Overview
As medical device innovation continues to push toward more compact and intelligent diagnostic systems, engineering teams face increasing pressure to balance performance, compliance, and space constraints. A medical-focused engineering design and contract manufacturing company developing an eye vision diagnostic system required a reliable embedded AI platform capable of supporting advanced image processing within a tightly integrated enclosure. Premio addressed these challenges with its compact NVIDIA Jetson-based edge computing solution designed for medical-grade reliability and long-term deployment.
Challenges
- Need for sufficient AI processing power to support vision-based diagnostic algorithms
- Limited internal space requiring a compact system footprint
- Requirement for multiple PoE connections to support peripheral medical imaging devices
- System integration into a larger enclosed medical device housing
- UL certification requirements for medical and regulated environments
Solution
- Premio’s Mid-Range AI Edge Computer: JCO-3000-ORN Series
- NVIDIA Jetson Orin NX 16GB for accelerated AI inference
- Support for up to 4x PoE RJ45 ports
- Slim form factor optimized for embedded installations
- UL certified industrial design
Benefits
- Reliable AI performance for medical diagnostics
- Simplified system integration within compact enclosures
- Long-term support and compliance confidence
Company Overview
The company specializes in engineering design and contract manufacturing for medical device innovators. It supports customers from early concept development through full-scale production across global markets. With a strong focus on regulatory readiness and advanced technology integration, the organization continues to enable next-generation medical solutions.
The Challenges
AI Processing Demands
The eye vision diagnostic system relies on sophisticated software algorithms that require high-performance AI inference. Ensuring real-time image processing without latency was essential for accurate diagnostics. The computing platform needed to deliver this performance consistently in a medical environment.
Space Constraints
The diagnostic system was designed as a fully enclosed medical device housing multiple components. Available space for the computing platform was extremely limited. A bulky system would have complicated thermal design and overall product ergonomics.
Peripheral Connectivity
Multiple imaging and sensing peripherals required reliable power and data connectivity. The system needed native PoE support to simplify cabling and reduce additional power components. This was critical to maintaining a clean and serviceable internal layout.
Enclosure Integration
The computing platform had to mount securely within the base of a larger enclosure. Mechanical compatibility and stability were necessary to ensure long-term reliability during continuous operation. Any integration challenges could have delayed product development timelines.
Regulatory Compliance
Medical applications require adherence to strict safety and certification standards. UL certification was a non-negotiable requirement for market readiness. Without it, the system would face delays in regulatory approval and deployment.
The Solution
Compact Jetson Edge AI Platform
Premio’s Mid-Range AI Edge Computer, JCO-3000-ORN Series, provided the ideal balance of performance and size. Its industrial-grade design allowed seamless integration into the medical device enclosure. The system delivered reliable computing without compromising space.
NVIDIA Jetson Orin NX Performance
Equipped with the NVIDIA Jetson Orin NX 16GB module, the platform delivered the AI acceleration required for advanced vision diagnostics. This ensured fast, accurate inference for real-time image analysis. The performance supported future software scalability as diagnostic capabilities evolve.
Integrated PoE Connectivity
With support for up to four PoE RJ45 ports, the system simplified connections to imaging peripherals. This reduced the need for external power supplies and streamlined internal wiring. The result was a cleaner, more reliable system architecture.
Slim Form Factor Design
The JCO-3000-ORN’s slim and compact design allowed it to fit easily within the constrained enclosure space. Its low-profile build supported efficient airflow and thermal management. This enabled stable operation in a continuously running medical environment.
UL Certified Industrial Reliability
UL certification ensured the system met essential safety and compliance requirements. This reduced regulatory risk and accelerated the path to deployment. The certification also reinforced long-term reliability for mission-critical medical applications.
The Benefits
Engineering Expertise and Support
Strong application engineering and technical support ensured smooth system integration and deployment. Premio’s team provided responsive guidance throughout development. Support from its Los Angeles-based team added confidence for long-term collaboration.
Compliance-Ready Deployment
UL certification and industrial-grade design supported regulatory requirements. This minimized approval risks and shortened time to market. The platform was ready for use in regulated medical environments.
Long-Term Reliability
Designed for continuous operation, the system delivered dependable performance over extended lifecycles. This reliability is critical for medical diagnostic equipment. The solution supports future upgrades without major redesigns.
Conclusion
By leveraging a compact, high-performance NVIDIA Jetson edge AI platform, the medical engineering team successfully integrated advanced vision diagnostics into a space-constrained medical device. Premio’s solution delivered the performance, connectivity, and compliance required for regulated medical environments. The result is a reliable foundation for next-generation eye vision diagnostic systems.