- January 8, 2020
- Artificial Intelligence, NLP, Technology
Attendance tracking for resources on the field is a critical task in most of the organization. It helps in monitoring employees’ attendance, their working hours, time spent at each location, geo-fencing the work locations and generating reports on the work done. While attendance tracking has traditionally been done manually, with employees logging in their hours using paper or electronic systems, technology has made it easier to streamline the process.
Face recognition is one such technology that has gained popularity in recent years. It uses facial recognition to identify employees and log their attendance. This system has several advantages over traditional attendance tracking methods. For instance, it eliminates the need for manual input, thereby reducing the risk of errors. It is also faster, as it takes only a few seconds to identify an employee and log their attendance.
The Scenario
For a leading construction or mining industry, accurate attendance tracking and monitoring of employees is a high priority. The industry seeks a high-efficiency solution for tracking the attendance, working hours, and locations of its expansive workforce. By implementing a secure face recognition system to monitor employee movements at all times, this organization can more reliably track work hours accurately.
Problem Statement
Face recognition attendance is not without its challenges, specifically when it comes to managing attendance for employees who work in different locations or on different projects. To address this issue, we can divide employees into three groups based on their attendance requirements.
Single Location Workforce is a group of employees who work in a single location. They need to be geofenced to their workplace and log in and out at the same place daily. This is a straightforward requirement, and a simple system can easily meet their needs.
Multiple Location Workforce is a group of employees who work on different projects and their work location changes based on the projects they work on each day. They need to be geofenced to the locations of the projects they work on for the day. They must log in and log out at each project location. Once they log in to a project location, they need to log out at the same location before logging in to another location. The log-out button should be disabled, or they should be logged out automatically once they move out of the location.
Live tracking Workforce is similar to multi-location workforce, but they have an additional requirement. They also work on different projects and their work location changes based on the projects they work on for the day. However, they need their live location to be tracked, and managers should be able to locate them at any given time.
Our Solution
To meet these requirements, DataMoo has created FaceViz – Attendance tracking application for field resources that can accurately track employees’ attendance, location, and working hours. It can also provide real-time location tracking for employees who need to be continuously monitored for their current location. The application will have a prerequisite on the database of employee facial data, which is collected through facial scanning and stored in a secure server. To ensure the accuracy and consistency of data, the system can be integrated with the company’s existing HR management software.
The workflow for this system is straightforward. Employees will log in and out using the face recognition system at their designated locations. The attendance data will then be submitted to the managers for approval on a daily, weekly, or monthly basis. FaceViz uses the geo tagging and geo-fencing technology to improve the accuracy and security of the system.
Geo tagging identifies the location where an employee has checked in or out using the face recognition system. By adding geographical identification metadata to the attendance data, the company easily monitors the location of their employees in real-time. This ensures that employees are at the designated work site and not using the face recognition system from a remote location.
Geo fencing creates virtual boundaries around the work site or specific areas within the work site. This allows the company to ensure that employees are within the designated work areas while on the job. If an employee exits the virtual boundary, the system sends an alert to the management team to investigate the situation and ensure that employee safety is not compromised. This improves overall employee productivity, safety, and accountability.
How our solution streamlined the field resource management
With FaceViz, the company can easily monitor and manage employee productivity, streamline payroll processing, and improve project management. This has resulted in increased efficiency, reduced costs, and improved overall performance. The system’s real-time location tracking for employees has also greatly improved safety and security on the field while optimizing resource allocation and project progress monitoring.
The integration with the company’s existing HR management software ensures that all attendance data is consistent and up-to-date. This eliminates the need for manual data entry and reduces the risk of errors or discrepancies. This can also offer insights into employee performance and activities helping management during appraisals. Faceviz emails automatic reports eliminating the need for tedious follow-ups.
Overall, our flagship product FaceViz has provided the company with a reliable and efficient way to manage resources on the field. The implementation of facial recognition technology has improved accuracy and reduced the risk of fraud or abuse. The system has also addressed privacy concerns by ensuring that employee data is stored securely and only accessible by role-based authentication. Please reach out to know more: reachus@datamoo.ai
