International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
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Volume 8 Issue 2
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Intelligent Staff Reallocation System

Author(s) Ms. Vijayalakshmi D M, Mr. Balakrishnan S, Mr. Gokul S, Mr. Gokul S
Country India
Abstract In modern organizations, efficient workforce management is essential for
maintaining productivity and ensuring optimal utilization of human resources. The
Intelligent Staff Reallocation System is designed to dynamically allocate and
reassign staff members to different departments or tasks based on workload,
employee skills, availability, and organizational requirements. Traditional staff
allocation methods are often manual, time-consuming, and prone to inefficiencies,
which may lead to uneven workload distribution and reduced operational
performance. The proposed system utilizes data-driven decision-making and
intelligent algorithms to analyze employee profiles, departmental workload, and task
priorities. By processing this information, the system recommends suitable staff
reallocations that balance workloads and improve overall efficiency. The application
provides an interactive interface for administrators to monitor staff distribution, track
resource utilization, and make informed decisions quickly. Additionally, the system
can incorporate machine learning techniques to predict staffing needs and optimize
future allocations. By automating the reallocation process, the Intelligent Staff
Reallocation System minimizes administrative effort, enhances workforce
productivity, and ensures better resource management within organizations. This
solution is particularly beneficial for institutions and companies that require flexible
workforce management in dynamic working environments.
Field Engineering
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-09
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E-ISSN 2582-2160
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