Team Name:
Team 1023
Team Members:
Team 1023
Background:
In the Barossa, Gawler, Wright and Adelaide Plains regions, a lot of organic waste is often produced. So what are the opportunities for using organic waste to add value? What lessons can we learn about the treatment of organic waste on a global scale? What infrastructure/equipment is needed to implement these opportunities? We will explore these topics in this project
Approach
1. Optimal routes to use electric Scooters
2. Use AI to Detect Vehicles on Congested roads using the Traffic Cams
3. Use AI-based systems for traffic Management using the Shortlisted Traffic Cam data
Stage 1: Decision making
* For finding the optimal routes we have to see where the freights are coming and going:
* These datasets helped us in mapping topographic information:
*The information varied from bus stops, car parks, open playgrounds, parks, hospitals and schools.
*The idea behind this was to detect heavy congestion in the Australia.
Optimal Routes for using heavy Vehicles
* The choice of optimal routes is based on Heuristics.
* In our proposal, we suggested that heavy Vehicles.
Stage 2: Use AI to Detect Vehicles on Congested roads using the Traffic Cams
Stage 3: Use AI-based systems for traffic Management using the Shortlisted Traffic Cam data
Data quality
Challenges
How good is the quality of the data?
We created a data model for power BI and AI by looking at data on Australian exports mainly to New Zealand, the United States and China. The model was also created on the basis of analysing data based on exports being done mainly by sea and air.
challenge 2: Monetary Overhead
Economical Feasibility?
Using the data analysis in the first step, we worked out a proven case as a Power BI model for analysing economic costs. With this model we get an intuitive, brief overview of the relevant information
challenge 3: Technology Incorporation
By incorporating existing proven technologies into the project, we used AI vision and traffic camera detection related technologies on the technical side to support the challenge of achieving transparent tracking of shipments and reducing overheads
Eligibility: Must use at least one dataset from the National Freight Data Hub.
Go to Challenge | 7 teams have entered this challenge.
