RGBC sensor has always-on capability and low power modes for AI

Equipped with low power modes to enable AI-based, always-on user experiences, the OV32C sensor is OmniVision’s first RGBC (colour sense) sensor. The 

32Mpixel image sensor is in a compact 1/3.2-inch optical format which is suitable for front-facing mobile phones’ selfie cameras. The colour sense technology is claimed to provide the highest quality images in challenging lighting conditions. The OV32C’s low power modes can help enable always-on user experiences by facilitating AI processing to automate many of the common tasks of the camera, such as face detection and QR code scans. 

The OV32C is built on OmniVision’s 0.7 micron PureCel Plus-S pixel technology to squeeze 32Mpixels into a 1/3.2-inch OF. RGBC technology uses a four-cell colour filter pattern with clear pixels and on-chip RGBC-to-Bayer fusion. It supports CPHY and DPHY interfaces and can output 15 frame rates per second (fps) at 32Mpixel, or 30 frames per second at 8Mpixels with on-chip fusion. The OV32C also offers dual DOVDD support at 1.8 and 1.2V.   

“Image sensors for front facing (selfie) cameras are expected to grow 4.7 per cent CAGR over the next five years, with smartphone front camera image sensor revenues reaching US$4.4 billion by 2026,” says Pierre Cambou, principal analyst, Imaging at Yole Développement. “Stacking technology is giving more degree of freedom to image sensor designers to embed advanced pre-ISP algorithms . . . . solving the difficulties of their non-Bayer arrangement. Adding ‘always-on’ smart capabilities to phone cameras will bring a new level of ergonomics and performance to the phone’s user interface,” he said.

The OV32C addresses the limited space challenge of a front facing camera module by providing 1/2.8-inch pixel size performance in the 1/3.2-inch OF. Arun Jayaseelan, staff marketing manager at OmniVision, comments: “The OV32C is our first sensor for the mobile phone market to feature RGBC―providing a 50 per cent boost in overall sensitivity to enhance low-light image quality”. The company has also reduced design complexity for OEMs with an on-chip RGBC-to-Bayer fusion algorithm, so that a separate RGBC processing unit is not required.  

OmniVision says that the OV32C offers fast access to camera functionality at all times. The low power modes help enable always-on features optimising the phone’s back-end AI applications, minimising power and data rate usage. 

Samples of the OV32C are available now. 

http://www.ovt.com 

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GaN-based inverter enhances motor drive for e-mobility, drones and robots

Claiming to match premium motor drives’ performance, the EPCD9145 GaN-baed inverter is designed for e-bikes, e-motion, drones and robots, says Efficient Power Conversion (EPC).

The EPC9145 GaN-based inverter enhances the performance of the motor for range, precision, torque, says the company. Additionally, it eliminates the requirement for electrolytic capacitors, resulting in lower overall system cost and higher reliability. The small size allows the inverters to be integrated into the motor housing for the lowest EMI, highest density, and lowest weight.

The EPC9145 demonstration board is a 1kW, three-phase brushless DC (BLDC) motor drive inverter which uses the EPC2206 eGaN FET.

The demonstration board features the 2.2 mOhm maximum RDS(on), 80V maximum device voltage EPC2206 eGaN FET. The board is tailored to e-bikes, e-motion, drones and robot motor applications. Its 48V bus voltage can deliver 15A RMS steady state at 50 degrees C temperature rise in natural air convection and can reach 20A RMS (28A peak) with a heatsink attached. The EPC9145 has been tested up to 100kHz, 60V input, and 50A peak.

The EPC9145 contains all the necessary critical function circuits to support a complete motor drive inverter, assures EPC. Board dimensions are only 130 x 100mm (including the connector). The EPC9145 also features the ST Microelectronics, STDriveG600, smart motor drive GaN half-bridge driver.

GaN FETs switch fast with zero reverse recovery, says EPC. This enables higher switching frequency in the 100kHz range to eliminate the need for electrolytic capacitors and to reduce the motor losses. Deadtime can also be reduced to approximately 20ns to allow higher torque per A. Overall, GaN devices improve inverter and motor system efficiency and reduce size and weight by integrating the inverter inside the motor.

The demonstration board highlights benefits of a GaN motor drive, such as lower distortion for lower acoustic noise, lower current ripple for reduced magnetic loss, lower torque ripple for improved precision, lower filtering for lower cost. The board’s low weight and size enables the driver to be incorporated into the motor housing. It also supports low inductance, higher power density motors, says EPC.

The company provides full demonstration kits, which include interface boards that connect this inverter board to the controller board development tool. Compatible controller interface and controller boards to the EPC9145 are EPC9147A for Microchip, EPC9147B for Texas Instruments, EPC9147C for ST Microelectronics, and EPC9147E as a generic interface board.

“Everyone wants a motor that is smaller, lighter, is less noisy, has more torque, more range, and greater precision,” said Alex Lidow, CEO of EPC. He says that eGaN devices, a cost-effective motor with a GaN inverter offer the same performance as an expensive motor with a silicon MOSFET-based inverter. 

The EPC9145 demonstration board is available for immediate delivery from distributor, Digi-Key.

http://www.epc-co.com

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Low power dual-channel receive modules and pre-drivers boost 5G, says NXP

Pre-drivers and dual-channel receive front end modules from NXP Semiconductors are claimed to reduce 5G operating costs. The BTS6302U/6201U pre-drivers and BTS7203/5 dual-channel receive (RX) front end modules are intended for 5G massive multi-input multi-output (MIMO) infrastructure. They are claimed to offer low current consumption, reducing carrier operating costs. They have been developed using NXP’s silicon germanium (SiGe) process and in-house test and assembly.

Traditional basestations provide four to eight transmit and receive channels, but the 5G MIMO infrastructure designs typically require 32 or 64 transmit and receive channels to deliver the increased network throughput and responsiveness of 5G. The dual-channel RX FEMs address the need for additional channels, while simultaneously reducing power needs and operating costs for both carriers and OEMs, says NXP.

The BTS6302U pre-driver offers optimised 5G performance, with low current consumption and an integrated balun to reduce external components, simplifying design and reducing overall system costs. The pre-driver and RX FEMs are compatible with NXP’s RapidRF series of reference boards, to further reduce 5G development cycles and time to market.

NXP Semiconductors specialises in secure connectivity solutions for embedded applications. NXP says it is driving innovation in the automotive, industrial and IoT, mobile, and communication infrastructure markets. 

http://www.nxp.com

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Sensor development kit delivers AI/ML for smart industrial applications

AI tool developer, SensiML has teamed up with onsemi to deliver ML for autonomous sensor data processing and predictive modelling. SensiML develops AI tools for building intelligent IoT endpoints. Its analytics toolkit development software has been combined with the RSL10 sensor development kit from onsemi for edge sensing applications such as industrial process control and monitoring. SensiML can support AI functions in a small memory footprint, and the RSL10 provides advanced sensing and Bluetooth Low Energy connectivity for smart sensing without the need for cloud analytics of highly dynamic raw sensor data.

Claimed to have the industry’s lowest power Bluetooth Low Energy connectivity,  the RSL10 sensor development kit combines the RSL10 radio with a range of environmental and inertial motion sensors onto a tiny form factor board that interfaces with the SensiML Toolkit. Developers using the RSL10-based platform and the SensiML software together can add low latency local AI predictive algorithms to industrial wearables, robotics, process control, or predictive maintenance applications regardless of expertise in data science and AI. 

The auto-generated code enables smart sensing embedded endpoints that transform raw sensor data into critical insight events where they occur and can take appropriate action in real time. The smart endpoints reduce network traffic by communicating data only when it offers valuable insight.

“Cloud-based analytics add unwanted, non-deterministic latency, and are too slow, too remote and too unreliable for critical industrial processes,” said Dave Priscak, vice president of Applications Engineering at onsemi. 

“Other AutoML solutions for the edge rely only on neural network classification models with only rudimentary AutoML provisions, yielding suboptimal code for a given application,” adds Chris Rogers, SensiML’s CEO. The company’s AutoML model search includes neural networks with an array of classic ML algorithms, as well as segmenters, feature selection, and digital signal conditioning transforms, he explains.

The SensiML analytics toolkit is available now from SensiML and the RSL10 sensor development kit is available now from onsemi.

 http://www.sensiml.com

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