We connect existing cameras at gas stations and turn them into a system for safety, queues, pumps, staff, store operations, service quality and incident management — with events, alerts and analytics across the whole network.
Cameras are already installed at most stations, but a conventional archive helps only after the incident. AI detects events as they happen: a queue grows, someone smokes near a pump, a vehicle drives off with the nozzle, a spill, conflict or accident occurs.
A gas station is a high-risk facility, a retail point and a service area at the same time.
Most networks already have CCTV, VMS, archive and remote access. We add an AI layer on top of this infrastructure.
Video becomes a source of events, KPIs and evidence, not just an archive.
When customer flow increases, it is important to see pump and checkout queues, blocked access, risky maneuvers, crowding and early signs of conflict in advance. The system shows station load in real time and sends an event to the operator before the situation escalates.
STATANLY combines video streams, AI modules, response scenarios, alerts, event logs and BI analytics. You can start with base scenarios and gradually add new models for a particular network.
Automatic detection of unsafe and emergency situations on site.
Monitoring queues, station load, service time and staff performance.
Analytics for the store, checkout, food zone and customer experience.
We do not require replacing the entire CCTV infrastructure. First, we connect pump, entrance/exit, cashier and store cameras, then add specialized scenarios and dashboards.
Pump queues, service time, spills, drive-off with nozzle, prohibited containers, smoking and unsafe behavior.
Accidents, unsafe maneuvers, blocked driveways, crowds of people and cars, night incidents and suspicious activity.
Queues, missing employee, service speed, events, alerts and management analytics across the network.
The system creates a digital event with a frame, zone, incident type, priority and timestamp. The operator sees not just video, but a specific situation that requires response.
Detection of open flames, smoke, bright flashes, equipment sparks and early signs of ignition.
Detection of stains on asphalt, fueling spills, pump leaks, tank overfill and emergency spills after a collision.
Smoking, open flame, phone use near pumps, fueling into prohibited containers and presence in dangerous zones.
Pump collision, traffic accidents, drive-off with the nozzle in the tank, wrong-way movement, blocked access and unsafe maneuvers.
Monitoring long queues, crowds, aggressive gestures, fights, falls and conflict escalation.
Theft attempts, pump damage, property damage, hooliganism, bin arson and night incidents.
Intrusion into reservoir manholes, unloading zones, technical cabinets and other restricted areas.
Flooding, structural damage, fallen wires, strong wind and other events affecting station safety.
Video analytics shows where the station loses throughput, which pumps are idle, how customer flow changes and where an additional employee or procedure change is needed.
Number of vehicles, queue length, waiting time, occupied positions and overload of specific pumps.
Customer crowding, waiting time, the moment to open a second cashier and service quality control.
Time spent on site, fueling time, payment speed, order handoff and SLA compliance.
Cars per hour, peak hours, traffic distribution, throughput and site-to-site comparison.
Store traffic, empty shelves, hall cleanliness, full bins, coffee queue and repeat purchases.
Presence at post, absent operator, idle time, territory rounds, uniform and work during peak hours.
For a distributed network, it is important not only to respond to individual incidents, but also to maintain unified safety and service standards. The platform shows a map of sites, statuses, incidents, queues, KPIs and deviation dynamics by region.
The page is built around practical tasks: safety, queues, pumps, store operations, staff and centralized network management.
Automatic detection of emergencies, suspicious activity, spills and conflicts with event transfer to the dispatch center.
Unified control center, site comparison, model rollout and management analytics for regions and executives.
Queue, crowding, conflict, blocked access and staff activity monitoring during high-load hours.
Fire, smoke, spills, smoking, prohibited containers, dangerous zones, accidents, pump collision and equipment damage.
The system can run locally on site, centrally on a GPU server or in a hybrid model. This allows you to start with a pilot and expand the set of scenarios without painful infrastructure changes.
Connect IP cameras, VMS, NVR, RTSP/ONVIF, video streams and individual frames without full CCTV replacement.
Local processing of critical events, lower channel load, autonomous operation and fast response.
A GPU server receives streams or frames from sites and manages models, events, dashboards and roles.
From one station to hundreds of sites: unified scenarios, model versions, alerts, reports and BI analytics.
First we connect cameras and basic scenarios, then add specialized models: spills, drive-off with nozzle, prohibited containers, accidents, queues and conflicts.
Cameras, fields of view, VMS, communication channels, risks, control zones and priority scenarios.
RTSP/ONVIF, NVR/VMS, zones, schedules, roles and operator access setup.
Fire, smoke, fall, fight, suspicious object, queue, personnel and vehicle analytics.
Fuel spill, leak, drive-off with nozzle, prohibited container, pump collision.
Event log, alerts, BI and integrations with VMS, control center and external systems.
Sensitivity tuning, false alarm reduction, procedure testing and scaling preparation.
The platform is not limited to a separate interface. Incidents can be sent to a control center, BI, VMS, Telegram, corporate systems and automatic response scenarios.
Integration with existing video surveillance, recorders, streams, archive and operator workstations.
Telegram, push, email, siren, alarm event to the control center and incident journal.
Network KPIs, reports, site ratings, integration with ERP, CRM, POS and service systems.
Add new incident types, retrain models on network data and manage scenario versions.
We start with a camera audit and priority risks: queues, pumps, safety, store, staff or network management. Then we propose a pilot architecture and model list without unnecessary modernization.