A large Automotive Tier-1 manufacturer required an automated attendance management solution capable of accurately identifying employees from video frames and associating them with a unique Employee ID. The objective was to accurately determine attendance, prevent attendance misuse such as buddy swipes, proxy attendance, and fake OT marking, and provide a contact-free attendance management solution capable of round-the-clock operation.

The project was delivered over six months by a dedicated ALTEN team of three engineers in India. The engagement focused on developing a deep learning-based facial recognition system, attendance data management capabilities, and reporting and dashboard generation. The solution was designed to deliver attendance determination with a target accuracy exceeding 95% while ensuring personal information was not stored within the application and was retrieved through company-controlled systems.

The scope included:

• Facial recognition-based attendance management
• Employee identification from video frames
• Attendance marking
• Prevention of attendance misuse
• Attendance reporting and dashboards
• Deep learning model development
• Real-time face detection and recognition
• Backend services and business logic development
• Attendance data management
• Access-controlled company data retrieval
• System deployment and validation

Challenge:

Accurate Attendance Identification

• Identifying employees from video frames while maintaining attendance determination accuracy above the target threshold
• Associating detected faces with the correct employee identities for attendance marking

Preventing Attendance Misuse

• Addressing attendance misuse scenarios such as buddy swipes, proxy attendance, and fake OT marking
• Ensuring accurate attendance determination through facial recognition

Real-Time Video Processing

• Detecting and recognizing individuals in real time using multiple concurrent predictions
• Supporting attendance identification through real-time AI/ML detections

Secure Data Management

• Supporting attendance processing without storing personal information within the application
• Ensuring required employee data was fetched from company servers using access-controlled methods

Around-the-Clock Operation

• Delivering a solution capable of round-the-clock operation
• Maintaining recognition performance independent of cultural and demographic factors

ALTEN Solutions

Deep Learning-Based Facial Recognition Engine

• Developed a facial recognition solution capable of detecting faces from video frames and mapping them to unique employee identities
• Enabled automated attendance marking through real-time face recognition
• Established a contact-free attendance process

DeepFace-Based Recognition Framework

• Implemented an AI/ML module using the DeepFace framework and state-of-the-art face recognition models including VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, ArcFace, Dlib, and SFace
• Leveraged multiple concurrent prediction mechanisms for employee recognition
• Enabled attendance identification with an accuracy target exceeding 95%

Attendance Data Management

• Developed a database module to store attendance data
• Enabled attendance data storage and retrieval for reporting purposes
• Supported attendance management through structured data handling

Backend Services and Dashboard Platform

• Developed backend services that execute AI/ML models and business logic
• Supported report generation, queries, and dashboard generation
• Enabled attendance reporting and dashboard capabilities

Privacy-Conscious System Architecture

• Designed the solution without storing personal employee information within the application
• Retrieved all required employee data through company-controlled access mechanisms
• Enabled attendance processing using access-controlled company data sources

Real-Time Operational Deployment

• Enabled real-time facial recognition using video frames with continuous processing capabilities
• Designed the solution to run round the clock with a constant lighting source controlling the environment
• Delivered recognition performance that remained independent of cultural and demographic factors

Dedicated Delivery Team

• Maintained a focused team of three engineers throughout the six-month engagement
• Delivered AI/ML development, backend services, attendance data management, dashboard creation, and validation activities from India

Business Benefits

High Accuracy Attendance Determination

• Attendance determination supported by AI/ML models with a target accuracy exceeding 95%

Attendance Misuse Prevention Capability

• Facial recognition capabilities supported prevention of buddy swipes, proxy attendance, and fake OT marking

Contact-Free Attendance Process

• Facial recognition enabled attendance marking without physical interaction

Privacy-Conscious Data Handling

• Employee data was fetched from company servers using access-controlled methods without storing personal information within the application

Continuous Real-Time Operation

• Real-time detections, multiple concurrent predictions, and round-the-clock operation supported attendance management requirements

Tools, Technologies & Expertise

Engineering & Development Tools

• Python
• JavaScript
• React
• HTML
• CSS
• Kafka
• RabbitMQ
• DeepFace Framework

Engineering Capabilities

• Facial Recognition System Development
• Deep Learning Model Development
• Real-Time Video Analytics
• Attendance Management Automation
• Dashboard and Reporting Development
• Backend Services Development
• Attendance Data Management
• Concurrent Prediction Optimization

Domain Expertise

• Workforce Management Solutions
• Attendance Tracking Systems
• Computer Vision Applications
• Video Analytics Platforms
• Attendance Data Management
• AI/ML-Based Automation

Where ALTEN Adds Value

• Developing facial recognition solutions that combine real-time video analytics with attendance management workflows
• Leveraging DeepFace and multiple face recognition models within a unified attendance management solution
• Integrating AI/ML capabilities, attendance data management, reporting, and dashboard functionality
• Delivering attendance management systems that support contact-free operation and privacy-conscious data handling

Why ALTEN
ALTEN combines expertise in computer vision, deep learning, and enterprise application development to deliver facial recognition-based attendance management solutions. By integrating facial recognition, attendance data management, reporting, and dashboard capabilities within a unified platform, ALTEN enables organizations to improve attendance determination and prevent attendance misuse through automated, contact-free processes.