We’re back with another week of component-related product news for those people interested building things, including robots, drones or other cool devices. Let’s go!
D3 Engineering’s Jetson development kit
D3 Engineering announced availability of its DesignCore NVIDIA Jetson RSP-TX2 Development Kit, enabling rapid development of autonomous and deep learning applications.
The kit includes an NVIDIA Jetson TX2 processor, six high-speed SerDes Inputs (FPD-Link III or GMSL2) for vision and spatial sensors, along with Wi-Fi, Bluetooth, Gigabit Ethernet, and USB 3.0 interfaces for control and data offload. The device supports two independent HDMI displays, and SSD and eSATA expansion options for raw data storage. The system has a rugged aluminum enclosure and connectors, making it useful for field deployments.
D3 said the kit can be used for such applications as artificial intelligence at the edge, camera monitoring systems, industrial vehicle systems, machine vision, robotics, and autonomous machines. The kit costs $3,999, and can be ordered online here. A data sheet with drawings and specifications can be accessed here.
New SmartSens CMOS image sensor
SmartSens has launched the SC4238, a 4-megapixel 1/3-inch CMOS image sensor, which combines black-illuminated pixel process technology. The sensor is aimed at the home IoT monitoring and mainstream consumer camera and professional camera markets, along with companies looking to deploy AIoT (AI + IoT) type systems.
In addition to the 4 megapixel resolution video output, the SC4238 can achieve a 2.0 μm, with sensitivity up to 2800mV/Lux’s, and a maximum signal-to-noise ratio of 39dB, the company said. The sensor can be used in many fixed focal length lenses, as well as zoom and wide field lenses. For low light and “highly complex environments”, the sensor supports a high dynamic range, with up to 100dB in HDR mode, and near-infrared enhancement, “which can effectively improve the quantum efficiency of the 850nm to 940nm band,” it added.
“With the rapid development of AIoT, the needs for human-computer interaction are slated to increase,” SmartSens said in its announcement. “High-quality CMOS image sensor products play an essential part in supporting and enhancing the performance of AIoT.”
While the SC4328 is aimed at the AIoT applications, the company said it also provides sensors for the autonomous driving, facial recognition, machine vision, and other similar applications.
Improved activity-tracking sensor
STMicroelectronics announced integrating a machine-learning component into its advanced inertial sensors that can improve activity-tracking performance and battery life in mobiles and wearables. The LSM6DSOX iNEMO sensor includes a machine-learning core that classifies motion data based on known patterns, the company said. Relieving the first stage of activity tracking from the main processor thereby saves energy and thus accelerate motion-based apps, including fitness logging, wellness monitoring, personal navigation, and fall detection.
“Machine learning is already used for fast and efficient pattern recognition in social media, financial modeling, or autonomous driving,” said Andrea Onetti, vice president in the Analog, MEMS and Sensors Group at STMicroelectronics. “The LSM6DSOX motion sensor integrates machine-learning capabilities to enhance activity tracking in smartphones and wearables.”
The company said the sensor is in full production and available now, for $2.50 for orders of 1,000 pieces.
Automotive Ethernet converter for lidar, radar connections
Intrepid Control Systems announced its RAD-Moon Duo, a device that can connect two ports of Automotive Ethernet 100BASE-T1 to two ports of a 4-wire 10/100 Ethernet (100BASE-TX), which can help high speed sensors such as lidar and radar for autonomous vehicle systems. The company said the RAD-Moon Duo “reduces the cost of autonomous systems by saving integration time, physical size, and cost per channel of sensors.”
The device includes features not yet available in Automotive Ethernet converters, such as a high-speed USB interface for configuration and monitoring, a stand-alone mode for simulations, and a LED membrane for live network status. The unit is based on two Marvell 88Q1010 Ethernet PHYs, and includes rugged packaging for use in in-vehicle autonomous vehicles.
“We doubled the value of our existing RAD-Moon device, significantly simplifying the large systems our autonomous vehicle customers are building,” said Don Hatfield, director of global sales for Intrepid Control Systems. “This, along with our other autonomous solutions we are delivering, reduce pain points and speed up autonomous vehicle development.”