Artificial intelligence is emerging as a practical way to strengthen hand hygiene monitoring in healthcare settings, where traditional observation often falls short because of the Hawthorne effect, high manpower demands, and limited ability to assess technique consistently. This scoping review maps the current evidence and shows that the leading approaches include computer vision, wearable sensors, IoT-integrated systems, and radar/radio frequency-based methods, all of which point toward a more objective and scalable model for compliance tracking.
At the same time, the article makes it clear that the field is still at a pre-translational stage. Beyond technical promise, real-world adoption will depend on stronger validation, ethical governance around privacy and automation bias, and pragmatic trials that demonstrate sustained clinical value in everyday healthcare workflows. For hygiene-led industries, this is a timely signal that the future of infection prevention will increasingly combine human discipline with data-driven monitoring.
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