• Snigdha Sangam
• Vishnu Priya Vummenthala
• Valli Manasa Jandhyala
• Laxmi Pamulaparthy

The proposed project introduces a real-time system designed to detect drowsiness among individual IT employees, aiming to enhance productivity using Artificial Intelligence (AI) and IoT. This system employs a basic webcam integrated with custom code, positioned to directly monitor the individual's eyes and mouth. By analyzing facial features, particularly through the detection of yawning and closed eyes, the system triggers alarms and activates a vibrating wristband to alert the employee. The methodology involves machine learning techniques coupled with image processing, implemented through Python programming interfaced with OpenCV. The core objective revolves around monitoring online employees to mitigate productivity declines caused by drowsiness and work fatigue. The system initially detects the face's edges, followed by identifying the eyes and mouth using the Facial Landmark Detector within the D-lib Library. Subsequently, it measures the distance between the eyes and mouth to ascertain their state—open or closed. Persistent instances of closed eyes or an open mouth for a specific duration are logged. If this repetition exceeds a threshold of two occurrences, the system triggers alerts in the form of a buzz and activates the vibrating wristband. Additionally, the system employs a hardware-software synergy, incorporating RF wireless technology to communicate between the laptop and the wristband.

Drowsiness detection, Productivity enhancement, IoT integration, RF wireless technology, Real-time monitoring, Artificial Intelligence (AI), Image processing, Internet of Things (IoT).

"IoT-Enhanced Drowsiness Detection System for IT Employees: Boosting Productivity with AI and Wearable Technology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.f241-f245, February-2024, Available :http://www.jetir.org/papers/JETIR2402531.pdf

"IoT-Enhanced Drowsiness Detection System for IT Employees: Boosting Productivity with AI and Wearable Technology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppf241-f245, February-2024, Available at : http://www.jetir.org/papers/JETIR2402531.pdf