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Related Concept Videos

Hearing01:31

Hearing

When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.
Perception of Sound Waves01:01

Perception of Sound Waves

The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same frequency...
Doppler Effect - I00:56

Doppler Effect - I

The Doppler effect and Doppler shift were named after the Austrian physicist and mathematician Christian Johann Doppler in 1842, who conducted experiments with both moving sources and moving observers. Consider an observer standing on a street corner, observing an ambulance with a siren sound passing by at a constant speed. The observer experiences two characteristic changes in the sound of the siren. Initially, the sound increases in loudness as the ambulance approaches and decreases in...
Echo01:06

Echo

The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case, then the...
Discrete Fourier Transform01:15

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by identifying...

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Updated: Jul 11, 2026

Flying Insect Detection and Classification with Inexpensive Sensors
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Registration of Sounds Emitted by the Madagascar Hissing Cockroach Using a Distributed Acoustic Sensor.

Artem T Turov1,2, Yuri A Konstantinov1, Ekaterina E Totmina2

  • 1Perm Federal Research Center of the Ural Branch of the Russian Academy of Sciences (PFRC UB RAS), 13a Lenin St., 614000 Perm, Russia.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
Summary

Fiber-optic distributed acoustic sensing (DAS) now records single insect sounds in a lab. This technology captures acoustic signals from individual insects, advancing agricultural monitoring.

Keywords:
DASGromphadorhina portentosaagriculturedistributed acoustic sensorfiber optic sensorhissing cockroachinsect

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Area of Science:

  • Acoustics
  • Sensor Technology
  • Entomology

Background:

  • Fiber-optic distributed acoustic sensing (DAS) is increasingly used for monitoring acoustic activity, including in agriculture.
  • Previous DAS studies focused on large insect colonies, limiting its application for individual insect acoustic analysis.
  • Understanding individual insect acoustics is crucial for pest management and beneficial insect identification.

Purpose of the Study:

  • To demonstrate, for the first time, the use of fiber-optic DAS for recording sounds from a single insect under controlled laboratory conditions.
  • To develop and optimize a cost-effective experimental setup for high-fidelity acoustic recording of individual insects.
  • To validate the capability of DAS in capturing distinct acoustic signatures of a specific insect species.

Main Methods:

  • Utilized a novel, cost-effective experimental setup with a custom-designed sensing element for fiber-optic DAS.
  • Recorded acoustic signals from a single Madagascar hissing cockroach (Gromphadorhina portentosa) in a controlled laboratory environment.
  • Analyzed the captured acoustic data to identify insect-generated sounds and their sources.

Main Results:

  • Successfully recorded acoustic signals from a single Madagascar hissing cockroach using fiber-optic DAS.
  • The DAS system captured both mechanical interactions between the insect and the optical fiber.
  • Distinct characteristic hissing sounds produced by the insect in response to external stimuli were clearly detected.

Conclusions:

  • Fiber-optic DAS is effective for recording the acoustic signals of individual insects in a laboratory setting.
  • The developed experimental setup provides a viable and cost-effective method for single-insect acoustic monitoring.
  • This advancement opens new possibilities for detailed acoustic analysis of insects, benefiting agricultural applications.