Solutions for security, safety and operations

Videolytical analytics modules, grouped by the job they do. Each section names the modules used, what the operator receives and where it applies.

Cameras: Existing IP cameras and recorders, over ONVIF and RTSP
Runs on: Edge devices, GPU servers or cloud instances
Alerts go to: Video management software (VMS), SMS, email or a webhook

Perimeter security

A long boundary is hard to watch by eye. Most movement near a fence is harmless, and the one crossing that matters is easy to miss.

Intrusion detection: A tripwire rule watches a line along a fence, wall or gate. A restricted-zone rule watches a marked area of the camera view. A crossing or an entry raises an alert.
Loitering detection: Flags a person who stays in a sensitive zone beyond a set time.
At the gate: Vehicle analytics adds under-vehicle inspection at high-security gates. Face recognition can match faces against a watchlist.
False-alarm suppression: False-alarm suppression is part of tuning for the site, which is done per camera. Our guide to reducing false alarms covers the general causes and controls.
What the operator receives: A real-time alert in the VMS console, by SMS, by email or to a webhook. In a control room, Command and Control shows cameras and alerts on a map.
Where it applies: Defence and paramilitary sites, industrial plants and warehouses at night, and retail premises after hours.

See defence and paramilitary

Crowd and people

When a concourse, platform or market fills up, the people in charge need to know while there is still time to act. It is hard to judge how full a space is getting from a wall of camera views.

Crowd monitoring raises alerts on density, flow and suspicious behaviour in a camera view. People counting records movement in both directions across a line at a gate or entrance. Loitering detection flags a person who lingers in a sensitive zone.

Alerts are raised in real time. In the airport deployment in our case studies, crowd analytics run on server GPUs and alerts reach the terminal control room with video bookmarks. A bookmark marks the moment in the recording.

Results depend on the camera view. A high, wide view of the space typically works better than a low camera that sees only the nearest people.

Modules: Crowd monitoring, people counting, loitering detection
Operator receives: Real-time alerts, and counts in and out
Applies to: Airport terminals, railway stations, bus depots, markets and public areas

See airports and transport

Traffic enforcement

On a busy road, violations are too frequent to watch for by eye. A penalty also needs evidence that ties the offence to a vehicle.

Highway camera view of a motorcycle carrying two people. A green box marks the rider's face under an on-screen label that reads Not Wearing Helmet.

Helmet violation detected on a city highway camera.

Modules: Helmet and traffic violations, with number-plate recognition
Operator receives: An evidence record that links each violation to a plate
Applies to: Highway and junction enforcement by traffic police
Hotlist: Plates can be checked against a list of stolen or flagged vehicles

A violation is detected

Models detect riders without helmets, triple riding and wrong-way driving.
The number plate is read

Automatic number-plate recognition (ANPR) reads the plate by day and by night, and is tuned for Indian plates. Reliable reads depend on where the camera is placed, as our camera placement guide explains.
An evidence record is made

Each violation becomes a record that links the offence to the plate.
The record enters the penalty workflow

Records feed the e-challan workflow, the electronic traffic penalty notice process used by traffic police. Our traffic police case study describes one deployment.

See smart cities and traffic

Retail intelligence

Most stores already have cameras for security. The same video can show where shoppers walk, where they stop and when a billing queue is building.

Heatmap and dwell time: Shows movement density and dwell time across the floor, to help plan layouts, staffing and merchandising.
People counting: Counts people in and out at store entrances, in both directions.
Queue-length alerts: Warn when the queue at a billing counter grows, so that staff can respond, for example by opening another counter.
Store security: Intrusion detection watches the premises after hours. Loitering detection covers sensitive areas of the store.
What the team receives: Counts on live dashboards, heatmaps for planning, and real-time alerts for queues and intrusion.

Illustration of a small shop with a colour heatmap overlaid on the floor, red in front of the counter and along the aisle and blue in the middle.

Illustration of a retail heatmap, not a product screen. In general, a heatmap colours the floor by how much movement each area sees.

See retail and malls

Industrial safety

A safety officer cannot be at each workstation through a whole shift. A missing glove or a person in a danger zone is easy to miss between rounds.

Overhead factory camera view of a vehicle chassis assembly line. Orange boxes mark the bare hands of two workers, each labelled NO-Gloves. — Small items such as gloves are harder for a camera to see than hard hats, so results depend on camera position and lighting.

Equipment checks and danger-zone alerts

The PPE (personal protective equipment) compliance module checks for hard hats, vests, gloves and masks on production lines. Danger-zone alerts warn when a person enters a marked area on the shop floor. Fire and smoke detection watches for visible flames and smoke.

Alerts go to the VMS console, or by SMS or email to the people responsible for the area. Our guide to camera-based PPE monitoring explains the limits.

See industrial and warehousing

Smart warehousing

A warehouse needs a record of movement through its docks and gates. Hand tallies and gate registers are slow to check.

Night camera view of a loading dock. A person carrying a sack is marked with a red box beside a white counting line, with on-screen counters for in and out.

Counts at docks and gates

People counting records movement in and out across a line in the camera view. It applies at docks, gates and entrances, and the counts appear on live dashboards.

In the yard, vehicle analytics adds classification, direction, dwell and parking. At the gate, number-plate recognition keeps a log of plate reads with the time and the gate. Object detection can flag a missing object or an unauthorised removal.

See industrial and warehousing

All analytics modules

Each module is a purpose-trained deep-learning model with its own rules engine. Modules are chosen per camera and can be combined.

Module	What it detects	Typical uses
Intrusion detection	A crossing of a tripwire line, or entry into a restricted zone	Perimeters, restricted areas, premises after hours
Crowd monitoring	Crowd density, flow and suspicious behaviour	Terminals, station platforms and concourses, public areas
Object detection	Abandoned objects, missing objects and unauthorised removal	Unattended baggage in terminals, watching over assets
Vehicle analytics	Vehicle class, direction, dwell and parking, with under-vehicle inspection	Gates, yards, parking areas, high-security entrances
Face recognition	Faces, matched in real time against staff, VIP or watchlist databases, with age and gender demographics	Watchlist alerts, recognising staff and VIPs
Fire and smoke	Visible flames and smoke	Industrial plants and warehouses
PPE compliance	A missing hard hat, vest, gloves or mask	Production lines and shop floors
Heatmap and dwell	Movement density and dwell time across a floor	Store layout, staffing and merchandising
Helmet and violations	Riders without helmets, triple riding and wrong-way driving	Highway and junction enforcement
People counting	Movement in and out across a line, in both directions	Gates, docks and store entrances
Loitering detection	A person who stays in a sensitive zone beyond a set time	Perimeters and sensitive zones
Video synopsis	Not a detector. It condenses hours of recorded footage and lets operators search by class, colour, direction or time	Reviewing footage after an incident

These modules are part of AI Video Analytics. Number-plate recognition is a separate product, ANPR and Vehicle Intelligence. Face Recognition is also offered as a product of its own.

Tuning for the site

Modules are set up camera by camera, first in a pilot on a small set of cameras and then at scale-out. These controls fit a rule to the scene.

Zones: Each camera has its own detection zones, so a rule applies only to the part of the view that matters: a fence line, a doorway or a dock.
Schedules: A rule can follow a timetable. An intrusion rule, for example, can run only when the site is closed.
Confidence thresholds: Each camera has its own threshold for how sure a model must be before it raises an alert. In general, a higher threshold means fewer false alarms but more missed events, so the setting is a choice to make with the site team.
Scene calibration: False-alarm suppression works with scene calibration, which fits a module to the camera's own view. Calibration is part of scale-out.
Custom model training: Models can be trained for objects that are specific to one site.
Field conditions: Models are trained and hardened for real field conditions: glare, dust, monsoon rain, low light, dense crowds and mixed camera quality.

Read the guide to planning a pilot

See the modules on your own footage

Send a sample clip or arrange a live demo. We run the modules you choose on the scenes that matter to you.

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