CCTV VideoAnalytics
Turn existing cameras from after-the-fact evidence into a source of alerts, counts and searchable events, with privacy limits built in.
CCTV Video Analytics: what the work involves
Most CCTV is only ever looked at after something goes wrong. Nobody watches sixteen screens all day, so intrusions, blocked fire exits, queues at the counter and unsafe behaviour go unnoticed in real time. When an incident does happen, staff scroll through hours of footage to find a thirty-second clip, and the evidence often ages out before anyone asks for it.
We pull streams from your existing IP cameras or NVR over RTSP and run analytics on a local server or edge box, so video need not leave the premises. Models detect people and vehicles, track them across frames, and apply rules you draw on the image: a restricted zone, a counting line, a dwell-time limit, a queue length. Safety checks such as helmets or high-visibility vests are possible with custom detectors. Events are saved as short clips with a thumbnail and timestamp, forming a searchable log, and alerts go to Telegram, WhatsApp or a control-room screen. We tune each camera and review false alerts together during the first weeks.
Core features
Works with existing cameras
Streams are read from IP cameras and NVR systems, so you usually avoid replacing working hardware.
Zone and line rules
Draw restricted areas, counting lines and dwell limits on the camera image, with different schedules for day and night.
People and vehicle counting
Footfall, occupancy and queue length are counted and reported by hour and day.
Safety compliance checks
Custom detectors look for helmets, vests or blocked exits, and raise an alert when the rule is broken.
Searchable event clips
Alert clips are stored with thumbnails, so finding an incident takes a search, not hours of scrubbing.
On-premises processing
Analysis runs on a local server or edge device, keeping footage inside your premises by default.
What we get right before launch
False alerts from shadows and weather
Lighting changes, insects and rain can trigger alerts. We tune each camera, schedule rules by time, and measure alert quality during a trial before real-time notification is relied on.
Surveillance, consent and signage
Analysing video of people carries privacy duties, especially for staff monitoring. We favour counts and zone events over identifying individuals, advise on signage and policy, and limit clip retention.
Hardware and bandwidth limits
Many streams need serious compute. We size the server for your camera count and frame rates, and may analyse fewer frames per second where fine detail is unnecessary.
Tools and technology
- Python
- YOLO
- OpenCV
- PyTorch
- RTSP
- NVIDIA Jetson
- FastAPI
- PostgreSQL
Common questions, answered
Can it work with our current cameras?
Usually, if they provide an RTSP or ONVIF stream, which most modern IP cameras and recorders do. Very old analogue systems may need an encoder. We check your equipment before quoting any hardware.
Does video leave our premises?
Not by default. Analysis runs on a local machine and only events or clips you choose are shared. If you want cloud storage or remote monitoring, we configure it deliberately and securely.
How good is detection at night?
It depends on camera quality and lighting. Infrared cameras help, but accuracy drops in darkness, glare and heavy rain. We test each camera at night before promising alerts from it.
Can it identify specific people?
That is a separate, more sensitive capability needing explicit consent and legal review. Most analytics projects focus on counts and rule events, which avoid identifying individuals.
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Ready to start your CCTV Video Analytics project?
Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.