Submission for ACM HACKDATA- 24 Hour Hackathon under the theme 'Future Society'
UrbanSolve was born out of a deep concern for urban roads, particularly the prevalence of potholes. We observed the significant impact of potholes on road safety, vehicle maintenance costs, and overall urban aesthetics. This inspired us to develop a solution that empowers individuals to actively contribute to the improvement of their cities by reporting potholes quickly and efficiently.
UrbanSolve is a user-friendly mobile app designed to streamline the process of reporting potholes. The app leverages computer vision technology to detect potholes in real time. Users can simply point their smartphone cameras at a pothole, and the app automatically analyzes the image to verify the presence of a pothole before allowing the report to be submitted. This ensures that only valid reports are submitted, saving time for both users and authorities.
We built UrbanSolve using Flutter for the front-end development, which allowed us to create a seamless and responsive user interface across different platforms. For the backend, we utilized Firebase to store user data and pothole reports securely. The core functionality of detecting potholes in images was achieved through machine learning models trained on a carefully curated dataset of annotated images.
One of the main challenges we faced was obtaining a diverse and representative dataset for training our machine-learning models. Collecting and annotating images of potholes required significant effort and resources. Additionally, integrating the computer vision model into the mobile app while maintaining real-time performance was a complex task that required careful optimization.
We are proud of creating a user-friendly app that simplifies the process of reporting potholes, thereby contributing to improving urban road safety. The seamless integration of advanced technologies, such as computer vision and machine learning, showcases our team's technical expertise and innovation.
Developing UrbanSolve taught us valuable lessons in mobile app development, machine learning, and user experience design. We gained hands-on experience building complex applications leveraging cutting-edge technologies to solve real-world problems. We also learned the importance of user-centric design in creating impactful solutions.
In the future, we plan to enhance UrbanSolve by incorporating additional features, such as predictive maintenance for road infrastructure based on pothole reports. We also aim to expand the app's capabilities to include other types of road hazards, such as cracks and debris, further improving urban road safety. Additionally, we envision integrating UrbanSolve with city infrastructure management systems to enable more efficient maintenance and repair processes.
- Clone the Repository
git clone https://github.com/abckhush/UrbanSolve.git
- Navigate to the project directory
cd potapp12/Pothole-Detection/MOBILE_APP/UrbanSolve - Install dependencies
flutter pub get
- Run the app
flutter run
For any issues or feedback related to Urban Solve, please contact our team at:
Team Leader: kalra.khushi@outlook.com
irishittiwari@gmail.com
shubh42003@gmail.com
22mc3025@rgipt.ac.in