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Autonomous Mining Equipment Market Map

Western Australia is a global leader in the adoption of autonomous mining technologies. However, there is no centralized, publicly accessible, and verifiable repository tracking autonomous mining equipment globally. This project …

Western Australia is a global leader in the adoption of autonomous mining technologies. However, there is no centralized, publicly accessible, and verifiable repository tracking autonomous mining equipment globally. This project is to build a web-based, crowdsourced, and queryable geospatial database designed to catalog every autonomous mining machine ever deployed. The objective of this project is to develop a robust Full-Stack Web Application that provides: A queryable database of global autonomous mining assets. A verified crowdsourcing mechanism allowing industry professionals to submit new kit data. An interactive GIS Map layer demonstrating geographical asset distribution. A Data Analytics Dashboard visualizing automation adoption trends across the industry. Example of data to include: Equipment Instance: Specific machine information including Type (Truck, Dozer, Loader, Drill), Manufacturer (CAT, Komatsu, Liebherr), Model, and machine-specific metadata (e.g., Max Payload, Operating Weight). Technology & Timeline: Tracking the technology provider/integrator (e.g., RCT, ASI, CAT) and the specific deployment/commissioning date. Geographic Grouping (Mine Sites): Equipment must support multi-layered grouping (e.g., individual autonomous trucks grouped under "Mine Site X", which is grouped under "Pilbara Region Operations", owned by "Company Y"). Verification Layer: To prevent misinformation, equipment must link to evidence (e.g., a URL to a press release, news story, or academic paper) to gain a 'verification' mark. Case Studies & Media: Allow users to upload or link case studies and cross-reference them with specific companies, sites, or equipment types. Technology stack is entirely up to the team to choose, but should support being deployed in a UWA IT environment as far as practical.

Client: Adrian Boeing

Location: UWA EECE

IP: Creative Commons (open source)

Spatial Data Analytics

Mineral exploration produces large volumes of spatial data, including geochemical samples, geological maps, mineral occurrences, drillholes, and geophysical observations. These datasets are often stored in different formats and can be …

Mineral exploration produces large volumes of spatial data, including geochemical samples, geological maps, mineral occurrences, drillholes, and geophysical observations. These datasets are often stored in different formats and can be difficult to query and analyse together. This project will investigate how spatial databases and Spatial SQL can support efficient geospatial data management and analysis for mineral exploration. Students will use publicly available datasets from the Geological Survey of Western Australia, such as geochemical sampling records, geological and structural layers, drillhole locations, and known mineral deposits. The input data will be imported into a spatial database such as PostgreSQL/PostGIS. Students will implement queries involving distance, intersection, containment, buffering, nearest-neighbour search, spatial aggregation, and multi-layer data integration. The desired output is a functional spatial database and a collection of reusable Spatial SQL queries for common exploration tasks, such as identifying samples near known deposits, summarising geochemical observations within a region, and finding geological structures close to target locations. A simple web interface, dashboard, map visualisation, or automatically generated analysis report may also be developed to demonstrate the results.

Client: Yihao Ding

NDA Required

Multiple Teams

IP: Open to further discussion about best IP options.

Exploration Report Mining

Spatiotemporal Information Extraction and Analysis from Mineral Exploration Reports Mineral exploration reports contain valuable historical information about where and when exploration activities were conducted, what methods were used, and what …

Spatiotemporal Information Extraction and Analysis from Mineral Exploration Reports Mineral exploration reports contain valuable historical information about where and when exploration activities were conducted, what methods were used, and what geological or mineralisation evidence was observed. However, much of this information is stored in unstructured PDF documents, making it difficult to search, compare, and analyse at a regional scale. This project will develop an AI-assisted workflow for converting exploration reports into structured spatiotemporal information. The main inputs will be publicly available mineral exploration reports and associated spatial records provided by the Geological Survey of Western Australia. Students will apply natural language processing, document parsing, and information extraction methods to identify locations, dates, commodities, exploration activities, geological observations, drilling results, and company or project names. Extracted information may be linked to report metadata, tenement boundaries, drillhole locations, and other GSWA spatial datasets. The desired output is a structured database containing the extracted entities, events, locations, and temporal relationships. Students will also develop an analysis or visualisation component, such as an interactive map, exploration timeline, regional activity summary, or trend report. The final system should allow users to explore how mineral exploration activities and reported discoveries have changed across Western Australia over time.

Client: Yihao Ding

Location: CSSE: 224

NDA Required

IP: Open to further discussion about best IP options.

Digital Occupational Therapy Assessment Guide

Technology for Ageing and Disability WA (TADWA) relies on Occupational Therapists (OTs) to conduct in-home assessments that inform the design, manufacture and installation of home modifications and assistive equipment, such …

Technology for Ageing and Disability WA (TADWA) relies on Occupational Therapists (OTs) to conduct in-home assessments that inform the design, manufacture and installation of home modifications and assistive equipment, such as ramps, handrails and mobility aids. The accuracy and completeness of these assessments are critical to downstream business processes; however, missing measurements, insufficient photographs and inconsistent documentation often result in technicians needing to revisit participant homes to collect additional information. This creates delays, increases costs and impacts the timely delivery of services to participants. This project will investigate and develop a digital assessment solution, accessible via a web or mobile application, that enables internal and external OTs to capture standardised assessment information through guided forms and mandatory fields. The solution should allow users to upload existing photos or capture photos directly within the application, linking images to specific measurements and assessment areas to ensure all required information is recorded at the point of assessment. Assessment data should be stored in a central repository and made accessible to relevant business units, reducing rework and improving information flow across the organisation. Students will explore opportunities for user-friendly design, secure external access, workflow automation and integration with existing systems, with the aim of improving efficiency, reducing repeat site visits and enhancing participant outcomes.

Client: Laura Stillone and Jayson Hitchens

Location: 371 Collier Road, Bassendean WA 6054

NDA Required

IP: Open to further discussion about best IP options.

A Tool for Comparing Neural Network Verifiers

Neural network verifiers are tools that can prove that a neural network satisfies a certain mathematical specification. There are hundreds of verifiers developed by academics around the world, and each …

Neural network verifiers are tools that can prove that a neural network satisfies a certain mathematical specification. There are hundreds of verifiers developed by academics around the world, and each one has it's own capabilities in terms of the types of neural networks it can support and the types of properties it can solve. This makes it very difficult for a user to compare and select an appropriate verifier for their problem. This project will look at building tools to allow users to freely search and compare neural network verifiers. To do so, the project will use the new VNN-LIB 2.0 standard (designed by UWA students!) that allows verifiers to report what sort of properties and networks they can handle. The final system should allow the developer of a neural network verifier to register a simple script that installs the neural network and then the system should query the verifier's capabilities and add it to a searchable database. A web-based frontend should then be constructed that allows users to search this database of verifiers for a verifier suitable for their needs. More details: The VNNLIB standard can be found at https://www.vnnlib.org/ . Currently half way down the page on the RHS, there is a small, very old and out-of-date table of compatible verifiers. The goal is to replace this table with a shiny new webpage which allows users to enter e.g. "I want a verifier that supports non-linear properties over a network with convolutional layers" and the page should list the verifiers that are suitable. No knowledge of neural networks is required to complete the project! At the same time, this project is guaranteed to have real world impact, as the VNN-LIB website is already used by 100s of academics world-wide.

Client: Dr Matthew Daggitt

Location: UWA

IP: Creative Commons (open source)

Autonomous Vehicle Job Profiles

UWA is developing a new Autonomous Vehicle (AV) course. To ensure our curriculum remains highly relevant and industry-aligned, we need clear data on the specific skills, tools, and roles currently …

AI-Enabled Smart Mooring

Recreational boat moorings are typically inspected periodically, providing limited information on their performance and condition between inspections. This project seeks to develop an AI-enabled smart mooring monitoring system that combines …

3D printer farm interface

Create a system like "print.uwa.edu.au", that allows you to upload either pre-sliced or slice online 3D printer files and then select a printer from a list and then send that …

Create a system like "print.uwa.edu.au", that allows you to upload either pre-sliced or slice online 3D printer files and then select a printer from a list and then send that file to the 3D printer. The aim of this is to create a web interface with the same functionality as "print.uwa.edu.au" and the Prusa connect software that is used to remotely send information to the printer "https://help.prusa3d.com/article/prusa-connect-and-prusalink-explained_302608?product=prusa-connect". The idea is to allow students and staff access to a printer farm through their UNI ID and ensure that the costs are accounted for and the filament for each printer is known so that the color or material is tracked. https://github.com/prusa3d/Prusa-Connect-SDK-Printer On the printing side either have the system set with pre-sliced profiles that can be sliced on the students computer and the file upload ensures that the settings in the gcode file match those that have been configured for the online interface to ensure no erroneous files are sent and that the material profiles matches the chosen machine. It should be designed for little requirements on the managing side apart from providing updates on the status of the farm and the current printers and being able to provide notifications to the student and to a farmer to collect the print and have them awaiting collection. The printers to be used are either the Prusa XL or Prusa Core one as these machines are currently available at UWA for use in this project. It would also be good to provide metrics or long term tracking regarding the consumption or usage of the printers and as a possibility having an image or web view of the printers so that the student can see their work being printed "https://www.prusa3d.com/cdn-cgi/image/width=750,format=auto,quality=85/content/wysiwyg/fotky/snapshot-Buddy3D%20Camera-1732719528.jpg"

Client: Dr Christopher Lamb

Location: The Harry Perkins Institute of Medical Research 6 Verdun Street, Nedlands or ENCM RM 1.59 35 Stirling Hwy, Crawley

Multiple Teams

IP: GNU General Public License (open source)

Web-based 3D visualiser for scientific data

<a href="https://mxrap.com/">mXrap</a> is a geotechnical analysis software platform in which suites of apps can be developed. It is used primarily in underground hard metal mines by geotechnical engineers for tasks …

mXrap is a geotechnical analysis software platform in which suites of apps can be developed. It is used primarily in underground hard metal mines by geotechnical engineers for tasks such as analysing and interpreting mining-induced seismicity. It would be useful to have the ability to export information from mXrap's 3D visualisation to a web-based system, so that key points of analyses or reports could be easily viewed by other people who do not have access to mXrap itself. This project involves the design and creation of a web-based system for 3D visualisation of exported data. In the simplest form, this data would represent a static scene made up of multiple data series. Each series has a certain type of representation in the 3D view: surfaces (polygonal data), lines, points, or texts. Each series also contains associated scalar data which is represented by colouring the 3D representation, for example the vertices of a surface may be coloured to show a calculated stress value at that point on the surface. The mXrap program uses the VTK library for visualisation, so it may be interesting to consider VTK.js when planning your implementation of this system, but it is not a requirement. Rendering large numbers of points represented by sprites is an important feature that is not covered by the core VTK library, in mXrap some scenes involve many millions of points.

Client: Matthew Heinsen Egan

Location: Australian Centre for Geomechanics, Civil and Mechanical Engineering, Room 273

Multiple Teams

IP: Open to further discussion about best IP options.

AI-Powered Medical Learning Navigator

This project focuses on developing a searchable platform for medical teaching resources stored within the LMS. The system would allow users to search for medical conditions, clinical terms, or keywords …

This project focuses on developing a searchable platform for medical teaching resources stored within the LMS. The system would allow users to search for medical conditions, clinical terms, or keywords across lecture slides, recorded lectures, SCORM packages, videos, PDFs, and other teaching materials. The goal is to improve curriculum visibility and make it easier to identify where specific concepts are taught throughout the program. Search results should identify the exact location of relevant content, such as slide numbers, document pages, or video timestamps. The team may utilise large language models (LLMs) and related AI technologies to process and analyse learning resources, with results ideally presented within Blackboard Ultra or through an integrated plug-in solution. The platform may also include visual heat maps showing the strength or frequency of topic coverage within individual learning resources. The project could initially be scoped to focus on Core Conditions and Presentations within MD learning resources. Depending on progress and available resources, it could later be expanded to include broader curriculum content across the entire medical program, potentially as a continuation project for another student team.

Client: Erica Yeh / Rose Berdin

Location: UWA Medical School

NDA Required

IP: Open to further discussion about best IP options.

Research Infrastructure Costing and Pricing Decision-Support Tool

The UWA Office of Research has developed an Excel-based costing and pricing methodology for shared research infrastructure platforms. While the underlying logic is robust, the current spreadsheet-based implementation is fragile, …

BITDOT Marketing and Training Setup

BITDOT Consulting Services Pty Ltd is a pioneer in providing AI Governance education and is one of the first organisations from WA to be registered in the national AI register. …

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CITS5206 - Master of Information Technology Capstone Project

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Autonomous Mining Equipment Market Map

Spatial Data Analytics

Exploration Report Mining

Digital Occupational Therapy Assessment Guide

A Tool for Comparing Neural Network Verifiers

Autonomous Vehicle Job Profiles

AI-Enabled Smart Mooring

3D printer farm interface

Web-based 3D visualiser for scientific data

AI-Powered Medical Learning Navigator

Research Infrastructure Costing and Pricing Decision-Support Tool

BITDOT Marketing and Training Setup

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