计算机科学
形势意识
杠杆(统计)
大数据
传感器融合
数据质量
数据科学
商业智能
背景(考古学)
领域(数学分析)
计算机安全
知识管理
数据挖掘
人工智能
数学分析
工程类
航空航天工程
古生物学
生物
经济
公制(单位)
数学
运营管理
作者
Paulo H. L. Rettore,Philipp Zißner,Mohammed Alkhowaiter,Cliff C. Zou,Peter Sevenich
标识
DOI:10.1109/mcom.001.2300396
摘要
Combining big data and artificial intelligence (AI) has revolutionized industry and research by enabling accurate predictions and informed decision-making. These advancements have also found their place in the military domain, with initiatives aiming to integrate data sources and sensors from different domains, providing a shared situational awareness. In urban military operations, timely and context-aware information is crucial for achieving precision and success. Data fusion, which combines information from diverse sources, is vital in achieving this goal. Furthermore, civilian data provides crucial context information and can significantly impact mission planning. This article proposes the military data space (MDS) concept to explore how big data can support military decision-making by combining civilian and military data. Use cases are presented, highlighting the benefits of data fusion and image authentication in enhancing data quality and trust-worthiness. Furthermore, the challenges of data security, privacy, integrity, acquisition, fusion, networking, and leverage AI approaches are discussed while emphasizing the opportunities to build the next generation of military applications.
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