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https://aswathypj27.github.io/Mind-sync/
MoodMatch is a fun dual-mode app that balances productivity and play. In Study Mode, it generates a smart study plan, tracks live study time with levels and XP, and even unlocks a “future letter” on a selected date. In Play Mode, it matches students with other players who share the same game interests using intelligent dummy matchmaking.
Many students struggle to balance academics and social life, often feeling stressed, unmotivated, or disconnected from peers who share similar interests. Existing apps focus only on productivity or only on entertainment, but not both together. There is a need for a unified platform that helps students manage their studies effectively while also connecting with others for recreational activities
We solve this by creating a dual-mode platform that combines productivity and social engagement in one app.
In Study Mode, the app generates a personalized study schedule, tracks live study time with a timer and progress levels (XP system), and includes a “Future Letter” feature that unlocks on a selected date to motivate users.
In Play Mode, the app matches students with others who share similar game interests using smart dummy matchmaking logic, helping them connect and build social interaction.
This way, the app supports both academic growth and mental well-being in a single ecosystem.
Framework: Built using Flutter (Dart) for cross-platform development (Android, Web, Desktop).
State Management: Uses StatefulWidget and setState() for dynamic UI updates.
Local Storage: Integrated SharedPreferences to store user data such as XP, study time, schedule, and future letter with unlock date persistence.
Timer System: Implemented using Dart’s Timer class to track live study sessions and calculate total study duration.
Matchmaking Logic: Uses dummy dataset filtering logic to match students based on selected game interests.
UI/UX: Custom themed UI with soft color palette, progress bars, emoji-based status indicators, and dashboard-style layout.
Navigation: Managed using Navigator.push and MaterialPageRoute for screen transitions between Login, Study Dashboard, and Play Dashboard. ### Technologies/Components Used 💻 Development Framework
Flutter – Cross-platform UI framework
Dart – Programming language used to build the app
📦 Packages & Libraries
shared_preferences – For local data storage (XP, timer data, future letter, schedule)
material.dart – For UI components and Material Design widgets
⏱ Core Components
Timer (Dart async library) – To implement live study timer
Stateful Widgets – For dynamic UI updates
Navigator & MaterialPageRoute – For screen navigation
🎨 UI Components
Scaffold
AppBar
Cards
TextField
DropdownButtonFormField
LinearProgressIndicator (for status bar)
ElevatedButton
ListView
📊 Functional Modules
Study Planner Logic
XP & Level System
Student Matchmaking (Dummy Data Filtering)
Future Letter Lock/Unlock System
Live Study Timer with Emoji Status
For Software:
For Hardware:
List the key features of your project:
The application is developed using Flutter and Dart with a modular screen-based structure.
The Study Mode includes schedule generation, XP calculation, and a live study timer implemented using Dart’s Timer.
User data such as study time, level, schedule, and future letter are stored locally using SharedPreferences for persistence.
The Play Mode uses dummy data filtering logic to match students based on selected game interests.
Navigation between screens is handled using Flutter’s Navigator and MaterialPageRoute.
User data such as study schedule, XP, timer progress, and future letter are stored locally using SharedPreferences for persistence.
The live study timer is implemented using Dart’s Timer, and student matchmaking in Play Mode is handled using dummy data filtering logic.
Navigation between screens is managed using Navigator and MaterialPageRoute.
flutter pub get
flutter run
[List all components needed with specifications]
[Explain how to set up the circuit]
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System Architecture:
Explain your system architecture - components, data flow, tech stack interaction
Application Workflow:
Add caption explaining your workflow
Add caption explaining connections
Add caption explaining the schematic
List out all components shown
Explain the build steps
Explain the final build
Base URL: https://api.yourproject.com
GET /api/endpoint
param1 (string): [Description]param2 (integer): [Description]{
"status": "success",
"data": {}
}
POST /api/endpoint
{
"field1": "value1",
"field2": "value2"
}
{
"status": "success",
"message": "Operation completed"
}
[Add more endpoints as needed…]
Explain the user flow through your application
For Android (APK):
For iOS (IPA) - TestFlight:
Building from Source:
# For Android
flutter build apk
# or
./gradlew assembleDebug
# For iOS
flutter build ios
# or
xcodebuild -workspace App.xcworkspace -scheme App -configuration Debug
| Component | Quantity | Specifications | Price | Link/Source |
|---|---|---|---|---|
| Arduino Uno | 1 | ATmega328P, 16MHz | ₹450 | [Link] |
| LED | 5 | Red, 5mm, 20mA | ₹5 each | [Link] |
| Resistor | 5 | 220Ω, 1/4W | ₹1 each | [Link] |
| Breadboard | 1 | 830 points | ₹100 | [Link] |
| Jumper Wires | 20 | Male-to-Male | ₹50 | [Link] |
| [Add more…] |
Total Estimated Cost: ₹[Amount]
Step 1: Prepare Components
Caption: All components laid outStep 2: Build the Power Supply
Caption: Power connections completedStep 3: Add Components
Caption: LED circuit assembledStep 4: [Continue for all steps…]
Final Assembly:
Caption: Completed project ready for testing
Basic Usage:
python script.py [options] [arguments]
Available Commands:
command1 [args] - Description of what command1 doescommand2 [args] - Description of what command2 doescommand3 [args] - Description of what command3 doesOptions:
-h, --help - Show help message and exit-v, --verbose - Enable verbose output-o, --output FILE - Specify output file path-c, --config FILE - Specify configuration file--version - Show version informationExamples:
# Example 1: Basic usage
python script.py input.txt
# Example 2: With verbose output
python script.py -v input.txt
# Example 3: Specify output file
python script.py -o output.txt input.txt
# Example 4: Using configuration
python script.py -c config.json --verbose input.txt
Example 1: Basic Processing
Input:
This is a sample input file
with multiple lines of text
for demonstration purposes
Command:
python script.py sample.txt
Output:
Processing: sample.txt
Lines processed: 3
Characters counted: 86
Status: Success
Output saved to: output.txt
Example 2: Advanced Usage
Input:
{
"name": "test",
"value": 123
}
Command:
python script.py -v --format json data.json
Output:
[VERBOSE] Loading configuration...
[VERBOSE] Parsing JSON input...
[VERBOSE] Processing data...
{
"status": "success",
"processed": true,
"result": {
"name": "test",
"value": 123,
"timestamp": "2024-02-07T10:30:00"
}
}
[VERBOSE] Operation completed in 0.23s
[Add your demo video link here - YouTube, Google Drive, etc.]
Explain what the video demonstrates - key features, user flow, technical highlights
[Add any extra demo materials/links - Live site, APK download, online demo, etc.]
If you used AI tools during development, document them here for transparency:
Tool Used: [e.g., GitHub Copilot, v0.dev, Cursor, ChatGPT, Claude]
Purpose: [What you used it for]
Key Prompts Used:
Percentage of AI-generated code: [Approximately X%]
Human Contributions:
Note: Proper documentation of AI usage demonstrates transparency and earns bonus points in evaluation!
This project is licensed under the [LICENSE_NAME] License - see the LICENSE file for details.
Common License Options:
Made with ❤️ at TinkerHub
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