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Computer Vision

Computer vision that turns cameras into operational data

Computer vision is the field of AI that lets systems recognize faces, objects, text and events in images or video. Cameras are already installed across many workplaces, but their footage is rarely processed. MBT builds computer vision solutions that pass detections to business applications as actionable data.

Computer Vision Solutions, Video Analytics

  • Face recognition & camera attendance
  • Object detection & safety monitoring
  • Connected to HRIS, dashboards and notifications
  1. 01Camera
  2. 02Vision Engine
  3. 03Detection / Recognition
  4. 04Business Rule
  5. 05Enterprise App

Business problems

Business problems we solve

CCTV footage is only watched after incidents

Important events are noticed too late because nobody monitors continuously.

Attendance and access can be shared

Cards and PINs can be lent to others, so attendance and access data are inaccurate.

Visual inspection depends on people

PPE, goods or product quality checks are inconsistent and hard to measure.

What we build

Computer vision use cases

  • 01

    Face Recognition

    Face-based identity verification for access and attendance.

  • 02

    Employee Recognition

    Recognize registered employees in specific work areas.

  • 03

    Camera Attendance

    Camera-based attendance connected directly to HRIS and payroll.

  • 04

    Entry / Exit Tracking

    Record people or vehicles entering and leaving gates and restricted areas.

  • 05

    Object Detection

    Detect and count objects such as goods, vehicles or equipment.

  • 06

    CCTV / Video Analytics

    Analyze CCTV footage for restricted zones, crowding or specific activities.

  • 07

    OCR Vision

    Read text from cameras, such as container numbers, labels or license plates.

  • 08

    Safety Monitoring

    Detect PPE usage and unsafe conditions in work areas.

  • 09

    Vehicle Recognition

    Recognize vehicles and license plates for gates, parking or fleets.

  • 10

    Industrial Vision

    Visual inspection on production lines to detect defects or non-conformities.

Example applications

Considerations before implementation

  • Camera quality & placement

    Resolution, angle and lighting determine accuracy, so we assess the cameras first.

  • Privacy & consent

    Facial data is sensitive personal data. Consent, processing purpose and access restrictions are set from the start.

  • Data retention

    How long footage, photos and face templates are kept is defined by need and regulation, then deleted automatically.

Architecture & approach

From camera to enterprise application

Every solution follows the same pipeline, so detections do not stop at recordings but become actions in your business systems.

  1. 01

    Camera

    Existing CCTV or IP cameras, or new devices.

  2. 02

    Vision Engine

    Models that process video in real time or on schedule.

  3. 03

    Detection / Recognition

    Faces, objects, vehicles, text or events that are recognized.

  4. 04

    Business Rule

    Rules that decide whether a detection is recorded or acted upon.

  5. 05

    Enterprise App

    Data flows into HRIS, dashboards, notifications or other systems.

Technology & integration

Technology & integration

Video processing and integration into business systems.

  • Python
  • IP camera / CCTV stream (RTSP)
  • Detection & recognition models
  • Edge devices
  • REST API
  • HRIS & dashboard integration

Deployment

Deployment, edge AI & data retention

Where processing runs depends on the number of cameras, latency needs, bandwidth and data policy.

Option Description Best for
Edge AI Processing on a device near the camera; only detections are sent to the server.
  • Low latency
  • Limited bandwidth
  • Video stays on site
On-premise server Many cameras processed on internal company servers.
  • Biometric data stays in-house
  • Integration with local systems
Cloud Processing and dashboards in the cloud for many locations.
  • Many branches
  • Centralized analytics

Proof of work

Built on CCTV experience

We built Smart Online CCTV for PT Mesin Isuzu Indonesia: a web-based platform for managing many cameras and users, with motion detection and real-time access. This experience with camera streams is the foundation of our computer vision solutions.

Multi-camera & multi-user Motion detection Real-time browser access
View case study: Smart Online CCTV

FAQ

Frequently asked questions

Can computer vision be used for attendance?
Yes. Camera attendance uses face recognition to record touchless attendance and sends the data to HRIS and payroll. Accuracy depends on camera placement, lighting and the face enrollment process.
Can we use our existing CCTV?
Often yes, as long as image quality, camera angles and stream access are adequate. We assess the cameras before defining the solution.
What about facial data privacy?
Biometric data is sensitive personal data. We design solutions with user consent, restricted access and data retention policies in line with personal data protection regulations.
Does processing have to run in the cloud?
No. Processing can run on edge devices near the cameras, on local servers (on-premise) or in the cloud, depending on the number of cameras, latency needs and data policy.

Discuss your computer vision requirements

Tell us about the area, cameras and events you want to detect. We will help assess feasibility and design a proof of concept.