Bench Talk

Join journalist Tommy Cummings for a weekly look at all things interesting, new, and noteworthy for design engineers.

Traditionally, we've been annoyed by backseat drivers—those people who dispense unwanted driving advice. They can be intrusive, misinformed, and can sometimes actually create the hazard they're trying to prevent. They’re no fun.

Thanks to the development of driver monitoring systems, driving advice has evolved full circle. Our backseat drivers have become assets because they're better informed and are smart driving partners, like having an additional set of eyes, ears, and brains for those doing the actual navigating. That sounds a bit more fun.

Driver monitoring systems are among the interrelated parts of advanced driver assistance systems (ADAS). They can be cameras, sensors, and processors fitted into modules in our vehicles that process data and algorithms to enhance a driver's awareness. Fully autonomous vehicles, whose technology has not been perfected, have also entered the development discussion. On top of that, design engineers face increased integration possibilities with ultra-wideband, next-generation wireless connectivity (Wi-Fi 6), and 5G access edge technologies.

But before these projects can be practically applied, they require development and secure processing connections.

In this week's New Tech Tuesdays, we'll look at development tools from Basler and Arduino and processors from NXP Semiconductors that are essential for automotive safety systems.

Computer vision applications must be tested, of course. The Basler Embedded Vision Kit with NVIDIA Jetson Nano features a plug-and-play package for rapid prototyping of computer vision applications. The kit includes a dart camera module with an S-mount lens, an NVIDIA Jetson Nano developer board, a special adapter board, and cabling to connect these components. The kit has an integrated camera driver and sample reference applications that leverage the NVIDIA Jetson platform's capabilities, giving developers a ready-to-use development package for edge artificial intelligence use cases. The NVIDIA Jetson lineup also features support for cloud-native technologies. This support helps manufacturers and developers implement improvements and use the latest features with Jetson-based AI edge devices. Two Add-on Camera Kits are also available to provide the appropriate vision extension for developers already working with a Jetson Nano processor board.

Arduino Portenta Vision Shield is a hardware add-on for the Arduino Portenta H7 development board. The add-on brings vision and sound to edge computing projects. The device can simultaneously run high-level code along with real-time tasks, making it ideal for always-on machine vision and audio applications. The shield is available with an Ethernet port or wireless Long Range (LoRA) on-board connectivity. Both share an on-board Himax low-power camera module, two microphones, and a microSD card slot for local data storage. It also has voice recognition and audio-event detection with ultra-compact and omnidirectional audio sensors.

Let's not forget the smallest components but the essential brains for these systems. NXP Semiconductors i.MX 8M Applications Processors feature up to four 1.5GHz Arm^® Cortex^®-A53 and Cortex-M4 cores for connected streaming audio/video devices, scanning-imaging devices, and various devices. The quad processors also address new requirements for streaming media and 3D graphics. The i.MX 8M support full 4K High Dynamic Range (HDR) and pro audio fidelity with up to 20 audio channels and DSD512 audio. They also include flexible memory options and high-speed connectivity in a small form factor (0.65mm pitch). NXP details its smart mobility and technologies in the Smart Mobility and the Technologies Paving the Way eBook.

Developers are finding driver monitoring technologies to help drivers be aware of events outside the range of their perception, such as pedestrians or vehicles coming from the opposite direction. The applications are broadening daily when you consider the continued development of fully autonomous vehicles. But before these technologies are put into application, they require development tools and processing systems to make sure they're on task.