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UOW and Computer Vision Start-Up to Drive Smart Video Analytics Innovations

The University of Wollongong (UOW) is collaborating with a Video Intelligence Platform connecting computer vision’s potential to real-world business outcomes, joining its research and development hub for Artificial Intelligence of Things (AIoT) Solutions.

Under the mutual non-disclosure agreement, the computer vision start-up and the University’s SMART Infrastructure Facility will share exclusive research and software development capabilities to propel innovations in smart video analytics, including machine learning (ML) models and learnings from real-world computer vision implementation and local employment opportunities.

As part of the partnership, the computer vision start-up has established a satellite office at UOW’s Illawarra-based Innovation Campus – a technology precinct that fosters industry-research collaboration – joining the Telstra-UOW Hub for AIoT Solutions.

An AU$ 1.7 million government funding grant through the Strategic University Reform Fund (SURF), designed to establish Illawarra as a global leader in AIOT solutions for communities, enterprises and governments, supports the hub. Collaboration with technology industry giants is also another way the hub receives backing.

The initiative brings together over 30 experts from industry and academia, focusing on delivering globally applicable AIOT outcomes in smart transport, smart logistics, resilient infrastructure and intelligent manufacturing.

The CEO and Co-Founder of the computer vision start-up stated that collaborating with UOW’s SMART Infrastructure Facility and AIOT solutions hub delivered practical outcomes in three key ways. He noted that UOW and SMART bring world-leading AI research capabilities to the fore, which have transformative potential within today’s computer vision market.

Because SMART and the Telstra-UOW Hub for AIoT Solutions are mandated to apply academic rigour to real-world problems, they collaborate extremely well with industry and the public sector. The ability to work with PhD students and doctors of AI, and directly apply their research and skills to tangible computer vision challenges, is truly exciting.

While the computer vision start-up provides a Video Intelligence Platform, which enables academics to productionise ML models at scale and see their research result in real-world change, UOW provides academic expertise, industry relationships, and data governance.

The partnership provides mutually benefits the industry as well as university researchers and students. The computer vision start-up requires access to a steady stream of the best available talent in order to scale. For UOW, the collaboration provides a clear employment pathway via the start-up’s talent exchange, internship and graduate hiring programs.

UOW’s SMART Infrastructure Facility specialises in applying data analytics, advanced simulation, Smart Cities technology and video analytics to core infrastructure challenges, including electricity, roads, rail urban growth and regional development.

SMART Infrastructure Facility Director stated that SMART Infrastructure Facility’s journey into smart video analytics is relatively recent, growth in effort and demand has been nearly exponential. He noted that currently, the majority of the video analytics market develops around vertical integration; and bespoke – if not ad-hoc – solutions for specific sectors, or even sub-sectors. This means that a lot of redundancies will be observed in terms of the deployment of all these single-use-case computer vision tools and the fees that end-users will have to pay. Thus, a transversal approach is needed, which is what the computer vision start-up is bringing to bear with its industry-agnostic platform, he said.

The Facility Director said that UOW and the start-up share the same approach to smart video analytics – the interest is in a transversal approach and the fundamentals behind the different use cases. SMART is adept at assessing new use cases for computer vision, optimising algorithms and wrapping them into a container. However, we need to push these new ML models into something for deployment, to be useful to the industry. The computer vision start-up’s Video Intelligence Platform provides that ideal something, he noted.

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