In recent years, with the development of medical imaging technology, low-dose computed tomography (CT) has become popular in clinical medicine. However, low-dose CT is often disturbed by noise, and the image becomes blurred, which is not conducive to diagnosis. Therefore, low-dose CT image denoising becomes an urgent problem. With the development and maturity of the Internet of Things (IoT), IoT is applied to more and more fields. It is worth mentioning that the combination of IoT technology and low-dose CT image denoising has made a significant contribution to the area of image denoising. For example, IoT provides more selectable datasets for low-dose CT image denoising. It makes real-time and automated processing of the denoising process possible, improving the efficiency of diagnosis and advancing the field of medical imaging. This paper focuses on the development of low-dose CT image denoising based on IoT technology. It describes the application of IoT in medical imaging and discusses the noise characteristics and classification of CT images. Different methods of IoT-based denoising of low-dose CT images are further discussed, as well as some current problems. Finally, new directions for future research are proposed in the hope that by combining different algorithms and techniques, the quality of low-dose CT images can be further improved to enhance a more solid guarantee for medical diagnosis.