| Autor: |
R. P. H. S. R., Thathsarani, D. M. D. M., Dissanayake, M. D. S., Nirmal, Daham Thameera, P. A., Pabasara, W. A. C., Caldera, H. A. |
| Předmět: |
|
| Zdroj: |
International Research Journal of Innovations in Engineering & Technology; Oct2023, Vol. 7 Issue 10, p326-332, 7p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
