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An intelligent traffic management system to guide traffic authorities understand the trends of traffic and predict the future traffic conditions so that they can prepare themselves. Along with this it gives many other features to improve traffic control.

License: Apache License 2.0

Python 30.66% HTML 47.02% CSS 14.12% JavaScript 8.20%
algorithms data-science deep-learning machine-learning machine-learning-practice traffic-analysis traffic-control traffic-monitoring traffic-sign-classification

smartflow-traffic-manager's Introduction

SmartFlow Traffic Manager

STM is a system that is responsible for predicting traffic flow to solve congestion problems and suggest alternate routes. It also controls the traffic lights using AI to optimize the singla timing based on traffic conditions. STM helps in finding accidents and alerting the users so that any emergency measures can be taken as early as possible. Along with this it gives traffic camera analytics, dashboards, optimizing public transportations.

User: City traffic management authority.

Goal: Efficiently manage and optimize urban traffic flow using the SmartFlow Traffic Manager system.

Features

SmartFlow Traffic Manager aims to solve some of the traffic related issues emerging in India using AI with following features-

Traffic Dashboard: User can see the dashboard of current traffic conditions like each vehicle count on each hour of the day, pedestrian count on each hour, congestion areas, incidents, vehicles and pedestrian count on each direction of the road.

AI-Based Traffic Monitoring: User can see the real-time view of the video feed coming from a camera along with a map beside it. The video feed will also show the vehicles and pedestrains being detected in real-time, whereas in the map vehicles will be seen as points and user can see the route of those vehicles in the map.

Traffic Analysis: Users are able to gather past data and analyze the historical data according to their choice of date range, topic. Using this data, they can take future measures and optimize the traffic conditions by taking immediate steps.

Traffic Condition Forecasting: User can access the predictions of the traffic conditions like the vehicle count, pedestrian count, congestion areas and incidents. It shows user how many vehicles will be seen for next few hours, how much pedestrian will be seen for the next hours, whether their are any possibility of congestion and in which route that congestion will happen, is there any possibility of accidents in any route etc. User also has choice on whether they actually experienced the forecasting or not and with how much accuracy, it works as a feedback to our system.

Dynamic Traffic Signal: System gives traffic signals based on the data it is provided and getting every hour. After getting the traffic signal from the signal, user can apply that suggestion to real-time or it can skip it in case user thinks the signal is not the optimized one based on the current situation.

Incident Management: User can get real-time alerts in case any accident is noticed by the system along with information of that accident like location, best route to reach that location. User also has options of sharing this data with responsible authorities or hospitals so that victims can be taken care of immediately.

How to Run

  1. Download Anaconda.
  2. Run the git comman in git bash - !git clone https://github.com/Arup3201/SmartFlow-Traffic-Manager.git.
  3. Get inside the SmartFlow-Traffic-Manager folder.
  4. Open terminal.
  5. Run the command python -m venv .venv.
  6. Then, run the command ./.venv/Scripts/activate.
  7. Then pip install -r requirements.txt. It will take some time to install all packages, wait for some time.
  8. Finally when completely downloaded run flask --app sftm_server init-db.
  9. Then, Run flask --app sftm_server run --debug --port=5000.
  10. Open your browser and type 127.0.0.1:5000.

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