Computer Vision Analytics Platform

A computer vision platform that turns recorded and live video feeds into people, vehicle, and maritime operational insights.

LIVE PLATFORM / AWS DELIVERY

OPERATIONAL ANALYTICS / MULTI-USE-CASE SYSTEM

Case study / 03

Project context

Transportation & Logistics

Plumfind contribution

AI & Intelligent Systems
Analytics & Data
Cloud & Infrastructure

Technology

YOLO, image segmentation, AWS

Timeline

Use-case research, shared platform, live deployment

BUSINESS CHALLENGE

Thousands of cameras. Millions of hours of footage. Zero operational insight.

Organizations have camera infrastructure but limited ways to turn footage into useful decisions, monitoring trends, or timely operational alerts.

CAMERA INFRASTRUCTURE / DECISION GAP

DISCOVERY & RESEARCH

01 / Business context

We began with the camera infrastructure and the operational questions.

02 / Reusable use cases

Transportation, logistics, smart infrastructure, retail, and facilities informed a shared platform foundation.

03 / Decision layer

The experience prioritizes clear counts, trends, modes, and alerts instead of exposing raw detections.

04 / Production plan

AWS EC2, Application Load Balancer, ACM, Route 53, and secure hosting controls supported live deployment.

REQUIREMENTS / operational field study

Reusable use cases. One operational language.

We compared transportation, logistics, smart infrastructure, retail, and facilities workflows to define a shared platform without losing the details each operation needed.

SOLUTION

From considered direction to a production system.

01

Reusable detection foundation

A shared platform was designed to support multiple industry use cases rather than a narrow deployment.

02

Decision-first analytics

Counts, trends, monitoring modes, and alerts were prioritized over a raw stream of model detections.

03

Maritime specialization

Custom fine-tuning extended the platform to a business-specific vessel detection workflow.

Architecture / system flow

The system is a set of deliberate connections.

Each layer was selected to support the business workflow, not to make the technical picture more complicated.

Implementation

From model output to a dependable production system.

01

Experience & system design

Counts, trends, monitoring modes, and alerts were designed around operational decisions rather than raw detections.

02

Engineering

YOLO, object tracking, custom maritime fine-tuning, analytics, and live-stream processing formed the intelligence layer.

03

Deployment & ownership

EC2, Application Load Balancer, ACM, Route 53, and secure controls supported reliable live delivery.

BUSINESS IMPACT

Operational intelligence people can act on.

Built workflows for people, vehicle, and vessel detection
Created operational trend dashboards
Implemented custom maritime detection
Connected live monitoring to automated alerts

LESSON LEARNED

Detection alone is not operational intelligence. A shared platform can support multiple industries, but every output still needs to answer specific business questions.