Risks and mitigation
Currently, the most significant risk is that we may be unable to incorporate the Machine Learning part into the system due to personal reasons. Hence, we would be unable to identify different pets in the room and the creation of the different forbidden zones for each pet would not make sense anymore. To mitigate this risk, each person is implementing a different part of the project. So, we could integrate the Web App and CV only if the Machine Learning would not be available for integration, and we could add in the Machine Learning portion if it is finished before the final demo. If the system only includes the Web App and CV, then the creation of one forbidden zone for all pets and detecting if any pet enters the forbidden zone would make the most sense as we would be unable to differentiate the pets without Machine Learning.
Project Changes (why & cost)
If we are unable to add in the Machine Learning part of the project, then we would not have to use a Jetson, which is most beneficial for training the machine learning model, to support integrating the system, which would reduce the cost of the project significantly as the Jetson costs $150 and the internet adapter needed for the Jetson costs $15-30. We would start with two computers (one for Web App and one for CV) to start integrating the system. If we can integrate Machine Learning into the project, then there would be no major changes.
Schedule Changes
We are going to change the order of integration from what was listed on the schedule. We plan to start with integrating Web App and CV, specifically sending forbidden zone data chosen by the user from the Web App for the CV to detect pets that violate the forbidden zone boundaries using sockets for the interim demo. We hope to integrate parts of the Machine Learning into the project for the interim demo as Max said he is feeling better enough to help with integrating.