Voice Based Employee Management System Using AWS and Alexa
Journal Title: International Journal of Innovative Research in Computer Science and Technology - Year 2020, Vol 8, Issue 3
Abstract
In the developing and creating world, everything is getting advanced, digital, computerized, and automated. With an oversized number of labor opportunities, the Human workforce has increased. Thus, there is a need for a system that can handle the information of such a large number of employees in a company. This project untangles the task of maintaining records and data of employees, thanks to its user-friendly GUI. The “EMPLOYEE MANAGEMENT SYSTEM using AWS" has been created to abrogate the issues with the existing manual framework. This application is designed in such a simplest way that it can eliminate and in some cases reduce the efforts faced by the live system. Moreover, this method is meant for the actual need of the corporate to holdout operations smoothly and effectively. A Voice command feature is additionally added to the system to avoid a waste of time. The application is coded in such a way that, it avoids mistakes while entering the data. It notifies the employee/admin if he entered the incorrect, or invalid data. No formal knowledge or special training is required by the employee/admin to use this application. Thus, it is approved as an easy to understand and person-friendly utility. The Voice command feature is additionally straightforward to use and informative. This project will allow admin to feature new employees after proper authentication (manual). Admin can even edit departments and posts (in a variety of bands). The database should store all personal details of employees like date of birth, full name, people, address, etc. this method enables employees to fill their time-sheets daily or at intervals. The admin can approve or reject the time-sheet filled by a worker together with remarks. Admin may make workdays, Performance charts, Leave details, and will edit employee details. An employee can access its details using Alexa.
Authors and Affiliations
Ritika Punia, Shubham Panwar, Ruchi Kamra, Rashmi Gupta
Keywords
Related Articles
- EP ID EP747823
- DOI 10.21276/ijircst.2020.8.3.28
- Views 34
- Downloads 0
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