Ma Zhongze, Zhang Chenjie, Jiao Pengcheng
Ocean College, Zhejiang University, Zhoushan 316021, Zhejiang, China.
Engineering Research Center of Oceanic Sensing Technology and Equipment, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang, China.
iScience. 2024 Mar 11;27(4):109479. doi: 10.1016/j.isci.2024.109479. eCollection 2024 Apr 19.
Marine activities typically face various risk factors such as marine animal attacks or unexpected collisions. In this paper, we develop underwater smart glasses (USGs) based on visual-tactile fusion for underwater hazard detection in real-time, ensuring operational safety. The proposed USG is composed of the vision module by artificial intelligence (AI)-enabled optical sensing and the tactile module by triboelectric metamaterials-enabled mechanical sensing. The vision module is obtained based on the underwater target detection algorithm (YOLO-UH) developed by the dataset to detect toxic marine organisms in the visual field. The tactile module is designed with the kirigami tribo-materials (KTMs) to sensitively detect and warn of collisions outside the visual field. Through numerical simulations, laboratory tests, and real-world experiments, we validated the performance of both modules. The reported USG with its visual-tactile fusion concept enables near-far all-around hazard detection and reduces the danger for divers working underwater.
海洋活动通常面临各种风险因素,如海洋动物攻击或意外碰撞。在本文中,我们开发了基于视觉-触觉融合的水下智能眼镜(USG),用于实时水下危险检测,确保操作安全。所提出的USG由通过人工智能(AI)光学传感的视觉模块和通过摩擦电超材料机械传感的触觉模块组成。视觉模块基于由数据集开发的水下目标检测算法(YOLO-UH)获得,以检测视野中的有毒海洋生物。触觉模块采用折纸摩擦材料(KTM)设计,以灵敏地检测并警告视野外的碰撞。通过数值模拟、实验室测试和实际实验,我们验证了两个模块的性能。所报道的具有视觉-触觉融合概念的USG能够进行远近全方位的危险检测,并降低潜水员在水下作业的危险。