In vivo electronic monitoring systems for underwater applications are promising technologies for obtaining information about aquatic animals. State-of-the-art devices are constrained by limits on the number of integrated sensors, large dimensions and weight, and short device longevity. Here, we report the Lab-on-a-Fish: the world’s first biotelemetry tag that combines edge computing with wireless sensing of in vivo physiology [electrocardiogram (ECG) and electromyogram (EMG)], behavior [activity level and tail beat frequency (TBF)], and ambient environment (temperature, pressure, and magnetic field). The Lab-on-a-Fish has a miniaturized form (dry weight: 2.4 g; wet weight: 0.8 g; and dimensions: 5.5 mm ${\times }\,\,6.5$ mm ${\times }\,\,37$ mm) for studying small animals. Engineering efforts spanning improvements in battery chemistry, electronic circuit efficiency, and power-saving algorithms extend the longevity of the device to as much as eight months. The designed piezoelectric transducer and its driving circuit enable underwater wireless communication of multiplexed digital sensor data over a distance up to 400 m. The Lab-on-a-Fish can also store the raw data using flash memory for use in locations that are challenging for acoustic communications or when more complex data postprocessing is needed. Long-term in vivo validation in three species—rainbow trout (Oncorhynchus mykiss), white sturgeon (Acipenser transmontanus), and walleye (Sander vitreus)—demonstrated the device’s sensing potential for biological and environmental applications.

Underwater acoustic telemetry has emerged as a powerful tool for practical applications, including resource exploration, environmental monitoring, and aquatic animal tracking. However, current acoustic telemetry systems lack the capability to transmit the collected data continuously in real time, primarily because the acoustic networking bandwidth is limited. Retrieval of the recorded measurements from the deployed receivers usually must be manual, leading to long delays in data retrieval and processing, high operational costs associated with the required manpower, and safety risks for the operators. In addition, there is no efficient way to continuously assess the status of the acoustic telemetry system, including the acoustic transmitters and receivers. Here, we describe the design, implementation, and field validation of a cloud-based, real-time, underwater acoustic telemetry system with edge computing for estimating fish behavior and monitoring environmental parameters. The system incorporates microcontrollers for edge computing and connects to a cloud-based service that further post-processes the transmitted data stream to derive behavior and survival information of tagged animals. The developed system has been demonstrated to have significantly improved performance over the benchmark system because of the integration of edge computing, with a greatly reduced energy consumption of 0.014 watts resulting in the energy used by the acoustic modem being reduced by over 300 times. This work opens up new design opportunities for future real-time and multifunctional underwater acoustic systems.

Approximately 16% of the world’s electricity and over 80% of the world’s renewable electricity is generated from hydropower resources, and there is potential for developing significantly more new hydropower capacity. In practice, however, optimizing the use of potential hydropower resources is limited by various factors, including environmental effects and related mitigation requirements. That is why hydropower regulatory requirements frequently call for targets to be met regarding fish injury and mortality rates. The sensor fish (SF) is a small autonomous sensor package that can be deployed through complex hydraulic structures, such as a turbine or spillway, to collect high resolution measurements that describe the forces and motions that live fish would encounter. The Hydropower Biological Evaluation Toolset (HBET), an integrated suite of science-based tools, is designed to use the SF (implemented) and other tools (to be implemented in the future) to characterize the hydraulic conditions of hydropower structures and provide quantitative estimates of fish injury and mortality rates resulting from exposure to various physical stressors including strike, pressure, and shear. HBET enables users to design new studies, analyze data, perform statistical analyses, and evaluate biological responses. It can be used by researchers, turbine designers, hydropower operators, and regulators to design and operate hydropower systems that minimize ecological impacts in a cost-effective manner. In this paper, we discuss the technical methodologies and algorithms implemented in HBET and describe a case study that illustrates its functionalities.

Acoustic emissions from current energy converters remain an environmental concern for regulators because of their potential effects on marine life and uncertainties about their effects stemming from a lack of sufficient observational data. Several recent opportunities to characterize tidal turbine sound emissions have begun to fill knowledge gaps and provide a context for future device deployments. In July 2021, a commercial-off-the-shelf hydrophone was deployed in a free-drifting configuration to measure underwater acoustic emissions and characterize a 25 kW-rated tidal turbine at the University of New Hampshire’s Living Bridge Project in Portsmouth, New Hampshire. Sampling methods and analysis were performed in alignment with the recently published IEC 62600-40 Technical Specification for acoustic characterization of marine energy converters. Results from this study indicate acoustic emissions from the turbine were below ambient sound levels and therefore did not have a significant impact on the underwater noise levels of the project site. As a component of Pacific Northwest National Laboratory’s Triton Field Trials (TFiT) described in this Special Issue, this effort provides a valuable use case for the IEC 62600-40 Technical Specification framework and further recommendations for cost-effective technologies and methods for measuring underwater noise at future current energy converter project sites.