A motivated and detail-oriented Flutter Developer with expertise in building cross-platform mobile applications using Flutter and Dart. Proficient in state management techniques, API integration, Firebase, and Google Maps integration. Committed to clean coding principles, problem-solving, and delivering high-quality user experiences. Adept at collaborating with teams to create scalable and responsive applications.
Summary
Education
helwan University
computer science and artificial intelligence - very good
2019 - 2023
Graduation Project: Pothole Detection and Management System . degree : Excellent
Developed an AI-powered system to detect and classify potholes on roads, leveraging advanced technologies to enhance road safety and maintenance.
Skills
General
OOP
Git
Clean code
Solid principles
Problem solving
Mvvm architecture
Flutter
dart
Bloc provider
localization
Firebase
Maps
postman
Animation
Shared preferences
Database
sql(basics)
sqlite
Shared preferences
Projects
News application
news application thats Consists of 3 sections (science news , sports news , Business news) ,with shared preferences and Api
pothole detection application
application developer
mobile Application that detect any pothole in the road and send it using Api to AI model to process it and if there is a pothole we mark in the map(Google Map) red marker(Dangerous) , yellow marker(Bad) . then the government employee open the application to find the potholes location to fix it and delete it from the map .
TODO Aplication
an application that the user put on what he want to do and when to remind him
Foody application
Developed a food delivery application where users can browse menus and place orders.
Integrated payment gateway and real-time order tracking.
Implemented a dynamic UI with smooth navigation for enhanced user experience.
Graduation Project: Pothole Detection and Management System
Developed an AI-powered system to detect and classify potholes on roads, leveraging advanced technologies to enhance road safety and maintenance. Key features include:
- Pothole Detection: Utilized the YOLOv8 object detection algorithm to identify and classify potholes as "Bad" or "Dangerous" based on severity.
- Mobile Application: Built a Flutter-based Android application to capture images, display pothole locations on Google Maps, and provide real-time updates.
- Backend Development: Implemented a FastAPI-based backend to process images and store data in Firebase Firestore, ensuring efficient communication between app and server.
- Google Maps Integration: Enabled location-based visualization of potholes, allowing road authorities to prioritize repairs effectively.
The system achieved 85% accuracy in detecting potholes and demonstrated scalability and reliability during testing. It contributes to safer road conditions and streamlined maintenance processes.