Category: Rohit’s Reports

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.

This week, I focused on web application development and cloud infra setup. I was able to build an initial Django backend structure and setup basic database models for storing user data, images, and location information. I did more research and documented our approach for AWS S3 integration for image storage. Additionally, I started to work on the database schema so that we have an efficient design for image retrieval and location data storage.

From a web design standpoint, I created some initial UI mockups using Figma. We plan on reviewing these mockups as a team and make any adjustments as needed. The main struggle here has been creating the calendar view page, as this page will be the most interacted with.  How should the functionality be? What data should be presented with users? Both of these questions play a big role into what the UI will appear like.

According to our schedule, we are slightly behind on the web app development. The delay is primarily due to waiting for the hardware components to arrive for full integration testing. While a lot of the basic setup is ready, I plan to catch up by: creating mock data endpoints to simulate hardware integration, parallelize the frontend and backend dev, and set up the AWS infra ahead of the hardware arrival.

Next week, I plan on completing a basic setup of the AWS S3 bucket, implement the initial version of the calendar view interface, and create some basic API endpoints for our location data processing.

Along with all the above, I also collaborated with Will and Dhruv on the design presentation and documentation.

This week, I focused on researching and planning the web application architecture and database design.

Frontend Research and Planning:
I primarily evaluated Django’s server-rendered HTML/CSS approach for the web interface, researched responsive design patterns to ensure 30-second page load time, started planning the calendar-based interface for daily entries, and began sketching some initial UI wire frames for the daily summary view.

Database Architecture:
Regarding the database, I investigated a schema design for storing the user diary entries, associating images with timestamps, location metadata from Google Maps API, and LLM-generated summaries. I also researched heavily on efficient storage mechanisms and retrieval patterns for image data using AWS S3.

LLM Integration Planning:
I explored AWS Rekognition API capabilities for image processing and started to work on an initial design for the data pipeline for processing daily images and generating summaries. I also looked into approaches for combining images analysis with location data for better context in the summaries.

The main challenge that I am anticipating from my research this week is optimizing the database queries to meet our performance requirements, especially when fetching and displaying multiple images and summaries for a single day’s view. I anticipate we will need to implement some kind of efficient caching system to address.