In order to improve the efficiency and quality of medical services, intelligent medical devices have emerged, such as through artificial intelligence, Internet of things and big data technologies, giving devices the ability to collect, analyze and use data to provide more accurate medical solutions for medical staff. But as technology changes, medical devices must also be updated to improve their performance, meet greater medical needs, or be able to adapt to the evolving software ecosystem. Therefore, this paper hopes to use optimization algorithms to help update intelligent medical equipment. In this paper, a modified particle swarm optimization algorithm based on the Internet of Things is used to accurately obtain the coordinates of medical equipment, so as to help medical personnel to detect the working status and internal information of the equipment in real time. In addition, this paper also verified the effectiveness of this method through comparative experiments at the end. In the comparison experiment on update time, the average update time of the experimental group based on this method was 9.36 min, while the average update time of the conventional method as the control group was 12.76 min. This fully shows that the method in this paper can indeed improve the efficiency of medical equipment updating.