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Industry problems confirmed – Countdown begins for RMIT IoT/AR Hackathon

RMIT University students are eagerly getting ready to tackle the 10 real-world industry problems submitted by companies from a diverse range of industries for the 2018 IoT/AR RMIT Hackathon, starting this Thurs Aug 30th and concluding Sat Sept 1st.

RMIT, PTC & LEAP are excited to unleash the power of the leading Industry 4.0 technologies covering Internet of Things (Thingworx) and Augmented Reality (Vuforia), combined with the best & brightest Engineering and IT students from across RMIT University, locked away for 3 days to solve these industry problems and present their solutions to a panel of prominent industry judges on Sat Sept 1st.

The event will also be an exciting way for industry sponsors to see first-hand how these new Industry 4.0 & IIoT technologies can resolve their real business issues, and gain fresh insights from the next generation of innovators from RMIT.

54 students are now confirmed to participate in this week’s Hackathon – coming from an diverse mix of disciplines including IT, Computer Science, Aerospace, Mechanical and Civil Engineering – which has allowed them to create teams with the required multidisciplinary skillsets.

During the recent Pre-Hack training (pictured above), most students picked up the software very quickly, aided by the benefit of a drag-and-drop interface without the needing for coding skills (although you do still have the option to code for deeper customisation, which some CS students are taking advantage of). Within just 2 days, most students began working independently and started creating their own IoT dashboards and AR experiences.

IoT and AR are exciting new technologies which will change the way engineers and designers work, all the way from design/conception through to construction and asset maintenance; and the most engaged, forward-looking students are the ones who sees this and are embracing the Hackathon as a way to differentiate themselves in the future job market. In an interesting twist, a number of industry sponsor companies have also registered their interest in taking on graduates from RMIT with IoT and/or AR skills within the next 6 to 12 months.

Industry mentors and judges at this year’s event will include:
Emma Hendry: CEO of Hendry Group
Danielle Storey: CEO of the Eastern Innovation Business Centre. A not-for-profit organisation supported by the City of Monash
Estelle Pages: Senior Sector Policy Officer for Advanced Manufacturing at the Department of Economic Development, Jobs, Transport and Resources
Audrey Zibelman: CEO and MD, Australian Energy Market Operator (AEMO)
Darcy Naughton: co-founder of the York Butter Factory, General Partner at Adventure Capital and co-founder of Clover.com.au
Nick Howard: Product Development Manager at Buzz Products
Alan Wickett: Market Director at PTC
Rod Hendricks: PTC Engineering Solutions Manager, LEAP Australia
David Graham: Regional Technical Manager at LEAP Australia
Allan Thompson: ThingWorx and Vuforia expert
Bryan Kirchner: ThingWorx expert
Taju Joseph: Vuforia expert
Pooja Sah: ThingWorx expert

The full range of industry problems (and sponsoring companies) are:

Lendlease: Smart documents, analyse contents, deliver results via Management Information Systems (MIS) and Augmented Reality (AR).
SEA Electric: Data capture & processing for Electric Vehicle performance optimisation.
RFS: Intelligent cable routing for RF transmission towers, using AR to reduce assembly times and reduce/eliminate reworks.
Wilson Transformers: Transformer system testing
B&R Enclosures: 1. Laser cutting machine – condition monitoring
B&R Enclosures: 2. Smart product assembly instruction system. Data driven with AR output.
Britax: AR instructor to assist in preventing the misuse of child restraints
Nova Systems: Product testing and validation management system
City West Water: Improve monitoring and visibility, performance and maintenance of vacuum sewer system.
Airconstruct IEQ: Heating Ventilation, Air Conditioning and Refrigeration machine learning solution for predictive maintenance.

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