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论文题目  A real-time underwater acoustic telemetry receiver with edge computing for studying fish behavior and environmental sensing 
论文题目(英文) A real-time underwater acoustic telemetry receiver with edge computing for studying fish behavior and environmental sensing 
作者 杨阳;Robbert Elsinghorst;Jayson J. Martinez;Hongfei Hou;Jun Lu;Zhiqun Daniel Deng 
发表年度 2022-04 
 
 
页码  
期刊名称 IEEE Internet of Things Journal 
摘要   水声遥测已经成为实际应用的有力工具,包括资源勘探、环境监测和水生动物跟踪。然而,当前的声学遥测系统缺乏实时连续传输收集的数据的能力,主要是因为声学网络带宽有限。从部署的接收器取回记录的测量值通常必须手动进行,这导致数据取回和处理的长时间延迟、与所需人力相关的高操作成本以及操作者的安全风险。此外,没有有效的方法来连续评估声学遥测系统的状态,包括声学发射器和接收器。在这里,我们描述了一个基于云的实时水声遥测系统的设计、实现和现场验证,该系统采用边缘计算来估计鱼类行为和监测环境参数。该系统包含用于边缘计算的微控制器,并连接到基于云的服务,该服务进一步对传输的数据流进行后处理,以获得标记动物的行为和生存信息。由于集成了边缘计算,开发的系统已被证明比基准系统具有显著提高的性能,能耗大幅降低至0.014 W,导致声学调制解调器使用的能源减少了300多倍。这项工作为未来的实时和多功能水下声学系统开辟了新的设计机会。 
摘要_英文

  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.

 

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