ConductVision Enterprise
ConductVision counts the people in wide and elevated camera views, section by section, so venue, transit and event teams see how full each area is.
22 detectionsConductVision detections on this photo. Photo: LaShawnda Jones, CC BY-SA 4.0, cropped.
Crowd Analytics goes beyond individual people detection to analyze group-level dynamics: how dense is a crowd, which direction is it flowing, where are bottlenecks forming, and is a dangerous surge developing. The system is designed to process wide-angle and elevated camera feeds covering large areas, stadiums, plazas, transit hubs, and festival grounds, where individual tracking is neither practical nor necessary. Density estimation models count approximate headcounts in regions where people overlap and occlude each other, while flow analysis maps the collective movement direction and speed across the scene.
Outcomes
Stewards judge how full a concourse, pen or plaza is by eye from where they stand.
Each steward gives a different answer, and the control room cannot compare sections on one scale.
Capacity limits for each pen, platform and plaza are written in the event plan, away from the control room screens.
Inflow gets held late because nobody sees a section near its limit until it looks packed.
In front of a stage or along a platform edge, people stand too close together for anyone to count.
The spots where a number matters most get the roughest guess.
After a crowded event, the debrief rests on radio logs and what staff remember.
Without counts, the team cannot show which section went over plan, or when.
What the model sees
ConductVision detections on this photo. Photo: LaShawnda Jones, CC BY-SA 4.0, cropped.
ConductVision detections on this photo. Photo: LaShawnda Jones, CC BY-SA 4.0, cropped.
Endpoints
Each endpoint is defined before the pilot starts, with what is counted, its unit and how the results are broken down.
| Endpoint | How it is counted | Unit | Broken down by |
|---|---|---|---|
| PrimaryPeak density | Highest people per square meter in a section during an event, from each sampled frame's headcount divided by the section's mapped area. | Unit:people per square meter | By:Section, event |
| SecondaryTime over limit | Minutes in which a section's density stays above the limit the safety team sets, summed per event. | Unit:minutes per event | By:Section |
| Section headcount | People counted in each section, reported for each minute as the mean and the peak. | Unit:people | By:Section, minute |
| Gate approach load | People counted in front of each gate, sampled every minute from doors-open to the start of the event. | Unit:people | By:Gate, minute |
Each pilot measures ConductVision on your own footage against a sample checked by hand, before anyone relies on its numbers.
Hand count agreement
Difference between the ConductVision headcount and a reviewer's hand count of the same sampled frames.
% of the hand count (mean absolute difference) · by section, density band
Dense-frame misses
Share of people a reviewer marks in the densest sampled frames that ConductVision did not box.
% · by camera, distance from camera
False boxes
Boxes a reviewer rejects, such as flags, banners or posters taken for people, per 100 boxes checked.
per 100 boxes · by camera
How it works
Connect
Mount cameras at elevated vantage points, rooftops, poles, overhead structures, overlooking gathering areas. Wide-angle and fisheye lenses maximize coverage per camera. The platform also accepts drone feeds for temporary event coverage.
Analyze
Density regression models estimate the number of people per square meter across the camera view, producing a continuously updated heat map. Optical flow analysis overlays directional vectors showing crowd movement speed and heading, identifying convergence points and counter-flow conditions.
Act
When density exceeds safe thresholds, flow reversals indicate a stampede risk, or crowd pressure builds at choke points, the system fires graduated alerts to event management and public safety teams. Real-time dashboards show density overlays on facility maps.
What it detects
Person
Each visible person in a wide or elevated view, boxed in every sampled frame
Section headcount
People inside each mapped section, per frame
Density
People per square meter in each section, once its floor area is mapped in a pilot
Gate approach count
People waiting or walking in front of each gate
Features
Use cases
Large venues need to monitor crowd density across concourses, gates, and seating sections during events. Real-time density maps can guide staff deployment, gate opening decisions, and identify sections approaching unsafe density.
eventshospitality
Train stations and bus terminals experience surge conditions during rush hours and service disruptions. Density and flow analytics can trigger dynamic signage, gate control, and platform access management to distribute crowd load.
transportationsmart city
Music festivals and public gatherings on open ground lack built-in crowd management infrastructure. Drone and tower camera analytics can provide the same crowd intelligence that fixed-venue systems offer, enabling safety teams to spot dangerous density buildups.
eventsgovernment
Shopping centers need to understand pedestrian flow through corridors, atriums, and food courts. Crowd analytics can reveal high-traffic corridors, underutilized areas, and peak congestion times to inform tenant placement and wayfinding design.
Public safety agencies monitoring large gatherings need real-time density and movement data. Crowd analytics can provide situational awareness to incident commanders without requiring individual identification or facial recognition.
governmentsmart city
Theme parks must balance crowd load across attractions, dining areas, and pathways. Density analytics can power dynamic wait-time displays, crowd-level alerts to staff, and guest flow optimization throughout the park.
hospitalityevents
Technical overview
Accuracy and speed are measured on your footage and cameras during the pilot, and reported with the conditions they were measured under.
Industries
Counts people, vehicles and bikes at intersections, stops and public spaces.
Counts shoppers, queues and carts from the store's existing cameras.
Measures flow, waits and occupancy in corridors, lobbies and entrances.
Counts people, bikes and vehicles across campus walkways and entrances.
Counts crowds at gates, concourses and stands.
Counts guests, luggage and table use in lobbies, restaurants and halls.
Related
Counts and tracks people in each camera view, by zone and hour.
Tracks posture, waiting and movement from pose keypoints in public spaces.
Pose tracking for work at height and on walkways, with fall alerts routed to staff.
Pilot
A pilot takes one prioritized outcome, runs on your cameras, reports the endpoints above and ends with a results review and a decision.
