The proposed uncertainty estimation module can be extended to handle dynamic environments or scenes with significant changes over time by incorporating temporal information into the feature embeddings. One approach could be to include a recurrent neural network (RNN) or a long short-term memory (LSTM) network to capture the temporal dependencies in the image sequences. By considering the evolution of features over time, the uncertainty estimation module can adapt to changes in the scene and provide more accurate predictions. Additionally, techniques such as optical flow estimation can be used to track feature movements between frames, enabling the module to account for dynamic elements in the environment.