This week, I finished the first implementation of the backend API. I also worked on writing code for the compute units on the sensor modules to be able to communicate with the backend. I mostly worked on testing and debugging the backend API by using Postman to send requests. Additionally, I changed the security settings and other parts of the AWS EC2 configuration to better fit our needs. I am on track with my schedule with my tasks. For our team, we plan on finishing up putting the sensor modules together tomorrow. Once the sensor modules are operational, the rest of the week I plan on testing communication between our sensor modules and our backend server.
Max’s Status Report for March 16, 2024
This week, I initially set up some testing for the IR sensors in both the people counter and the bench sensor modules. The supply voltage was a little unstable, so I’m looking to add the 5V voltage regulator tomorrow to help with that. I also helped Derek with some testing with the EC2 instance as we look to set up everything this week in the gym.
Our progress is on schedule, it is essential for this next week that we have the people counter and the sensor hardware set up in the UC gym so that we can begin collecting data. I do not have any immediate projects this week so I look forward to having plenty of time to work on finalizing everything.
Team Status Report for March 9, 2024
As of now, there are no significant risks in the project. We look to build our people counter and a bench sensor module this and next week, and have everything set up in the gym so that we can begin collecting data for our predictive model.
There were no big changes to the system as a whole. We have decided to focus more on the model using the people counter component along with a bench sensor set up in the gym. We look to set these up this week.
There was a slight change to our schedule with setting up the components and testing certain pieces.
Part A was written by Max Adams
While times have returned to normalcy, our product design applies to the importance of social distancing and crowd control. Our product solution addresses the need for social distancing by providing users with a mobile window and predictions on the crowding of the UC gym. While our product is specific to the UC Gym, it is scalable to other gyms. With real-time data, governing bodies can ensure that gyms are abiding by occupancy limits to ensure public health and safety are protected.
Part B was written by Sid Sapra
Our app offers a comprehensive solution to address the increasing need for efficient gym utilization, aligning with cultural values of time optimization and health consciousness prevalent in many societies today. By providing real-time tracking of gym occupancy and predictive analytics on crowdedness and machine availability, our product empowers users to plan their workouts effectively, optimizing their time spent at the gym. In cultures where time is a precious commodity and adherence to fitness routines is highly valued, our app becomes a valuable tool for individuals striving to maintain their health and fitness goals amidst busy schedules. Additionally, by fostering a sense of community and consideration for others’ workout experiences, our solution promotes a culture of shared responsibility and respect within gym environments, enhancing the overall experience for all users.
Part C was written by Derek Kim
Our system addresses excess carbon emissions by giving gym goers and gym owners a medium of tracking crowding and the real-time occupancy of a gym. At times when there is very low crowding, gym owners can save resources by reducing electricity use to lower their carbon footprint, helping the environment and saving money. Also, gym users who drive only need to travel to the gym at times best for them if there is low crowding. If a gym is very crowded users can opt for other activities or at-home workouts, thus reducing their carbon emissions.
Sid’s Status Report for March 9, 2024
Over the last weeks, I initially worked with my team to complete the design proposal. This included me finalizing and writing about the design decisions made for the machine learning model, as well as the people counter. To this end, I also met with the gym administrators, to decide the installation of the people counter on-site, and ordered the necessary parts to build it. I am also almost done writing the code for the Machine Learning Model, which should be ready to run soon.
For the following week, I hope to successfully build and test the people counter and set it up at the gym. I also want to try a few different methods for the ML Model, and begin implementing its automatic training with the newly collected data.
With these updates, I am on track with our schedule.
Max’s Status Report for March 9, 2024
This past week I began testing the active IR sensor by setting up a circuit with a voltmeter and seeing how different distances were affecting the output. I also worked on my team’s design report. We finalized the bulk of our orders and looked to begin testing this upcoming week and building our components.
We are on schedule, but we want to hastily set up the people counter and a sensor module to begin collecting data at the UC gym.
This upcoming week I’d like to have integrated the IR sensor with the NodeMCU for the bench sensor module. I would also like to finish some formal testing with the sensors themselves.
Derek’s Status Report for March 9, 2024
Since the last status report, I have mostly worked with my team to finalize our design report which consisted of communicating about design details and helping my team figure out how we will put our different components together. For my own work, I created an AWS account and stood up an EC2 instance. Additionally, I began working on implementing the Flask API for our backend. First, I specified endpoints for requests to be sent to and began implementing the logic for how different requests should be handled. I also started reading up on the Flutter documentation so that I can begin implementing the frontend user interface.
This week, I plan on finishing the backend API; I need to finish implementing the logic for handling requests on the server side and also implement the logic for sending requests to the server from both the mobile app and the computing units in the sensor modules. We are on schedule and want to have a simple implementation of our system up and running soon so that we can start collecting data.
