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Standard Digital Camera, AI To Monitor Soil Moisture For Affordable Smart Irrigation

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Adelaide (Australia): Researchers at the University of South Australia have developed a cost-effective new technique to monitor soil moisture using a standard digital camera and machine learning technology. The United Nations predicts that by 2050 many areas of the planet may not have enough fresh water to meet the demands of agriculture if we continue our current patterns of use. One solution to this global dilemma is the development of more efficient irrigation, central to which is precision monitoring of soil moisture, allowing sensors to guide'smart' irrigation systems to ensure water is applied at the optimum time and rate. Current methods for sensing soil moisture are problematic -- buried sensors are susceptible to salts in the substrate and require specialised hardware for connections, while thermal imaging cameras are expensive and can be compromised by climatic conditions such as sunlight intensity, fog, and clouds. Researchers from The University of South Australia and Baghdad's Middle Technical University have developed a cost-effective alternative that may make precision soil monitoring simple and affordable in almost any circumstance.


An affordable 'smart irrigation' proof of concept

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Researchers at UniSA have developed a cost-effective new technique to monitor soil moisture using a standard digital camera and machine learning technology. The United Nations predicts that by 2050 many areas of the planet may not have enough fresh water to meet the demands of agriculture if we continue our current patterns of use. One solution to this global dilemma is the development of more efficient irrigation, central to which is precision monitoring of soil moisture, allowing sensors to guide'smart' irrigation systems to ensure water is applied at the optimum time and rate. Current methods for sensing soil moisture are problematic – buried sensors are susceptible to salts in the substrate and require specialised hardware for connections, while thermal imaging cameras are expensive and can be compromised by climatic conditions such as sunlight intensity, fog, and clouds. Researchers from The University of South Australia and Baghdad's Middle Technical University have developed a cost-effective alternative that may make precision soil monitoring simple and affordable in almost any circumstance.


Deep science: AI is in the air, water, soil and steel – TechCrunch

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Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect some of the most relevant recent discoveries and papers -- particularly in but not limited to artificial intelligence -- and explain why they matter. This week brings a few unusual applications of or developments in machine learning, as well as a particularly unusual rejection of the method for pandemic-related analysis. One hardly expects to find machine learning in the domain of government regulation, if only because one assumes federal regulators are hopelessly behind the times when it comes to this sort of thing. So it may surprise you that the U.S. Environmental Protection Agency has partnered with researchers at Stanford to algorithmically root out violators of environmental rules.


IoT Applications in Agriculture

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Despite a growing population, now predicted to reach 9.6 billion by 2050, the agriculture industry must rise to meet demand, regardless of environmental challenges like unfavorable weather conditions and climate change. To meet the needs of that growing population, the agriculture industry will have to adopt new technologies to gain a much-needed edge. New agricultural applications in smart farming and precision farming through IoT will enable the industry to increase operational efficiency, lower costs, reduce waste, and improve the quality of their yield. So, what is smart farming? Smart farming is a capital-intensive and hi-tech system of growing food cleanly and sustainable for the masses.


IOT TRANSFORMING THE FUTURE OF AGRICULTURE IOT Solutions World Congress DIGITALIZING INDUSTRIES

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With the exponential growth of world population, according to the UN Food and Agriculture Organization, the world will need to produce 70% more food in 2050, shrinking agricultural lands, and depletion of finite natural resources, the need to enhance farm yield has become critical. Limited availability of natural resources such as fresh water and arable land along with slowing yield trends in several staple crops, have further aggravated the problem. Another impeding concern over the farming industry is the shifting structure of agricultural workforce. Moreover, agricultural labor in most of the countries has declined. As a result of the declining agricultural workforce, adoption of internet connectivity solutions in farming practices has been triggered, to reduce the need for manual labor.