ICs & Semiconductors

Analog Devices and Jungo monitor vehicle safety

Thu, Feb 13, 2020

Analog Devices will develop a time-of-flight (ToF) and 2D infra red (IR) –based camera, using Jungo’s Co-driver software to enable driver and in-cabin monitoring in vehicles.

The system will monitor vehicle occupants for levels of drowsiness and distraction by observing head and body position as well as eye gaze. It is also expected to enable smart vehicle interaction based on face, body, and hand gestures and offer a facial recognition capability that identifies individuals and gives them access to features such as infotainment personalisation, personalised services, and ridesharing payments.

3D ToF is a type of scannerless light detection and ranging (lidar) that uses high power optical pulses in durations of nanoseconds to capture depth information (typically over short distances) from a scene of interest. Analog Devices specialises in products and solutions that enhance the capabilities of 3D ToF systems, including processing, laser drivers and power management, development boards and software/firmware to implement 3D ToF solutions.

Jungo’s Co-driver software uses deep learning, machine learning, and computer vision algorithms to detect, in real-time, the head and body position of the driver from cameras.  It also supports in-vehicle full detection technology with functions such as counting of the number of occupants, detection of seat belt wearing or detection or observing of critical medical conditions.

“Jungo’s Co-driver monitoring algorithms are used by original equipment manufacturers (OEMs) to keep their drivers and passengers safe and develop innovative use cases that understand an occupant’s state while in the vehicle,” said Ophir Herbst, CEO, Jungo. “We are delighted to collaborate with Analog Devices to make vehicles smarter and enable OEMs to comply with regulations and innovate in their next-generation vehicles by using our algorithms and ADI’s leading ToF technology.”

Jungo Connectivity was founded in 2013 as an automotive software divestiture from Cisco Systems. The company focuses on in-cabin driver monitoring.

http://www.analog.com

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DC/DC converters simplify design of smart industrial applications

Tue, Feb 11, 2020

High efficiency at all loads, with a maximum value of 95 per cent is maintained byt eh L6983 38V/3.0A synchronous DC/DC converters, says STMicroelectronics.

They are integrated with synchronous MOSFETs on-chip to save external components and to simplify design.

The L6983 converters have low quiescent current of just 17 microA. Two variants, the low current consumption L6983C and the low-noise L6983N, are available. The L6983C enters pulse-skipping mode when the load current is below 0.6A while the L6983N, stays in PWM (pulse-width modulation) mode at all loads to minimise electromagnetic disturbances, making it suitable for noise-sensitive applications.

The L6983 converters have a wide input range from 3.5 to 38V, and are suitable for use over in 12 and 24V industrial bus-powered systems, battery-powered equipment, decentralised intelligent nodes such as smart-building controllers, and always-on devices including smart sensors. They can be ordered with 3.3V, 5.0V, or adjustable output voltage.

All L6983 converters have a ‘power-good’ output pin that can be used for power-up/power-down sequencing, enabling logic circuitry, or as a fault indicator. In addition, integrated feedback-loop compensation, over-voltage protection, and soft-start circuitry simplify the design of a complete power supply system. The switching frequency is programmable from 200kHz to 2.2MHz. Frequency spread-spectrum operation and external frequency synchronisation ease electromagnetic compatibility (EMC) compliance.

ST has also released the STEVAL-ISA208V1 evaluation board to help accelerate device selection and power-supply development using the L6983.

The L6983C and L6983N are in production now, packaged in 3.0 x 3.0mm QFN16 packages.

http://www.st.com/l6983-pr

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Low-power DDR5 DRAM achieves data speeds for AI and 5G

Fri, Feb 07, 2020

Micro Technology is shipping what it claims is the first low-power DDR5 DRAM in mass production. The LPDDR5 DRAM will be used in Xiaomi’s the soon-to-be-released Mi 10 smartphone. Micron says that the LPDDR5 DRAM provides Xiaomi with power efficiency and fast data access speeds to meet consumer demand for artificial intelligence (AI) and 5G functionality in smartphones.

Dr. Raj Talluri, senior vice president and general manager of the Mobile Business Unit at Micron, said: “Micron’s LPDDR5 DRAM addresses [AI and 5G] requirements with a 50 per cent increase in data access speeds and more than 20 per cent power efficiency compared to previous generations.”

The LPDDR5 DRAM has been designed to address the growing demand for higher memory performance and lower energy consumption in automotive, client PCs and networking systems built for 5G and AI applications. LPDDR5 can provide more than a 20 per cent reduction in power use compared to LPDDR4x memory.

It delivers the speed and capacity needed to feed AI engines built directly into mobile processors. These processors rely on high data rates from Micron’s internal LPDDR5 memory to power their machine learning capabilities.

The next-generation LPDDR5 memory allows 5G smartphones to process data at peak speeds of up to 6.4Gbits per second, to prevent 5G data bottlenecks, explains Micron. Examples are autonomous vehicles that require a memory subsystem with a larger bandwidth to support real-time computing and data processing.

Micron is shipping LPDDR5 to customers in capacities of 6Gbyte, 8Gbyte and 12Gbyte and at data speeds of 5.5Gbits per second and 6.4Gbits per second.

The LPDDR5 in a multichip package will also provide longer battery life and higher bandwidth to enable high-performance image processing that was previously reserved for premier smartphones.

In the first half of 2020, the Micron LPDDR5 will also be available in a UFS-based multi-chip package (uMCP5) for use in mid- and high-tier smartphones.

http://www.micron.com

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Hailo-8 has processor architecture specifically for deep learning

Wed, Feb 05, 2020

Artificial intelligence (AI) chipmaker, Hailo, is sampling the Hailo-8 deep learning processor. The chip’s architecture enables edge devices to run sophisticated deep learning applications that could previously run only on the cloud. It can be used in multiple industries, but the company has a focus on automotive.

The Hailo-8 processor features up to 26 Tera operations per second (TOPS), to “significantly outperform” other edge processors in terms of area and power efficiency, says Hailo. The architecture design relies on the core properties of neural networks, so that edge devices can now run deep learning applications at full scale more efficiently, effectively, and sustainably than traditional solutions, while significantly lowering costs, explains the company.

Hailo is working with leading OEMs and Tier-1 automotive companies in advanced driver assistance systems (ADAS). The processor is also suitable for smarter edge and IoT devices which also require the use of high-performance cameras to perform tasks such as semantic segmentation and object detection in real-time. The Hailo-8 can perform these at full resolution, yet consuming only a few Watts. The processor’s heat dissipation removes the need for active cooling systems in the automotive industry, claims Hailo.

Hailo is an AI-focused Israel-based chipmaker. The company has developed a specialised deep learning processor that delivers the performance of a data centre-class computer to edge devices. Hailo’s AI processor is the product of a rethinking of traditional computer architecture, enabling smart devices to perform sophisticated deep learning tasks such as object detection and segmentation in real-time, with minimal power consumption, size, and cost. The deep learning processor is designed to fit into a multitude of smart machines and devices, including autonomous vehicles, smart cameras, smartphones, drones, AR/VR platforms, and wearables. The company was founded in 2017 by members of the Israel Defense Forces’ elite intelligence unit.

https://www.hailo.ai/

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