Tool accelerates edge-native AI development

To simplify and accelerate the design, development, testing and deployment of smart systems, MicroAI has introduced Launchpad, a quick start development and deployment tool. It is designed to run embedded MicroAI software on microcontrollers  and microprocessors in edge and endpoint devices.

The tool handles customers with SIMs around the world and provides a flexible way to manage and reconfigure device profiles. Launchpad allows engineers to customise dashboards, including account creation, authentication, mobile SIM or LoRaWAN connectivity activation, credit card billing for global SIM connectivity with MicroAI’s embedded software libraries.

“MicroAI’s goal is to democratise the development of smart machines for all organisations across any industry,” said MicroAI CEO Yasser Khan. “Regardless of industry or product, building . . .  smart device includes creating an edge AI model, but also integrating connectivity and cloud resources, as well as device activation and management.”

MicroAI’s embedded software, AtomML, enables OEMs to deploy personalised, edge-native AI models, without needing to develop static edge-AI models first in a cloud or laptop and then port them to the embedded device. Instead, MicroAI AtomML moves the training and inferencing directly to the embedded device. Launchpad then simplifies and reduces the time and cost to integrate the microcontrollers and microprocessors into an edge device, which can be tested and scaled to proof of concept for mass deployment.

MicroAI Launchpad can be white labelled for use by semiconductor companies, OEMs  and service providers. Semiconductor companies that offer stock keeping units (SKUs) with MicroAI embedded AI software can leverage its end-to-end device management and deliver it to their customers to help expedite design, development, testing and deployment. OEMs directly engaged with MicroAI benefit from Launchpad’s flexibility to evaluate various hardware, software, and cloud solutions before finalising a deployment model. For IoT service providers, Launchpad will provide device certification, connectivity, and deployment for a deeper insight view of connected devices on networks.

MicroAI is based in Dallas, Texas, USA and specialises in edge-native artificial intelligence (AI) and machine learning (ML) products. The company is personalising AI for connected machines, edge devices, and critical assets by embedding its proprietary edge-native AI technology directly onto microcontrollers and microprocessors within edge endpoints. This enables device-specific and more accurate AI modelling for edge and endpoint cyber security, advanced predictive maintenance, IoT performance optimisation and significant improvements in overall equipment effectiveness (OEE). The company’s mission is to democratise edge-native AI for all connected, smart devices by reducing the complexity, time, and cost to design, develop, and deploy embedded, edge-native AI.

http://www.micro.ai

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IAR Embedded Workbench supports Arm Cortex-55 core for AI

Support for the latest Arm Cortex-M55 processor has been announced by IAR Systems. The latest version of IAR Embedded Workbench for Arm adds support for the Arm Cortex-M55 processor. In addition, version 9.20 of the toolchain includes support for latest microcontroller devices from several semiconductor vendors.

The Arm Cortex-M55 processor is Arm’s AI-capable Cortex-M processor and the first to feature Arm Helium technology, M-Profile Vector Extension (MVE). It is characterised by energy-efficient digital signal processing (DSP) and machine learning (ML) capabilities. The IAR Embedded Workbench for Arm toolchain delivers powerful optimisation capabilities to assist developers in getting the most out of the performance of the microcontroller while maintaining energy efficiency. To ensure code quality, code analysis tools are completely integrated with IAR Embedded Workbench.

The support for Cortex-M55 is intended to help early development based on the core in the ecosystem. 

In a simultaneous announcement, the company announced that the latest IAR Build Tools for Arm provides support for Linux and Windows installations, which enables implementation in cross platform-based frameworks and large-scale deployments of critical software building and testing. 

IAR Systems says it supplies future-proof software tools and services for embedded development, enabling companies worldwide to create the products of today and the innovations of tomorrow. Since 1983, IAR Systems’ solutions have been used in the development of over one million embedded applications. 

The company is headquartered in Uppsala, Sweden and has sales and support offices all over the world. In 2018, Secure Thingz, the global domain expert in device security, embedded systems, and lifecycle management, became part of IAR Systems Group AB. 

http://www.iar.com

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Face recognition uses 3D SLM camera and NXP’s i.MX RT117F crossover MCU 

A 3D face recognition access control systems uses  NXP Semiconductor’s crossover MCU with a 3D camera to enable faster secure face recognition under challenging lighting conditions.

The 3D structured light module (SLM) camera is combined with the i.MX RT117F crossover MCU and is believed to be the first time a 3D SLM camera has been combined with an MCU to deliver the performance and security of 3D face recognition at the edge. It therefore removes the need to use an expensive and power-hungry Linux implementation on a microprocessor which is conventionally the case with high-performance 3D cameras, reports NXP.

The i.MX RT117F MCU is part of the i.MX RT1170 family of crossover MCUs. It is based on an Arm Cortex-M7 CPU with 2Mbyte of on-chip SRAM, running at up to 1GHz. 

The turnkey system is the latest EdgeReady solution from NXP. It enables developers of smart locks and other access control systems to add machine learning-based secure face recognition quickly and easily to smart home and smart building products. Reliable 3D face recognition can be achieved in indoor and outdoor applications, across varied lighting conditions, including bright sunlight, dim night light, or other difficult lighting conditions that are challenging for traditional face recognition systems.

The use of a 3D SLM camera enables advanced liveness detection, helping distinguish a real person from spoofing techniques, such as a photograph, imitator mask or a 3D model, to prevent unauthorised access.

The i.MX RT117F uses an advanced machine learning model as part of NXP’s eIQ machine learning software running on its CPU core.

 Advanced liveness detection and face recognition are performed locally at the edge, making it possible for personal biometric data to remain on the device. This helps address consumer privacy concerns, while also eliminating the latency associated with cloud-based solutions.

The development kit for this 3D face recognition system, the SLN-VIZN3D-IOT, will be available later in November from NXP and authorised distributors.

The i.MX RT117F includes a license to use the NXP 3D face recognition software development kit (SDK), and is available in consumer, industrial and automotive temperature grades.

http://www.nxp.com

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DC/DC converter can extend industrial devices’ battery life by up to 20 per cent 

Boasting low quiescent current (IQ) of 60nA, the TPS61094 buck/boost converter can extend the battery life of industrial applications, says Texas Instruments. The bi-directional buck/boost converter’s IQ is one-third that of competing boost converters, says the company. It integrates a buck mode for supercapacitor charging while providing low IQ, to extend battery life by as much as 20 per cent when compared to commonly used hybrid-layer capacitors (HLCs). Supercapacitor charging and discharging help support peak loads and backup power, which are important for continuous operation in battery-powered industrial applications such as smart meters, smoke detectors and video doorbells, as well as medical applications.  

Engineers designing battery-operated systems frequently face a common design challenge: a need to achieve high efficiency at no- or light-load conditions, in the low milliampere or microampere range. This requires power supplies to regulate their output while maintaining low supply current in the nA range. 

Today’s lithium thionyl chloride (Li/SOCl₂) battery-based designs often manage peak load with HLCs. This are expensive and not optimal for controlling charge current, explains TI. The TPS61094’s combined low IQ and supercapacitor charging and discharging allow HLCs to be replaced with supercapacitors for peak load support and to extend battery life in applications that must run on a single battery for 10 years or more. 

The TPS61094 can provide back up power in applications that require safe power-down or last-gasp communication during a power outage. 

In addition to extending battery life, the buck/boost converter has a 2.0A inductor current limit in boost operation, which doubles the output current of competitive boost converters, according to the company.

The additional output current enables the TPS61094 to support radio standards – such as narrowband Internet of Things (NB-IoT), LTE-M, Wi-SUN, MIOTY, Bluetooth and wireless M-Bus – over a wider input voltage range. For example, it can support more than 250mA of output current down to an input voltage of 0.7V.

Typical industrial applications such as smart meters require several power components for back up power features or peak load support. Integrating a buck charger and a boost converter into a single IC removes the need for a discrete buck charger, inductor and two external capacitors.  

The integration of the buck charger and boost converter also allows design engineers to easily control the handshake between all functions, for a seamless transition between operating modes.

The TPS61094 is now available through TI and authorised distributors in a 2.0 x 3.0mm, 12-pin very thin, small outline no-lead (WSON) package. Full and custom quantity reels are available and there is also the TPS61094EVM-066 evaluation module.

http://www.TI.com

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