Overview
Intensive care environments generate a constant stream of patient and device data, creating growing demand for computing systems that can process information locally and help clinicians act faster. An AI healthcare technology developer needed an embedded computing platform for an intelligent ICU system capable of performing AI inference while connecting multiple cameras and operating within the stringent quality expectations of medical device development. Premio’s JCO-3000-ORN Series fanless Mid-Range Edge AI Computer powered by NVIDIA Jetson Orin Nano/NX provided the processing, connectivity, customization, and manufacturing foundation needed for the application.
Challenges
- Sufficient edge AI processing performance was required to run inference workloads directly within an ICU system
- Multiple LAN connections were needed to integrate several cameras into the bedside vision system
- Wireless connectivity was required to provide Wi-Fi functionality within the system architecture
- Medical device manufacturing experience and ISO 13485-certified quality processes were essential
- UL-certified computing hardware was required to support safety and compliance objectives
Solution
- Premio’s mid-range NVIDIA Jetson AI edge computer (JCO-3000-ORN Series)
- NVIDIA Jetson Orin Nano Super 8GB delivers efficient local AI inference performance
- 4x RJ45 GbE LAN ports provide direct camera connectivity with optional PoE support
- M.2 E Key expansion enables Wi Fi and Bluetooth connectivity
- UL-certified hardware supported by ISO 13485-certified medical device manufacturing processes
Benefits
- Strong application engineering and technical support
- Long term reliability for critical medical infrastructure
- Medical focused quality and compliance support
Company Overview
Focused on transforming intensive care through predictive artificial intelligence, the healthcare technology developer converts fragmented ICU information into actionable clinical intelligence. Its platform combines bedside data integration, AI driven risk prediction, and clinical visualization to help care teams identify deterioration earlier and make more informed decisions.
The Challenges
AI Inference at the Bedside
The ICU system needed enough computing performance to run AI inference close to patient data. Edge processing helps analyze information locally without relying on continuous cloud connectivity. The platform needed efficient AI acceleration in a compact form factor.
Connecting Multiple Vision Inputs
The ICU system needed to connect several cameras for vision-based data collection. Limited Ethernet connectivity would require additional switches and cabling. Multiple LAN ports were needed to simplify integration and maintain reliable data transmission.
Adding Wireless Connectivity
Wi-Fi was also required within the system architecture. Wireless connectivity needed to coexist with Ethernet ports dedicated to cameras and other devices. Expandable Wi-Fi support gave engineers greater deployment flexibility.
Meeting Medical Quality Requirements
The developer required a computing supplier experienced in medical applications. ISO-13485 certified quality processes were important for supporting medical device manufacturing requirements. This helped align the project with the quality standards expected in healthcare environments.
Supporting Safety and Compliance
The embedded computer also needed recognized safety certification. UL-certified hardware helped support the system’s broader compliance objectives.
The Solution
Premio’s JCO-3000-ORN Series Mid-Range NVIDIA Jetson AI Edge Computer
Premio’s JCO-3000-ORN Series was selected as the AI edge computing platform for the ICU system. Its fanless design supports reliable integration within medical equipment while enabling local AI inference. Industrial grade construction further supports dependable long-term operation.
NVIDIA Jetson Orin Nano Super 8GB
The JCO-3000-ORN Series supports NVIDIA Jetson Orin NX and Orin Nano modules for different AI performance requirements. For this ICU application, the developer selected the Jetson Orin Nano Super 8GB configuration. Its up to 67 TOPS of AI performance provides efficient processing for real time AI inference at the edge.
Multi-Camera Integration at the Edge
Four RJ45 GbE LAN ports provide direct connectivity for multiple cameras. Optional PoE can deliver both power and data to compatible devices. This reduces additional networking hardware and simplifies system integration.
Expandable Wi Fi Connectivity
An M.2 E Key slot supports Wi-Fi and Bluetooth modules. Wireless connectivity can be added without using the Ethernet ports reserved for cameras. This provides greater flexibility for different hospital network environments.
Medical Manufacturing and Certified Hardware
The platform combines UL certified hardware with Premio’s ISO 13485-certified manufacturing capabilities. Premio’s medical industry experience helps support the quality requirements of healthcare technology development.
The Benefits
Engineering Support
Application engineering and technical support provide the development team with a direct resource for system integration, configuration, and troubleshooting throughout deployment.
Long-Term Reliability
Industrial grade construction, fanless operation, and a rugged hardware design help support dependable operation across the lifecycle of critical medical systems.
Medical Quality and Compliance
UL-certified hardware and ISO-13485 certified manufacturing provide a stronger foundation for meeting the quality and compliance expectations associated with medical device development.
Conclusion
By combining NVIDIA Jetson Orin edge AI performance, multi camera connectivity, wireless expansion, and certified hardware, the JCO-3000-ORN Series provided a strong foundation for real time AI inference within the ICU system. Premio’s ISO 13485 certified manufacturing capabilities and medical industry experience further supported the quality and compliance needs of the application. Together, these capabilities help enable reliable long term deployment for critical care environments.
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