West Australia

WA Traffic Analysis

Team Name: 
Bit Byte Bit

We are Team Bit Byte Bit from Perth, Western Australia. At the 2016 Australian GovHack competition, we have taken the direction of crunching data obtained from Main Roads Western Australia, Bureau of Meteorology and Insurance Commission of Western Australia. Our aim is to produce an analysis report on Western Australia's motor vehicle accident rate based on traffic volume, weather conditions and motor injury insurance data.

We dwell into:

1. Correlation between Rainfall and Traffic Incidents

2. WA Traffic Incident with No Rain

Colourful Past

Colourful Past
Team Name: 
Colourful Past

Colourful Past uses machine learning to instantly and intelligently recolour historical images. It applies deep learning to images from data sources across Australia and NZ. The AI is based on research published by a team from UC Berkley, trained to use educated guesses to apply colour to photographs.


Team Name: 
Geraldton Hack

We plan to build a user friendly website and complemetary educational video and materials, to generate positive community sentiment about the benefits of migrants to regional Western Australian communities.

We are looking at communities with similar characteristics:

E-Map: Spatio-temporal modelling of traffic and emissions

Spatio-temporal modelling, prediction, analysis, new knowledge, data checking and geovisulisation system
Team Name: 

We have combined traffic volume data with NASA satellite data to predict traffic-induced emissions across the Perth Metro region.

First, we use the traffic data from the Main Roads WA data on 988 road sections in the Perth Metro region. From this, we can see the traffic volume, speed, and type, such as freight or private vehicle. Then, we use modelling to predict the volume and speed of traffic on the rest of the roads in the Perth metro region: over 10,000 road segments in total.

The Transac Initiative

Crash Test Dummies Team
Team Name: 
Crash Test Dummies


Big data analysis has often been encouraged at GovHack events over the past few years, but finding the data and sanitizing in preparation for a hack typically consumes the majority of the weekend and leaves little time for creating a finalized product, hack or prototype. This makes us sad, especially as university students who often go through this mindless and unproductive leg work as part of the typical research process. We love the open data policy the Government is championing, but like wingy kids, we're always complaining for more. Yeh, sorry.



Team Name: 
Perth Urbanist

#BudgetHack is project undertaken by Perth Urbanist for GovHack 2016. The aim of our project is to use data from the Department of Local Government and Communities' MyCouncil and the Department of Industry, Innovation and Science's Region Innovation Data to explore corrolations between what local government spends its money on and the rate of return in terms of measures of innovation.

Crash Course

Team Name: 

This project aims to discover the relationship between congestion and the type of accident that occurs under specific traffic conditions. By analysing the MRWA 2011 to 2015 Crash Data and Network Operations Traffic Data, we hope to inform the public and government of the most statistically probable traffic risks for certain levels of congestions.

MentalHelp Application

Team Name: 

MentalHelp is a mental health application for linking members of the community to appropriate mental health services in their area.

1 in 5 Australians will suffer from a mental illness in any given year. In young Western Australians it will affect almost 1 in every 3. Only a quarter of those will seek out effective help, others resorting to substance abuse, self harm before getting help or in the worst scenarios taking their own life.

Street Shark

Street Sharks
Team Name: 
Pre-crime Street Sharks

Getting home is typically a matter of choosing the shortest or fastest path. A typical directions service will choose the cheapest, or fastest, or shortest path, but when it comes to safety it's up to the user to decide based on 'gut-feeling' which way to go home.

Street Shark knits together publicly available crime data with a various predictors to build a totally JAWSOME dataset of the safest areas in your city.