NXP i.MX Category - Page 16 of 69 - CNX Software

June 19, 2021 by Saumitra Jagdale - 2 Comments

Digi ConnectCore 8M Mini SOM and Mini Development Kit for Industrial IoT Applications

Digi International has announced the Digi ConnectCore 8M Mini System-on-Module (SOM) which is an addition to its ConnectCore family modules. We saw the Android application development kit featuring earlier Digi Wireless modules based Freescale i.MX51 (ConnectCore Wi-i.MX51) and i.MX53 (ConnectCore Wi-i.MX53) in early 2012. The new Digi ConnectCore 8M Mini comes with a built-in Video Processing Unit specialising in vision use cases. The Digi ConnectCore 8M Mini SOM is an industrial i.MX 8M Mini quad-core system-on-module that comes with Arm Cortex-A53 cores, one Cortex-M4 core, and the Cortex-M0-based Digi Microcontroller Assist. This enables optimal power consumption while simultaneous maintenance of highly efficient performance. Main benefits of Digi Connect Core 8M Mini SOM Digi SMTplus form factor (40 x 45 mm) for flexibility and reliability while designing. Power management with both hardware and software support for low-power designs. Display and camera capabilities with graphics and video hardware acceleration make it suitable […]

June 14, 2021 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Cellular system-on-module integrates Quectel BG95-M3 Cat M1, NB-IoT, GPS module

Most systems-on-module come with a processor, memory, storage, and maybe a PMIC and some extra chips such as an Ethernet PHY. Some add wireless connectivity with a WiFi & Bluetooth module, but TT Electronics S-2Connect Creo SoM is more unusual as a Linux-powered SO-DIMM module with built-in Cat M1 & NB-IoT cellular connectivity, as well as GPS. This is implemented through Quectel BG95-M3 multi-mode LPWA module and an eSIM and a micro SIM socket in combination with an NXP i.MX 6UL processor Cortex-A7 processor along with 256MB RAM and a 4GB eMMC flash. S-2Connect Creo SoM specifications: SoC – NXP i.MX6UL Cortex-A7 System Memory – 256MB DDR3L Storaage – 4GB eMMC flash Connectivity LTE Cat M1 (eMTC), Cat NB2 (NB-IoT) 2G/EGPRS fallback via Quectel BG95-M3 module based on Cortex-A7 processor running ThreadX Bands LTE – 1, 2, 3, 4, 5, 8, 12, 13, 18, 19, 20, 25, 26, 27, 28, […]

June 7, 2021June 8, 2021 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Combining OSTree and SW Containers for reliable IoT Device updates

CNXSoft: This is a guest post by Drew Moseley, Technical Solutions Architect at Toradex, explaining how the company updates Linux IoT devices firmware with OSTree (aka libostree) open-source operating system build and deployment tool, as well as Docker software containers. Every day more and more connected devices are being brought to market and estimates for the total size of the Internet of Things (IoT) market are as high as $1.5 trillion by 2027. Gas pumps, medical devices, and point of sale systems are increasingly connected, making it virtually impossible to avoid interacting with these devices, even for complete Luddites. In the home, devices such as power meters, light switches, and security cameras are commonly internet-enabled allowing for smart home functionality. The level of complexity in the software for these devices increases with the functionality, and the number of devices with software defects in the field is growing. In many cases, […]

June 4, 2021June 4, 2021 by Jean-Luc Aufranc (CNXSoft) - No Comments

TQ unveils i.MX 8M Plus LGA module and evaluation single board computer

We’ve seen plenty of systems-on-module based on NXP i.MX 8M Plus AI processor announced at Embedded World 2021 either with edge or board-to-board connectors. TQ TQMa8MPxL is a bit different as an i.MX 8M Plus LGA (Land Grid Array) system-on-module meant to be soldered on a carrier board. The company also took the occasion to unveil STKa8MPxL evaluation kit based on TQMa8MxML in single board computer format to demonstrate its new LGA module. TQMa8MPxL i.MX 8M Plus LGA module Specifications: SoC – NXP i.MX 8M Plus “Quad 8 ML/AI”, “Quad 6 Video”, or “Quad 4 Lite” processor with four Cortex-A53 cores, one Cortex-M7 core, Vivante GPU, video encoder/decoder, HiFi4 audio DSP, and 2.3 TOPS AI accelertor System Memory – Up to 4 GB LPDDR4 Storage – Up to 256 MB (MBytes)Quad SPI NOR flash, up to 256 GB eMMC flash, optional EEPROM up to 64 Kbit 362-pin LGA with Storage […]

June 3, 2021 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Arm introduces Open-CMSIS-Pack and Keil Studio Cloud for MCU software development

Arm has just announced two new initiatives that aim to boost the productivity embedded, IoT, ML, and MCU software developers: the Open-CMSIS-Pack project and Keil Studio Cloud. The Open-CMSIS-Pack Project The Cortex Microcontroller Software Interface Standard (CMSIS) packs have been around for years providing a vendor-independent hardware abstraction layer for microcontrollers, mostly Cortex-M based, but others too, and currently support close to 9000 different microcontrollers. I always assumed CMSIS was open-source as the source code is available in Github under an Apache 2.0 license. But apparently, not all components are, and Arm has now announced the Open-CMSIS-Pack project that will move part of CMSIS into the open project in collaboration with the Linaro IoT and Embedded Group. Linaro, Arm, and other partners like STMicro and NXP will initially focus their work on command-line tools and CMake workflows, with the ultimate goal of making the CMSIS-Pack technology into a true open […]

May 12, 2021May 12, 2021 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

The Zigbee Alliance renames to the Connectivity Standards Alliance (CSA), Project CHIP becomes “Matter”

connectivity-standards association matter

The Zigbee Alliance is/was an organization of hundreds of companies creating, maintaining, and delivering open standards for Zigbee… and other Internet of Things (IoT) standards including Smart Energy, Green Power, JupiterMesh, rf4ce, Dotdot, etc… Since the organization does not reflect its involvement beyond Zigbee, the name has just been changed to the Connectivity Standards Alliance (CSA), and while they were at it they also rebranded “Project CHIP” (Connected Home over IP) to “Matter”, maybe because “connectivity standards matter!” 😉 There’s also a new website csa-iot.org but it may not have complete information just yet, and they invite you to access the Full website (https://zigbeealliance.org/about/) for extra details. Nothing much has changed here besides the name. But there’s more to report about Matter. A dedicated website has launched for the new standard, although the code remains under the Project Chip GitHub account at this time. What’s more interesting is that formal […]

May 12, 2021May 12, 2021 by Jean-Luc Aufranc (CNXSoft) - No Comments

Gateworks GW7200 Dual Gigabit Ethernet industrial SBC, also supports WiFi, Cellular, and GPS

Gateworks GW7200 dual GbE industrial SBC

Gateworks GW7200 is a versatile dual Gigabit Ethernet industrial single board computer with an NXP i.MX8M Mini processor, 1GB to 4GB of RAM, mini PCIe expansion sockets for wireless connectivity, serial interfaces, industrial temperature range, wide range input voltage, and long-term supply. The board should be a better match to projects with industrial requirements, for example, an industrial IoT gateway than lower-cost dual GbE alternatives such as NanoPi R2S or Raspberry Pi CM4 IoT Router Carrier Board Mini. Gateworks GW7200 specifications: SoC – NXP i.MX 8M Mini quad-core processor @ 1.6GHz with Vivante 2D & 3D GPUs System Memory – 1GB to 4GB DDR4-2133 SDRAM Memory Storage – 8GB to 64GB eMMC flash, MicroSD card slot, serial configuration EEPROM Connectivity Dual GbE Ethernet ports supporting 802.3at/af and passive PoE Optional 802.11ac/n WiFi 5/4 via mini PCIe socket Optional Cellular (Cat M1, 4G, 5G) via mini PCIe socket + NanoSIM card […]

May 5, 2021 by Jean-Luc Aufranc (CNXSoft) - No Comments

Imago “VisionAI” Smart AI Camera supports Tensorflow Lite & AutoML Vision Edge

Imago Technologies GmbH “VisionAI” is a programmable Smart AI camera that combines a quad-core Cortex-A53 processor @ 1.8 GHz together with Google Edge TPU, and designed for embedded image processing applications in the fields of AI, Deep Learning, and Machine Learning. The smart camera supports TensorFlow Lite and AutoML Vision Edge frameworks, and is suited for tasks such as pattern recognition, classification, anomaly or defect detection in inspection applications, code reading, and other machine vision applications. Imago VisionAI (VisionSensor PV3 AI) camera specifications: SoC – Unnamed quad-core Arm Cortex-A53 processor @ 1.8 GHz (likely NXP i.MX 8M Mini) AI Accelerator – Google Edge TPU with up to 4 TOPS of AI processing power System Memory – 2 GB DDR4 RAM Storage – MicroSD card up to 32GB Connectivity – Gigabit Ethernet M12 connector Camera 1/1.8” 5MP mono or color CMOS sensor with 2560 × 1936 pixels resolution, up to 65 […]