Face Recognition System – Overview
- Facial recognition of the human face is an active issue for authentication purposes, specifically in the context of the attendance System.
- An attendance system using face recognition is a procedure of recognizing employees by using face biostatistics based on high-definition monitoring and other computer technologies.
- A Face recognition-based attendance system recognizes people at work using face biostatistics on high-definition monitoring coupled with AI&ML algorithms and technologies.
- The system was developed for deploying an easy and secure way of taking down attendance.
- The Initial step is face detection, the second is normalization, the third is feature extraction, and the final step is face recognition.
Why AI in Construction Industry?
- Artificial intelligence in construction market growth will be majorly driven by the cost efficiency and advanced artificial intelligence products
- AI is primarily a data-driven technology. Availability and collection of data are very important for accurate results, especially in the case of safety and monitoring applications.
- With AI-based Facial attendance in place, it prevents site engineers from providing proxy and unauthorized attendance for other co-workers when they aren’t on the site.
Facial Attendance System– 5 Key Advantages
- Image Capture & Recognition
- Profile Creation
- Attendance Registration
- Geo Location
- Time Stamp
How have We Implemented a Facial Attendance System for One of The World’s Top 5 Construction industries?
Solution Overview
- This application captures Daily attendance using facial recognition and pushes the count against the WBS.
- In case there is a new workman with the minimum records (trailing mail), the site engineer will enroll the workmen with the app.
- Once done, newly enrolled details will be pushed to the Screening platform for completing the screening procedure.
Application Flow
Tech Stack
Key Features
Market Size: AI & ML in Construction Industry
MarketsandMarkets expects the global market to grow from USD 329.3 Million in 2017 to USD 1,831.0 Million by 2023, at a Compound Annual Growth Rate (CAGR) of 35.1% during the forecast period.
