Dashboard of Bloomy
Smartwatch Hardware
Spreadsheet of results of Pre-Building User Survey for Parents
Pre-Building User Survey for Parents Results Visual Charts
POST-SURVEY for Bloomy
Ideation Process with the Team

Inspiration

We built Bloomy after discovering a gap between concern and action.

In our pre-build survey (n = 14):

Parents rated concern about their child’s nutrition at 4.0 / 5 71% said they would test an early version Trust in sharing child health data scored 3.4 / 5

Parents clearly care — but they do not want more manual work.

We realized the issue was not awareness. It was friction.

Bloomy was designed to automatically translate daily nutrition and wellness data into structured, easy-to-understand insights.

What it does

Bloomy helps families monitor, understand, and support their child’s daily nutrition and wellness through AI-powered tracking and smartwatch-integrated reminders.

Core Features

Child Profile

Name, age, dietary preferences
Allergy and medical condition tracking
Multi-child household support

AI Food Recognition

Upload a meal photo
AI identifies food items
Returns structured nutrient breakdown (calories, macros, key nutrients)
Automatically logs meals

Nutrition Insights

Meals are interpreted into:
Meal Type (Breakfast / Lunch / Dinner / Snack)
Nutrient Status (Balanced / Lacking / Excess)
Timestamped summary

Smartwatch Integration (Hardware Prototype)

Wearable device integration
Reminders for:
Drinking water
Mealtimes
Sleep schedule
Syncs activity data to dashboard

Simplified Reports

Downloadable structured summaries
Organized nutrition logs
Centralized allergy and wellness tracking

Privacy & Parent Control

Parent-controlled settings
Secure health data storage
Transparent data handling design

How we built it

Bloomy was built using a research-first, automation-driven approach.

Frontend

React (Vite)
Responsive dashboard
Clean visual hierarchy
Hardware-integrated smartwatch interface

Backend

Python (FastAPI)
PostgreSQL database
Gemini API for food recognition
Cloud storage for uploaded images
REST architecture

System Flow

Parent uploads meal photo
Backend sends image to Gemini
AI returns structured nutrition data
Data stored in PostgreSQL
Dashboard updates automatically
Smartwatch syncs reminders and activity logs

Challenges we ran into

Designing for both parents and children
Reducing manual input while maintaining clarity
Building trust around child health data
Integrating wearable hardware with web architecture
Balancing automation with transparency

Accomplishments that we're proud of

We validated Bloomy through real user testing.

Post-survey usability test (n = 5):

Clarity score: 4.2 / 5
Ease-of-use score: 3.8 / 5
Importance of automation: 4.2 / 5
Trust rating: 3.4 / 5

Pre-survey validation (n = 14)

Concern about child nutrition: 4.0 / 5
71% expressed interest in early testing

These results confirmed:

The problem is real
Automation is highly valued
Clarity is strong
Trust and ease-of-use can be improved through iteration

What we learned

High concern does not guarantee consistent tracking — convenience drives behavior.
AI must return structured, readable outputs — not just descriptions.
Trust must be actively communicated in health-focused products.
Small UX refinements significantly impact perceived usability.
Hardware + software integration requires careful synchronization logic.