Smart Cities

Machine learning (ML) and deep learning (DL) insights are used to provide OEMs and tier-1 suppliers enhanced security and operation efficiency via SafeRide Technologies’ vXRay advanced AI technology for connected vehicles.

Automotive cybersecurity company, SafeRide Technologies, believes it is the first to offer multi-layer deterministic and heuristic anomaly detection and threat prevention technology in the form of vXRay, a behavioural profiling and anomaly detection technology for connected vehicles’ security operation centres (SOC). vXRay can be integrated into connected vehicles’ SOCs independently of vehicle architecture or ECU sourcing. It can help customers uncover vulnerabilities, provide early detection of vehicle malfunctions and flag misuse and abuse problems.

vXRay uses advanced, unsupervised ML paradigms in an autonomous process to establish the vehicle’s normal behaviour without dependencies or previous knowledge of ECU properties and protocols. Once the behavioural baseline is established, the ML models can detect, categorise and flag any abnormal behaviour and report it to the vehicles’ SOC for further analysis.

Vehicle data can be used for anomaly detection, using in-vehicle analysis of signatures and error codes based on partial data, yet use limited computational power, points out SafeRide. Security measures installed in vehicles today can only detect and prevent known attacks, yet cybersecurity threats mean that OEMs need to install intrusion detection capabilities that can detect unknown threats and facilitate remediation. Upgrades with advanced intrusion detection systems can be costly, but the company believes that vXRay technology provides OEMs with immediate intrusion detection capabilities with minimal or no modifications to the vehicle platform.

SafeRide’s vXRay technology was proven to effectively detect all cyberattacks and vehicle malfunctions in multiple vehicle models in customer testing, and is being implemented by several major automotive vendors as part of their 2019 security strategies.

SafeRide will demonstrate its vXRay technology at the Automotive Grade Linux (AGL) booth 1614, Westgate Pavillion, Tech East at CES 2019 (8 to 11 January), Las Vegas.

http://www.saferide.io

Distributor, Mouser Electronics, is now stocking the SAM R34 LoRa sub-GHz system in package (SiP) family from Microchip Technology. The SAM R34 SiP devices are claimed to delivering industry-leading low-power performance for a range of IoT applications. The SiP family integrates a 32-bit microcontroller, software stack, and sub-GHz LoRa transceiver in a small 6.0 x 6.0mm package.

The Microchip SAM R34 LoRa sub-GHz SiPs, available from Mouser Electronics, incorporate a Microchip SAM L21 microcontroller based on a 32-bit Arm Cortex-M0+ core with up to 256kbytes of flash and 40kbytes of RAM. The onboard UHF transceiver supports LoRa and FSK modulation and covers frequencies from 137 to 1020MHz with maximum transmit power up to +20dBm without external amplification. The SAM R34 family is supported by Microchip’s LoRaWAN protocol stack and supports Class A and Class C end devices, as well as proprietary point-to-point connections.

The SiPs offer sleep modes as low as 790nA, which help to extend battery life and conserve power consumption in smart devices. The SAM R34 SiP includes a USB interface, making it suitable for USB dongle applications or for software updates via USB. The SiPs are suitable for battery-powered and sensor-based connected applications, including smart agriculture, smart city devices, and tracking devices for supply chain management.

Mouser also stocks the SAM R34 Xplained Pro evaluation kit, supported by the Atmel Studio 7 integrated development platform. The kit includes reference designs and software examples that enable engineers to develop SAM R34-based LoRa end-node applications. The kit is certified with the Federal Communications Commission (FCC), Industry Canada (IC), and Radio Equipment Directive (RED) so designs can meet government requirements across geographies.

Mouser claims to stock the world’s widest selection of the latest semiconductors and electronic components for the newest design projects. Mouser Electronics’ website is continually updated and offers advanced search methods to help customers quickly locate inventory. Mouser.com also houses data sheets, supplier-specific reference designs, application notes, technical design information, and engineering tools.

http://www.mouser.com

At CES 2019 in Las Vegas (8 to 11 January 2019), AImotive will showcase its automated driving technology.  It will display aiDrive2, aiSim2, and the silicon-proven aiWare hardware IP core.

The modular self-driving software stack aiDrive will be demoed alongside aiSim2, the autonomous technology simulator running on AImotive’s purpose-built simulation engine.

Demonstrating its highway autopilot capabilities, the aiDrive2 will run on Nvidia’s Drive PX2 embedded platform. The Budapest-based AImotive aims to encourage wider collaboration in the autonomous industry by providing a modular and customisable platform for the development of automated driving systems.

The aiSim2 simulator will also be on display. The engine has proprietary hardware and the simulator runs on a single GPU and a multi-GPU set-up side by side. The ability to ensure deterministic physically-based rendering on any hardware set-up, enables aiSim2 to drastically accelerate the development of autonomous technologies while overcoming the limitations of game engine-based simulators, explains AImotive.

The aiWare test chip will be on display in Las Vegas, running AImotive’s own algorithms to prove the capabilities of the hardware IP core when implemented on silicon. Created through a partnership between AImotive, VeriSilicon and Global Foundries, the chip runs aiWare1. AImotive is currently offering the scalable aiWare2 and aiWare3 architectures to customers looking to create smart sensors or centralised AI acceleration clusters for automotive use.

Visit AImotive at CES 2019, at Tech East North Hall booth 7538

AImotive is one of the largest independent teams in the world working towards fully self-driving car technology. It addresses challenges of autonomous mobility, powered by AI, simulation technology, and supporting hardware architectures.

It has partnered with the Khronos Group to develop the Neural Network Exchange Format (NNEF), the first neural network data exchange standard to make communication easier and more reliable between AI toolsets and inference engines.

The company was granted licenses to test their self-driving vehicle fleet in Hungary, Finland and the states of California and Nevada.

http://www.aimotive.com