Performance Analysis of an Ice-Based Buoy Operating from the Packed Ice Zone to the Marginal Ice Zone with an Imaging System

Arctic sea ice can be regarded as a sensitive indicator of climate change, and it has declined dramatically in recent decades. The swift decline in Arctic sea ice coverage leads to an expansion of the marginal ice zone (MIZ). In this study, an ice-based buoy with an imaging system is designed for the long-term observation of the changes in sea ice from the packed ice zone to the marginal ice zone in polar regions. The system composition, main buoy, image system, and buoy load were analyzed. An underwater camera supports a 640 × 480 resolution image acquisition, RS485 communication, stable operation at –40 °C, and long-term underwater sealing protection through a titanium alloy housing. During a continuous three-month field deployment in the Arctic, the system successfully captured images of ice-bottom morphology and biological attachment, demonstrating imaging reliability and operational stability under extreme conditions. In addition, the buoy employed a battery state estimation method based on the Extreme Learning Machine (ELM). Compared with LSTM, BP, BiLSTM, SAELSTM, and RF models, the ELM achieved a test set performance of RMSE = 0.05 and MAE = 0.187, significantly outperforming the alternatives and thereby improving energy management and the reliability of long-term autonomous operation. Laboratory flume tests further verified the power generation performance of the wave energy-assisted supply system. However, due to the limited duration of Arctic deployment, full year-round performance has not yet been validated, and the imaging resolution remains insufficient for biological classification. The results indicate that the buoy demonstrates strong innovation and application potential for long-term polar observations, while further improvements are needed through extended deployments and enhanced imaging capability.