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UrbanSolve: Turning Road Frustrations into Action!

Inspiration

UrbanSolve was born out of a deep concern for the state of 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.

Screenshot_20240204-112200 Screenshot_20240204-112203 Screenshot_20240204-112206 Screenshot_20240204-112210 Screenshot_20240204-112216 Screenshot_20240204-112229 Screenshot_20240204-112232 Screenshot_20240204-112324 Screenshot_20240204-112339 Screenshot_20240204-113931 Screenshot_20240204-114006

What It Does

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.

How We Built It

We built UrbanSolve using Flutter for the frontend 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.

Challenges We Ran Into

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.

Accomplishments That We're Proud Of

We are proud of creating a user-friendly app that simplifies the process of reporting potholes, thereby contributing to the improvement of urban road safety. The seamless integration of advanced technologies, such as computer vision and machine learning, showcases our team's technical expertise and innovation.

What We Learned

Developing UrbanSolve taught us valuable lessons in mobile app development, machine learning, and user experience design. We gained hands-on experience in building complex applications that leverage cutting-edge technologies to solve real-world problems. We also learned the importance of user-centric design in creating impactful solutions.

What's Next for UrbanSolve

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.

Installation

To use Urban Solve, simply download the app from the App Store or Google Play Store and follow the on-screen instructions to set up your account.
Step - 01:
Make sure to be in the right directory (UrbanSolve).
Screenshot (1) Step - 02:
Write Command 'flutter pub get' to get all the plug-ins and packages.
Screenshot (2) Step - 03:
Write Command 'flutter pub outdated' because of incomparibility of some dependencies with other dependency.
If you are still facing some isssues run 'flutter pub get' again.
Screenshot (4) Step - 04:
Write 'flutter run' to run the app on your emulator or on your physical device.
Screenshot (6)

Support

For any issues or feedback related to Urban Solve, please contact our team at:
irishittiwari@gmail.com
22cs3035@rgipt.ac.in
shubh42003@gmail.com
22mc3025@rgipt.ac.in

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