The main inspiration was to make the cities smarter and safer for their citizens and to implement a 'smarter transportation infrastructure'. We know that when it comes to emergency rescues, even one second can save the life of a person currently fighting for it. And that's where we have decided to save tens of seconds or maybe minutes to help them.
What it does
It tracks the emergency vehicles and it activates the green lights on intersections based on their positions and routes to help them pass the intersections quickly, safely and fluently. This is a web application
How we built it
Our system consists of these modules:
Smart traffic lights running on Raspberry-pi with integrated algorithm and running server to process the requests for changing the lights which is built with Python
GPS application for Android and iOS as a replacement to GPS module in the vehicle, which is updating the current position of the vehicle which is built with Flutter and Firebase
Server responsible for storing the city areas, intersections, and calculating and creating a path for the emergency vehicles which is built with Java, Spring, Hibernate, Firebase, PostgreSQL, and Google APIs
Web application for the operational center for viewing the emergency vehicle's positions and creating paths for these vehicles which is built with React, Firebase, and Google APIs
Challenges we ran into
Figuring out how to integrate everything together
Accomplishments that we're proud of
We were able to come up with a good solution for the hackathon "Smart Transportation Infrastructure"
What we learned
We have mainly learnt how to cooperate, deploy apps, how to create branching strategies, and how to design and connect many different modules together.
What's next for Smart Emergency
-adding some smart devices like cameras or buttons to our traffic lights systems.
-covering the area of the whole city.
-optimization of algorithms, that create paths.
-creating client mobile applications showing the current position and path of the vehicle.
-integrating with sensors of vehicles and showing statistics for them and many more