Cross-Platform Productivity App Development
Budget: €8 – €40 EUR
I'm seeking a skilled app developer to create a productivity app for both Android and iOS. The app will primarily focus on car evaluations and should incorporate the following key features:
1. Introduction
1.1 Purpose
The Car Evaluation App is a mobile application designed to help users evaluate, document, and estimate the value of cars through structured data entry and guided photo documentation. The app will use AI-powered image quality checks and integrate market price comparison to provide accurate valuation reports.
1.2 Scope
Platform: Cross-platform mobile app for iOS & Android.
Framework: Developed using .NET MAUI (Multi-platform App UI).
Users: Classic car owners, collectors, insurance providers, and car dealerships.
Core Features:
Vehicle data collection (model, VIN, mileage, etc.).
Guided photo capture with AI-based image validation.
Automated valuation using market data.
PDF report generation for insurance or sales.
Admin dashboard for manual verification and approval.
2. Functional Requirements
2.1 User Management
Registration & Login
Sign up via email & password or social media (Google, Apple ID).
Secure authentication via OAuth 2.0.
Password reset functionality.
User Roles
Standard User: Can add vehicles, take photos, and generate reports.
Admin: Can verify user-submitted data and approve valuations.
Expert Reviewer: Optional role for market validation.
2.2 Vehicle Data Collection
Required Inputs:
Make, Model, Year
VIN (Vehicle Identification Number)
Mileage (in km or miles)
Restoration details
Condition rating (structured input form)
Dynamic Data Validation:
VIN lookup (via API integration with vehicle databases).
Input validation for numeric and text fields.
2.3 Guided Photo Capture & AI-Based Image Validation
Photo Guidance:
Overlay instructions for required angles: ✅ Front View
✅ Rear View
✅ Side Profiles (Left & Right)
✅ Roof / Convertible Top
✅ Engine Bay
✅ Interior (Seats, Dashboard, Door Panels)
✅ Odometer Reading
AI Image Quality Control:
Sharpness detection (no blurry images).
Lighting assessment (checks for over/underexposure).
Angle verification (detects incorrect positioning).
Object detection (ensures full vehicle visibility).
GPS & Timestamp Validation:
Photos are automatically geo-tagged and time-stamped.
Helps prevent fraud or outdated submissions.
2.4 AI-Powered Vehicle Valuation
Market Data Integration:
Pulls real-time market price comparisons from:
Classic car auctions
Online marketplaces (eBay, Classic Trader, Mobile.de)
Insurance databases
Valuation Algorithm:
Uses machine learning to assess condition vs. price history.
Provides estimated resale and insurance value.
Displays historical price trends of similar vehicles.
2.5 Report Generation & Export
Automated PDF Generation:
Includes vehicle details, photos, AI valuation, and expert notes.
Downloadable and shareable for insurance, resale, or documentation.
Export Options:
Email sharing.
Integration with insurance providers.
Cloud storage backup (Google Drive, OneDrive).
2.6 Admin & Expert Verification Dashboard
Manual Review Process:
Admins can review user submissions.
Option to approve, reject, or request corrections.
Logs and history tracking for audit purposes.
Data Analytics & Insights:
Admin dashboard with analytics on vehicle trends.
Market reports for high-value vehicles.
User activity tracking (for fraud prevention).
3. Non-Functional Requirements
3.1 Performance & Scalability
App should load within 3 seconds on modern smartphones.
AI-based image validation should process photos in under 2 seconds.
Backend API should support up to 10,000 concurrent users.
3.2 Security
Data encryption (AES-256 for stored data).
End-to-end encryption for API requests (HTTPS).
User authentication via JWT Tokens.
3.3 Compliance
GDPR compliance for user data protection.
Time & location-stamped photos for fraud prevention.
Compliance with insurance industry standards.
4. Technical Stack & Development Environment
4.1 Development Environment
Framework: .NET MAUI (Cross-platform mobile development).
Language: C#
Database: PostgreSQL / Firebase Firestore
Backend: ASP.NET Core Web API
Cloud Storage: AWS S3 or Azure Blob Storage
Authentication: Firebase Auth / Identity Server 4
AI & ML Integration:
TensorFlow for image recognition.
OpenCV for quality verification.
Azure ML for valuation algorithm.
4.2 Third-Party Integrations
Google Vision API – Image analysis.
Twilio SendGrid – Email notifications.
Stripe/PayPal – Payment gateway for premium reports.
Google Maps API – Location validation.
1. Introduction
1.1 Purpose
The Car Evaluation App is a mobile application designed to help users evaluate, document, and estimate the value of cars through structured data entry and guided photo documentation. The app will use AI-powered image quality checks and integrate market price comparison to provide accurate valuation reports.
1.2 Scope
Platform: Cross-platform mobile app for iOS & Android.
Framework: Developed using .NET MAUI (Multi-platform App UI).
Users: Classic car owners, collectors, insurance providers, and car dealerships.
Core Features:
Vehicle data collection (model, VIN, mileage, etc.).
Guided photo capture with AI-based image validation.
Automated valuation using market data.
PDF report generation for insurance or sales.
Admin dashboard for manual verification and approval.
2. Functional Requirements
2.1 User Management
Registration & Login
Sign up via email & password or social media (Google, Apple ID).
Secure authentication via OAuth 2.0.
Password reset functionality.
User Roles
Standard User: Can add vehicles, take photos, and generate reports.
Admin: Can verify user-submitted data and approve valuations.
Expert Reviewer: Optional role for market validation.
2.2 Vehicle Data Collection
Required Inputs:
Make, Model, Year
VIN (Vehicle Identification Number)
Mileage (in km or miles)
Restoration details
Condition rating (structured input form)
Dynamic Data Validation:
VIN lookup (via API integration with vehicle databases).
Input validation for numeric and text fields.
2.3 Guided Photo Capture & AI-Based Image Validation
Photo Guidance:
Overlay instructions for required angles: ✅ Front View
✅ Rear View
✅ Side Profiles (Left & Right)
✅ Roof / Convertible Top
✅ Engine Bay
✅ Interior (Seats, Dashboard, Door Panels)
✅ Odometer Reading
AI Image Quality Control:
Sharpness detection (no blurry images).
Lighting assessment (checks for over/underexposure).
Angle verification (detects incorrect positioning).
Object detection (ensures full vehicle visibility).
GPS & Timestamp Validation:
Photos are automatically geo-tagged and time-stamped.
Helps prevent fraud or outdated submissions.
2.4 AI-Powered Vehicle Valuation
Market Data Integration:
Pulls real-time market price comparisons from:
Classic car auctions
Online marketplaces (eBay, Classic Trader, Mobile.de)
Insurance databases
Valuation Algorithm:
Uses machine learning to assess condition vs. price history.
Provides estimated resale and insurance value.
Displays historical price trends of similar vehicles.
2.5 Report Generation & Export
Automated PDF Generation:
Includes vehicle details, photos, AI valuation, and expert notes.
Downloadable and shareable for insurance, resale, or documentation.
Export Options:
Email sharing.
Integration with insurance providers.
Cloud storage backup (Google Drive, OneDrive).
2.6 Admin & Expert Verification Dashboard
Manual Review Process:
Admins can review user submissions.
Option to approve, reject, or request corrections.
Logs and history tracking for audit purposes.
Data Analytics & Insights:
Admin dashboard with analytics on vehicle trends.
Market reports for high-value vehicles.
User activity tracking (for fraud prevention).
3. Non-Functional Requirements
3.1 Performance & Scalability
App should load within 3 seconds on modern smartphones.
AI-based image validation should process photos in under 2 seconds.
Backend API should support up to 10,000 concurrent users.
3.2 Security
Data encryption (AES-256 for stored data).
End-to-end encryption for API requests (HTTPS).
User authentication via JWT Tokens.
3.3 Compliance
GDPR compliance for user data protection.
Time & location-stamped photos for fraud prevention.
Compliance with insurance industry standards.
4. Technical Stack & Development Environment
4.1 Development Environment
Framework: .NET MAUI (Cross-platform mobile development).
Language: C#
Database: PostgreSQL / Firebase Firestore
Backend: ASP.NET Core Web API
Cloud Storage: AWS S3 or Azure Blob Storage
Authentication: Firebase Auth / Identity Server 4
AI & ML Integration:
TensorFlow for image recognition.
OpenCV for quality verification.
Azure ML for valuation algorithm.
4.2 Third-Party Integrations
Google Vision API – Image analysis.
Twilio SendGrid – Email notifications.
Stripe/PayPal – Payment gateway for premium reports.
Google Maps API – Location validation.