Publication Type: | Journal Article |
Year of Publication: | 2013 |
作者: | Rach, Gomis, Granado, Malumbres, Campoy, Martín |
Journal: | Sensors |
Volume: | 13 |
Issue: | 2 |
Pagination: | 1706 - 1729 |
Date Published: | Jan-02-2013 |
關鍵字: | acoustic sensor design, acoustic signal processing, pattern matching, pest detection, wavelet transform, wireless sensor networks |
摘要: | 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%. |
URL: | http://www.mdpi.com/1424-8220/13/2/1706 |
DOI: | 10.3390/s130201706 |
Short Title: | Sensors |
On the Design of a Bioacoustic Sensor for the Early Detection of the Red Palm Weevil
BioAcoustica ID:
53338
Taxonomic name: