Mood Tracking At Mardi Gras – Phone and mood will be tracked as part of a temporary CCTV system and crowd monitoring video analytic from Dynamic Crowd Management being deployed at Sydney’s Mardis Gras Parade this Saturday.
Dynamic Crowd Measurement provides real-time data driven intelligence for informed decision making. Security or event managers link temporary or existing cameras and the software delivers crowd insights at events, venues, transport hubs and smart cities.
Dynamic Crowd Measurement observes facial expressions and counts smiles to measure and categorise mood as positive, negative or neutral, as well as identifying the number of people in comparison to useable space measured as people per square metre.
The Mood Tracking At Mardi Gras system can also measure speed and direction of pedestrian traffic, undertake a live headcount, assess social distance and social distance compliance.
A geospatial heatmap facilitates the effective identification of hot spots for density, mood and velocity (speed and flow) at each active location, while the customisable Alert Level Indicator visualises the level of risk for each location by analysing the relationship between density, mood and velocity at each location.
The data playback feature provides real time and retrospective data analysis. It enables users to validate data against a live image and heat-map to gain understanding of key moments and metrics, which is specifically useful for activity benchmarking and planning input.
Mood Tracking At Mardi Gras
The notifications manager provides updates on changes to crowd metrics and alert levels. Notifications can be customised to provide specific updates on crowd characteristics at certain locations, while a visual validator enables comparison of data against a live image or heatmap and helps to increase situational awareness across each location.
“Simply knowing a head count does not provide critical information,” a Mardi Gras source told SMH. “For example, knowing the density or mood of a specific area of Oxford Street allows us to identify if a pinch point is occurring there (which can lead to crowd crush if not addressed), whereas simply knowing the headcount across Oxford Street doesn’t give any of that information, and it would be incorrect [and] dangerous to assume the crowd will distribute themselves evenly and safely.
“There is no facial recognition tracking and it cannot track people from one place to another,” the source said. It provides real-time metrics that snapshot the crowd across the entire route at any given point to inform proactive crowd management decision-making.”
A Sydney Gay and Lesbian Mardi Gras officer will monitor the Mood Tracking At Mardi Gras software on parade night and “feed specific metrics to police who help direct crowds”, Mardi Gras told SMH.
“All data will be handled by the Sydney Gay and Lesbian Mardi Gras team and only provided to event stakeholders including police at specific times on the night when it is relevant for crowd safety decisions.”
WorldPride will also use radio frequency density measuring technology from Behavioural Analytics to measure crowds attending mini street festivals on Crown, Riley and Foley streets in Surry Hills.
“Sydney WorldPride is using safety technology that estimates how many people are in an area via pings to mobiles phones,” a Sydney WorldPride spokesperson said.
“This technology does not require cameras and the data is not personally identifiable. All that is reported is the number of mobile phones in the area.
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2 COMMENTS
This made me laugh, I would of thought the mood / culture is a given 😉 (no offence)
Agree participants’ mood predictably happy. An interesting aspect to me was the preparedness of organisers to use AI to manage the rolling events around Pride. Organisers pointed out no face recognition was used and phones were tracked without IDs being collected but the underlying power of the technology and its efficacy in such applications makes it almost impossible to ignore from the point of view of efficiency and safety. In the future will failing to use AI to support public safety applications be considered a failure of duty of care? When you consider events like Seoul’s Halloween crowd crush, in which 159 people died and another 200 were badly hurt, I can’t help but think it will be. Properly commissioned and managed, this system has significant capacity to save lives.
This made me laugh, I would of thought the mood / culture is a given 😉 (no offence)
Agree participants’ mood predictably happy. An interesting aspect to me was the preparedness of organisers to use AI to manage the rolling events around Pride. Organisers pointed out no face recognition was used and phones were tracked without IDs being collected but the underlying power of the technology and its efficacy in such applications makes it almost impossible to ignore from the point of view of efficiency and safety. In the future will failing to use AI to support public safety applications be considered a failure of duty of care? When you consider events like Seoul’s Halloween crowd crush, in which 159 people died and another 200 were badly hurt, I can’t help but think it will be. Properly commissioned and managed, this system has significant capacity to save lives.