Have you ever heard of deep learning or artificial intelligence? As you may know, deep learning is machine learning about billions of images like monitoring a traffic, of facing expression, and of detecting obstacles in front of or back of a car. In this article, machine learning studies soil grain particle sizes, which causes a problem for heavy machines in forest in Finland. What is soil particle grain size? There are many types of soil such as clay, silt, sand, and gravel. Each type of soil has different particle size. The smallest one is clay, which is about . The biggest one is a type of gravel, which is about . Billions of different soil particles are in ground. Many scientists study what those soils particles are about every day. There is a science team, which studies forest soil. In Finland, heavy machines, which are logging machines, forwarder, harvester-processor, feller-buncher, shovel logger, and skidder, go into forest to cut trees, and a truck carries the trees to a factory and a port. Those machines weigh is several tons minimum. When those heavy machines travel in forest, those create deep ditch, which damages forest. In order to estimate the strength of the ground, a team focuses on soil grain particle size. Studying soil grain particle size prevents heavy machines from accidents. The finer the grain particle size is, the deeper ditch is created in forest when working with a heavy machine because fine grain size holds more water, which affects the strength of the ground. The strength of ground is weaker when the grain size is finer. You may imagine the difference between wet mud in your hand and wet sand in your hand. Which one holds more moisture? It is mud, which is finer than sand. At present, many soil samples are collected in forest, and then a laboratory analyzes those samples and issues grain size particles report. It takes some time and costs a lot of money. What if we can omit the process in a laboratory? What if it can be analyzed instantly? Machine learning is one way to improve our work life and our environment. If grain particle size in an image are accurately estimated by machine learning, not only forest workers but also construction workers and farmers can easily, cheaply and quickly analyze the condition of soil. The more data is stored in brain, the smarter it gets. The machine might take over some laboratory work, but it will surely help us improving our work life and our environment. Image of soil (Saito, 2017) References Butcher, S. 30.5.3017. J.P.Morgan’s massive guide to machine learning and big data jobs in finance. EfinancialCareers Ltd. Read (27.11.2017) https://news.efinancialcareers.com/uk-en/285249/machine-learning-and-big-data-j-p-morgan Lewis-Kraus, G. 14.12.2016. The Great A.I. Awakening. The New York Times Magazine. Read (13.11.2017) https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html 2013. U.S. Geological Survey Open-File Report 2006-1195: Nomenclature. U.S. Department of the Interior & U.S. Geological Survey. Read (19.11.2017) https://pubs.usgs.gov/of/2006/1195/htmldocs/nomenclature.htm |
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