Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
The
proposed system aims to detect and address depression levels among IT
employees, offering recommendations to alleviate their distress. Comprising
four key components—Face Recognition and Mood Detection, User Friendly Chat
Agent, Activity Recommendations based on moods and severity levels, and Voice
Analysis, the system leverages cutting-edge technologies to revolutionize
employee well-being in the workplace. The Face Recognition and Mood Detection
component employs machine learning techniques to create an advanced system.
Using computer vision algorithms, it recognizes employee faces and analyzes
facial expressions to gauge their mood. This system not only records employees'
mood statuses, encompassing emotions like sadness and anger, but also empowers consultants.
When an employee seeks guidance, the consultant can access their mood history,
aiding in understanding behavior and tailoring support. The overarching goal is
to preemptively mitigate mental stress, rectify moods, and enable consultants
to address issues effectively. The User Friendly Chat Agent acts as a secure
space for employees to interact with the company. Utilizing advanced natural
language processing and AI technology, the agent promotes positive mental
health and camaraderie while collecting valuable conversation and mental health
trend data. Integrating with the consultant team, it provides personalized
support and resources, enhancing well-being across the organization.
Incorporating the promising avenue of voice analysis, the third component
targets early depression detection. The algorithm dissects vocal
characteristics such as pitch and intonation, indicative of emotional states.
By processing voice recordings from employees with known depression levels,
this approach offers a low-cost, non-invasive method to recognize at-risk
individuals and provide timely support. The activity recommendation module
proposes suitable activities based on the employee's emotional condition,
categorized as mild or severe levels of depression. These activities are
straightforward, easily comprehensible, and not require significant time
investment. The system keeps activities log for each user, allowing filtering
choices for suggested activities based on user approval. Additionally, the
system generates music frequencies customized to the user's mood, potentially
fostering a positive effect on the employee's mental well-being and alleviating
the monotony of the office surroundings. This comprehensive system embodies a
holistic approach to tackle employee depression. By integrating
state-of-the-art technologies and leveraging real-time data, it aims to create
an empathetic, informed, and supportive workplace, ultimately enhancing mental
well-being and productivity among IT employees.
Country : Sri Lanka
IRJIET, Volume 7, Issue 11, November 2023 pp. 664-670