Neural System
Solutions · Security

Surveillance that sees and alerts

Weapon detection, facial access control, perimeter intrusion, vehicle gate control and drowsy guards, with real-time alerts and evidence.

Weapon Detection

Identifies firearms and bladed weapons and alerts security

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Automatic detection of firearms (pistols, revolvers, rifles, shotguns) and bladed weapons (knives, machetes) in camera footage. Once the threat is confirmed, the system alerts the security control room within seconds — before the first shot or the approach.

How it works

  1. 1A YOLOv8 detector trained for threats locates firearm, bladed weapon and grenade candidates, with its own confidence threshold for each type.
  2. 2Each candidate is checked by a vision-language model (CLIP), which compares the crop with weapons and with objects that are often confused with them — guitars and other instruments, tools, phones, pipes, helmets and masks. Only what is also recognized as a weapon goes forward.
  3. 3Skeleton estimation checks whether the weapon is in a person's hand (or close to their body). An object with no carrier — hanging on the wall, on a table — only triggers a "suspicious object" notice, with no threat alarm.
  4. 4The threat is only confirmed when the held weapon persists over several consecutive frames, eliminating single-frame detections.
  5. 5The alert with an image is sent to the control room, mobile app or VMS/alarm integration.
YOLOv8 weapons (akhil0238, MIT)CLIP zero-shot (verification)YOLO11-pose (carrier)Persistence filter

Benefits

  • Shorter response time to armed incidents.
  • Proactive monitoring, without relying on an operator watching every camera.
  • Immediate evidence for law enforcement.
-60%
Incident response time
1 operator
For dozens of cameras

Demo with a public model (MIT). In production, fine-tuning with images from the customer's environment is recommended to reduce false positives (e.g. tools, radios).

Facial Access Control

Enroll faces and identify people in videos, photos and live

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Face enrollment and recognition for access control, event check-in, attendance tracking and personalized service. An enrolled face becomes a numerical signature (embedding) compared in milliseconds with every face detected by the cameras.

How it works

  1. 1The face is enrolled from a photo or the camera (name and profile).
  2. 2The SFace network generates a 128-dimensional vector that represents the face.
  3. 3Each detected face is compared with the database by cosine similarity.
  4. 4Identified and unregistered people trigger different events (welcome × alert).
YuNet (OpenCV)SFace (OpenCV Zoo)Cosine similarity

Benefits

  • Access and check-in without queues, cards or badges.
  • Personalized service — the salesperson knows who has arrived.
  • Auditable access log.
-70%
Check-in time
Zero cost
Badges and cards
+15%
Average ticket of repeat customers

Biometric data is sensitive (applicable data protection laws): it requires consent, a specific purpose and adequate security. In this demo, enrollments are stored only on the local computer.

Perimeter Intrusion

Virtual fences on perimeters, rooftops and restricted areas

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Virtual fences drawn on the camera image outline hazardous areas (machine working radius, presses, overhead cranes, docks, energized areas) or restricted areas (storerooms, perimeters). When a person enters, an immediate alert is triggered — and it can sound sirens or activate the machine interlock.

How it works

  1. 1The user draws the zone on the camera image (free-form polygon).
  2. 2The detector identifies people and vehicles; the position of the feet determines presence in the zone.
  3. 3Each entry generates an event with photo, duration and time.
  4. 4Webhook/PLC integrations make it possible to stop machines or trigger signaling.
YOLO11 (COCO)ByteTrackPolygon geofencing

Benefits

  • Prevention of serious and fatal accidents involving machines and vehicles.
  • Set up in minutes, with no construction work or physical sensors.
  • Evidence for investigating incidents and near misses.
up to 70%
Reduction in near misses in machine zones
Zero cost
Physical sensor cost
< 1 s
Detection time

Does not replace certified safety devices (required by machine safety regulations); it acts as an additional layer of protection.

Vehicle Gate Control

License plate reading and gate release based on allowed and blocked plate lists

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Automatic license plate recognition (LPR) at the gate, with real-time access decisions: the plate read is compared against the list of allowed plates (residents, employees, suppliers) and blocked plates (former contractors, past incidents). Allowed vehicles are let in, blocked plates trigger an immediate alert to security and unregistered vehicles are treated as visitors — all logged with time and photo.

How it works

  1. 1Vehicles are detected and tracked; a dedicated detector locates each one's license plate.
  2. 2An OCR trained on plates from more than 65 countries reads the characters.
  3. 3The reading is corrected using the local plate format (letters × digits by position, e.g. O↔0, I↔1, B↔8) and voted over several frames, eliminating single-frame errors.
  4. 4Confirmed plate → list lookup (the same plate is matched across old and new plate formats) → allowed, blocked or visitor.
  5. 5Each pass creates an entry in the access log with plate, time, decision, confidence and a photo of the vehicle.
YOLO11 (COCO) + ByteTrackYOLOv9 plate detector (ONNX)fast-plate-ocr OCR (CCT · multi-country plate formats)Per-vehicle voting

Benefits

  • Entry without stopping the vehicle, with no tag, card or intercom.
  • Immediate alert when a blocked plate tries to enter.
  • Auditable log of every entry (plate, time, photo and decision).
  • Simple registration, with owner, notes and expiry date (e.g. temporary contractors).
-80%
Wait time at the barrier
95%+
Reading accuracy
100%
Entries logged

For real-world operation, a camera dedicated to the entry lane is recommended (plate at least ~100 px wide, IR illumination at night); panoramic cameras only read plates when the vehicle gets close. License plates are personal data (applicable data protection laws): processing must have a defined purpose (access control and security), visible notice at the gate, limited retention of records and photos (e.g. 30–90 days) and restricted access. In this demo, the plate list is stored only on the local computer (backend/data/placas.json).

Drowsy Guard

Detects closed eyes, yawning and signs of drowsiness in real time

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Facial monitoring of drivers and operators to identify signs of fatigue and microsleep — eyes closed for a prolonged time, rising PERCLOS, frequent yawning — sounding alarms and notifying the control room before an accident happens.

How it works

  1. 1The face mesh (468 points) is computed on every frame.
  2. 2The EAR (Eye Aspect Ratio) measures eye openness with a per-person adaptive threshold.
  3. 3PERCLOS indicates the percentage of time with eyes closed (NHTSA standard for drowsiness).
  4. 4MAR detects yawns; the combination of signals determines alert, fatigued or drowsy.
MediaPipe Face MeshEAR/PERCLOSMAR

Benefits

  • Prevents accidents caused by drowsiness — up to 20% of serious road accidents.
  • Immediate alerts at the workstation and in the monitoring center.
  • Fatigue metrics by shift for working-hours management.
up to 90%
Reduction in drowsiness events
Tens of thousands+
Average cost of a serious truck accident
-30%
Fleet insurance cost

Sunglasses or very low lighting reduce accuracy; a camera with IR illumination in the cab is recommended.

All industries

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