Author: ziz500

This week I worked on setting up a Google Cloud account and gaining access to the Google Maps APIs. After doing that, I was able to play around with the API  and read more documentation to gain insight on how it works. Initially, I thought that we would need another API (maybe Overpass) to be able to geocode intersections, however I figured out that Google Maps actually has this capability, which is great. I also did research on communication latency with the Google Maps API. I expect the average will be around ~200ms, with maximum ~500ms. While this is fine, I want to implement a cache so we do not have to repeatedly ping Google Maps (hypothetically this is also a great cost-saving method).

Additionally, I worked on the design presentation slides that Colin presented on Wednesday. One particular point of feedback that I thought was important was that we currently have no form of input to our system. While Colin and I had discussed this before our presentation, we did not have time to come up with a solution since we were short on time due to pivoting. However, I think perhaps an audio input with an on-off switch (ie. button) could be a viable way of approaching this problem. I will talk more with Colin about this.

Referencing our Gantt chart, I will start implementing the backend this week. I think we are still slightly behind schedule given our late pivot, but hopefully we will be able to catch back up over the next two weeks. I will also be writing the design report with Colin.

Due to Eshita dropping the course, Colin and I have decided to quickly pivot on  our project after meeting with Prof. Mukherjee yesterday. As our team status report indicates, we’ve pivoted towards a route planning project, which helps visually impaired people navigate from point A to point B, while helping them avoid “unfriendly” crosswalks.

Because Eshita only told us she was dropping yesterday, I’ve only had time today to do research on our new project. Since alot of the focus of this project will be on route planning and identification of crosswalks, I searched through potential APIs that could be useful for this. In particular, I spent alot of time going through the Google Maps API, and looking through its capabilities.

In addition, the identification of street intersections/crosswalks is my biggest concern right now. As far as I know, the Google Maps API does not have the capability to give information on things like “the nearest intersection from point X”, or if a coordinate is an intersection or not. A potential solution I’ve found so far is the overpass API, which can given information on the location of an intersection, given two street names as input.

Due to this unforseen circumstance, I am currently behind schedule. However, Colin and I are prepared to work hard in the upcoming weeks to get back on track. For next week, I want to read more into the Google Maps and Overhead APIs, and start interacting with them, and also talk more with Colin so we can flesh out the details of the design.

This week, I was mainly focused on editing the slides and preparing for the presentation, which I presented on Monday. I appreciated the feedback and questions that we received from the Instructors and classmates, and particularly the pushback on the false positive rate, which I feel is a valid concern. As an aside, I felt that some of the feedback I received saying that I did not know the material well, or that I was underprepared, was unwarranted, as I had spent a substantial amount of time on the presentation. However, perhaps due to being too softspoken and having technical difficulties during the presentation, I was not able to reflect that.

Additionally, I have also spent a bit of time doing research on object detection algorithms for the implementation of the walk sign detection.

I am currently on schedule, as our team has put aside time in our schedule for the first four weeks, to specifically do research and flesh out our design (as well as prepare for presentations) before we start implementing.

Since I have limited experience with ML, I really want to get a head start on the material and implementation. In this upcoming week, I will be doing more research, as well as working with Eshita to find/create a dataset for walk signs fo the ML model that I will implement. Additionally, I also hope to set up a github repo and start writing down some code, if possible. Lastly, I will talk with my teammates to see if AWS may be needed for model training, and talk with the TAs and professor if we do to set that up.