This week, I focused on understanding how to build our new version of the people counter, as well as what would be the optimal way to train the Machine Learning Model for predicting crowdedness. For the counter, I noted down a bill of materials, and worked on understanding how to get the sensor to interact with the raspberry pi. For the Model, I gathered the appropriate data, and researched previously developed models for similar predictions. I have begun writing a script to determine other factors such as temperature that can be included in the training data to increase the model’s accuracy.
By next week, I primarily hope to have the people counter ready, so that I can begin working on collecting more data for the model. I would also like to have the current dataset fully completed by then.
I believe I am currently on schedule, although some of the previous progress was nullified due to the fact that we will no longer be using a CV model for counting people.