POTHOLE DETECTION USING MACHINE LEARNING & BETTER GOVERNANCE

concept of Detection of the potholes on the public routes with the help of Machine learning and connecting local administration with the concerned user with the help of an intelligent user interface.

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Inspiration

Sir, sometimes people visit my country and they see many potholes, and also in rural areas there is no care for roads and roots, so I made this application to represent my country's condition well. My team made this "Pothole Detection Using Machine Learning to Provide Better Governance and Tourism " 

What it does

The application of this project is not limited to local routes it can also be used on the national highways and by other government entities such as the ministry of transport and NHAI. Our solution is very easy to implement and at the same time very easy to scale. We use a central cloud shared database hence it makes it easier to apply Machine Learning technologies in identifying which route is having max possibilities of potholes or which road has the maximum number of complaints registered so the administration can take action on the concerned road contractor. Our mobile application also uses GPS service so we can track our exact location. we use modern-day Machine Learning to run various analyses on the Data collected for providing a better user experience. Our cross-platform application is a smart user interface with the key features such as a camera feature to detect the pothole, GPS location tracker so that we can send the exact location to the concerned authorities. Backend Machine Learning to predict and analyze data for a better and more efficient user experience.In a governance context, Our the app is an form of a tool for the local government to promote and provide better, smart, fast and much more accessible, and much a cheap solution to connect the public issues with the concerned department and track whether action is taken or not.

How we built it

The system is developed by using the following software:

Front-End • flutter • Figma

Back-End • Cloud Firestore(NoSQL Database) • Cloud Storage • python

APIs Used • ML model • GPS

Challenges we ran into

The key issue in this is to connect the end-user with the authorities here comes the Technology which plays a vital role in the solution to this problem. Our smart user interface makes it easy for the citizens to use this app and also encourages them to use it more often as it is very easy to use and not a very complex and tedious process.

And in the technology domain, we face errors 2 times

  1. Image capture and location tracking 2.Tracking and analysis

Accomplishments that we're proud of

Best Accomplishment is we solve one of the biggest problems of India and solve the Smart India hackathon problem and also we won the national batch in this project because it is a government project.

What we learned

1 Teamwork 2 new technologies • flutter • Figma • Cloud Firestore(NoSQL Database) • Cloud Storage • python • ML model • GPS 3 audience retention about the country and many more things like how to face problems and find solutions.

What's next for POTHOLE DETECTION USING MACHINE LEARNING & BETTER GOVERNANCE

The success of Transfer Learning depends on the variety of data that might change according to the sort of vehicles, the shape of bumps and potholes, etc. Many types and shapes means difficult of learning, but big data will be helpful to solve them. Also, not a general Inception V3 but a domain-specific Convolutional Neural Networks should be considered to handle the problem well

(audience retention and providing better features in-app UI.)

The development of software or website includes so many people like user system developer, the user of the system, and the management, it is important to identify the system requirements by properly collecting required data to interact with suppliers and customers of the system. The proper design builds upon this foundation to give a blueprint, which is actually implemented by the developers. On realizing the importance of systematic documentation all the processes are implemented using a software engineering approach. Working in a live environment enables one to appreciate the intricacies involved in the System Development Life Cycle (SDLC).

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