Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
A
significant issue which is reported by most of the employees suffering from
stress is, allocation of heavy workloads by their project managers without the
acknowledgement of their stress condition. This study intends to investigate
the connection between workload distribution and workplace stress levels and
automate the work allocation based on stress metrics. To accomplish the need of
identifying stress, a voice based chatbot to track emotions and a device
developed to track the body parameters of the employee has been implemented.
The speech data and body parameters collected while the employee is at work has
been converted to a stress level in this study. And also, this project
concerned with protecting the privacy of employee personal data collected by
IoT sensors and chatbot. It aspires to improve data security, integrity, and
accessibility by leveraging blockchain and advanced AI, addressing the critical
importance of data privacy in today's world. Proposed method will automatically
assign tasks for the employees based on stress metrics by using Machine
Learning techniques. The anticipated findings of this study will have an impact
on the IT workforce, particularly Project Managers and Developers. This
project's contribution will allow Project Managers to assign work based on
employees' actual stress levels. While getting less complaints from developers
about hefty workloads.
Country : Sri Lanka
IRJIET, Volume 7, Issue 10, October 2023 pp. 326-332
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