Project - Future of Public transportation

Project Info

Team Members


6 members with unpublished profiles.

Project Description


The project aims to improve the entire transportation system by using the Internet of things, face recognition and artificial intelligence. The first part focuses on using such technology to communicate between traffic lights and buses in such a way that they only encounter green lights. The system further can be integrated with cars to reduce traffic congestion and eventually get rid of traffic lights.


Data Story


We studied the data and found that the speed of public transport has been decreasing over the years, the waiting time between two buses is also extremely long. We also found that people do not want to go through the hassle of recharging or having to use MetroCards. We focused on all these problems and tried to come up with a project that would tackle these problems.


Video

Team DataSets

Public complaints received by the Department of Planning, Transport and Infrastructure

Description of Use To analyse the problem areas

Data Set

Public Transport Services

Description of Use Get information about the public transport

Data Set

Adelaide Public Transport Stop Data

Description of Use To analyse if the stop is worth keeping

Data Set

Public Transport - Timetables - For Realtime

Description of Use We looked at this data to see the conflict in time between 2 buses.

Data Set

Challenges

Reducing CBD Traffic Congestion

How to reduce traffic congestion or parking problems in CBD?

Go to Challenge | 39 teams have entered this challenge.

Public Transport for the Future

How might we combine data with modern technologies - such as AI/ML, IoT, Analytics or Natural Language interfaces - to better our public transport services. Outcomes could take the form of new commuter experiences, reduced environmental impact, or helping plan for the future.

Go to Challenge | 45 teams have entered this challenge.