Risk and Plans
What are the most significant risks that could jeopardize the success of the project? How are these risks being managed? What contingency plans are ready?
- Accelerometer only works using C code
The integration of the accelerometer gives challenges as it required a different programming approach compared to the rest of the system. While all other components and functionalities were implemented in Python, the accelerometer could only be configured and operated through C code using SPI. The python library for SPI does not work for weird reasons. This created a layer of complexity in our setup, as we had to bridge the gap between the C-based accelerometer data and the Python-based logic driving the rest of the system. The accelerometer’s dependency on C necessitated careful handling of its output, which was streamed in real-time and needed to be parsed and interpreted by the Python script. This approach introduced additional steps, such as running the C program as a subprocess, parsing its output in Python, and ensuring seamless communication between the two environments. Furthermore, debugging and troubleshooting the accelerometer involved navigating both the intricacies of C programming and its interaction with Python, which added to the technical complexity of the project. Despite these challenges, we successfully integrated the accelerometer into the system for now. However, the compiling and bridging of C code has a obvious delay in setup, which might potential mess up the system at integration and pipelining everything together.
Change in Design
Were any changes made to the existing design of the system (requirements, block diagram, system spec, etc)? Why was this change necessary, what costs does the change incur, and how will these costs be mitigated going forward?
There is no change to the existing design from this week.
Schedule Updates
Provide an updated schedule if changes have occurred.
Despite the technical challenges, our project remains on schedule. The hardware and software components have been tested individually, and integration work is beginning as planned. Next week, we will focus on:
- Accelerometer calibration for improved fall detection accuracy.
- Testing gps and phone-based geolocation to determine its feasibility for indoor positioning (continue from last week).
We are now almost for the first subsystem, the obstacle detection system using radar and audio hat. We could further improve the accuracy and make sure all use case scenarios are met with more fine tuning. As of now, the system is stable and robust for normal cases. Edge case scenarios still remain to be determined.