ConductVision Enterprise
ConductVision times cars stopped in fire lanes, charging bays and garage entry queues for property managers who run parking, entrances and drop-off loops.
13 detectionsConductVision detections on this photo.
Commercial and residential property managers oversee portfolios of buildings where security, tenant satisfaction, operational efficiency, and maintenance planning all depend on understanding how spaces are actually used. Most properties have extensive camera infrastructure installed primarily for security, yet the behavioral and occupancy data captured by those cameras remains untapped. ConductVision's technology can extract actionable intelligence from existing property camera networks, providing real-time occupancy analytics, parking management, common area utilization metrics, security monitoring, and building condition assessment that inform operational decisions and capital planning.
Outcomes
Rideshare cars and deliveries stop in the fire lane and the drop-off loop.
Blocked lanes hold up other drivers, and the manager hears about it from tenants first.
Cars stay in EV charging bays for hours after drivers park them.
Other drivers find every charger taken, and the property cannot show which bays turn over.
Cars back up at the garage entry gate during the morning peak.
A queue onto the street blocks traffic and starts tenants' days with a wait.
Property managers lack real-time visibility into how tenants and visitors use building spaces, leading to inefficient HVAC scheduling, under-optimized common areas, and parking management based on permit counts rather than actual utilization. Security monitoring depends on guard patrols and reactive footage review, and building condition assessment for maintenance planning relies on periodic walk-throughs that miss developing issues.
ConductVision can process feeds from lobby, parking, common area, and perimeter cameras to generate occupancy patterns, parking utilization data, security alerts, and maintenance inspection records. Analytics dashboards can inform lease negotiations with actual traffic data, optimize building operations based on occupancy patterns, and provide tenants with amenity utilization insights.
What the model sees
ConductVision detections on this photo. Photo: Tdorante10, CC BY-SA 4.0, cropped.
ConductVision detections on this photo. Photo: Rob Oo from NL, CC BY 2.0, 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 |
|---|---|---|---|
| PrimaryFire lane stops over limit | Cars stopped in a fire lane or drop-off loop longer than the set limit, counted once per stop. | Unit:stops per day | By:Lane, hour |
| SecondaryEV bay dwell | Hours from a car's arrival in a charging bay to its departure. | Unit:hours (median) | By:Bay, weekday |
| Charger turnover | Different cars using each charging bay in a day, counted from arrivals. | Unit:cars per bay-day | By:Bay, weekday |
| Entry queue wait | Seconds from a car joining the garage entry queue to passing the gate. | Unit:seconds (median) | By:Entry, hour |
Each pilot measures ConductVision on your own footage against a sample checked by hand, before anyone relies on its numbers.
Stop time error
Difference between the ConductVision stop duration and a reviewer's timing of the same sampled stops.
seconds (median absolute difference) · by camera
Bay status agreement
Share of sampled frames where the ConductVision occupied or empty call for a bay matches a reviewer's.
% · by bay, light conditions
Queue count agreement
Difference between the ConductVision queue count and a reviewer's hand count on sampled frames.
cars per frame (mean absolute difference) · by entry
Capabilities
Counts and tracks people in each camera view, by zone and hour.
Classifies, counts and tracks cars, trucks, buses, motorcycles and bicycles.
Counts dense crowds and maps where people gather, section by section.
Finds each vehicle and its plate at gates, lanes and car parks.
Tracks posture, waiting and movement from pose keypoints in public spaces.
Use cases
Cameras at entries, elevators, and floor access points can measure real-time and historical occupancy by floor, zone, and time period. Data can drive HVAC and lighting schedules, inform space planning decisions, and provide tenants with utilization reports for their lease negotiations.
Cameras at entries, exits, and level transitions can track vehicle counts and available spaces in real time. License plate recognition can manage permit compliance and visitor access. Occupancy data can be displayed on level indicators and mobile apps, reducing circling time and tenant complaints.
Cameras in lobbies, fitness centers, conference rooms, rooftop areas, and co-working spaces can measure usage patterns by time and day. Utilization data can justify amenity investments, inform programming schedules, and identify underperforming spaces for redesign consideration.
Perimeter cameras, loading dock feeds, and building entry points can detect after-hours access, tailgating at controlled doors, and suspicious loitering. Integrated with access control systems, visual verification can confirm that badge holders match authorized personnel.
Exterior cameras and periodic drone imagery can assess facade conditions, roof membrane integrity, parking deck surface degradation, and landscape maintenance quality. Visual change detection over time can identify developing issues before they escalate into costly repairs.
Cameras at loading docks can track delivery vehicle arrival, bay occupancy, and dwell times. Dock scheduling can be optimized based on actual usage patterns, and unauthorized use of tenant-reserved bays can be flagged automatically.
Related
Counts people, vehicles and bikes at intersections, stops and public spaces.
Counts guests, luggage and table use in lobbies, restaurants and halls.
Counts customers and waits in branch lobbies and at ATMs.
Pilot
Tell us about your sites and cameras, and a ConductVision engineer replies with a scoping plan built around the endpoints above.
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