Workload Management System for IT Professionals through Stress Identification

Thathsarani R.P.H.S.R.Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri LankaDissanayake D.M.D.M.Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri LankaNirmal M.D.S.Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri LankaP.A. Daham ThameeraFaculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri LankaW.A.C. PabasaraFaculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri LankaH.A. CalderaFaculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

Vol 7 No 10 (2023): Volume 7, Issue 10, October 2023 | Pages: 326-332

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 02-11-2023

doi Logo doi.org/10.47001/IRJIET/2023.710044

Abstract

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.

Keywords

Artificial Intelligence, Automation, Access Control, Emotion Recognition, IoT (Internet of things), Information Technology, Machine Learning, Natural Language Processing, Stress Identification


Citation of this Article

Thathsarani R.P.H.S.R., Dissanayake D.M.D.M., Nirmal M.D.S., P.A. Daham Thameera, W.A.C. Pabasara, H.A. Caldera, “Workload Management System for IT Professionals through Stress Identification” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 10, pp 326-332, October 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.710044

References

[1]

S. S. S. S. K. S. K. R. S. R. S. A. Sriman B, "Virtual Assistant for Automatic Emotion Monitoring using," in Proceedings of the International Conference on Inventive Research in Computing Applications, 2022.

[2]

D. V. S. J. P. G. K. Y. K. Amogh N. Parab, "Stress and Emotion Analysis using IoT and," in Fourth International Conference on Electronics, Communication and Aerospace Technology, 2020.

[3]

W. e. al, "Automatic stress detection using facial expressions and physiological signals," 2016.

[4]

S. a. Sinha, "Real-time stress detection using facial expressions," 2019.

[5]

V. M. a. M. P. T. Arora, "Automated Stress Detection Using Thermal Imaging and Facial Expression Analysis," in IEEE International Conference on Signal Processing and Communication, 2019.

[6]

M. S. Y. W. a. Y. C. M. Liu, "Facial Expression Analysis for Stress Detection," in IEEE International Conference on Multimedia and Expo, 2017.

[7]

K. J. M. M. H. S. M. B. a. D. B. Kamran Kowsari, "Text Classification Algorithms: A Survey," Information, vol. 10, p. 150, 2019.

[8]

T. Joachims, "Text Categorization with Support Vector Machines," in Proc. European Conf. Machine Learning.

[9]

J. Z. S. S. D. L. Xueping Liang, "Integrating Blockchain for Data Sharing and Collaboration in Mobile Healthcare Application," in The 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2017 .

[10]

Y. Z. W. S. ,. S. K. K.-K. R. C. Ning Lua, "A secure and scalable data integrity auditing scheme based on hyperledger fabric," in N. Lu, Y. Zhang and W. Shi et al. / Computers & Security, 2020.

[11]

P. P. ,. N. P. S. K. a. W. J. Charalampos Stamatellis, "A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric," Sensors, vol. 20, 2020.

[12]

Z. W. Y. Y. D.A. Adeniyi, "Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method," 2014.

[13]

S. A. a. M. I. Daud, "A Dynamic and Automated Access Control Management System for Social Networks," in Security and Communication Networks Volume, 2022.