Fig 1.
A sketch diagram summarizing the concept of the electronic McPhail trap.
The insect flying in occludes with its flapping wings the path of light from emitter to receiver. The electronics of the trap analyze the light fluctuation of the receiver. Light intensity fluctuations constitute a ‘biometric signature’ directly related to insect’s wingbeat frequency, size and shape of its wings. The signature is compared to pre-embedded patterns from the target pest. Finally, counts of the target pest, temperature, humidity and GPS coordinates are transmitted through the mobile GSM network from the field to the monitoring agency.
Fig 2.
(top) A typical 200 ms B.oleae. wingbeat event recorded as the insect crossed the optical sensor (18°C). (bottom) Magnitude spectral density.
The fundamental frequency of B. oleae typically drifts between 170 and 210 Hz.
Fig 3.
Top: Flute playing Note A4 at 440 Hz. Middle: Violin playing the same note. Bottom: Wingbeat of the insect Musca domestica.
The time domain plots show 30 ms of data. The spectrum is derived from approximately 2.5 s from the same signals. Note how the flute and violin time-domain plots have the same period but different shapes leading to a different weighting on the importance of the harmonics.
Fig 4.
(top) A diagram of the candlestick optoelectronic sensor in mm, (bottom) the optical sensor in its final standing inside the insectary cage.
As insects fly freely in the cage, some of them randomly pass through the square thus interrupting the light path from emitter to receiver.
Fig 5.
The optical sensors in their final setup, inside insectary cages with B.oleae.
Each time an insect incidentally flies through the rectangle, a recording of a wing flap is acquired.
Fig 6.
Normalized Power Spectral Density of B. oleae wingflap as measured by a photodiodes array vs a phototransistors array.
Both sensors resolve the fundamental frequency of the wingbeat around 180 Hz. The diodes resolve better the harmonics at multiples of ~180 Hz.
Fig 7.
An optical sensor and a microphone transducer embedded in the same cage holding B. oleae insects.
PSD of photodiodes array vs microphone transducer. Both sensors resolve the fundamental frequency of the wingbeat and have good accordance until the 5th harmonic. In this particular controlled setup, the microphone can resolve higher harmonics as well.
Fig 8.
PSD of photodiodes array resolving the spectrum of two typical flying patterns: straight, short-time passes (left) and slower maneuvering passes of insects (right).
Fig 9.
Flow chart of processing stages.
Processing is continued to the next stage only in case of a positive event otherwise transmission stage rests in sleep mode
Fig 10.
Spectra of 20 different cases of B. oleae optoacoustic, in-flight recordings.
Fig 11.
A detailed 3D CAD of the electronic McPhail trap.
Dimensions are in mm.
Fig 12.
Different views of the prototype electronic trap.
Table 1.
Automated verification of B. oleae.
Various insect species tested against the target species.
Fig 13.
Confusion matrix of Verification results of B. oleae vs Mosquitoes (A. gambiae and C. pipiens molestus).
Fig 14.
The electronic McPhail trap inside an insectary cage with B. oleae.
To help interpret system operating characteristics, the analog output from the sensor is recorded before it is sent to the microcontroller, and recordings are also made after the signals are processed by amplifier and filter circuits.
Fig 15.
Spectrum of wingbeat recording of insect flying in the trap.
(Left) B.oleae, (right) A. gambiae.
Table 2.
Accuracy measures for classifying B.oleae against two mosquito species.
Fig 16.
Spectrum of wingbeat recording of insect flying in the trap.
(Left) B.oleae, (right) A. mellifera.
Fig 17.
Confusion matrix of Verification results of B. oleae vs A. mellifera.
Table 3.
Accuracy measures for classifying B.oleae against A. mellifera.
Fig 18.
Spectrum of wingbeat recording of insect flying in the trap.
(Left) B.oleae, (right) member of the Chironomidae family.
Fig 19.
Confusion matrix of Verification results of B. oleae vs Chironomidae.
Table 4.
Accuracy measures for classifying B.oleae against members of the Chironomidae family.
Fig 20.
Spectrum of wingbeat recording of insect flying in the trap.
(Left) B.oleae, (right) Lonchaea aristella (Diptera: Lonchaeidae).
Table 5.
Model-based techniques classifying B. oleae vs L. aristella.
Average scores over 10-fold cross-validation, 20% hold-out.
Fig 21.
Confusion matrix of verification results using a random forest classifier (B. oleae vs L. aristella) accuracy measures.
Fig 22.
Confusion matrix of verification results using the absolute distance between spectra and a codebook of 4 spectrum prototypes for each species B. oleae vs L. aristella.
Table 6.
Accuracy measures for classifying B.oleae against L. aristella.
Table 7.
Accuracy measures for classifying B.oleae against L. aristella using a codebook of 4 spectrum prototypes.
Fig 23.
Detection counts received from the GPRS module.
The figure shows the online web interface that presents detection results of trapped insects in general and target species in particular, based on Freeboard.io and OpenStreetMap. (Figure is similar but not identical to the original image, due to copyright restrictions, and is therefore for representative purposes only).
Table 8.
Cost breakdown of the hardware of the electronic McPhail trap (date last viewed 30/6/2015).