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  • One of the really insidious parts of illegal logging is that the same criminal enterprises

  • are also engaged in trafficking drugs, weapons, and typically human trafficking as well. It's

  • not just damage to the environment where the trees were cut down, and it's not just the

  • source country losing those resourcesit's also the fact then that those profits go on

  • to support these other kinds of international crime.

  • We're at a point in time where the

  • world's forests need all hands on deck, if we are not actively engaged in some form of

  • protection and some form of combating illegal logging, if we don't do it now, we may

  • not have a chance. We lose habitat that maybe we can never get back.

  • Internationally, we see the bulk of illegal logging happening in the tropics.

  • So we talk about deforestation,

  • illegal logging, land conversion in places like Congo, in sub-Saharan Africa, or the

  • Amazon in South America. The role that the US plays in the global illegal logging trade

  • is that we're a demand side, we're a consumer side of this problem. We know from research

  • and investigations that have been going on now quite actively for about 10 years, that

  • there's actually a lot more fraud and misrepresentation of forest products than people realize and

  • some of that material is doubtless of illegal origin. So when we're involved in the fight

  • against illegal logging, our role is really on this forensic timber identification piece.

  • This is the Center For Wood Anatomy Research. We're the home of the world's largest scientific

  • research wood collection. Everyone, I think, is familiar with forensics nowadays. One area

  • of forensics that people often overlook is botanical forensics. We'll work on whatever

  • cases that we need to. We've done plane crashes, we've done murder cases, we've worked on arson

  • cases, attempted car bombings. Since about 1999, one of the places that we've really

  • focused on heavily is using forensic wood anatomy to combat illegal logging. We develop

  • the technology and the tools for field deploying this kind of information so that field agents

  • can look at a paper and it says, "This is supposed to be species X. This is supposed

  • to be species Y." They need some kind of knowledge or technology to let them look at the wood

  • and see whether it lines up with the paperwork. And traditionally that's done by someone like

  • me, or I would train someone. And training human beings to do this takes a lot of time,

  • it takes a lot of effort. I really started saying, "How can we solve this problem of

  • needing to build this capacity and needing to get this information out, because I don't

  • think we can train human beings fast enough". And that actually led us down a pretty interesting

  • road of trying to come up with a technological solution to this problem.

  • It is essential to have an interdisciplinary team that knows about law enforcement, AI,

  • wood anatomy, and all these fields come together here. Alex is the wood anatomist, and he's

  • learned a little bit of machine learning from me. I'm a machine learner and I've learned

  • a little bit of wood anatomy from Alex. The Xylotron itself is this handheld, portable

  • device connected to a laptop to do wood identifications. The XyloTron is built from off the shelf components

  • and uses all open source technologies.

  • It has two primary components. It has the imaging device itself, which we call the xyloscope,

  • and then it has the laptop where we actually do the AI portion of it where the actual identification is made.

  • The biggest advantage is you can carry this thing in two hands and take it anywhere in the world.

  • That is not true of any of the other forensic technologies. They're really restricted to the laboratory.

  • The artificial intelligence model that we use in the XyloTron to identify wood is a neural network.

  • A neural network is basically

  • a mathematical computation, which has some numbers or knobs and parameters that can be

  • tweaked and changed in a data driven manner. In our case, the input is the image of a wood

  • and the output is going to be what species or what category this wood belongs to.

  • To operate this, all we have to do is have a specimen of wood and then place this flush

  • on the top surface there. Turning on the light, pressing this onto the surface of the specimen,

  • and then I have to orient the Xyloscope so that a certain botanical feature called "rays"

  • are running vertically in the imageIt captures an image, it feeds that image into the system,

  • it breaks it down according to the machine learning algorithm, and then it gives me my

  • output. It's basically the exact same thing I see when I look with my hand lens at a block of wood.

  • There's always going to be this cat and mouse game between what the criminals

  • are doing and technology catching up with their misdeeds. Illegal logging is a global

  • problem, and to address it at a global scalewhat we need is access to technology and expertise

  • that is scalable, affordable, and easy to adopt and adapt. The XyloTron project ticks

  • boxes on all these levels and it can be deployed at many different points in the wood supply chain.

  • In an ideal world, we would combat illegal logging in the forest. Right?

  • We would stop the people with the chainsaws.

  • And there are people out there trying to do that, but that's not a place where the science that we do here

  • can contribute muchIf a shipment comes into the United States and we do the identifications

  • and it's illegal because they mis-declared what it was or because it's an endangered

  • species, we have the legal authority to seize that shipment. And if you can do that enough,

  • you're going to reduce the demand, you're going to reduce the degree

  • to which it's desirable to be out there illegally logging.

  • Because if they can't make money, they're not going to do it as frequently.

  • It's just that simple.

One of the really insidious parts of illegal logging is that the same criminal enterprises

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This New AI Forensic Tool is Fighting Illegal Logging

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    林宜悉 posted on 2021/03/16
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