An exciting opportunity exists as part of the UTS & NBN partnership ASTRID.
Project Title: Sensing and Perception for Blockage Detection in Underground Broadband Pipe
Project Description: Hidden beneath our urban landscapes, broadband networks serve as the digital backbone of modern connectivity, enabling communication essential for homes, businesses, and industries. Despite their resilience, these underground pipes that house network cables are susceptible to degradation and faults. Traditional methods that facilitate the detection of blockages remain outdated, inefficient, and often result in unnecessary excavation and costly remediation, causing delays and budget overruns.
Inspired by large-scale broadband infrastructure deployments by entities like NBN Co in Australia, BT Openreach in the United Kingdom, and Chorus in New Zealand, the project aims to produce robust, novel solutions that revolutionise blockage detection in small-diameter underground pipes.
The successful candidate will focus on analysing multimodal sensing technologies and their capability to assess the continuity and characteristics of broadband pipes. Analytical solutions and numerical studies will be validated by experimental data obtained from testbenches setup to imitate common pipe conditions and environments. The effects of various parameters such as, blockage type, ground material, pipe depth and length, environmental noise, and sensor array parameters will be investigated, as well as the potential for leveraging advanced signal processing, AI, and machine learning techniques.
Applicants that have a strong background in robotics, mechatronics, AI, and machine learning are encouraged to apply by emailing their CV and cover letter to sarath.kodagoda@uts.edu.au and ray.owen@uts.edu.au.