Machine Learning for Strategic Facility and Project Management in Multi-Disciplinary Education

Dayanand Jamkhandikar

Abstract: Strategic facility and project management in multi-disciplinary education requires innovative and data-driven solutions to improve operational efficiency, resource allocation, and predictive maintenance. This paper explores the application of Machine Learning (ML) to enhance strategic decision-making and optimize facility and project management processes. Emphasizing cloud integration, IoT solutions, and real-time analytics, the study demonstrates the transformative potential of ML in addressing complex challenges within educational environments. By leveraging diverse use cases and modern frameworks, this work illustrates how ML-based strategies can bridge gaps across disciplines and foster collaborative ecosystems for sustainable management.

Keywords: Machine Learning, Facility Management, Project Management, Multi-Disciplinary Education, Predictive Analytics, Cloud Integration, IoT Solutions, Real-Time Analytics, Collaboration, Strategic Decision-Making