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Stream/Area:
-
Subject:
-
Paper ID:
IJSREMWP0009
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The increasing complexity of workforce management in field services has led to the need for intelligent, scalable scheduling tools. This paper explores schedulo, a cloud-based management platform designed to optimize mobile workforce operations. By leveraging real-time scheduling, AI-driven allocation, and mobile-first experiences, Schedulo enhances operational efficiency. This study reviews existing literature on workforce management, analyzes Schedulo’s features and methodology, and evaluates its effectiveness across different industries. Our findings show a marked improvement in workforce utilization, customer satisfaction, and task execution speed. Future enhancements such as deeper AI integration and IoT device compatibility are also discussed.
KEYWORDS
Publication Date
4/4/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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