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Team Status Report for 3/15/2025

Will successfully resolved the Wi-Fi connection reliability issues with the Raspberry Pi Pico W, which was one of our major technical obstacles from last week. This achievement establishes a stable foundation for our hardware communication. While the Blues Notecard still has some connection challenges, progress is being made and a resolution is expected soon.

Dhruv made progress on the software backend, completing the location change detection program and implementing a simulation environment to demonstrate the system’s functionality. His work includes a map interface with user movement simulation that triggers image capture when the simulated user becomes stationary. He’s also integrated a vision model for image analysis and connected it to the OpenAI API for summary generation.

Rohit completed the implementation of the calendar view interface in Django and the API endpoints needed for handling image and location data from the hardware components. He’s also developed a working prototype of the daily summary generator using the OpenAI API, which aligns with Dhruv’s simulation work.

The most significant risks currently facing the project are:

  1. Blues Notecard Connectivity: While the Raspberry Pi Pico W connection has been stabilized, the Blues Notecard is still experiencing some connectivity issues with our hotspot. This risk is being managed by Will’s troubleshooting.
  2. Integration Between Hardware and Software Components: As we move towards integrating the hardware (Raspberry Pi Pico W, Blues Notecard, Arducam) with the software (location detection, image processing, web interface), there’s a risk of compatibility issues. We’re mitigating this by establishing clear API contracts between components and developing modular code that can be adapted if requirements change. Dhruv’s simulation environment also helps us test the software side independently of hardware completion.There have been no significant changes to the overall system design this week. The core architecture, consisting of wearable hardware for image capture, cloud infrastructure for storage and processing, and a web application for user interaction remains the same.

For the coming week, our focus will shift to:

  1. Will will continue working on the Blues Notecard configuration and then transition to setting up the Arducam.
  2. Dhruv, having made significant progress on the software backend, will assist William with the Arducam setup to accelerate hardware development.
  3. Rohit will focus on finalizing the user authentication system, implementing the settings interface, and preparing for integration testing with the hardware components.
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William’s Status Report for 3/15/2025

This week, I continued working on the script/microcontroller code with the Raspberry Pi Pico W. Last week, there were still some reliability issues with maintaining the connection. However, after adding some additional configuration code to the microcontroller, it appears that the connection is now stable, which is the main improvement from last week.

After fixing the wifi connection with the RPI Pico, I am still in progress with the configuration process of the Blues Notecard as it is also having some connecting issues with our hotspot, but I am close to getting the configuration of Blues Notecard completed.

I am still slightly behind schedule. However,  the Blues Notecard is close to being done, and I will almost next focus on the Arducam. Since Dhruv is close to being done on the software end, he will jump in to help me with the Arducam next week as well to speed up the technical development progress.

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Rohit’s Status Report – 3/15/2025

This week I made progress on the backend integration of our database models. I completed the implementation of the endpoints that will receive image and location data from the hardware components. I’ve tested these endpoints using mock data to simulate the incoming information from the Blues Notecard and verified that they correctly sore the data in our database models.

Since Will was able to resolve the connection issues, I worked on implementing a queuing system that can process incoming images. Additionally, I added error handling for cases where image uploads might fail.

My progress is now on schedule, catching up on the slight delays from last week after resolving the connectivity issues of the Pico.

For the coming week, I plan to complete the user authentication system, including account creation, login, and profile management.  I also plan to implement the settings interface that would allow users to configure the glass and image taking parameters.

I’ll also be working closely with Dhruv as he transitions to help with the hardware side to ensure that software backend remains compatible with any changes.

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status report march 15th – Dhruv

Accomplishments this week:
This week I did a lot of work on the software back-end. Specifically, I spent a lot of time coding the location change detection program and got it working. I made a dummy website to show the model of this working. I have a map with a user that can be controlled by arrow keys that shows this program working. When the user becomes stationary, a signal to capture an image is sent and I use a vision model to get details about the image. I store all these details in a string and send these to an LLM (Open AI API) to get the summary.

Reflection on Schedule:
I am ahead of schedule now and have finished a large portion of the early developments of my part for the software back-end

Plans for next week:
Since I have done a lot of the early work on my part, I will be working on the hardware next week. In specific, I will be working on getting the arducam set up with Will.

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status report 3/8/25 – Dhruv

This week I worked on the raspberry Pi Pico, blue’s notecard, and arducam to learn how to set it up. I learned what all the pins do and how to connect each one together. I also spent a lot of time working on the paper that was due. I spent time researching section 6 and 7. I have also been working on setting up our AWS. I am configuring all the roles and IAM permissions we will need for this project. I have also been working on our location change detect function and will be testing it soon when we get the hardware side working. Overall, I believe I am slightly behind schedule but can catch up soon.

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Rohit’s Status Report – 3/8/2025

For the web app, I’ve made some more progress on the Django backend structure. I completed the initial database models for users, image records, location history, and daily summaries. I’ve established the relationships between these models and implemented the basic query functions needed to retrieve and display the data efficiently. I also created the first version of the calendar view that will serve as the main interface for users to access their daily logs.

On the cloud infrastructure side, I’ve been working with Dhruv to address the AWS configuration. I researched alternative approaches for handling image storage within the AWS free tier constraints, focusing on ways to optimize our S3 bucket usage through aggressive image compression and efficient data structures.

For the frontend, I refined the UI mockups based on our design requirements and began converting them into Django templates with responsive CSS.

My progress is slightly behind schedule due to the unexpected AWS configuration challenges and the time spent on the design report. To catch up, I plan to dedicate additional hours next week to the web app dev and will parallelize certain tasks by working on the frontend and backend simultaneously.

For next week, I plan to complete implementation of the calendar view with mock data integration and finalize API endpoints for image and location data processing.

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Team Status Report for 3/8/2025

One of the most significant risks currently facing the project is ensuring stable communication between the RPI Pico W and the Blues Notecard. Initial tests are indicating some reliability issues with maintaining a Wi-Fi connection, which could impact data transmission. To mitigate this, we are experimenting with different network configurations and will consider implementing a fallback mechanism that attempts reconnection in case of failure.

On the software side, integrating cloud services remains a challenge. While we initially planned to use AWS, we are still working within the constraints of the free-tier model. If we encounter limitations, we will most likely have to pay out-of-pocket in available AWS services.

Our contingency plan involves storing data locally on the Pico W and batch uploading it when a stable connection is available.

There are currently no design changes to our system architecture.

Thus, this week, we successfully flash the RPI Pico W and establish a basic Wifi connection. We also set up initial configurations for Blues, though further debugging is required to achieve stable data transmission.

Global Factors (written by William Wang)

GlassMate addresses a global need for effortless journaling by automating image capture and AI-driven summaries. It benefits travelers, professionals, and individuals with memory challenges by reducing cognitive load and eliminating manual documentation.

The system leverages IoT and cloud computing for scalable, secure data management, making it accessible worldwide. Privacy concerns are addressed with configurable capture settings and allowing users to not use glasses when doing sensitive tasks, ensuring ethical data collection. By integrating widely supported platforms like Raspberry Pi Pico W and Django, GlassMate remains adaptable and easy-to-use for all types of interested users.

Cultural Factors (written by Dhruv Dixit)

GlassMate considers cultural sensitivities around photography and privacy, allowing users to control when and where images are taken. Multilingual support in the web app enhances accessibility across diverse communities.

Beyond personal use, GlassMate benefits professionals by enabling automated documentation of fieldwork and events during the day. Its AI-generated summaries cater to both visual and text-based memory-keeping preferences, ensuring broad cultural relevance.

Environmental Factors (Written by Rohit Chand)

GlassMate prioritizes sustainability with energy-efficient components, data compression for reduced cloud storage use, and a modular design for easy upgrades.

Its reliance on cloud-based AI processing minimizes hardware requirements, lowering energy and waste consumption. Future iterations can incorporate recycled materials, reducing e-waste while maintaining product longevity and efficiency.

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William’s Status Report for 3/8/2025

This week, I made progress on embedded development with the Raspberry Pi Pico W. I successfully flashed the microcontroller and established a basic connection to Wi-Fi. While there are still some reliability issues with maintaining the connection, I plan to debug and refine this in the coming week.

Additionally, I started experimenting with the Blues Notecard, going through the setup process and initial configuration. I encountered some challenges in getting it to properly send data, but I will continue troubleshooting and refining the integration.

Overall, while I am making progress, I am still slightly behind schedule in getting the different components to communicate effectively. My goal for next week is to establish a stable connection between the Pico W and the Blues Notecard, allowing for basic data transmission. If time permits, I will also begin working on integrating the Arducam into the system.

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Dhruv’s Status Report for 2/22/2025

This past week I spent time doing research on the software block diagram of the project. We realized this project is much more complex than we originally thought. The main concern I was researching was how to transfer images from the glasses to the cloud. My original idea was to do it through the blue’s notecard onto notehub which can connect to AWS. However, I found out that blues notecard cannot send large files and instead needs to send images in chunks. We can also send through raspberry pi but after research, I was not able to find out how large of an image we can send. Therefore, we are going to have to do tests to determine what size of image we can send. If we cannot send a large image file, we will try to compress our image down to 8kB as that is the max file size we can send in one chunk through blues notecard. I also practiced my presentation this week as I presented on Monday. We have also received our parts and I have begun brainstorming on how I will start the implementation. I am going to start with the image capture trigger as that is the start of the software pipeline and work from there.

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Rohit’s Status Report – 2/22/2025

This week, I focused on our web app dev. I spent more time researching and implementing alternative cloud solutions after learning about the AWS reimbursement limitations. I’ve explored the Google Cloud Platform as our backup option, setting up an initial testing environment to ensure that we can transition our project easily if needed.

For the web app itself, I’ve completed the initial Django project setup with basic URL routing and view templates. Additionally, I have also completed the first version of the calendar view interface which will be our main entry point for users to view in their daily summaries.

I also started working a bit on the integration with Google Maps API for location display. I’ve successfully implemented a basic map component that can display location markers based on coordinates. This will help us provide context to the captured images in the daily summaries.

During testing image compression, Dhruv found out about the some of the limitations of the Blues Notecard’s file size. Given these challenges, I’m researching on solutions on the server-side to potentially handle fragmented image data and then efficiently reconstruct the complete images and store them into our database.

My progress is slightly behind due to having to spend some time researching a new cloud infra in case we may need to pivot our project there. However, I can catch up by working on the frontend and backend dev simultaneously.

Below I’ve attached a screenshot of our UI mockup overview and database schema designs thus far.