Most often, the case is that you have built a model suitable for your problem and want to use it for real-time detection. TIM requires two things for detection - model and new data.
There are a couple of things you have to care about related to data. You have to make sure that the data you are sending to TIM are in the same form as when training. It might be also useful first to read the section about required data properties. Also, to make detection possible for the chosen period, you have to include at least that amount of data which is required by the underlying model, see image below. Otherwise, points without all the expected inputs can't be calculated by the model. The length of data required differs from predictor to predictor.