Transforming Healthcare with Smarter Solutions Al-Assisted Diagnostic Imaging Medication i Delivery Robot Fall Detection System

Where innovation meets smarter care AAEON's Mission Where Technology Meets Healthcare Use Cases # AI-Assisted Diagnostic Imaging Fall Detection System # Medication Delivery Robot

Empowering healthcare innovators with reliable edge AI platforms that make care safer, faster, and smarter. From concept development and platform selection to mass production and after-sales support, AAEON helps bring healthcare solutions to market with confidence. /fl£p AAEON delivers dependable industrial and embedded ^ computing platforms, including motherboards, systems, rugged tablets, AI edge platforms, and wireless solutions designed for stability and long-term deployment. Working with healthcare equipment providers, AAEON develops platforms that enhance patient safety, streamline workflows,...

With the adoption of edge AI solutions increasing across sectors, many new technologies can be harnessed to streamline workflows, increase efficiency, and enhance the effectiveness of existing healthcare tools. Such examples include: AMRs can be used to deliver medication from pharmacies to wards and transport lab samples between departments. CNN-based object detection and segmentation models can be used to automatically identify anomalies in medical imaging. Embedded systems can be used in conjunction with live camera feeds to enable early detection of patient falls.

Real-world applications of edge AI in healthcare. Al-Assisted Diagnostic Imaging Supporting faster, more accurate image analysis for earlier and more confident diagnosis. Real-time monitoring and alerts to help prevent falls and improve patient safety. Continuous patient monitoring for faster insights and proactive care. Medication Delivery Robot Autonomous medication delivery to support timely, accurate, contactless care.

Case Study A medical technology startup partnered with AAEON to develop an innovative AI-assisted colonoscopy device using the BOXER-8641AI-PLUS. The objective was to increase the detection rate of subtle or ambiguous anomalies such as polyps, lesions, and adenomas during colonoscopies. Compliance with electromagnetic compatibility (EMC) standards. Capable of delivering a continuous, high-speed stream of uncompressed image data. Able to remotely update multiple systems at scale. Sufficient AI performance to execute the customer's complex object detection and image classification algorithms.

DIO Peripheral Medical Equipment NVIDIA Jetson AGX Orin Object Detection Model

AI-Assisted Diagnostic Imaging Compliant with EMC, EMI, & EMS standards for use with medical equipment. Could support an endoscopic camera for high-resolution video. ® Allowed precise execution of complex object detection algorithms. RS-232/485 & DIO to interact with peripheral equipment. Remote hardware monitoring checks. Remotely integrate new model datasets.

Case Study In a bid to leverage technological innovation to expedite the response times to falls and improve outcomes for care home residents that suffer falls, AI software development company AIRUCA teamed up with AAEON and leading systems integrator Novalux to produce the AI-Behavia FD fall detection system using the BOXER-8621AI, a Compact Fanless Embedded AI System powered by the NVIDIA® Jetson Orin Nano™ with Super Mode. Support continuous video streams from up to four network cameras without frame drops. Provide a display interface through which video feeds could be output for local monitoring....

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Fall Detection System Gigabit Ethernet for Centralized Data Acquisition The BOXER-8621AI's RJ-45 Gigabit Ethernet LAN port was able to host four network cameras through a PoE switch, providing sufficiently fast video data acquisition while maintaining stability to avoid frame drops. An Efficient Yet Powerful Al Engine An onboard NVIDIA® Jetson Orin Nano™ module offered up to 67 TOPS, making it powerful enough for the parallel processing and matrix multiplication needed to run AIRUCA's AI algorithms. Digital 10 for Dynamic Alert Mechanisms The system's network-independent digital I/O could be...

Case Study A system integrator wanted to develop a real-time, AI-powered Intensive Care Unit (ICU) monitoring station capable of analyzing patient vitals signs, detecting anomalies, and alerting medical staff to potential emergencies. To do so, they used the MIX-Q670A1 equipped with a GPU powered by the Intel® Arc ™ A750E graphics platform. Capable of handling large volumes of patient data in real time. Needed support for Wi-Fi and Bluetooth to connect medical IoT devices while ensuring secure data transmission with WPA3 encryption and TPM 2.0 Extremely strong AI performance to detect trends...

Patient Monitoring Devices Dashboard Audio Header Audio Alert Intel Arc GPU Deep Learning Model

Powerful Hybrid Computing Architecture The MIX-Q670A1 motherboard + Intel' Core™ i7-13700 CPU ensured efficient task allocation between background processes and real-time data analysis. The board's TPM 2.0, WPA3 encryption, and Intel® Hardware Shield ensured data integrity and protection for patient information. Through its PCIe Gen 5 [x16] slot, the MIX-Q670A1 could host exceptionally high-performance GPUs, such as those utilizing Intel® Arc™ A750E Graphics technology, which offered 229 TOPS of AI performance. The modular form factor enabled scalability, allowing future processors, storage,...

Case Study Noting the inefficiency of existing medication dispensation on hospital wards, a leading healthcare equipment provider developed an automated medication delivery cart. To do so, the company employed AAEON’s RICO-MX8P, a fanless PicoITX single-board computer powered by the NXP i.MX 8M Plus processor platform. The platform chosen would need to be installed within a larger robotic unit, so a small form factor was required, and fanless operation was a plus. The application would need both wired and wireless connectivity, as well as support for RFID card readers and QR code scanners. The...