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Research Article

Employee Monitoring Software

  • Paper ID 530
  • Volume 3, Issue 3
  • Pages 508-512
  • Published Online: May-June 2022
  • 1 Views
Open Access Peer Reviewed

Authors

  • Pranav Paigude1
  • Sahil Gupta2
  • Prof. Rupali Gavaraskar3
  • Prof. Dnyaneshwar Kanade4

1234Department of Electronics Engineering, Vishwakarma Institute of Technology Pune, Maharashtra, India.

Article Information

DOI
No DOI
Published Online
May-June 2022
Pages
508-512
Article Type
Research Article
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No DOI available for cross-reference

Abstract

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Abstract: In recent years information technology (IT) has transformed workplaces tremendously. Nowadays organizations all over the world are relying on technology to monitor the activities performed by their employees during work hours and to increase the productive tasks done by them. This was because, a lot of studies concluded that if employees are not supervised, they have the tendency to waste time online. Monitoring employee helps organizations to keep a track on activities performed by them. This allows them to improve employee productivity. To effectively observe and monitor the employees during working hours there should be a proper check, so there is need of an intelligent, automated and efficient software. Hence the idea of developing a program that will monitor the screens of the employees of an organization was conceptualized. The text from the screenshot will be extracted and scanned for certain keywords. If the work related keywords are present in the text, the screenshot will be discarded. Else the screenshot will be blurred and saved on the employee’s profile on a database, which would be accessible to the manager or the employer. The employer can see the count of such images on each employee’s profile and take any action if necessary. Other information such as login time of employee, last seen time, total hours of work of a particular day would also be displayed in the database. This project will use python as the programming language and also use Tesseract-OCR for detecting the images and the text present in them.

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