Department of Physics and Computer Science, Miguel Hernandez University, Ave. Universidad s/n-Ed. Alcudia, 03202 Elche, Spain.
Sensors (Basel). 2013 Jan 30;13(2):1706-29. doi: 10.3390/s130201706.
During the last two decades Red Palm Weevil (RPW, Rynchophorus Ferrugineus) has become one of the most dangerous threats to palm trees in many parts of the World. Its early detection is difficult, since palm trees do not show visual evidence of infection until it is too late for them to recover. For this reason the development of efficient early detection mechanisms is a critical element of RPW pest management systems. One of the early detection mechanisms proposed in the literature is based on acoustic monitoring, as the activity of RPW larvae inside the palm trunk is audible for human operators under acceptable environmental noise levels (rural areas, night periods, etc.). In this work we propose the design of an autonomous bioacoustic sensor that can be installed in every palm tree under study and is able to analyze the captured audio signal during large periods of time. The results of the audio analysis would be reported wirelessly to a control station, to be subsequently processed and conveniently stored. That control station is to be accessible via the Internet. It is programmed to send warning messages when predefined alarm thresholds are reached, thereby allowing supervisors to check on-line the status and evolution of the palm tree orchards. We have developed a bioacoustic sensor prototype and performed an extensive set of experiments to measure its detection capability, achieving average detection rates over 90%.
在过去的二十年中，红棕榈象鼻虫（RPW，Rynchophorus Ferrugineus）已成为世界许多地区棕榈树的最危险威胁之一。由于棕榈树在感染后出现明显症状之前，难以进行早期检测，因此开发有效的早期检测机制是 RPW 害虫管理系统的关键要素。文献中提出的早期检测机制之一是基于声学监测，因为在可接受的环境噪声水平下（农村地区、夜间等），人类操作员可以听到 RPW 幼虫在棕榈树干内的活动声。在这项工作中，我们提出了设计一种自主生物声学传感器的方案，该传感器可以安装在每一棵受研究的棕榈树上，并能够在长时间内分析捕获的音频信号。音频分析的结果将通过无线方式报告给控制站，以便随后进行处理和方便存储。该控制站可通过互联网访问。它被编程为在达到预定义的报警阈值时发送警告消息，从而允许主管人员在线检查棕榈树果园的状态和发展。我们已经开发了一种生物声学传感器原型，并进行了广泛的实验来测量其检测能力，平均检测率超过 90%。
