. Christmann informationstechnik + medien GmbH has developed a microserver evaluation kit taking up to 4 Toradex Apalis SoMs for example based on Nvidia Tegra K1 processor, and also offers full rack systems with up to 72 modules. Christmann RECS|Box Atlas Quad Apalis specifications: Modules – 4x Slots for Apalis SoM Connectivity – 1 GBit/s Compute Ethernet, 1 GBit/s Management Ethernet Video Output – 1x HDMI USB – 3x USB host ports, 1x micro USB port Misc – 5 Status LEDs for USB, communication, and serial console, 4x fan connectors, KWM switch, 5x temperature sensors, 6x current sensors, 1x voltage monitor, fan speed monitoring Power Supply – 12V via a 4-pin jack Dimensions – 300 x 145 x 68 mm The evaluation kit includes an Atlas board with an  acrylic base plate and 2 fans, a power …

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Posted on by Jean-Luc Aufranc (CNXSoft) - 8 Comments on A Look at Three Options to Develop Real-Time Linux Systems on Application Processors – HMP, Real-Time Linux and Xenomai

A Look at Three Options to Develop Real-Time Linux Systems on Application Processors – HMP, Real-Time Linux and Xenomai

This is a guest post by written by Guilherme Fernandes, Raul Muñoz, Leonardo Veiga, Brandon Shibley, all working for Toradex. Introduction Application processor usage continues to broaden. System-on-Chips, usually powered by ARM Cortex-A cores, are taking over several spaces where small ARM Cortex-M, and other microcontroller devices, have traditionally dominated. This trend is driven by several facts, such as: The strong requirements for connectivity, often related to IoT and not only from a hardware point of view, but also related to software, protocols and security The need for highly interactive interfaces such as multi-touch, high resolution screens and elaborate graphical user interfaces; The decreasing price of SoCs, as consequence of its volume gain and new production capabilities. Typical cases exemplifying the statement above are the customers we see every day starting a product redesign upgrading from a microcontroller to a microprocessor. This move offers new challenges as the design is more complicated and the operating system abstraction layer is much …

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Posted on by Jean-Luc Aufranc (CNXSoft) - 9 Comments on Allwinner A64 based Pine A64 and Banana Pi M64 Boards Can Now Run Windows 10 IoT Core

Allwinner A64 based Pine A64 and Banana Pi M64 Boards Can Now Run Windows 10 IoT Core

Windows IoT is a version of Windows 10 that’s optimized for smaller devices with or without a display, and was fist released for Raspberry Pi 2 and MinnowBoard MAX. Since then a few more boards are now officially supported, including DragonBoard 410c, and Raspberry Pi 3. But there’s been some recent developments as two Allwinner A64 64-bit ARM boards are now supported according to two wiki entries (here and there) explaining how to run a simple Csharp sample on Windows 10 IoT Core on either Banana Pi M64 or Pine A64 boards. The guide shows how to configure Azure IoT Hub, register the IoT device, and build and deploy Azure IoT SDK on the board. But basically if all you want to is to run Windows IoT core on either board, you’ll need to download either: Windows 10 IoT Core for Banana Pi M64: Windows10IoT_BPI-M64.ffu (Link removed as Microsoft does not allow redistribution of ffu for now, despite the link …

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Posted on by Jean-Luc Aufranc (CNXSoft) - 8 Comments on Setting a VoIP SIP user agent with Embedded Linux

Setting a VoIP SIP user agent with Embedded Linux

This is a guest post by Leonardo Graboski Veiga, working for Toradex. Introduction This article’s main goals are: to cross-compile the PJSIP libraries and the PJSUA API reference implementation; deploy it to the target system; give an overview about the SIP protocol; and explore the reference implementation features, regarding audio only. For this purpose, a Computer on Module (CoM) from Toradex was chosen in the following configuration: Colibri iMX6DL* + Colibri Evaluation Board. The evaluation board and CoM are displayed in Figures 1 and 2, respectively.   VOIP or Voice over IP, is a term designed to refer to a set of methods and technologies targeted for the implementation of telephony services over the Internet. For the purpose of this article, the scope will be limited to the use of a reference implementation built upon the SIP communication handling protocol by means of the PJSIP libraries and PJSUA2 API. If you wish to gather more information about VOIP itself, there …

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Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Isurki IRIS Industrial Embedded Computer Takes Nvidia or NXP System-on-Modules

Isurki IRIS Industrial Embedded Computer Takes Nvidia or NXP System-on-Modules

Isurki is a Spanish company providing electronics & IT services to hydraulic resources management companies, and one of their products is IRIS industrial embedded computer based on Toradex Iris carrier board that supports Toradex Colibri ARM system-on-modules based on either Nvidia Tegra 2/3 or NXP Vybrid VF50/VF61 processors. Main board connectors and features: Video – DVI-I LCD Interface – RGB / LVDS with 4/5 resistive touch interface Audio – Line-In, line-Out, Mic-In Storage – Micro SD Connectivity – 10/100M Ethernet USB – 1x USB host, 1x USB OTG Expansion – 24 GPIOs, 3x UART ports Misc – 1x IrDA, RTC Power Supply – 6 to 27V DC, reverse polarity and short circuit protected Then you can choose among several variations of ARM based Colibri system-on-modules: Colibri T20 Nvidia Tegra 2 dual core Cortex A9 processor with 256 to 512MB DDR3, and 512MB to 1GB flash Dual independent displays 2D/3D hardware acceleration and hardware video decoding. Power consumption – 1.1 to …

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Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Toradex Colibri i.MX6 SoM with Freescale i.MX6 Solo and DualLite Processors

Toradex Colibri i.MX6 SoM with Freescale i.MX6 Solo and DualLite Processors

Toradex has added a new system-on-module to its Colibri family with Colibri IMX6 SoM powered by either Freescale i.MX 6Solo singl core processor, or i.MX 6DualLite dual core core processor. The SoMs are available in both both commercial and industrial temperature grade, come with up 4GB eMMC, 256 to 512MB RAM, and support Linux or Windows Embedded operating systems. Specifications listed for the Toradex Colibri i.MX6 module include: SoC – Freescale i.MX6 Solo single core or DualLite dual core Cortex-A9 core @ 800MHz (Industrial temp.) or 1GHz (Commercial temp) with Vivante 2D/3D GPUs. System Memory –  256MB (Solo) or 512MB (DualLite) DDR3 Storage – 4GB eMMC flash I/Os available via the 200-pin SO-DIMM connector: 3x 8-bit SDIO/SD/MMC 10/100M Ethernet (Micrel KSZ8041NL PHY) USB 2.0 host, USB 2.0 OTG Video Output HDMI 1.4a up to 1080p resolution RGB up to 1920×1200 (24bpp) Camera – 2x Camera Parallel inputs Audio – Audio line-in (stereo), mic-in (mono), and headphone (stereo). Freescale SGTL5000 Audio Codec …

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