Category: Uncategorized

Work Accomplished:

This week, I was working on the connection between the rasberry pi and the mobile app. Unfortunately, I ran into some networking issues with the rasberry pi. I was unable to connect it to to my desktop due to networking issues. I set up the server on the rasberry pi, but need to have the mobile app connect to the rasberry pi server to obtain the upc info. I also put in the 3D printing request to tech spark for the overall case.

Progress Status:

I expected the last connection between mobile app and rasberry pi to be finished last week, but unfortunately ran into issues. This is the last connection, however, and should be completed in the beginning of this week.

Next Week’s Goal:

• Retrieve 3D printed case
• Finish last system connection
• integration testing

 

• Worked on Allergen Filtering Module
  Developed and tested an NLP-based allergen detection function to parse ingredient lists and flag common allergens. Wrote a modular script that supports updates to allergen keywords and is usable with incoming Spoonacular ingredient strings.

• Tools Used: Python, Regular Expressions, unittest

• Next Week Goals:

  • Integrate the allergen detection with the existing barcode -> Spoonacular pipeline.

  • Connect to personalized allergens

  • Send flags via MQTT to frontend.

  • Begin testing on dietary profile filtering logic.

 

Work Accomplished:

This week, I worked on connecting the barcode scanner upc values to the mobile app and rasberry pi. This is used in order to automatically retrieve the product information from the UPC code. I also updated the 3D model’s dimensions to start printing

Progress Status:

The main data pipeline has been set up, so the additional features are the focus now in addition to testing.

Next Week’s Goal:

• Test full barcode scanner -> rasberry pi -> product query -> mobile app using real grocery products
• 3D printing techspark request

 

Progress:

• Successfully connected the Raspberry Pi to the HiveMQ Cloud MQTT broker.
• Implemented a robust publish-subscribe system to send scanned UPC data and receive product details.
• Developed and tested API calls to Spoonacular for retrieving product details, including title, brand, price, image, and ingredients.
• Published test UPC codes to HiveMQ Web Client to verify data flow from backend to frontend.
• Ensured that product information updates in real-time upon scanning new items.

Goals:

• Work closely with the frontend to integrate the correct API response format
• Implement caching for frequent scans to minimize redundant API requests

 

Progress:

Backend API Integration:

• Implemented barcode scanning API using Spoonacular UPC lookup instead of Open Food Facts, reducing API latency and improving product data accuracy.
• Optimized API usage by implementing Redis caching to store frequently scanned products and reduce redundant API calls.

Goals for Next Week:

Refine Allergen Detection & Database Structure

• Implement database indexing for faster allergen lookup queries.
• Test OpenAI API’s NLP model for edge cases in ingredient parsing.

Optimize Barcode Processing & API Calls

• Fine-tune Redis caching logic to prioritize frequently scanned items.
• Implement error handling & API fallback strategy if Spoonacular is unavailable.
• Expand the database to store scanned products for historical tracking.

Work Accomplished:

This week, I was able to successfully set up the barcode scanner connected to the rasberry pi. I created code that is able to send the UPC value to the Rasberry Pi for processing. I tested this on various items and barcodes. I was also able to create the CAD design for the 3D printed case.

Progress Status:

I am on progress as now it is able to successfully scan barcodes and send it to the rasberry pi. Now, I will focus on connecting this with Aanya’s software system to retrieve the specific product using the UPC.

Next Week’s Goal:

• Identify the product using the UPC code
• Begin 3D printing case

Work Accomplished:

This week, I focused on setting up the rasberry pi along with its power bank that was purchased through amazon. I was able to connect it to my computer and setup the initial configurations. However, I am still waiting on the barcode scanner to continue the hardware requirements of this week.

Progress Status:

I am still waiting on the delivery of the barcode scanner, which will allow me to start integrating it with the larger hardware system and connect the scanner’s output to the rasberry pi.

Next Week’s Goal:

• Scan items through the barcode scanner + rasberry pi pipeline
• Connect this with the open food facts api query

I started building out the backend for SmartCart, focusing on getting the barcode scanning and meal plan updates working together. Using FastAPI, I set up the initial API endpoints to handle barcode scans, pull product details from the Open Food Facts (OFF) API, and return structured grocery data. To make meal plans adjust in real-time, I began integrating LangChain, which takes the scanned items, checks them against the planned meals, and queries Spoonacular for substitutions if an ingredient is missing. Next week I want to focus more on the database side, to set up a PostgreSQL schema to store scanned products, user dietary preferences, and updated meal plans, along with basic CRUD operations for easy data access. The main challenges are making sure FastAPI, LangChain, Spoonacular, and OFF API communicate smoothly, improving query efficiency, and ensuring grocery matching happens in real-time without delays.

Work Accomplished:

This week, I focused on the hardware design aspects. We took a trip to ALDI on Thursday in order to mimic the customer experience and decided to make changes to our original proposal.

1. New Hardware Design
   1. Barcode Scanner – $40
   2. Rasberry Pi
      • main controller / sync with mobile app
   3. Battery Pack
2. System Flow
   1. User scans item (Barcode Scanner -> Rasberry Pi)
   2. Look up barcode in local database
   3. Extract Product Info
   4. Update App Data
   5. Display on App
3. Database
   1. online API providing ALDI UPC (public)
   2. select subset of items
   3. Exceptions: some produce did not have barcodes. We will selectively leave them out for the scope of this project as there were not many of these products.

Progress Status:

Due to changing the product design, I am behind on the original schedule that involved setting up the Jetson and camera. However, a new schedule has been made with the new design concepts in light of the change, which should keep us on track for the MVP.

Next Week’s Goal:

• Reserve Rasberry Pi and request for Barcode Scanner
• Build local database of Aldi inventory (web scraping)
  • collect UPC and allergen info etc
• CAD Prototype of clip-on device (casing + power supply)