Automated Identification of Flying Insects by Analysis of Wingbeat Frequencies

Moore, Aubrey; Miller, James R.; Tabashnik, Bruce E.; Gage, Stuart H.

doi:10.1093/jee/79.6.1703

Cited by 66 publications

(50 citation statements)

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“…Taking into account these difficulties, Moore et al [21] proposed the use of an optical sensor based on the phototransistor previously presented by Unwin & Ellington [37]. The authors used the optical sensor to record the variation of the light caused by the passage of insects.…”

Section: Related Workmentioning

confidence: 99%

Exploring Low Cost Laser Sensors to Identify Flying Insect Species

Silva

Souza

Ellis

et al. 2015

J Intell Robot Syst

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Insects have a close relationship with the humanity, in both positive and negative ways. Mosquito borne diseases kill millions of people and insect pests consume and destroy around US $40 billion worth of food each year. In contrast, insects pollinate at least two-thirds of all the food consumed in the world. In order to control populations of disease vectors and agricultural pests, researchers in entomology have developed numerous methods including chemical, biological and mechanical approaches. However, without the knowledge of the exact location of the insects, the use of these techniques becomes costly and inefficient. We are developing a novel sensor as a tool to control disease vectors and agricultural pests. This sensor, which is built from inexpensive commodity electronics, captures insect flight information using laser light and classifies the insects according to their species. The use of machine learning techniques allows the sensor to automatically identify the species without human intervention. Finally, the sensor can provide real-time estimates of insect species with virtually no time gap between the insect identification and the delivery of population estimates. In this paper, we present our solution to the most important challenge to make this sensor practical: the creation of an accurate classification system. We show that, with the correct combination of feature extraction and machine learning techniques, we can achieve an accuracy of almost 90 % in the task of identifying the correct insect species among nine species. Specifically, we show that we can achieve an accuracy of 95 % in the task of correctly recognizing if a given event was generated by a disease vector mosquito.

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Section: Related Workmentioning

confidence: 99%

Exploring Low Cost Laser Sensors to Identify Flying Insect Species

Silva

Souza

Ellis

et al. 2015

J Intell Robot Syst

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“…The work of Richards inspired a generation of researchers to use different photosensors to detect fluctuations in light intensity caused by reflections of flying insects [13]. By that time, it was clearly suggested that automatic instrumentation and various types of photosensors could be used to discriminate among flying insects by analyzing not only the fundamental frequency associated with the wing-flap but also the harmonics produced by this action [14], [15]. Various configurations of opto-electronic systems have been developed to study different insects [16]- [19].…”

Section: Introductionmentioning

confidence: 99%

Novel Noise-Robust Optoacoustic Sensors to Identify Insects Through Wingbeats

Potamitis

Rigakis

2015

IEEE Sensors J.

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For certain countries, the production of olive oil and fruits is a significant percentage of the total gross income. Fruit flies affect a yearly crop loss calculated in billions of dollars worldwide. At the top of the hazard scale, certain mosquitoes and flies transmit harmful organisms that cause serious illnesses and even death to humans, pets, and livestock. In this paper, we develop a novel, noise-robust optoacoustic sensors to record insects' wingbeats. Our experiments with various insects of economic and social importance demonstrate that the sensors deliver high SNR recordings of the wing-flap. This paper emphasizes the development of the sensors and successfully analyzes the wingbeats of many insects of economic importance. Accurate analysis of insects' wing-flaps will allow the embedding of the sensors in common traps. The goal is to achieve species classification and remote monitoring of crops, which is currently carried out manually, and to develop reliable decision making regarding the initiation of large-scale spraying.Index Terms-Optoelectronic sensors, precision agriculture, electronic insect traps.

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“…In the following study, we recorded the transient waveforms produced by mosquitoes ßying in a beam of light to detect differences in the fundamental harmonic of their wave spectra, equivalent to their wingbeat frequency (Moore et al 1986). We also recorded the amplitude of the Þrst, second, third, and fourth harmonic peaks of the waveform spectra to detect potential differences in wing morphology or wing behavior in ßight (Moore et al 1986, Moore ScientiÞc andQubit Systems 2001).…”

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confidence: 99%

The "Wingbeat Hypothesis" of Reproductive Isolation Between Members of theAnopheles gambiaeComplex (Diptera: Culicidae) Does Not Fly

Tripet¹,

Dolo²,

Traoré³

et al. 2004

J Med Entomol

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Recent advances have demonstrated that, in the absence of postmating barriers to hybridization, reproductive isolation between different forms of Anopheles gambiae sensu stricto is maintained by strong assortative mating. The forms of An. gambiae s.s. and the sister species An. arabiensis commonly form mixed swarms in which they mate. This raises the question as to how individuals recognize mates of their own species or form within swarms. It has been proposed that wingbeat frequency is used as a cue to discriminate potential mates. This has important implications for prospective genetic control programs. We used a photosensor to record the transient waveforms generated by individuals An. arabiensis and from the M and S molecular forms of An. gambiae s.s. as they flew through a beam of light. We found no significant between-species or between-form differences in the fundamental harmonic--equivalent to wingbeat frequency--either in males or females collected from sympatric populations in Mali, West Africa. However, there were significant differences in the amplitude of the first and third harmonics in females and of the first and second harmonics in males. Whereas these results suggest some morphological or behavioral differences between species and forms, the extensive overlap in the distributions of harmonic amplitudes does not point to them as reliable cues for assortative mating. Combining all waveforms parameters into a discriminant analysis did not yield characteristic scores either for males or females. Thus, our results do not support the wingbeat hypothesis of premating isolation in the An. gambiae complex.

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Automated Identification of Flying Insects by Analysis of Wingbeat Frequencies

Cited by 66 publications

References 0 publications

Exploring Low Cost Laser Sensors to Identify Flying Insect Species

Exploring Low Cost Laser Sensors to Identify Flying Insect Species

Novel Noise-Robust Optoacoustic Sensors to Identify Insects Through Wingbeats

The "Wingbeat Hypothesis" of Reproductive Isolation Between Members of theAnopheles gambiaeComplex (Diptera: Culicidae) Does Not Fly

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