TDK InvenSense’s ultrasonic ToF range sensor for ultra-long-range applications

Mouser is now stocking the ICU-30201 ultrasonic time-of-flight (ToF) range sensor from TDK InvenSense. The ICU-30201 is a high-performance ToF sensor for ultra-long-range applications, measuring distances from 30 cm to 9.5 m with millimeter accuracy. The sensor enhances contextual awareness and reliability in diverse environments, including smart homes, robotics, and obstacle avoidance.

The TDK InvenSense ICU-30201 ultrasonic ToF range Sensor delivers accurate measurements in any lighting condition, from full sunlight to complete darkness, and can detect optically transparent surfaces such as glass and clear plastics. The ICU-30201 supports multi-object detection with a customisable field-of-view (FOV) up to 180°. The sensor also features a 53 kHz piezoelectric micro machined ultrasonic transducer (PMUT) — a second-generation ultra-low power System-on-Chip (SoC) — and a 40 MHz integrated CPU for on-chip algorithms including range finding, human presence, and wake-on approach.

The ICU-30201 sensor offers a sample rate of 75 samples per second at two meters and 18 samples per second at nine meters. With ultra-low power consumption (22µA to 318µA depending on the number of samples per second), the ICU-30201 helps extend battery life in devices including smart speakers, meeting room devices, and smart door locks. A single bottom port package for receiving and transmitting allows for easy mechanical integration. The ICU-30201 sensor comes in a compact 5.17 × 2.68 × 0.9 mm LGA package and includes an integrated digital signal processor (DSP). The sensor is compatible with standard surface mount device (SMD) reflow and has an operating temperature range of -40°C to +85°C.

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ST announces mass production for turnkey Bluetooth/Wi-Fi modules developed with Qualcomm

STMicroelectronics has announced mass-production start for its ST67W611M1 combined Wi-Fi 6 and Bluetooth Low Energy 5.4 module, describing the early success of Siana, a lead customer for its fast-to-market connectivity.

The module is the first product of ST’s collaboration with Qualcomm Technologies, announced by the two companies in 2024, to simplify implementing wireless connectivity in systems containing STM32 microcontrollers (MCUs). Their vision, now realised in silicon, fuses ST’s expertise in embedded design and the STM32 ecosystem of microcontrollers, software, and development tools integrated with Qualcomm Technologies’ wireless connectivity technologies.

“Wireless connectivity is a key enabler for the cloud-connected intelligent edge and demand for smart, connected devices continues to expand and accelerate throughout consumer and industrial markets,” said Jerome Vanthournout, Connectivity Business Line Director, STMicroelectronics. “Mastering the complex Wi-Fi and Bluetooth protocols, and bringing that connectivity to devices and IoT applications, are huge challenges. Our modular solution, created with industry-leading knowhow of all aspects, lets product developers focus their resources at the application level and bring new products to market quickly.”

Shishir Gupta, Senior Director, Product Management at Qualcomm Technologies added, “Qualcomm Technologies is thrilled to see the impact of our collaboration with STMicroelectronics through the ST67W module. This module, which contains Qualcomm Technologies’ wireless connectivity components, not only simplifies the integration of Wi-Fi and Bluetooth into a wide range of devices powered by STM32 microcontrollers but also offers incredible flexibility and scalability. This module is a testament to our joint commitment to driving innovation and excellence in the IoT space.”

The ST67W module is ready to integrate with any STM32 MCU and contains a Qualcomm Technologies multiprotocol network coprocessor and 2.4GHz radio. All RF front-end circuitry is built-in, including power/low-noise amplifiers, the RF switch, balun, and integrated PCB antenna, with 4Mbyte Flash for code and data storage and a 40MHz crystal. The module comes pre-loaded with Wi-Fi 6 and Bluetooth 5.4 and is pre-certified according to mandatory specifications. Thread and Matter will be supported soon via software update. There is also an optional coaxial antenna or board-level connections for an external antenna. Security is handled with cryptographic accelerators and services including secure boot and secure debug reaching PSA Certified Level 1, making it easy for customers to comply with the upcoming Cyber Resilience Act and RED directives.

Product developers need no RF design expertise to create a working solution using this module. Highly integrated in a 32-lead LGA package, it is ready to place on the board and permits simple, low-cost PCB designs with as few as two layers.

Siana Systems is among the first IoT technology companies to explore the opportunities this wireless connectivity module brings to enhance product performance and accelerate time to market.

“The ST67W module expands opportunities to add Wi-Fi to devices powered by various STM32 microcontrollers and worry less about the minimum requirements. We can simply integrate the module and quickly get Bluetooth and Wi-Fi connectivity, with minimal additional engineering, which provides us with a simple go-to solution for our next generation designs,” said Sylvain Bernard, Founder and Solution Architect, Siana Systems. “The module’s RF performance, with the radio and front-end circuitry integrated, is very strong, and the flexible power management with fast wake-up times lets us create extremely energy-efficient new products.”

The ST67W611M1 leverages the STM32 ecosystem, which contains over 4,000 commercial part numbers, powerful STM32Cube tools and software, and enhancements that boost edge AI development. The STM32 family covers a broad spectrum from economical Arm® Cortex®-M0+ devices to variants with high-performing cores like Cortex-M55, Cortex-M4 with DSP extensions, and Cortex-A7 in the STM32MP1/2 MPUs.

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Rohm has developed a breakthrough in AI-equipped MCUs

Rohm has developed AI-equipped MCUs (AI MCUs) – ML63Q253x-NNNxx / ML63Q255x-NNNxx – that enable fault prediction and degradation forecasting using sensing data in a wide range of devices, including industrial equipment such as motors. According to Rohm these MCUs are the industry’s first to independently execute both learning and inference without relying on a network connection.

As the need for efficient operation of equipment and machinery continues to grow, early failure detection and enhanced maintenance efficiency have become key challenges. Equipment manufacturers are seeking solutions that allow real-time monitoring of operational status while avoiding the drawbacks of network latency and security risks. Standard AI processing models, however, typically depend on network connectivity and high-performance CPUs, which can be costly and difficult to install.

In response, Rohm has developed AI MCUs that enable standalone AI learning and inference directly on the device. These network-independent solutions support early anomaly detection before equipment failure – contributing to a more stable, efficient system operation by reducing maintenance costs and the risk of line stoppages.

The new products adopt a simple 3-layer neural network algorithm to implement Rohm’s proprietary on-device AI solution “Solist-AI™.” This enables the MCUs to perform learning and inference independently, without the need for cloud or network connectivity.

AI processing models are generally classified into three types: cloud-based, edge, and endpoint AI. Cloud-based AI performs both training and inference in the cloud, while edge AI utilises a combination of cloud and on-site systems - such as factory equipment and PLCs - connected via a network. Typical endpoint AI conducts training in the cloud and performs inference on local devices, so network connection is still required. Furthermore, these models typically perform inference via software, necessitating the use of GPUs or high-performance CPUs.

In contrast, Rohm’s AI MCUs, although categorised as endpoint AI, can independently carry out both learning and inference through on-device learning, allowing for flexible adaptation to different installation environments and unit-to-unit variations, even within the same equipment model. Equipped with Rohm’s proprietary AI accelerator “AxlCORE-ODL,” these MCUs deliver approximately 1,000 times faster AI processing compared to Rohm’s conventional software-based MCUs (theoretical value at 12MHz operation), enabling real-time detection and numerical output of anomalies that “deviate from the norm”. In addition, high-speed learning (on-site) at the point of installation is possible, making them ideal for retrofitting into existing equipment.

These AI MCUs feature a 32-bit Arm® Cortex-M0+ core, CAN FD controller, 3-phase motor control PWM, and dual A/D converters, achieving a low power consumption of approximately 40mW. As such, they are ideally suited for fault prediction and anomaly detection in industrial equipment, residential facilities, and home appliances.

The lineup will consist of 16 products in different memory sizes, package types, pin counts, and packaging specifications. Mass production of 8 models in the TQFP package began sequentially in February 2025. Among these, two models with 256KB of Code Flash memory and taping packaging are available for purchase, along with an MCU evaluation board, through online distributors.

Rohm has released an AI simulation tool (Solist-AI Sim) on its website that allows users to evaluate the effectiveness of learning and inference prior to deploying the AI MCU. The data generated by this tool can also serve as training data for the actual AI MCU, supporting pre-implementation validation and improving inference accuracy.

 

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BeagleBoard Wi-Fi 6 Bluetooth LE wireless modules now at Mouser

Mouser is now shipping the CC33 wireless modules from BeagleBoard. The BM3301 modules are high-performance 2.4GHz Wi-Fi® 6 and Bluetooth Low Energy 5.4 combo wireless modules for industrial IoT, automotive, smart home, consumer electronics, healthcare, and embedded systems applications.

The BeagleBoard CC33 wireless modules, available from Mouser, are powered by TI’s 10th-generation connectivity chip (CC3301), delivering application throughput of up to 50 Mbps and are designed for reliable performance in extreme conditions (-40°C to +85°C), making them ideal for diverse applications requiring robust wireless connectivity. There are two variants to this module: The BeagleMod BM3301-1313 is a 13mm × 13mm BGA module, footprint-compatible with the TI WL18xxMOD series for easy drop-in design upgrades. The BeagleMod BM3301-1216 is a 12mm × 16mm M.2 1216 LGA module that includes an IPEX Gen 4 connector, and a u.FL antenna connector to simplify board layout, with both featuring Wi-Fi 6, Bluetooth LE 5.4, and integrated 2.4 GHz PA for complete wireless solutions with up to +20.5 dBm output power.

Mouser also stocks the BeagleY-AI single-board computer (SBC), a low-cost, open-source, community-supported development platform in a familiar form factor compatible with other popular SBC accessories. It was developed to streamline the process of building smart human-machine interfaces (HMI), incorporating cameras and high-speed connectivity into a reliable embedded system. The BeagleY-AI SBC features a powerful 64-bit, quad-core A53 processor and numerous powerful AI accelerators paired with C7x DSPs capable of 4 TOPS (trillion-operations per second) combined (2 TOPS each), an integrated 50GFLOP GPU supporting up to three concurrent display outputs and modern connectivity with USB 3.1 and PCIe Gen 3. An onboard BeagleMod CC33 module (BM3301- 1313) provides Wi-Fi 6 and BLE 5.4 connectivity.

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