  Insect monitoring is critical to improve our understanding and ability to
preserve and restore biodiversity, sustainably produce crops, and reduce
vectors of human and livestock disease. However, conventional monitoring
methods of trapping and identification are time consuming and thus expensive.
Here, we present a network of distributed wireless sensors, recording
backscattered near-infrared modulation signatures from insects. The instrument
is a compact sensor based on dual-wavelength infrared light emitting diodes and
is capable of unsupervised, autonomous long-term insect monitoring over weather
and seasons. The sensor records the backscattered light at kHz pace from each
insect transiting the measurement volume. Insect observations are automatically
extracted and transmitted with environmental metadata over cellular connection
to a cloud-based database. The recorded features include wing beat harmonics,
melanisation and flight direction. To validate the sensor's capabilities, we
tested the correlation between daily insect counts from an oil seed rape field
measured with six yellow water traps and six sensors during a 4-week period. A
comparison of the methods found a Spearman's rank correlation coefficient of
0.61 and a p-value of 0.0065, with the sensors recording approximately 19 times
more insect observations and demonstrating a larger temporal dynamic than
conventional trapping.
