Artificial Intelligence and its integration in Naval Operations

Abstract

A literature review was carried out with the objective of analyzing the impact of artificial intelligence (AI) in the improvement of surveillance and reconnaissance systems, with emphasis on the early detection of threats in coastal areas. For this purpose, the parameters of the systematic methodology were followed to identify, select and analyze the most relevant information on the integration of AI in naval operations, with a particular focus on surveillance and reconnaissance systems. The search for information was carried out in recognized academic and technical databases, both in the general field and in the defense sector. The main sources used included academic databases such as Scopus, Google Scholar, Semantic Scholar and JSTOR, 35 studies were selected that met the defined inclusion and exclusion requirements, for the period between 2020 - 2025. Common patterns and factors were found within the review, which were organized into 6 topics for further analysis, namely: fundamentals and advances of AI in naval operations. AI techniques applied in surveillance and reconnaissance. Integration of AI with existing surveillance technology. Early warning systems and threat prediction. Practical implementation in security and defense strategies. Ethical, legal and cybersecurity aspects. The relevant results of the review show that the use of advanced algorithms (deep learning, neural networks, etc.) significantly improves the detection and classification of threats in maritime environments, optimizing the accuracy and speed of operational decision making. Likewise, it is evident that AI-based predictive models allow detecting anomalies and foreseeing threats in coastal areas, facilitating proactive responses and improving operational safety, depending largely on the quality and availability of data.