Powering In-Vehicle AI at the Edge
Rugged AI edge computers designed for fleet intelligence, vehicle perception, and autonomous systems.
What is In-Vehicle AI?
In-Vehicle AI enables vehicles to process sensor and camera data in real time using embedded edge computers. This allows vehicles to analyze their surroundings, improve safety, automate operations, and optimize fleet performance.
Driver Monitoring
Multi-Camera Video Analytics
Sensor Fusion
Autonomous Navigation
Levels of In-Vehicle AI
Premio defines in-vehicle AI across four levels—Level 1: Basic AI Telematics, Level 2: Smart Fleet AI, Level 3: Advanced Vehicle Perception Systems, and Level 4: Autonomous Vehicle Systems—to simplify how AI capabilities evolve in vehicle systems, from basic monitoring to full autonomy. Each level reflects increasing AI workload complexity, sensor integration, and compute requirements.
Level 1: Basic AI Telematics
Basic AI telematics systems use embedded computing to monitor vehicle status, record video, and perform lightweight AI analytics. These systems focus on improving visibility into vehicle operations and enhancing basic safety monitoring.
Level 2: Smart Fleet AI
Smart fleet AI platforms enable vehicles to analyze multiple data sources such as cameras, sensors, and vehicle networks in real time. These systems enhance fleet safety, operational efficiency, and situational awareness.
Level 3: Advanced Vehicle Perception Systems
Advanced vehicle perception systems use high-performance AI computing to process multi-camera and sensor data for real-time environmental understanding. These platforms enable intelligent perception for robotics, industrial vehicles, and advanced transportation systems.
Level 4: Autonomous Vehicle Systems
Autonomous vehicle systems use powerful AI platforms to enable vehicles to perceive their environment, make decisions, and operate with minimal or no human intervention. These systems combine perception, localization, and planning to support autonomous mobility.
- Super-Rugged
JCO-1000-ORN Series
Entry-level AI Edge Computer
Rugged Fanless AI Edge Computers leveraging NVIDIA Jetson Orin Nano module (Up to 40 TOPS).
- Ultra-Compact Form Factor
- 2x USB 3.2 Gen2
- 4K HDMI
- Out-of-Band Module for Remote Management
JCO-3000-ORN Series
Mid-Range AI Edge Computer
Rugged fanless AI edge computers leveraging NVIDIA Jetson NX & Nano (Up to 100 TOPS)
- Support up to 4x PoE Camera
- Multiple DIO Ports with 8x/16x DIO
JCO-6000-ORN Series
High-Performance AI Edge Computer
Rugged fanless AI edge computers leveraging NVIDIA Jetson AGX Orin module (Up to 275 TOPS)
- Modular EDGEBoost I/O Support (M12/RJ45, USB, 10GbE, PoE)
- 8x USB3 Vision Locking Ports
- 8x Mini-Fakra connectors for GMSL Cameras
- Out-of-Band Port for remote management
RCO-3000 Series
Mid Range Small Form Factor Computer
High-performance within a small form factor to streamline real-time edge processing and rich I/O connectivity.
- x86 Intel Core Embedded Processors
- Modular M12/RJ45, USB, 10GbE, PoE Support
- Hot-swappable SSD Bay
- Automation-Ready Wireless Connectivity
- Fanless & Cableless
- Specialized
- Rugged
ACO-6000-RPL Series
Railway & In-Vehicle Computer
Optimized for intelligent transportation, railway systems, and rugged mobile edge deployments.
- Intel® Core™ Processors Series 2/14th/13th/12th Gen
- EN50155 & EN50121-3-2 Railway EMC Conformity
- Rich M12/RJ45, USB, CAN Bus, and Serial Connectivity
- Power Ignition Management & Wide 12-48VDC Input
- Hot-Swappable Storage & Wireless Expansion Support
- Rugged Fanless Design for Harsh Environments
RCO-6000 Series
High Performance Industrial Computer
Maximizes edge Al performance and modular EDGEBoost flexiblility for optimized edge deployments.
- Intel Core Processors
- EDGEBoost Nodes for dedicated GPU, NVMe/SATA storage, & PCIe expansion
VCO-6000 Series
Rugged Edge AI Workstation
Built for rugged edge AI deployments with high-performance Intel® Core™ processing, FHFL dual-GPU support, and fanless computing node design.
- Intel® Core™ 35W/65W processors
- FHFL dual-GPU support
- 600W GPU power budget
- Rugged fanless computing node design
RCO-1000 Series
Entry Level Industrial Mini Computer
Industrial-grade NUC Alternative optimized with low-power efficiency for lite edge workflows in space constrained deployments.
- x86 Intel Celeron Embedded Processors
- Scalable EDGEBoost I/O Support (USB, COM, DIO)
- Embedded CAN Bus
- Industrial NUC Alternative
The growing need for low-latency performance, system reliability, and data privacy is accelerating the transition from cloud-dependent AI architectures to edge-based systems that execute intelligence directly within the vehicle.
McKinsey
Key In-Vehicle AI Applications
Fleet Safety AI
Driver monitoring and incident detection.
Smart Public Transportation
Passenger analytics and surveillance.
Traffic & Smart City AI
Intersection monitoring and traffic flow analysis.
Autonomous Mobile Machines
Mining vehicles, agriculture equipment, robotics.
Must-Have Requirements for In-Vehicle AI
Scalable AI Compute
AI workloads range from edge inference to GPU-accelerated perception, requiring flexible compute platforms. (when clicked will have a dropdown like below)
Rugged Reliability
Vehicles operate in extreme temperatures, vibration, and shock conditions requiring industrial-grade hardware.
Real-Time AI Processing
Low-latency AI inference is critical for perception, safety analytics, and automated decision-making.
Industrial 5G Connectivity
Reliable ultra low-latency 5G connectivity (Wi-Fi 6E, 4G/LTE, and private 5G) enables real-time data transmission and seamless integration with cloud and fleet management systems.
Vehicle-Ready Power Design
Wide voltage input and ignition control are required for seamless integration with vehicle power systems.
E-Mark Certification for In-Vehicle AI
In-vehicle AI systems must meet strict automotive standards to ensure safe and reliable operation within transportation environments. E-mark certification verifies that electronic systems are compliant with vehicle regulations and suitable for deployment in mobile applications.
Premio in-vehicle AI platforms are designed to meet E-mark certification requirements for safe deployment across transportation and mobility applications.
Why Choose Premio
An ‘Inside Outsource’ To Your Success
With 30+ years of embedded manufacturing, Premio emphasizes its specialty in highly reliable and rugged edge computing hardware for Industry 4.0 deployment applications. Our dedicated teams ensure Premio provides swift time-to-market solutions with our global turnkey manufacturing and support infrastructure for scalable deployment.
- State-of-the-art facility in Los Angeles, California (ISO9001, ISO14001, ISO13485)
- Regulatory testing and compliance for North American market
- In-house burn-in testing and simulation chambers
- Dedicated support and supply chain teams to navigate disruptions
Real-World In-Vehicle AI Deployments
Discover how one company empowered their self driving, EV shuttles with Premio's VCO-6000-RPL.
Discover how Premio’s JCO-1000-ORN-A Series enables reliable in-vehicle AI bin detection with rugged performance, flexible customization, and support for smart waste management!
Discover how a leading provider of the material handling industry utilizes our NVIDIA Jetson AI Edge Computer for factory-floor route planning.
Explore how an automation robotics company utilizes our AI Edge Inference Computer to power their autonomous forklift solution!
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