Team Name:
Hekaton
Team Members:
Hekaton
Using flood, fire, congestion and rest stop data the most resilient and cost-effective route can be determined while also offering live service updates depending on current road conditions to ensure safety!
Team Members (UniSC Sippy Downs):
Samuel Jorgensen
Michael Calzada
Riley Ellacott
Tyson Holscher
Firstly geometries data was converted from linestring to vector columns and plotted in MATLAB using the geoscatter function to map 106 main roads/motorways used by freight companies over Australia. Freighting companies can use this to identify alternative routes in the case of a natural disaster. Using the same method, 2000 rest stops were plotted all over Australia using latitude and longitude data on to the same geomap. Hence safe stopping locations for truck drivers can be located.
800'000 data entries from the 2020 NASA hotspot data was plotted on the same geomap using the geodensity function to show the major hotspots and severity of bushfires. This provides a visual representation of the major bushfire areas recorded over the course of a year.
Finally flood location and severity data was manually extracted from various flood maps and added to the geomap to demonstrate the ability to display affected areas and road closures.
Overall, over 1 million data entries were expertly analysed using excel and MATLAB programs. Which in turn created a interactive map that can be used to predict road closures due to natural disasters and provide safe alternative routes or resting areas.
Description of Use Bushfire hotspot data was imported into MATLAB and plotted using geodensity function to create a geomap that indicates the location and severity of bushfires in Australia over the course of a year.
Description of Use By using a multitude of flood maps, key areas of flooding along main freight routes have been plotted in MATLAB on a geomap. This will allow future road closures do to flooding to be predicted and relayed to freight companies or truck drivers.
Description of Use Firstly road geometry data was meticulously reformatted from text to columns of latitude and longitude co-ordinates. This was imported into MATLAB to plot the main freight routes of Australia. Route metrics and time data could further be incorporated to allow detail time and cost analysis for alternate routes.
Description of Use CSV file converted to excel format. Reformatted to align latitude and longitude data into columns. Imported data into MATLAB to create a geoscatter plot to allow easy identification of rest stops for truck drivers. This can be used to avoid truck drivers becoming trapped at unsafe rest stops.
Eligibility: Must use at least one dataset from the National Freight Data Hub.
Go to Challenge | 11 teams have entered this challenge.
Eligibility: Must use at least one dataset from the National Freight Data Hub.
Go to Challenge | 7 teams have entered this challenge.
Go to Challenge | 12 teams have entered this challenge.
Eligibility: Must use a least one Australian relevant dataset - combining datasets preferred.
Go to Challenge | 31 teams have entered this challenge.
