Building a Computer Vision Model Hosting Platform for a Leading Indian Conglomerate

19 Nov 2022

Building a Computer Vision Model Hosting Platform for a leading Indian Conglomerate

About the Company

This conglomerate is the third-largest in the Indian private sector. It has interests in viscose staple fibre, metals, cement (largest in India), viscose filament yarn, branded apparel, carbon black, chemicals, fertilisers, insulators, financial services, and telecom. This multinational has a dedicated cell, which is the data science center of the conglomerate, which is managed from their Mumbai headquarters.

Problem Statement

One division of the organization is building a platform that deploys custom-built AI/ML models for analyzing videos and providing customized solutions for solving business problems. The platform is scalable and built for quick deployment to process multiple camera streams in parallel and apply advanced video analytics in near real-time.

They required solutions to automate the safety guidelines that had to be followed within their cement and aluminum plants, using pre-installed cameras and computer vision processing. Compliance with guidelines has become even more significant to avoid spreading any infectious diseases, such as COVID-19.

HashedIn’s Solution

HashedIn built the data pipelines and a dashboard for the plant supervisor to view and/or receive an alert (voice, SMS, email, etc.) for any employees that are breaking the stipulated safety guidelines, in near real-time. We built a dashboard for the business stakeholders to visualize the violations happening on the plant to make business decisions, accordingly. A technical dashboard was developed for system and application health anomalies and data transfer checks from one subsystem to another.

This platform can be used to build solutions across sectors and functions, with features such as:

Helmet detection

Vest detection

Fire detection

Intrusion detection

Social distancing detection

Arrow direction detection

Unattended object detection

Face-mask detection

Vehicle detection

The administrator can configure the email id’s of area managers and plant-heads in the system so that they can receive detailed daily/monthly/annual reports daily. To expose this data, events, alerts to external systems for integration, which would be similar to the existing voice alert system. External systems such as turnstiles (automatic doors – for the unauthorized personnel, the doors won’t open), the plant siren (can be used for fire alert to inform all the workers to evacuate the area), etc. For the safety of the employees who were back to work amid the COVID-19 circumstances, face-mask and social distancing features were deployed, before the plants were opened.

Let us look at the use case for Helmet and Vest Identification:

A helmet and vest should be worn by everyone present on the plant, as there is heavy equipment operating in the area. Employees will be exposed to risks if their helmet/vest is removed while working on the site. To check compliance (whenever anyone is observed without their helmet/vest), the client wanted a system that plays a voice alert and a supervisor dashboard, that gives real-time data to the supervisor/plant-head.

Technology Stack

Django

Celery

RabbitMQ

FFMPEG

React (Typescript)

Python Scripting

Grafana

PostgreSQL

Nginx

Docker

Business Outcomes

A web interface to the end-user (plant supervisors, plant safety managers, compliance officers, etc.) to view any safety violations/intrusions/compliance exceptions/etc. happening at the plant in a near real-time environment.
Enabled real-time alerts on specific exception events through multiple channels (on-premise speakers, dashboards, SMS, emails, etc.)
A web interface for the business stakeholders to view the summary of any violations happening at the plant on a daily level.
The data is exported to the cloud on a daily basis.
In the near future, a cloud-based dashboard will be created on cloud for the business users to analyze the violation trends of multiple plants, giving them reports at an hourly level.