Background:

Forest pest damage costs the U.S. billions of dollars annually, according to experts. And that cost could skyrocket if certain non-native insect species were to spread more widely across the nation. Tens of millions of acres of tree cover, both urban and rural, are potentially at risk.

One of the biggest threats to houses comes in the form of Wood Destroying Insect. These pests silently and almost invisibly consume wood. Some estimates put the damage caused by these creatures at more than $1 billion a year. It is often difficult for one to spot these pests. The damage inflicted by WDI occurs over a long time (months) and it is likely the creatures were there long before one notices them.

Currently wood boring insects are a significant threat in the context of import and export between countries. Each pallet needs to be inspected at great time and expense. The current system saves inspectors a substantial amount of time and allows them to conduct more inspections. It also allows the ability to detect and classify insects in noisy environments.

Summary:

This device has sensitive vibration and acoustic sensors and special algorithms capable of detecting insects in the presence of strong background noise. It is comprised of acoustic and vibration sensors connected to a Data Acquisition Board that digitizes the information and a computer that processes the data and provides a display of the detection results.

The team carefully recorded the vibrations produced by the two species of wood-boring pests of particular concern — the emerald ash borer and the Asian longhorn beetle — with high-quality vibration sensors. (USDA scientists estimate the longhorn beetle alone, left unchecked, has the potential to eliminate up to 30 percent of all urban tree cover in North America, more than a billion trees: a potential $670 billion hit to the economy.)

Next the team analyzed the larva-vibration libraries it created, developing artificial intelligence that's capable of analyzing signals recorded in the forest and picking out the distinctive vibrations of those two-insect species. Background noises such as wind, vehicles, walkers, machinery, aircraft, electronics and human voices can produce vibrations in trees and interfere with the insect larva-produced vibrations.

To filter out those signals, the team created another library of typical interfering sounds and their vibrations in its lab, tweaking their algorithm to flag the known vibro-acoustic signatures of those various types of background noise. The team also tuned the algorithm with additional filters, such as one that rejects all vibrations that last longer than an insect's single longest continuous vibration could last, and they incorporated additional mathematical transformations to the process, as well, to perform feature extraction on the larval signatures.

Benefits:

- It allows the ability to detect and classify insects in noisy environments.

- The system saves inspectors a substantial amount of time and allows them to conduct more pallet inspections

- The threats to houses from the wood destroying insects can be reduced to a great extent

- Many trees which are centuries old can be saved

Applications:

- Lumber and forestry industry

- Detecting threats from wood-boring insects in shipping pallets and similar structures