Integrating Edge and Cloud Computing for Actionable Insights in Military Decision-Making

Kodam, Anuhya (2023) Integrating Edge and Cloud Computing for Actionable Insights in Military Decision-Making. Masters thesis, Dublin, National College of Ireland.

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Abstract

In military operations, critical decisions made with time sensitive data can often determine success or failure, yet delayed decision-making has led to substantial losses in military lives. This project addresses this issue by focusing on the integration of edge and cloud computing paradigms. Leveraging an existing public dataset centered on terrorist prediction, the project meticulously cleans and preprocesses data using Pandas, NumPy, and Matplotlib within a Jupyter Notebook environment. By employing Scikit-learn’s Random Forest and Decision Tree algorithms, the project generates predictive insights through machine learning models. Serialized as pickle files, these trained models enable future utilization. Furthermore, a Flask-based web application, equipped with HTML templates, facilitates user interaction for decision-making support. Through Boto3 SDK integration, the application seamlessly connects to Amazon S3, efficiently storing decision outcomes. This project aims to showcase the integration’s synergy between edge devices and cloud services. By processing data at the edge and subsequently storing it in the cloud for further analysis, it presents a user-friendly interface empowering military decision-makers with actionable insights derived from predictive analytics. The core findings underscore the successful integration of technologies, providing a scalable and efficient framework for real-time decision support in military operations, ultimately aiming to reduce losses attributable to delayed decisions.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heeney, Sean UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science U Military Science > U Military Science (General) T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	28 Mar 2025 15:15
Last Modified:	28 Mar 2025 15:15
URI:	https://norma.ncirl.ie/id/eprint/7353

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