Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/1219
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Amarasinghe, A.A.S.M. | - |
dc.contributor.author | Malassri, I.M.S. | - |
dc.contributor.author | Weerasinghe, K.C.N. | - |
dc.contributor.author | Jayasingha, I.B. | - |
dc.contributor.author | Abeygunawardhana, P.K.W. | - |
dc.contributor.author | Silva, S. | - |
dc.date.accessioned | 2022-02-17T06:59:01Z | - |
dc.date.available | 2022-02-17T06:59:01Z | - |
dc.date.issued | 2021-12-09 | - |
dc.identifier.issn | 978-1-6654-0862-2/21 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/1219 | - |
dc.description.abstract | Working from home (WFH) online during the covid-19 pandemic has caused increased stress level. Online workers/students have been affecting by the crisis according to new researches. Natural response of body, to external and internal stimuli is stress. Even though stress is a natural occurrence, prolonged exposure while working Online to stressors can lead to serious health problems if any action will not be applied to control it. Our research has been conducted deeply to identify the best parameters, which have connection with stress level of online workers. As a result of our research, a desktop application has been created to identify the users stress level in real time. According to the results, our overall system was able to provide outputs with more than 70% accuracy. It will give best predictions to avoid the health problems. Our main goal is to provide best solution for the online workers to have healthy lifestyles. Updates for the users will be provided according to the feedback we will have in the future from the users. Our System will be a most valuable application in the future among online workers. | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.subject | stress detection | en_US |
dc.subject | fatigue recognition | en_US |
dc.subject | emotion detection | en_US |
dc.subject | behavior detection | en_US |
dc.subject | keystroke detection | en_US |
dc.subject | CNN | en_US |
dc.subject | VGG16 | en_US |
dc.title | Stress Analysis and Care Prediction System for Online Workers | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC54203.2021.9671106 | en_US |
Appears in Collections: | 3rd International Conference on Advancements in Computing (ICAC) | 2021 Research Papers - Dept of Computer Systems Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Stress_Analysis_and_Care_Prediction_System_for_Online_Workers.pdf Until 2050-12-31 | 2.06 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.