Using artificial intelligence in hydroacoustic communications of AUV fleets

Today, intelligent marine facilities such as floats and intelligent underwater robots are an integral part of marine industries and science, performing a diverse range of tasks, from inspecting dangerous environments inside a nuclear reactor to repairing complex submarine facilities in the oil and gas industry. AI can effectively analyze cumulative data from various sensors and systems and extract key insights. AI uses machine learning algorithms, natural language processing, neural networks, robotics, expert systems and fuzzy logic and so on. It can identify behavioral patterns and provide predictions about potential problems and challenges in sub-surface operations. The use of AI in resource management optimizes the use of energy, fuel and other resources and positively affects the economic efficiency of the sub-surface fleet. With the advancement of technology and the need to increase efficiency and security in sub-surface operations, the intelligence of the sub-surface fleet has become one of the fundamental challenges. This article examines the approaches and solutions of sub-surface fleet intelligence and analyzes the role of new technologies such as the Internet of Things, Big Data Processing and machine learning in optimizing fleet performance. In this regard, it is proposed to identify existing challenges such as communication problems, high costs and the need for intelligent operations management, automation-based solutions, intelligent sensors and rapid data analysis. The results show that implementing these solutions can lead to increased efficiency, reduced costs and improved safety of sub-surface fleet operations. Finally, this article examines the future prospects of intelligence in this area and its impact on Sustainable Development.

کلیدواژه ها:

Fleet intelligence ، the Internet of Things ، machine learning ، smart sensors ، automate systems