AI-Based Food Barcode Scanner App with Data Mapping
Custom-building a mobile platform analyzing and recommending products in real-time
PROJECT IN BRIEF
Client
Bobby Parrish, food blogger, organic goods producer and distributor, recipe creator, and shopping advisor with 5M+ social media followers
Industry
FoodTech
Services
Backend development
Mobile app engineering
Integrations
Platforms
A good magician never reveals their secrets. Yet, this time we won’t keep this under the hat. Remember, a robust barcode scanner app takes a steady backend to garner a grocery barcode database, a lightweight mobile client, plus accurate AI data mapping.
Add to this reliable integrations to delegate routines like input, search, optical character recognition, and ML analytics, and you have your users at a tap. Make sure they are here to stay.
PROJECT BACKGROUND
Seeking mobility and business scaling
A popular YouTube influencer runs a food review blog focused on finding the best cost-quality ratio for products. To cover mobile and expand audience reach, the blogger devised a barcode scanner app for buyers to overview products’ nutrient profiles and make informed purchasing decisions on the spot.
CLIENT’S OBJECTIVES
Obtain a scalable and load-resistant solution for customers to analyze groceries based on their ingredients. The resulting mobile app was to support an extensive catalog, scan products, automatically analyze their composition, and provide shopping advice.
CHALLENGE
Data input and processing
The system scalability, functional reliability, and fault tolerance were mission-critical since the system was to host and process massive multisource data.
To enrich the product base, the client initially opted for manual data input, which was resource overkill. Thus, they ended up with a flawed data analysis process.
VENDOR COMPETITION WIN
The Amitech Group team weighed in on the product architecture and performance improvement, proving to be well up on microservice development and boasting massive automated AI data mapping best practices, which got us the project in the end.
SOLUTION
Food barcode scanner app
The platform is composed of backend data storage and a cross-platform mobile product information management system (PIM) for managers and buyers. Via the mobile barcode scanner app, end users get a thorough ingredient overview alongside shopping advice.
By pointing their cameras and scanning barcodes, the users make sure the product contains the approved ingredients or find out it’s better to avoid the purchase.
Both the customers and managers can add images, product descriptions, and ingredients. Managers also oversee and approve the submitted items, adjust user access, and analyze system statistics.
INTEGRATIONS
Automates manual data entry, provides food composition analytics
Automates label data extraction and analyzes it with ML
Autonomously comprehends natural language, processes, and generates it
Enables convenient full-text search for specific products
ENGINEERING STACK
TECH UNDER THE HOOD
Amazon Web Services
TypeScript, Java
PostgreSQL
React Native, React Native Reanimated, React Native Camera Kit, Redux, Firebase
Node.js, Amazon Textract, ChatGPT, Amazon S3, AWS Lambda, AWS CloudFront, Amazon EC2, Elastic Load Balancer, Amazon ECS, Amazon Route 53, Amazon ECR, REST API, Spring, Firebase
“Comprising a set of microservices that run on AWS, the solution is highly scalable, stable, fault-tolerant, and secure. The microservices ensure consistent catalog and credentials storage, user authentication, and email distribution.”
FEATURE HIGHLIGHTS
- Custom recommendation mechanism analyzes food ingredient data
- Multiparameter search allows exploring goods by store, brand, and even aisles
- Mobile PIM grants managers uninterrupted access to relevant product data
- Government-regulated database integrations sustain accurate product cataloging
WORK DONE
- Data mapping enables easy multisource data retrieval and transmission
- Persistent data management ensures data accuracy, consistency, and integrity
- Food scanner processes product labels and provides shopping advice
- Image recognition and NLP reduce manual effort with Machine Learning
Results
2M+
requests
Handled daily
7M+
scans
Processed monthly
1.1M+
products
In the catalog
4.8
stars
On the App Store and Google Play
1M+
app downloads
In 3 years
COMPLEMENTED WITH
Scalability
To smoothly tackle enormous loads
Optimization
To enable accurate data flow and app performance
Automation
To minimize human effort and error with AI food recognition
FURTHER COLLABORATION
Beyond satisfied with the outcome, the client entrusted our team with their new projects on performant website design and Shopify store development.
THE UNDERLYING MASTERY INGREDIENTS
Engagement model
Scrum Team
Team composition
- Software Architect
- Product Owner
- 2 Software Developers
Methodology
Scrum
Last updated: May 30, 2024
ABOUT THE AUTHORS
Has wizardly powers to magically bring in web and mobile platforms, thus breaking heavy eCommerce spells.
Democratizes those royally sophisticated tech phenomena by means of concise copy and occasional wit.
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