Industrial Touch Panel PCs and Monitors
IP Rated Touchscreen Computers For HMI Integration
IP Rated Touchscreen Computers For HMI Integration
Developing and improving autonomous vehicle systems and driver assistance systems (ADAS) requires massive real-world data from the various high-resolution cameras and vehicle sensors to train AV (autonomous vehicle) and ADAS (advanced driver assistant systems) algorithms. Obtaining this data requires purpose-built computing solutions capable of storing and recording data in real-time with speed and accuracy.
Premio offers AI Edge Inference computers that are engineered for autonomous vehicle fleets and ADAS data deployments. Our AI Edge inference computers leverage the latest technologies in compute, storage, and connectivity to accelerate machine learning and real-time inference in the harshest environmental settings on and off the road.
What is an Autonomous Vehicle Data Computer?
Autonomous Vehicle and ADAS Data Capture and Storage Computers are designed with powerful multi-core processors, ultra-fast NVMe SSD (solid-state drive) storage, graphic engines, and high-speed connectivity to process and store incredible amounts of data generated by vehicle sensors and high resolutions cameras on the road. With more and more test vehicles being deployed, it’s critical that autonomous vehicles manufactures leverage reliable computing solutions to ensure stable development for test drives.
Power Multi-Core Processors
Ultra-fast NVMe SSD
GPU Acceleration
High speed Connectivity
Premio’s ruggedized computing solutions are capable of capturing, processing, and storing terabytes of data generated from autonomous vehicles equipped with ADAS and smart IoT sensors. These purpose-built computing solutions can assist with autonomous vehicle development for data acquisition, logging test miles and IoT senor validation for in-vehicle deployments.
Discover EDGEBoost Nodes
The primary function of ADAS and AV computing solutions is to record raw data generated from high-resolution cameras, radar, lidar, GPS, from automotive networks and fleet vehicles. Valuable data is collected, aggregated and then offloaded from the system for further analytics. Intelligent algorithms use this data to train and enable a neural network for smarter and safer vehicles. By using AI edge inference computers for data acquisition, autonomous vehicle manufactures can track and improve intelligence through the different stages of vehicle autonomy.
Data Ingest Stage
Consist of a mixed data from a variety of sensors on the vehicles, requiring raw storage Input/output per second (IOPS)
Data Processing Stage
The data from the ingest stage is processed for metadata tagging which requires random I/O performance from storage devices
Data Training Stage
The training stage uses data for training and relies on powerful GPUs combined with robust computing solutions that provide low latency and random read throughput from the storage media.
The future of autonomous vehicles requires a wealth of data. New and emerging solutions provide the necessary infrastructure for high-performance compute as well as the successful deployment for intelligent training models. AI Edge Inference computers accelerate autonomous vehicle developments by addressing challenges in data logging and acquisition, inference analysis with real-time processing, and the ability to run machine learning models at the edge.
ADAS and autonomous vehicle computing solutions are equipped with powerful multi-core processors, providing systems with plenty of power to process and compute the Terabytes of data from a variety of sensors and high-resolution cameras.
Learn More About Hardware Accelerators
High-resolution cameras and sensors can generate ~4TB+ of data per vehicle per day. With such an enormous amount of data generation, vehicle computing solutions must be equipped with high capacity, high-speed SSD storage options that deliver high-performance and low latency. Modern day storage technology provide durable read/write options for a variety of random IOPS with incredible speed.
Learn More About NVMe
The computing solution must support multiple interfaces to log data from a variety of sensors. For this reason, ADAS and AV computers are equipped with plenty of I/O ports, such as USB Type-A ports, Serial COM ports, Gigabit Ethernet ports, PoE+ ports, GPIO, and video output ports, enabling connectivity to sensors, cameras, and vehicle buses and networks.
Learn More About Industrial I/O ports
ADAS and AV computing solutions are equipped with wired and wireless connectivity technologies, such as Gigabit Ethernet, 10 Gigabit Ethernet, Wi-Fi 6, and Cellular 4G, LTE, and 5G connectivity. Multiple connectivity options allow the computing solution to remain connected to the internet to offload mission-critical data to the cloud as well as for the system to receive over-the-air updates.
Learn More About Wireless Technologies
ADAS and AV recording computers are equipped with CANBus support to log vehicle data from vehicle buses and networks. Data logged from CANBus include vehicle speed, engine RPM, wheel speed, steering angle, and various other rich data that can provide real-time insight and valuable information about the vehicle.
Learn More About CANBus Network And Technology
ADAS and Autonomous Vehicle data recording computers are designed to endure challenging vehicle deployments where systems will be exposed to impacts, vibrations, extreme temperatures, dust, and other environmental challenges.
Learn More About Essential Computing Hardware Requirements For Edge Computing
