CROWDSOURCED TRAFFIC SIGNAL SYSTEMS
UNSW RESEARCH
CYAMAST
UNSW SPINOUT
As digital transformation continues to accelerate , so too will the mass adoption of connected ( IoT / OT ) devices organisations . With billions of devices connected to our corporate and operational networks , we are witnessing a significant rise in risk and exposure through an increased cyber-attack surface .
CyAmast has leveraged a ground-breaking innovation developed in collaboration with UNSW to pioneer a new approach that provides organisations with a costeffective and scalable asset intelligence and network risk management tool .
CyAmast successfully raised venture capital to commercialise the research through a proprietarily developed , enterprise-grade software product . The product is now in-market and deployed in live networks around the world .
100 INNOVATIONS AND CAPABILITIES
To develop low-cost traffic signal optimization tool , focused on the future of mobility driven by behaviour and enabled by convergence of Smart Technology . Traffic signal controller that relies on crowdsourced data such as Waze or Google Maps to manage traffic signals in real time .
The platform through which traffic agencies and personnel can remotely control the traffic signal system .
A reliance on 4G / 5G communication protocols with an integrated modular hardware and software infrastructure relying on crowdsourced traffic data . Trails have been successfully implemented over 30 locations internationally in India , Indonesia and Oman and demonstrated up to 37 % reduction in delays .
> Pioneered a new approach to asset management and anomaly detection .
> Developed enterprise-grade software , now deployed in global organisations .
> Successfully solicited two investments from a global venture-capital fund .
> Created opportunities for > 10 paid work integrated learning student placements .
> Cost-effective installation , reduction in cost by 50 % and reduction of 10 % of time than other traffic control systems .
> Cost-effective maintenance − 1 % of time needed compared to other traffic control systems .
> Delay Reduction by approximately 20 %.
> Reduction in Emissions by approximately 8 %.
> Improvement in Safety by approximately 18 %.
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