Face Recognition System – Overview
- In the framework of the attendance system, facial recognition of the human face is a current issue for identity verification.
- A facial recognition software attendance system uses high-definition monitors and other computing infrastructure to select individuals using face biostatistics.
- A face recognising presence system uses high-definition video monitoring, face biostatistics, and AI&ML strategies and tools to identify persons at work.
- The system was devised to establish a simple and secure technique of taking attendance.
- Face detection will be the first phase, accompanied by standardization, edge detection, and computer vision as the last step.
Why AI in Construction Industry?
- The expense and powerful artificial intelligence products will be the major growth engines for the construction industry’s use of artificial intelligence.
- The real driving force behind AI for the construction industry is data. For precise conclusions, data availability and collection are crucial, notably for protection and monitoring applications.
- The implementation of AI-based facial attendance stops site engineers from supplying unapproved and proxy attendance for other workers when they is not on the work place.
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.
