Objective: Implement a dual-system solution that accurately tracks attendance and working hours for 70 onsite staff via facial recognition, while simultaneously monitoring the actual productivity and activity of 10 offsite workers to prevent unnecessary overtime costs.
Scope:
- Onsite: Hardware supply, installation, and biometric registration for 70 employees.
- Offsite: Software deployment for 10 remote workers to track activity and productivity.
- Admin: Centralized dashboard for reporting and management.
Goal: Replace manual or insecure check-ins with a frictionless facial recognition system at the entrance.
- Device Procurement: Supply of a high-capacity facial recognition terminal (supports 70+ users with local storage or cloud sync).
- Installation: Mounting the device at the main entrance, configuring power and network connectivity (Ethernet/Wi-Fi).
- Setup: Configuration of the device IP, server connection, and time zone settings.
- Enrollment Drive: Capture high-quality facial data for all 70 employees.
- Profile Creation: Assigning unique IDs, names, and department tags to each user.
- Testing: Live test runs to ensure recognition speed and accuracy during peak arrival times.
- Check-In/Check-Out: Employees simply look at the device upon arrival and departure.
- Data Sync: Real-time transmission of attendance logs to the central admin software.
- Working Hours Calculation: Automatic calculation of total hours worked per day/week.
Goal: Monitor actual work activity for remote staff and eliminate "ghost" overtime caused by idle systems being left on.
- Agent Installation: Install lightweight tracking software on the 10 offsite workers' desktops/laptops.
- Configuration: Set up individual profiles for the offsite team.
- Active vs. Idle Time: The system must distinguish between system active (screen on) and user active (mouse/keyboard input).
- Application Usage: Track which apps are being used (e.g., Excel vs. YouTube).
- Screenshots (Optional): Periodic random screenshots for verification of work.
- Productivity Scoring: Categorize apps/websites as "Productive," "Neutral," or "Unproductive."
The Requirement: Overtime must only be counted when actual work is being performed, not just when a system is left on.
The Solution:
- Idle Detection: If the user is idle for more than X minutes (e.g., 10 mins), the system stops counting "Work Time" even if the computer is on.
- Active Work Overtime: Overtime will only be calculated when there is active input and productive application usage after hours.
- Auto-Logout/Shutdown (Optional): Configure the system to alert the admin if a machine is left on and idle for extended periods.
Goal: Provide management with a single view of both onsite and offsite workforce data.
- Onsite View: Real-time presence (who is in the building right now).
- Offsite View: Real-time status (who is active, who is idle).
- Attendance Reports: Daily, weekly, and monthly attendance sheets for onsite staff.
- Daily/Weekly Reports: Automated reports generated for the 10 offsite workers.
- Actual Hours Worked: Reports will show "Total Hours Logged In" vs. "Total Active Productive Hours."
- Overtime Audit: A specific report highlighting overtime claims that were flagged as "Idle" or "Low Activity" to prevent fraudulent payouts.
| Week | Milestone |
|---|---|
| Week 1 | Procurement of hardware and software licenses. |
| Week 2 | Onsite installation and configuration of biometric device. |
| Week 3 | Enrollment of 70 onsite staff (facial registration). |
| Week 4 | Installation of offsite tracking agents on 10 machines. |
| Week 5 | Admin training and system handover. |
- 1x Facial Recognition Terminal (installed & configured).
- 70x Registered user profiles.
- 10x Offsite productivity tracking licenses (installed).
- 1x Admin management system (web-based or desktop).
- Automated reporting system for attendance and overtime.
- Onsite: 100% of staff registered and using facial check-in daily.
- Offsite: Accurate distinction between "System On" and "User Working."
- Financial: Reduction in unnecessary overtime payouts by identifying idle time after hours.