Functional characteristics
Terms and abbreviations
Event — a fact recorded by the system about a vehicle, geofence or camera: zone entry, started moving, overspeed, alarm and others.
Fixation — a vehicle passage recorded by a camera, holding a snapshot, a timestamp, the camera, the recognised registration plate and a recognition confidence.
Geofence — a virtual area on the map marked out by the user, used in GPS/GLONASS monitoring systems to control the movement of objects.
Registration plate — a vehicle's state registration number.
Road network — the street and road network.
Transport graph — a mathematical model describing the transport network as nodes (towns, junctions, slip roads) and edges (roads, bridges, flyovers). It is used for routing, route optimisation, congestion analysis and traffic flow modelling.
Vehicle — a monitored transport unit.
1. Purpose of RUBIN-T
RUBIN-T is intended for vehicle monitoring and for transport security at observation sites.
It is used by organisations and institutions that manage commercial, passenger, freight and specialised transport.
RUBIN-T automates the management of a vehicle fleet.
2. Problems RUBIN-T solves
RUBIN-T addresses the following:
- monitoring vehicle location;
- monitoring vehicle speed compliance and distance travelled;
- adherence to routes and visits to predefined places;
- recording vehicle passages by registration plate;
- processing telematics data to determine and monitor vehicle positions;
- analysing the work of the fleet and of individual objects against various performance indicators;
- logging and processing the various events that arise in vehicle monitoring.
3. RUBIN-T functions
3.1 Vehicle monitoring
The tool provides real-time monitoring of location, routes and speed, fuel consumption and technical operating parameters of vehicles.
Capabilities:
| Capability | Description |
|---|---|
| Vehicle position display | Current coordinates, course and speed on the map, updated in real time without reloading the page |
| Telemetry | Speed, course, coordinates, satellite signal quality, data lag |
| Vehicle statuses | Moving, idle, stopped, loading |
| Equipment state | Whether the onboard terminal is in contact, and its connection history |
| Trips | Automatic trip detection, the trip track on the map, and a speed profile along the track with maximum and average markers |
| Distance and driving time | Computed over any period for a single vehicle or the whole fleet |
| Equipment records | Binding of onboard terminals to vehicles by unique identifier, with history |
| Vehicle card | Photo, attributes, current location, the geofences the vehicle is inside, attached documents |
3.2 Monitoring geofence visits
The tool provides real-time monitoring of vehicle visits to particular user-defined places (sites).
| Capability | Description |
|---|---|
| Zone types | Operational zone, speed zone, restricted zone |
| Creation and editing | Drawing a polygon on the map, reshaping it, setting the name, group, colour and active schedule |
| Speed limit | Setting a zone speed limit and recording violations inside it |
| Crossings | A log of entries and exits with entry time, exit time and dwell duration |
| Zone occupancy | How many vehicles are inside at this moment and how many entered today |
| Key figures | Vehicles passed, average dwell, peak occupancy, average speed inside, alerts triggered, longest visit |
| Alert rules | Notification of entry, exit, overspeed inside the zone and dwell time exceeded |
3.3 Recording vehicle passages (cameras)
The tool works with video cameras to assess transport security at observation sites and to monitor, in real time, vehicle activity and visits to particular places (geofences).
| Capability | Description |
|---|---|
| Recognition | Detecting a vehicle in frame, classifying the object, reading the registration plate |
| Confidence estimation | Separate confidence figures for the object and for the plate |
| Fixation log | Snapshot, time, camera, recognised plate, matched vehicle |
| Filtering | By camera, period, confidence threshold, successful-recognition flag and plate text |
| Views | A list for scanning large volumes, and a grid of snapshots for visual checking |
| Export | Export of the selected fixations in CSV format |
3.4 Working with the map
The tool works with objects on the map: cameras, vehicles and geofences.
| Capability | Description |
|---|---|
| Layers | Vehicles, geofences, cameras, cargo, traffic conditions; each switched on and off independently |
| Filtering and grouping | Selecting layer objects by status and type, sorting and grouping in the object tree |
| Layer styling | Configuring labels, colour, size, fill, border and drawing order |
| Search | Searching objects across every layer at once |
| Object cards | Viewing attributes and telemetry, opening the object's page |
| Object creation | Adding vehicles, cameras and geofences directly on the map |
| Measurement | Measuring distance and area |
| Route building | A route over the road network with turn-by-turn directions |
| Destinations | Assigning an arrival point for a vehicle, with route building and an arrival time forecast |
3.5 Working with the road network graph
The tool works with the transport graph: creating new segments (roads) and editing existing ones, assigning attributes to graph objects and exporting the map.
The transport graph is the input data for route building and arrival forecasts.
3.6 Reports
The tool provides data on the events recorded from vehicles and cameras, on vehicle activity (daily and hourly statistics), on camera fixations (daily and hourly statistics), and on vehicle activity by owning organisation. Reports can be exported in XLSX format.
| Report | Contents |
|---|---|
| Headline figures | Trips, distance, average speed, driving time, active vehicles and camera fixations for the period; distribution across the hours of the day |
| Vehicle analytics | Distance, trips, time moving, average trip and event count per vehicle; event distribution by type; each vehicle's share of distance |
| Geofence analytics | Crossings, entries, exits, average dwell and alerts per zone; distribution across the hours of the day; speed compliance and overspeed severity |
| Camera analytics | Fixations, detections, average recognition confidence and uptime per camera; detection distribution by class |
| Transport analytics | Volume, delivery counts, on-time share and average transit time |
| Route punctuality | The share of arrivals meeting the schedule, per route and per day |
| Event log | The full list of events, filterable by vehicle, event type and period |
Reports are exported in XLSX and CSV formats with the applied filters.
3.7 Working with cameras
The tool works with video cameras and provides real-time monitoring of vehicle visits to particular user-defined places (geofences).
| Capability | Description |
|---|---|
| Live viewing | Low-latency camera broadcast, fullscreen mode, quality selection |
| Video wall | Viewing several cameras at once in a configurable grid of windows |
| Video archive | Recording of camera streams, scrubbing on a shared timeline, synchronised archive playback across several cameras |
| Camera state | Online, offline, recording, detecting |
| Camera events | Service events, motion detector triggers, object detections, plate recognitions |
| Configuration | Stream and serving-node parameters, display name, attached images and documents |
3.8 Additional functions
| Function | Description |
|---|---|
| Cargo records | Managing shipments and items (packages), binding items to vehicles with transfer history, delivery milestones, arrival forecasts |
| Public transport | Managing stops and routes, building a route line through a sequence of stops, assigning a route to a vehicle with a schedule and service days, stop arrival forecasts and punctuality monitoring |
| Alerts | Subscribing to events on a specific vehicle or geofence; delivery by email, Telegram, in-app notification, webhook and push notification to a mobile device |
| Data import | Loading reference data from Excel and CSV files with automatic table detection, column-to-attribute mapping and resolution of relations against existing records |
| Access control | User accounts, roles and access policies restricting the available operations and the visible subset of data |
| Programmatic access | Integration of external information systems through the REST API and the MCP endpoint with token authorisation |
| Mobile applications | Map, vehicle cards and alerts on Android and iOS devices |
| Multilingual interface | Switching the interface language without reloading the page |
4. Resources required to run RUBIN-T
The resources required depend on the volume and content of the data RUBIN-T will work with.
Table 1 — Minimum system requirements
| User workstations | Server hardware | |
|---|---|---|
| Operating system | Any OS supporting current browsers | Ubuntu 24.04 |
| Processor | 2 cores | 4 cores at 2.4 GHz or faster |
| Memory | 4 GB or more | 32 GB or more |
| Disk | 50 GB or more | 1 TB SSD or more |
| Browser | Yandex Browser, Google Chrome, Mozilla Firefox, Microsoft Edge (no more than one year old) | — |
5. Information used
5.1 Input data
RUBIN-T works from the following input data:
- GPS tracks from the various devices fitted to vehicles;
- video streams from surveillance cameras;
- the road network graph;
- data from integration with other information systems (through REST API services).
The principal input formats are JSON, CSV, MP4 and XML (.osm).
Reference data can additionally be loaded from spreadsheet files in XLSX, XLS and CSV formats.
5.2 Output data
RUBIN-T produces the following output data:
- interface forms;
- video files (MP4);
- text data (XLSX);
- maps (XML).
It additionally produces CSV exports of selected data and alerts delivered by email, Telegram, webhook and push notification to mobile devices.
Printable version
The PDF edition of this document is available in Russian:
⬇ Download PDF (RU)