By With a looming global shortfall of over four million nurses projected by 2030, Foxconn has set its sights on easing this crisis using cutting-edge AI and robotics. Enter Nurabot, a collaborative nursing robot designed to handle some of the physically demanding and repetitive tasks that consume a significant portion of nurses’ time.
Nurabot isn’t just a standalone solution—it’s part of a broader vision for smart hospitals powered by NVIDIA technology. Foxconn’s ecosystem includes AI-powered health monitoring systems, virtual hospital replicas (digital twins), and real-time decision-making tools enabled through edge computing. These elements are being trialled at several major Taiwanese hospitals, including Taichung Veterans General Hospital, Baishatun Tung Hospital – Mazu Hospital, and Cardinal Tien Hospital.
A Shift Toward Smart Healthcare Infrastructure
Foxconn’s smart hospital framework leverages a three-tiered AI computing approach. At the foundation are supercomputers that train large AI models. Next, digital twins simulate hospital environments to test these models in real-world scenarios. Finally, edge devices—such as those built on NVIDIA Jetson platforms—deploy these models directly into hospitals, enabling robots like Nurabot to operate efficiently on-site.
This system-wide approach is designed not to replace healthcare professionals, but to support them in delivering higher-quality patient care. As Shu-Fang Liu of Taichung Veterans General Hospital explains, the integration of robots is allowing nurses to spend less time on logistics and more time on direct patient interaction.
From AI Models to Hospital Floors
Behind this effort is Foxconn’s Honhai Super AI Computing Center 1, which uses NVIDIA DGX systems to build AI models optimized for clinical applications. These models are deployed through the CoDoctor AI platform to assist with diagnostics, monitor vital signs, and flag conditions like arrhythmias or potential cancer indicators.
The CoDoctor platform is already in use at institutions like Taichung MetroHarbor Hospital, where it supports radiologists with image analysis. Foxconn is also introducing AI-driven video tools that monitor live feeds, detect medical events in real time, and generate video summaries for clinical and administrative teams.
Notably, Foxconn is contributing to the broader medical community through open-source collaborations. One such example is its CoroSegmentater AI model, which enhances coronary artery segmentation and will be integrated into MONAI, a medical imaging framework backed by NVIDIA. This will help clinicians visualize 3D models of vascular systems and simulate drug responses using NVIDIA’s Omniverse platform.
Digital Twins and Robotic Training
Foxconn’s use of digital twins isn’t limited to patient simulations. Hospitals are digitally replicating their physical spaces, from wards to nursing stations, to test robotic functionality before deployment. This is particularly helpful for training robots like Nurabot to navigate complex environments and adapt to real-world challenges.
Taichung Veterans General Hospital has already built a full digital replica of its facilities, allowing Nurabot to rehearse tasks such as medication delivery and corridor navigation before being introduced to live settings.
Nurabot in Action
Nurabot is the result of a collaboration between Foxconn and Kawasaki Heavy Industries. It integrates several layers of AI: natural language processing via FoxBrain, simulation training through Isaac for Healthcare, and real-time processing powered by NVIDIA Holoscan running on Jetson Orin.
Early field tests have been promising. Nurabot is currently helping deliver wound care supplies, educational materials, and even guiding patients and visitors through hospital corridors. During night shifts, when staffing is typically limited, Nurabot helps maintain essential operations without compromising patient care.
The impact is tangible. Nurses report reduced physical strain and fewer interruptions, enabling them to devote more attention to patient needs. In the future, Foxconn envisions Nurabot evolving further—communicating in multiple languages, recognizing individual patients, and potentially assisting with physically demanding tasks like repositioning bedridden patients.
A Broader Vision for the Future
The integration of AI and robotics in healthcare is no longer a distant concept. With dozens of Nurabot units planned for deployment and continued investment from major players like NVIDIA, Foxconn’s model signals a significant shift in how hospitals operate. Rather than replacing human caregivers, technology is being developed to extend their reach and improve working conditions.
The early success of Nurabot reflects a wider move toward smarter, more responsive healthcare infrastructure—one that harnesses the power of AI not just for efficiency, but to restore the human element in caregiving. As the global demand for healthcare services grows, innovations like these may well become a cornerstone of modern medicine.