The Integration of Big Data and Artificial Intelligence Technologies Into Modern Artillery Systems
Abstract
Purpose. To systematize the principal directions for integrating big data and artificial intelligence technologies into modern artillery systems and to assess their potential impact on the speed, accuracy, resilience, and decision-making processes of artillery operations, based on documented international experience.
Method: The study employs a structured qualitative review and comparative analytical approach. Academic literature, official military documents, materials published by international organizations, and documented examples of contemporary technological applications were analyzed according to predefined functional criteria.
Theoretical implications. The study contributes to the theoretical understanding of AI and big data integration in artillery systems by conceptualizing their application as a multidimensional transformation process rather than solely as weapon automation. It highlights the interconnected roles of data management, sensor-based information processing, decision support, fire control, technical sustainment, human oversight, and accountability.
Practical implications. The findings provide a functional basis for assessing and developing AI-enabled artillery systems, particularly in relation to data processing, sensor integration, decision support, fire control, maintenance, and logistics. The study also highlights the importance of data quality, cybersecurity, explainability, human oversight, and legal and ethical frameworks for the reliable implementation of such systems.
Value. The value of the study lies in its systematic synthesis of documented international experience and its identification of the principal functional areas in which big data and AI can be integrated into modern artillery systems. It provides a structured perspective for understanding both the potential benefits and the technological, organizational, and governance requirements associated with such integration.
Paper type. Research paper.
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