People
| Professor Klara Nahrstedt: Principle Investigator Beitong Zhao: Ph. D. Student Lingzhi Zhao: Ph.D. Student Bo Chen: Postdoc Haozhen Zheng: Ph. D. Student Mingyuan Wu: Ph. D. Student Jingchen Yang: Undergraduate Student |
Timeline
- Fall 2023-
Project Description
Project 1: AquaScope
Underwater communication is essential for both recreational and scientific activities, such as scuba diving. However, existing methods remain highly constrained by environmental challenges and often require specialized hardware, driving research into more accessible underwater communication solutions. While recent acoustic-based communication systems support text messaging on mobile devices, their low data rates severely limit broader applications. We present AquaScope, the first acoustic communication system capable of underwater image transmission on commodity mobile devices. To address the key challenges of underwater environments — limited bandwidth and high transmission errors — AquaScope employs and enhances generative image compression to improve compression efficiency, and integrates it with reliability-enhancement techniques at the physical layer to strengthen error resilience. We implemented AquaScope on the Android platform and demonstrated its feasibility for underwater image transmission. Experimental results show that \sysname achieves a 36.7% improvement in visual quality while compressing a 256×256 color image into under 1k bits, outperforming existing systems across bandwidth-constrained and error-prone underwater conditions.
Project 2: AquaVLM
Underwater activities like scuba diving enable millions annually to explore marine environments for recreation and scientific research. Maintaining situational awareness and effective communication are essential for diver safety. Traditional underwater communication systems are often bulky and expensive, limiting their accessibility to divers of all levels. While recent systems leverage lightweight smartphones and support text messaging, the messages are predefined and thus restrict context-specific communication.
In this project, we present AquaVLM, a tap-and-send underwater communication system that automatically generates context-aware messages and transmits them using ubiquitous smartphones. Our system features a mobile vision-language model (VLM) fine-tuned on an auto-generated underwater conversation dataset and employs a hierarchical message generation pipeline. We co-design the VLM and transmission, incorporating error-resilient fine-tuning to improve the system’s robustness to transmission errors. We develop a VR simulator to enable users to experience AquaVLM in a realistic underwater environment and create a fully functional prototype on the iOS platform for real-world experiments. Both subjective and objective evaluations validate the effectiveness of AquaVLM and highlight its potential for personal underwater communication as well as broader mobile VLM applications.
Funding Agencies
Publications
Beitong Tian, Lingzhi Zhao, Bo Chen, Haozhen Zheng, Jingcheng Yang, Mingyuan Wu, Deepak Vasisht, Klara Nahrstedt. AquaVLM: Improving Underwater Situation Awareness with Mobile Vision Language Models. Arxiv, 2025.
Beitong Tian, Lingzhi Zhao, Bo Chen, Mingyuan Wu, Haozhen Zheng, Deepak Vasisht, Francis Y. Yan, Klara Nahrstedt. AquaScope: Reliable Underwater Image Transmission on Mobile Devices. Arxiv, 2025.