Edge AI Vision Chips & Main Control SoCs
| Cat | Products Name | Price |
|---|---|---|
| AIMRSE-AIG-EM-001 | Industrial Robot Processor | |
| AIMRSE-AIG-EM-002 | High Performance Robot Chip | |
| AIMRSE-AIG-EM-003 | AI Powered Robot Processor | |
| AIMRSE-AIG-EM-004 | Intelligent Robot Control Chip | |
| AIMRSE-AIG-EM-005 | Multi-function Processing Chip | |
| AIMRSE-AIG-EM-006 | Multi-Pattern 3D LiDAR Module | |
| AIMRSE-AIG-EM-007 | High-Precision Single-Line LiDAR | |
| AIMRSE-AIG-EM-008 | Compact dToF 3D Scanner Unit | |
| AIMRSE-AIG-EM-009 | Long-Range 3D LiDAR Assembly | |
| AIMRSE-AIG-EM-010 | Mid-Range dToF Measurement Unit |
High-Performance Edge AI Vision Chips & Main Control SoCs
As the central computational "brain" of next-generation wearable intelligence, our Edge AI vision chips and Main Control SoCs deliver unprecedented processing power within extreme power envelopes. AIMRSE designs semiconductor solutions specifically optimized for the unique constraints of AI smart glasses, where high-speed neural processing must coexist with ultra-low thermal signatures. Our SoCs integrate high-performance NPU engines, advanced image signal processors (ISP), and comprehensive sensor fusion hubs to enable real-time object recognition, SLAM (Simultaneous Localization and Mapping), and natural language processing. Engineered for the future of ambient computing, our chips set the benchmark for efficiency, latency, and integration in the global AI wearable market.
Contact our semiconductor engineers for hardware design guides, NPU benchmarking, and SDK documentation.
Request SoC Datasheet24/5 Technical Support with <24h Response Time.
Product Overview
In the landscape of augmented reality and smart wearables, the Main Control SoC is the most critical component determining the balance between device capability and user comfort. Unlike generic mobile processors, our Edge AI vision chips are purpose-built for "Always-On" vision processing. They solve the paradox of requiring high TOPS (Tera Operations Per Second) for complex AI models while maintaining the milli-watt power consumption necessary for all-day battery life and fanless thermal management.
- On-Device AI Inference: Local execution of neural networks for privacy, security, and zero-latency response.
- Heterogeneous Computing: Optimized distribution of tasks across CPU, GPU, and dedicated NPU cores.
- Advanced Sensor Fusion: Real-time synchronization of IMU, ToF, and multiple camera streams for perfect SLAM.
- Ultra-Compact Package: Advanced Wafer-Level Chip-Scale Packaging (WLCSP) for minimal PCB footprint.
By shifting computational loads from the cloud to the edge, AIMRSE SoCs empower AI glasses to recognize faces, translate text, and provide spatial navigation in real-time, even without an active internet connection. Our architecture utilizes advanced 6nm and 4nm process nodes to maximize performance-per-watt, ensuring that smart glasses remain lightweight and cool to the touch. Whether for consumer lifestyle assistants or high-precision industrial AR headsets, our SoCs provide the stable, high-performance foundation required for the most demanding wearable applications in the AI era.
Technical Architecture Deep-Dive
Our SoC architecture is built upon four pillar technologies, each meticulously engineered to handle the specific data-heavy workloads of AI-enabled wearable vision systems. Click below to view detailed performance metrics for each core:
Proprietary NPU architecture delivering up to 4.0 TOPS for real-time AI model inference.
Neural Processing Unit (NPU)
Our third-generation NPU supports INT8 and FP16 quantization, offering native acceleration for YOLO and Transformer models. It enables sub-10ms object detection while consuming less than 100mW.
Compare NPU Tiers
High-fidelity Image Signal Processor supporting multi-camera synchronization and HDR.
Multi-Core Vision ISP
Designed for multi-sensor inputs, our ISP handles 4K/60fps video with advanced noise reduction. It features specialized hardware for low-latency video "pass-through" to AR displays.
View ISP Capability
Integrated Wireless and 6-Axis sensor hub for seamless environmental tracking.
Connectivity & Sensor Hub
Includes integrated Wi-Fi 6, BT 5.3, and a dedicated Always-On Sensor Hub. The fusion engine processes IMU and ToF data with microsecond precision for rock-solid SLAM stability.
Check Wireless Specs
Intelligent PMU for dynamic voltage scaling and extreme thermal efficiency.
Intelligent PMU Engine
Our Dynamic Voltage and Frequency Scaling (DVFS) technology adapts power usage in real-time based on workload, maximizing battery life while preventing thermal throttling.
Request Power GuideKey Features & Technical Advantages
Unrivaled Performance-per-Watt
Built on advanced semiconductor nodes, our SoCs provide up to 4 TOPS of AI performance while maintaining a sub-1W typical power consumption. This efficiency is critical for fanless AI glasses, allowing for high-speed neural network inference without causing heat discomfort for the user or requiring bulky battery packs.
Deterministic Low-Latency Processing
Our "Fast-Path" hardware architecture reduces motion-to-photon latency to under 15ms. By integrating vision sensors directly with the NPU and display engine via high-speed internal buses, we eliminate the bottlenecks common in general-purpose mobile chips, ensuring a nauseafree and perfectly synchronized AR experience.
Comprehensive SDK & AI Toolchain
We provide a unified development environment that supports major AI frameworks including TensorFlow Lite, ONNX, and PyTorch. Our compiler automatically optimizes neural network models for the NPU architecture, enabling developers to deploy complex algorithms like hand-tracking or scene semantic segmentation with minimal manual tuning.
Industrial-Grade Reliability
Our SoCs are engineered for 24/7 continuous operation in challenging environments. They support a wide temperature range (-40°C to 85°C) and feature robust ECC memory protection, making them suitable for mission-critical industrial AR applications where system failure is not an option.
Ecosystem Compatibility
Our Edge AI SoCs act as a universal integration hub, supporting a wide range of industry-standard sensors, displays, and software frameworks.
Technical Parameters Comparison
Key specifications for our Edge AI SoC series. All models support our unified AI SDK for rapid application development.
| Chip Model | NPU Performance | CPU Architecture | ISP Capability | Memory Support | Power (Typ) | Process Node |
|---|---|---|---|---|---|---|
| Vision-L1 (Entry) | 0.5 TOPS | Quad-Core A53 | 1080p @ 30fps | LPDDR3/4 | < 300mW | 12nm |
| Vision-P1 (Pro) | 2.0 TOPS | Octa-Core A55 | 2K @ 60fps | LPDDR4X | ~ 550mW | 7nm |
| Vision-E1 (Enterprise) | 4.0 TOPS | Octa-Core A76/A55 | 4K @ 60fps | LPDDR5 | ~ 900mW | 6nm |
| Vision-S1 (Special) | 1.5 TOPS | Quad-Core A73 | Dual-Stream HDR | LPDDR4X | ~ 450mW | 8nm |
Need detailed pinout diagrams or hardware design guides?
Our unified SDK provides comprehensive code samples and power profiling tools to slash your R&D time.
Typical Application Scenarios
Our Edge AI SoCs are the driving force behind modern AR innovation, enabling high-speed data processing at the eye-level across various sectors:
Real-Time Object & Face Recognition
By executing neural networks locally on the NPU, our SoCs enable instant facial recognition and object classification for security and social interaction. This on-device processing ensures that user data never leaves the device, providing enterprise-grade privacy and sub-millisecond recognition speeds in crowded environments.
Spatial SLAM & 3D Navigation
The integrated sensor fusion hub and vision acceleration cores enable high-precision SLAM for indoor navigation and 3D environment mapping. This allows AI glasses to place digital information accurately within the physical world, supporting "anchored" digital content that stays in place as the user moves.
Voice Interaction & Translation
Equipped with dedicated DSPs and AI audio processing, our SoCs support multi-language real-time translation and natural language processing (NLP). This enables hands-free operation and instant communication across language barriers, making them ideal for international business and travel applications.
Case Studies
Enterprise AR Remote Assistance
A global energy company required a hands-free AR solution for field technicians to receive real-time repair instructions. The primary challenges were high-latency video streaming in low-bandwidth remote areas and device overheating during extended use in high-temperature environments.
The Solution: High-Efficiency Vision-E1 SoC Deployment
The client implemented our Vision-E1 SoC, which leveraged its dedicated H.265 hardware encoder to reduce video stream bandwidth by 50% while maintaining 4K clarity. The NPU was used to perform local "Region of Interest" (RoI) detection, focusing bandwidth only on critical components. The chip's advanced thermal management allowed for 4 hours of continuous high-load operation without external cooling.
Operational Excellence
60% Reduction in Downtime
The deployment resulted in a 60% reduction in equipment downtime. By enabling clear, low-latency remote communication and local AI-driven diagnostic overlays, technicians solved complex issues faster, and the company saved over $2M in annual travel costs for senior specialists.
Why Choose Our SoC Solutions
Semiconductor Excellence
With over a decade in silicon design and vision algorithms, our team delivers world-class semiconductor reliability and performance optimization tailored for the wearable market.
Security-First Architecture
Our SoCs feature hardware-based Root of Trust, Secure Boot, and TEE (Trusted Execution Environment), ensuring that biometric data and sensitive vision feeds are protected from unauthorized access.
Long-Term Supply Support
We guarantee a minimum 7 to 10-year supply lifecycle for our flagship industrial SoCs, providing the stability and peace of mind required for long-term enterprise product roadmaps.
Frequently Asked Questions
What AI models are natively supported by your NPU toolchain?
Our unified AI toolchain supports the most popular neural network architectures including CNNs (YOLOv5/v8, MobileNetV2/V3, ResNet), RNNs, and increasingly Transformers for NLP tasks. We provide a model conversion tool that translates standard ONNX or TensorFlow Lite files into NPU-optimized instructions, maximizing hardware utilization while ensuring minimal accuracy loss through INT8/FP16 quantization.
How do you handle the high power consumption and thermal issues of AI chips in glasses?
Thermal management is at the core of our "Wearable-First" design philosophy. By utilizing advanced 6nm and 7nm process nodes, we significantly reduce leakage current. Furthermore, our architecture offloads repetitive tasks to specialized low-power hardware blocks (like the ISP and Sensor Fusion Hub) instead of the main CPU, allowing the device to remain cool during "Always-On" vision tasks.
What kind of software support is provided for SLAM and spatial tracking?
We provide a pre-optimized SLAM library as part of our SDK, which is designed to take full advantage of our SoC's heterogeneous architecture. The library fuses data from the 6-axis IMU and stereo cameras with sub-millisecond precision. Developers can also integrate third-party SLAM solutions via our standard ROS2 or OpenXR middleware layers for specialized navigation requirements.
Can these chips operate without a persistent cloud or internet connection?
Yes. Our Edge AI SoCs are designed for fully autonomous "Local Inference." This means object recognition, voice commands, and spatial tracking are processed entirely on-device. This not only eliminates the privacy concerns and latency of cloud processing but also ensures that critical AR functions remain operational in remote or offline environments where internet access is unavailable.
What is the typical development cycle for integrating your SoC into a new AR product?
A typical integration cycle ranges from 6 to 12 months. To accelerate this process, we offer comprehensive "Reference Design Kits" (RDKs) that include a production-ready PCB layout, BSP (Board Support Package), and validated drivers for common cameras and displays. Our dedicated technical support team also provides design reviews and remote debugging to help you transition from prototype to mass production.
Related Products
Technical data represent typical values. As applications vary, we recommend consulting our technical team to ensure the best fit for your specific requirements.
Contact Form
