Stress Detection of the Employees Working in Software Houses using Fuzzy Inference

Abstract

In the modern era where the use of computer systems in software houses is mandatory and in various organizations has increased, it has given rise to the level of stress of employees working for hours at the system as well. Employees working in software houses are prone to have increased stress and anxiety level. It is important to detect the stress level of the employees so that various solutions can be applied in the working environment to get a better output. This paper would be beneficial for detecting the stress level of employees working on the computer using various inputs i.e. heart rate, pupil contraction, facial expressions, skin temperature, blood pressure, age and number of hours working on the computer. This research would indicate the raised level of stress of employees and this indication can be used to increase the yield of the quality of work and satisfaction of employees working in a particular organization. According to the levels of stress, within the working environment, during break hours various steps can be taken as a solution and applied during break hours of employees to ensure maximum satisfaction and the improved quality of work.

Authors and Affiliations

Rabia Abid, Nageen Saleem, Hafiza Ammaraa Khalid, Fahad Ahmad, Muhammad Rizwan, Jaweria Manzoor, Kashaf Junaid

Keywords

Related Articles

Bootstrap Approximation of Gibbs Measure for Finite-Range Potential in Image Analysis

This paper presents a Gibbs measure approximation method through the adjustment of the associated estimated potential. We use the information criterion to prove the accuracy of this approach and the bootstrap computation...

Comparatative Analysis of Energy Detection Spectrum Sensing of Cognitive Radio Under Wireless Environment Using SEAMCAT

In the recent years, the Cognitive Radio technology imposed itself as a good solution to enhance the utilization of unused spectrum and globalized the radio environment for different band users that utilize or require di...

Weighted Unsupervised Learning for 3D Object Detection

This paper introduces a novel weighted unsuper-vised learning for object detection using an RGB-D camera. This technique is feasible for detecting the moving objects in the noisy environments that are captured by an RGB-...

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

Web-services have become a governing technology for Service Oriented Architectures due to reusability of services and their dependence on other services. The evolution in service based systems demands frequent changes to...

Traffic Signs Recognition using HP and HOG Descriptors Combined to MLP and SVM Classifiers

Detection and recognition of traffic signs in a video streams consist of two steps: the detection of signs in the road scene and the recognition of their type. We usually evaluate globally this process. This evaluated ap...

Download PDF file
  • EP ID EP448746
  • DOI 10.14569/IJACSA.2019.0100129
  • Views 92
  • Downloads 0

How To Cite

Rabia Abid, Nageen Saleem, Hafiza Ammaraa Khalid, Fahad Ahmad, Muhammad Rizwan, Jaweria Manzoor, Kashaf Junaid (2019). Stress Detection of the Employees Working in Software Houses using Fuzzy Inference. International Journal of Advanced Computer Science & Applications, 10(1), 217-224. https://europub.co.uk/articles/-A-448746