Reducing CBD Traffic Congestion
How to reduce traffic congestion or parking problems in CBD?
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 39 teams have entered this challenge.
Team Name:
Team Radio
Team Members:
Project - Future of Public transportation
Project Info
Team Name
Team Radio
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6 members with unpublished profiles.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.
Team DataSets
Public complaints received by the Department of Planning, Transport and Infrastructure
Description of Use To analyse the problem areas
Public Transport Services
Description of Use Get information about the public transport
Adelaide Public Transport Stop Data
Description of Use To analyse if the stop is worth keeping
Public Transport - Timetables - For Realtime
Description of Use We looked at this data to see the conflict in time between 2 buses.
Challenge Entries
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.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 45 teams have entered this challenge.