Vibro-Acoustic Signatures of Various Insects in Stored Products

Stored products, such as grains and processed foods, are susceptible to infestation by various insects. The early detection of insects in the supply chain is crucial, as introducing invasive pests to new environments may cause disproportionate harm. The STAR Center at Stevens Institute of Technology developed the Acoustic Stored Product Insect Detection System (A-SPIDS) to detect pests in stored products. The system, which comprises a sound-insulated container for product samples with a built-in internal array of piezoelectric sensors and additional electret microphones to record outside noise, was used to conduct numerous measurements of the vibroacoustic signatures of various insects, including the <i>Callosobruchus maculatus</i>, <i>Tribolium confusum</i>, and <i>Tenebrio molitor</i>, in different materials. A normalization method was implemented using the ambient noise of the sensors as a reference, to accommodate for the proprietary, non-calibrated sensors and allowing to set relative detection thresholds for unknown sensitivities. The normalized envelope of the filtered signals was used to characterize and compare the insect signals by estimating the Normalized Signal Pulse Amplitude (NSPA) and the Normalized Spectral Energy Level (NSEL). These parameters characterize the insect detection Signal Noise Ratio (SNR) for pulse-based detection (NSPA) and averaged energy-based detection (NSEL). These metrics provided an initial step towards the design of a reliable detection algorithm. In the conducted tests NSPA was significantly larger than NSEL. The NSPA reached 70 dB for <i>T. molitor</i> in corn flakes. The insect signals were lower in flour where the averaged NSPA and NSEL values were around 40 dB and 11 dB to 16 dB, respectively.

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Publication Details

Journal
Sensors
Published
2024-10-19
DOI
https://doi.org/10.3390/s24206736
Citations
6
Primary Topic
Insect Pest Control Strategies
Type
article
Field-Weighted Citation Impact
3.60

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article

Vibro-Acoustic Signatures of Various Insects in Stored Products

Alexander Sedunov, Hady Salloum, Daniel Kadyrov, Nikolay Sedunov et al.
6 citations
Sensors
Insect Pest Control Strategies
3.60
article

Vibro-Acoustic Signatures of Various Insects in Stored Products

Alexander Sedunov, Hady Salloum, Daniel Kadyrov, Nikolay Sedunov, Alexander Sutin
article en
6 citations

Abstract

Stored products, such as grains and processed foods, are susceptible to infestation by various insects. The early detection of insects in the supply chain is crucial, as introducing invasive pests to new environments may cause disproportionate harm. The STAR Center at Stevens Institute of Technology developed the Acoustic Stored Product Insect Detection System (A-SPIDS) to detect pests in stored products. The system, which comprises a sound-insulated container for product samples with a built-in internal array of piezoelectric sensors and additional electret microphones to record outside noise, was used to conduct numerous measurements of the vibroacoustic signatures of various insects, including the <i>Callosobruchus maculatus</i>, <i>Tribolium confusum</i>, and <i>Tenebrio molitor</i>, in different materials. A normalization method was implemented using the ambient noise of the sensors as a reference, to accommodate for the proprietary, non-calibrated sensors and allowing to set relative detection thresholds for unknown sensitivities. The normalized envelope of the filtered signals was used to characterize and compare the insect signals by estimating the Normalized Signal Pulse Amplitude (NSPA) and the Normalized Spectral Energy Level (NSEL). These parameters characterize the insect detection Signal Noise Ratio (SNR) for pulse-based detection (NSPA) and averaged energy-based detection (NSEL). These metrics provided an initial step towards the design of a reliable detection algorithm. In the conducted tests NSPA was significantly larger than NSEL. The NSPA reached 70 dB for <i>T. molitor</i> in corn flakes. The insect signals were lower in flour where the averaged NSPA and NSEL values were around 40 dB and 11 dB to 16 dB, respectively.

SensorsVol. 24(20)
Stevens Institute of Technology (US), University of Houston (US)
U.S. Department of Homeland Security
Openalex Percentile: Top 7%
Insect Pest Control Strategies
3.60
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