We are excited to share some of the advances we have made to support our crowd management decision making with our innovative Dynamic Crowd Measurement software (DCM).
Since 2015 we have been defining the quantitative and qualitative characteristics of crowds to determine trigger points when the crowd density and crowd flow impact crowd mood. This year we have reached a significant milestone, to fully automate our data collection by using artificial intelligence software developed by Dr Roman Marchant, lecturer and research fellow at the Centre for Translational Data Science, The University of Sydney. Roman is an expert in machine learning and computer vision, who has developed a framework which allows cameras to become smart by identifying and recording relevant features that feed into the unique and innovative DCM crowd models.
The DCM software is simple to use and can work on existing camera systems in your current infrastructure without the investment in additional hardware. Our dashboard is designed to assist with real-time decision-making. DCM models crowd volatility which takes the graph data you can see below and converts it to predict and alert before mood de-escalation.
This dashboard solution enables event producers and place managers to predict when crowd density and volumes rise and proactively implement real-time crowd calming or crowd diversion techniques. DCM also has application for addressing crowd management pain points in transport hub design.
We will share more results in July with some announcements about our progress in the commercialisation of DCM. In the meantime, we’d love to show you how DCM is the ideal addition to your crowd measurement and analysis.