OpenFreight

Team Name

Ctrl+Alt+Elite

Team Members

Project Description

Trucks and trains are the vital arteries of Australia's national freight network. Yet, due to commercial sensitivities and a scarcity of accessible data, the precise logistics and planning that underpin route selection for transporting freight from Point A to Point B remain largely enigmatic. Our analysis of traffic and demand patterns, however, reveals a striking insight: freight is often shipped simultaneously, resulting in road congestion, elongated travel times, and subsequently, increased fuel costs. This lack of coordination translates to lost productivity, costing the Australian economy an estimated $16.5 billion annually. At , we are committed to fostering transparency in this crucial sector. Our mission is to open-source the freight data, equipping freight operators with the essential information and tools they need to collaborate effectively and optimise their routes. Together, we are paving the way towards a more efficient and sustainable future for Australian freight.

https://www.canva.com/design/DAFsCxoUWls/08hi4TICGY4DZ2CpT_nxAw/edit?utm_content=DAFsCxoUWls&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton

Data Story

Step one - Data Collection
Major Manufacturers and Distribution Centres: Used the Google Maps Places API to identify the locations of major manufacturing plants and distribution centres across Australia. These could include facilities for automotive, electronics, machinery, and food products, among others.
Ports and Intermodal Terminals: Identify the major seaports and intermodal terminals where goods can move between trucks and trains. These could include key ports like Sydney, Melbourne, Brisbane, Perth, and Adelaide, and major intermodal terminals in these cities and others.
Commodity Data: Gather data on the broad categories of commodities moved by trucks, trains, or both. For instance, perishable goods and high-value items might be more likely to move by road, whereas bulky and heavy commodities like coal or grain might be transported more efficiently by train.

Step two - Data Analysis
Route Efficiency: Analyze potential routes between manufacturers, distribution centres, and ports/intermodal terminals. Use the Google Maps API or other routing algorithms to determine the most efficient routes based on distance, travel time, and traffic conditions for trucks. For trains, consider the existing rail infrastructure and scheduling.
Mode of Transport Decision: Based on the commodity data, determine which goods are likely to be moved exclusively by trucks, by trains, or by both. For goods that could use both modes, analyse which would be more efficient based on speed, cost, and volume.

Step three - Data Visualization
Interactive Map: Use a mapping tool (e.g., Google Maps API, ArcGIS, or QGIS) to create an interactive map that displays: Major manufacturers and distribution centres (as points) Ports and intermodal terminals (as points) Optimized routes for trucks (as lines) Railway lines for freight trains (as lines)
Summary Insights: Provide graphs and charts that summarize key insights, such as: The busiest routes used by trucks and trains and the locations of critical points in the australian freight network.