Among the most fundamental trends in the consumer electronics industry today is the proliferation of sensors. For applications such the Internet of Things (IoT), wearables, and AR/VR, sensing has been a core technology. As devices become embedded with more and more sensors, system developers face about how to best handle and fuse that data into a useful format. To address this issue, STMicroelectronics (ST) has recently released a new 6-axis IMU which includes a number of integrated features such as sensor fusion blocks and Machine Learning (ML) cores. In this article, we'll discuss sensor fusion, why it's a challenge, and how ST's new product hopes to enable low-power sensing applications.

Oakland, California – When Silicon Valley chipmaker Marvell learned that one of its chips was found in a Russian surveillance drone recovered in 2016, it set out to investigate how that came to be. The chip, which costs less than $2, was shipped in 2009 to a distributor in Asia, which sold it to another broker in Asia, which later went out of business. "We couldn't trace it any further," Marvell Technology Group Chief Operations Officer Chris Koopmans said in a recent interview. Years later, it reappeared in the drone recovered in Lithuania. Marvell's experience is one of myriad examples of how chipmakers lack ability to track where many of their lower-end products end up, executives and experts said.

Companies in the Semiconductor – General industry are at the forefront of the ongoing technological revolution based on HPC, AI, automated driving, IoT and so on. These semiconductors also enable the cloud to function and help analyze the data into actionable insights that can be used by companies to operate more efficiently. If anything, the pandemic has strengthened the conviction that these technological changes are required and inevitable, because it is these technology platforms that enabled us to function when it was unsafe for us to go to work or meet people. Even with the opening up of the economy, the race to digitization, cloud, AI, etc. is expected to continue at an accelerated rate, driving strong demand for semiconductors. NVIDIA has pioneered and built a whole lot of this cutting-edge technology, so it remains a top recommendation.

In this one-hour webinar followed by live Q&A, you will learn about the STM32Cube function packs that allow you to run AI computer vision applications on STM32 microcontrollers, such as the FP-AI-VISION1. We will showcase several examples of computer vision applications based on Convolutional Neural Networks, including people-counting and facial recognition demos, and present the roadmap for edge AI computer vision on STM32 MCUs. After the webinar, there will be a 15-minute Q&A session where our experts will be available to answer any questions. This webinar will be broadcast twice, at convenient times for international audiences. Please review the times listed below and register for the most appropriate option for your time zone.

STMicroelectronics and Schneider Electric are demonstrating a prototype IoT sensor that enables new building-management services and efficiency gains by understanding building-occupancy levels and usage. The two companies have collaborated to integrate Artificial Intelligence (AI) into a high-performance people-counting sensor, which overcomes the challenge of monitoring attendance in large spaces with multiple entrance points. Schneider Electric will demonstrate this IoT sensor as a guest ST Live Days, during the IoT&5G session on November 19, 2020. With the digitization of building occupancy, Schneider is following its mission to be its customers' digital partner for sustainability and efficiency by delivering new and highly valuable insights such as queue monitoring to assist smart building management while respecting individuals' privacy by design. The advanced IoT sensor has been developed by combining the high expertise of ST's AI group and the deep sensor-application expertise of Schneider Electric to identify and embed a high-performing object-detection neural network in a small microcontroller (MCU).

Qeexo announces that its Qeexo AutoML platform now supports machine learning on Arm Cortex -M0 and Cortex -M0 processors, which power devices including sensors and microcontrollers from companies such as Arduino, Renesas, STMicroelectronics, and Bosch Sensortec. The Arm Cortex-M0 processor is the smallest Arm processor available, and the Cortex-M0 processor builds on Cortex-M0 while further reducing energy consumption and increasing performance. Qeexo is the first company to automate adding machine learning to a processor of this size. The Cortex-M0 and Cortex-M0 processors are designed for smart and connected embedded applications, and are ideal for use in simple, cost-sensitive devices due to the lower power-consumption and ability to extend the battery life of critical use cases such as activity trackers. Machine learning models built with Qeexo AutoML are highly optimized and have an incredibly small memory footprint.

In this 1-hour session, we will introduce Artificial Intelligence for Edge computing and show you how ST's offer can help you run Neural Networks on microcontrollers and microprocessors. Thanks to concrete application examples, you will know more about running Artificial Neural Networks and you will learn how to use the STM32Cube.AI tool to convert Neural Networks into optimized code for STM32 MCUs. Use the power of Deep Learning and hop on board: discover how ST's AI solutions, ecosystem and network of expert partners can support AI application development and help you reduce time-to-market. There will be a live Q&A session at the end of the webinar where ST's experienced engineers will be available to answer your questions. This webinar will be broadcast twice, at convenient times for international audiences.

LG Innotek, a unit of LG group, will supply 3D facial recognition modules for Apple's upcoming iPhone 8, Korea Economic Daily reported Thursday. Apple and LG Innotek got together last year to develop the first-ever 3D facial recognition camera, which will be used for "a variety of applications from biometric authentication to games," the report said. Read: Apple's A11 Processor For iPhone 8, 7s, 7s Plus And iPad Refreshes Enter Production LG already supplies Apple with dual-lens camera modules found on the back of the iPhone 7. The upcoming camera is expected to be on the front side of the iPhone 8 and be smaller than the one on the iPhone 7. Both reasons are why LG is building a plant, the report said. LG reportedly invested 269.7 billion won ($239.5 million) in a new facility that will be dedicated to Apple's orders. The facility was announced at the end of April and had an initial deal price of about 200 billion won ($177.6 million).