CONet: A Cognitive Ocean Network

TL;DR

This paper introduces CONet, a new cognitive ocean network architecture designed to enhance ocean monitoring and exploration by integrating AI with ocean sensor networks, addressing unique challenges like low reliability and narrow bandwidth.

Contribution

The paper proposes a detailed architecture for CONet, demonstrates practical applications, and discusses future research directions in cognitive ocean networks.

Findings

Proposed a comprehensive architecture for CONet.

Presented demonstration applications for ocean monitoring.

Discussed future trends and challenges in CONet research.

Abstract

The scientific and technological revolution of the Internet of Things has begun in the area of oceanography. Historically, humans have observed the ocean from an external viewpoint in order to study it. In recent years, however, changes have occurred in the ocean, and laboratories have been built on the seafloor. Approximately 70.8% of the Earth's surface is covered by oceans and rivers. The Ocean of Things is expected to be important for disaster prevention, ocean-resource exploration, and underwater environmental monitoring. Unlike traditional wireless sensor networks, the Ocean Network has its own unique features, such as low reliability and narrow bandwidth. These features will be great challenges for the Ocean Network. Furthermore, the integration of the Ocean Network with artificial intelligence has become a topic of increasing interest for oceanology researchers. The Cognitive Ocean Network (CONet) will become the mainstream of future ocean science and engineering developments. In this article, we define the CONet. The contributions of the paper are as follows: (1) a CONet architecture is proposed and described in detail; (2) important and useful demonstration applications of the CONet are proposed; and (3) future trends in CONet research are presented.