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Team Status Report for April 6, 2024

– 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?

Right now, our biggest risk is the battery life of the bench sensor module. We have concluded that some data has been missing because it dies prematurely. The NodeMCU is the cause of the batteries being drained, so Max is currently looking for ways to conserve power consumption.

– 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?

No immediate changes have been made, but one might have to be made this week. Our investigation will determine if it is necessary or not to make any significant changes.

• Provide an updated schedule if changes have occurred.

We updated our schedule for the interim demo this

Status Report 8 Answer:

We have already been able to validate our system with each subsystem that is set up in the UC gym being able to communicate with our server. To validate more rigorously, we plan on replicating several scenarios with both the people counter and bench sensor on our own, and ensure that results are both real-time (as we defined) and accurate as we defined.

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Derek’s Status Report for April 6, 2024

This week, I worked on helping my team debug the sensors. The issue we had this week was with our bench sensor not collecting data properly. Our priority is to have enough data to train our machine learning model so I focused a lot of my effort into figuring out why it was not collecting data properly. The source of the issue had to do with the battery dying very quickly. I also had issues with how the backend was logging hourly data. Instead of logging only once an hour, it would log twice an hour with one entry having an occupancy value of 0.   I am currently working on a solution for this.  Additionally, there is a problem with resetting the people count each day which I am also working on.

In addition to debugging our system, I worked on adding to the front end of the app. Specifically, I worked on implementing the google maps API into the front end so that users are able to see how long it will take for them to get to the gym and how crowded it will be when they arrive.

I am currently slightly behind of schedule because of the problems we are having with our system. This week I plan on focusing all of my effort into debugging all of the software issues. I also plan on continuing to work on the front end.

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Sid’s Status Report for March 30, 2024

This week, i completed building the people counter, and worked to set it up at the gym. We first worked to set up the circuit for the counter, after which I spent some time finalizing the code for the counter to make it more accurate and less susceptible to not detecting people. This also included testing and modifying certain parameters for the sensors. After this, I worked with the team to have the counter set up at the gym, along with have a tmux session to SSH into to constantly run and monitor the code.

For the next week, I intend to get back to working on the ML model using the new weather API that I was able to find. I also want to work on building a system to collect occupancy data from the EC2 instance. Finally, I will work on the interim demo.

With these updates, I am on track with our schedule.

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Derek’s Status Report for March 30, 2024

 

This week, my team and I set up and tested our system at the gym and made sure everything was working correctly (sensors are able to detect in the gym, able to send information to the server, able to update the app live). Additionally, I ran into issues with how the server is storing the occupancy and bench data. I worked on debugging the storing of data and based on the preliminary data collected, we noticed that in the actual gym setting, the people counter may be buggy. Based on our data, we worked on tuning our sensors to be more robust. I also worked on the front end and added more past the basic functionalities of the app. 

With this update, I believe we are on the right track. Once we have collected more data, our plan is to work on how we can analyze the data to provide unique insights. Once our model is working, I also plan on testing data transmission between the machine that is hosting the model and our backend server. Additionally, I plan on further improving the usability of the mobile app while we collected data.

Our data after setting up this week:

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Max’s Status Report for March 30, 2024

I finished testing the components for both the people counter and bench sensor, and implemented the hardware for both the people counter and the bench sensor. I also implemented the software for the bench sensor and worked with Sid to implement the software for the people counter. We were able to integrate everything together with the EC2 instance and we set everything up in the gym (check our Team Report).

My progress was behind, but setting up early this week has helped me go back to schedule.

I do not have any deliverables for the week, I look to just refine both the people counter and bench sensor casing by most likely using laser-cut wood.

Here is the link to the bench sensor code: https://github.com/maxcadams/capstone-bench-sensor/blob/main/bench_sense.ino

 

 

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Team Status Report for March 30, 2024

There are no immediate risks that could jeopardize the success of our project. We have been monitoring the output of both the people counter and bench sensor systems, and they seem to be working well. We look to make a new poster and notify gym administrators to not move any equipment and also to not stand in front of the people counter as that can have an effect on the occupancy count of the gym.

No changes have been made to the existing design of the system. We have the bench sensor and the people counter as mentioned before running in the UC gym.

There has also been no updates to the schedule.

The two components set up in the gym^, people counter on the disk and the bench sensor is at the window sill.

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Derek’s Status Report for March 23, 2024

This week I worked on testing the backend API. Last week I started initial testing on Postman and this week I tested the backend with both the NodeMCU and the Raspberry Pi. I also began implementing the frontend design for the mobile app. I set up a floor layout graphic that updates bench colors as it receives bench status updates from the backend as well as display for the gym occupancy.

This week I plan on working more on the frontend. I plan on implementing the google maps feature on our app. Additionally, I want to make the mobile app design more user friendly once the basic functionalities are established. Tomorrow our team is setting up the sensor system at the gym to begin collecting data.

I am on track with my tasks and believe that our team is on the right trajectory. 

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Max’s Status Report for March 23, 2024

I finished testing all of our hardware components this week, soldering together the ADC for the people counter and performing tests on the IR sensors that will be used. I measured the distances with voltage readings and then compared these to the ADS1015 (the ADC) in the NodeMCU. I also set up the Raspberry Pi for the people counter. I have an algorithm for the bench sensors ready for set up this upcoming week.

 

 

My progress is slightly behind, I wasn’t able to set up the system in the gym with my group. Since we are finished testing everything and are putting our systems together, we are going to have the preliminary systems set up in the UC gym at the start of this week.

We’d like to have the systems up in the gym and begin analyzing the data we collect.

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Team Status Report for March 23, 2024

There are no big risks right now that could jeopardize the success of the project. Any risk was mitigated this week through our testing of components and prototypes of our subsystems. The components also interact with the E2C instance with the backend API. We will be testing in the gym tomorrow and then setting up Monday.

The only change that occurred was the IR sensor being used with the people counter. We decided to use the longer-range sensors in practice because the actual range worked better with our tests.

We are slightly behind in setting up the system in the gym, but we will be doing this early the week of 3/23.

This is our people counter prototype^

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Sid’s Status Report for March 23, 2024

This week, I worked to build and test the people counter using the Raspberry Pi. First, I built a basic setup with the team to understand the voltage values given as outputs by the IR sensors for various distances. Next, I soldered the parts and assembled the circuits. Lastly, I wrote the code for the RPi, and tested the functionality of the counter. It appears to have worked, but its values need to be tuned for the gym. Beyond this, I also worked on implementing the new Weather API, as well as on the ethics assignment.

For the next week, I intend to test the people counter at the gym, and then set up to start data collection. Furthermore, I will get back to running the ML model using the new weather API that I found.

With these updates, I am on track with our schedule.