Medical errors pose a significant threat to patient safety in Uganda, with global estimates indicating that approximately 1 in 20 patients are affected, and drug-related errors accounting for a substantial portion—up to 12% of which may result in disability or death. These errors are especially common in operating rooms, where anesthesia providers must prepare and administer multiple medications quickly under pressure. A critical point of failure is the manual matching of medications to syringes, a process vulnerable to human error. To address this issue, we propose developing a real-time wearable camera system that uses computer vision to identify medications, verify syringe matching, and immediately alert providers to potential errors at the point of selection. By integrating seamlessly into the provider’s workflow, this system aims to reduce anesthesia-related medication errors, enhance patient safety, and improve clinical outcomes in Ugandan healthcare facilities.