Major events produce fragmented data across CCTV, sensors, ticketing, and venue systems. PMY Group will show how Optic, built on AWS, brings these sources together to create real-time crowd intelligence. Using the Australian Grand Prix as a case study, this session explores how operators gained live visibility into movement and congestion to support faster operational decisions. It also highlights how the same AWS foundation can support scalable analytics and broader unified data outcomes across venues and events.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Optic platform unifies CCTV + sensors + ticketing + venue systems. Real-time crowd intelligence at major events.
Why it matters
Major events generate fragmented data; live operational decisions need unified views.
The hard parts
Multi-source synchronisation at sub-second granularity. CCTV and sensor latency vary; alignment is non-trivial.
Playbook moves
(1) Define the operational decision *before* the data architecture. (2) Start with one decision type (congestion routing); add more once it works. (3) Plan the post-event analytics from day one.
The surprise
The real value of unified event analytics is post-event, not live. The same data informs next year's layout, staffing, and pricing. Most teams build for live and then have to retrofit for the more valuable post-event use case.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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