Underwater monitoring of marine life has traditionally followed a "set it and retrieve it” approach due to the challenge of transmitting high-bandwidth data like video from subsurface sensors to land networks. As a result, data must be physically collected, causing delays or data loss. However, on-device machine learning with affordable, off-the-shelf hardware and open source models now enables real-time conversion of video into text that can be reliably transmitted, overcoming prior limits.