Browsing by Author "Hou, Hongfei"

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    A large dataset of detection and submeter-accurate 3-D trajectories of juvenile Chinook salmon
    Martinez, Jayson J.; Fu, Tao; Li, Xinya; Hou, Hongfei; Wang, Jingxian; Eppard, M. Brad; Deng, Zhiqun Daniel (2021-09-06)
    Acoustic telemetry has been used extensively to study the behavior of aquatic animals. The Juvenile Salmon Acoustic Telemetry System (JSATS) is one such system; it was developed for studying juvenile salmonids but has been used to study numerous species. A recent innovation of the JSATS system is an acoustic transmitter that is small enough to be implanted through injection or small incision that doesn't require sutures. Use of the JSATS system involves deploying cabled acoustic receivers at hydroelectric dams, or other structures, and autonomous acoustic receivers in free-flowing sections of a river. The raw detections from acoustic-tagged fish are processed to remove potential false positives. The clean detections (5,147,996 total) are used to generate detection events and to compute 3-D trajectories (403,900 total), which are used to assign fish to a passage route through a dam. Controlled field testing involving a high-accuracy Global Positioning System receiver is done to validate the submeter accuracy of the trajectories. The JSATS dataset could be reused for expanding the understanding of near-dam fish behavior.
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    A Real-Time Underwater Acoustic Telemetry Receiver With Edge Computing for Studying Fish Behavior and Environmental Sensing
    Yang, Yang; Elsinghorst, Robbert; Martinez, Jayson J.; Hou, Hongfei; Lu, Jun; Deng, Zhiqun Daniel (IEEE, 2022-09)
    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 W 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.