REC 00:00:00
CAM 01 – Parking Lot
Pixel-based motion detection fires on rain, headlights, shadows crossing a yard and a plastic bag. After two weeks of that nobody looks at the alerts, and the system is functionally switched off while still appearing to work.
The employment lands around Pearson are among the densest concentrations of warehousing and freight forwarding in the country, and they operate around the clock. Sites here are characterized by continuous trailer movement, high driver turnover, and dock doors that are open for most of the working day — which is a different design problem from a single-shift plant. Sheridan Park and Meadowvale add a research and pharmaceutical tenancy where access records and audit trails matter as much as the cameras.
High-value, small-footprint freight and pharmaceutical inventory in an environment with constant third-party vehicle access. Dock-door coverage and gate plate capture usually matter more than perimeter fencing.
Analytics running on the camera cost no bandwidth and no server, and scale linearly as cameras are added — but they are fixed to that camera's capability. Server-side analytics allow richer search across the whole system and retrospective re-analysis, at the cost of hardware and network. Most commercial sites are best served by edge classification for alarms and server-side search for investigations.
Any analytic needs a settling period per scene — masking a flag, excluding the road beyond the fence, setting a loiter threshold that suits how your yard actually operates. A system handed over without that period generates false alarms and gets ignored, which is the same as not having it.
Plate recognition depends on the angle to the plate, the vehicle's speed and controlled infrared illumination — not on the analytics engine. Beyond roughly 30 degrees off-axis, accuracy degrades quickly. A general-purpose camera pointed at a gate will disappoint; a dedicated LPR camera at the right angle, shutter speed and IR wavelength will read reliably day and night. Budget one camera for plates and a separate one for the overview scene.
Specified by pixel density, not by megapixels
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Retention you can actually prove, on hardware built for it
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Credentials that cannot be copied in a parking lot
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Protection on day one, before there is power or a fence
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Someone watching, not just something recording
Read more →Under controlled conditions — a dedicated camera, a constrained lane, a reasonable angle and proper IR — it is reliable enough to drive gates and yard logs. Applied to a general camera watching a wide entrance, it is not. The install geometry matters more than the software.
No, but object classification removes the overwhelming majority of them — weather, light changes and animals. What remains is people and vehicles where they should not be, which is the alarm you wanted in the first place.
With server-side analytics, yes — by object type and attributes such as colour, across weeks. It turns a multi-hour scrub into a query, which is usually the moment a client realizes what the system is for.
High-value, small-footprint freight and pharmaceutical inventory in an environment with constant third-party vehicle access. Dock-door coverage and gate plate capture usually matter more than perimeter fencing. The employment lands around Pearson are among the densest concentrations of warehousing and freight forwarding in the country, and they operate around the clock.