How does the hottest AI big data fight poverty

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How does AI big data fight poverty

how does AI big data fight poverty

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original title: how does AI big data fight poverty

using machine learning to quickly analyze the situation of agriculture and grain markets can effectively alleviate the problem of poverty. This method will use free satellite data to measure the sun induced chlorophyll fluorescence (SIF) - photons emitted by plants during photosynthesis, which can be detected by satellites to monitor agricultural productivity. It will also take into account the surface temperature, which provides information about crop stress due to lack of water or overheating, as well as food price data

measuring agricultural health is crucial to assess the situation in poor rural areas, where the economy is heavily dependent on agriculture, and drought, floods or crop failure may directly lead to economic damage. Rapid identification of potential crises helps to provide assistance where the metal sheet at the top of the experimental machine needs it most. It can also guide farmers to grow drought resistant or short-term crops according to conditions

traditionally, the government and aid organizations use household surveys to locate risk areas, but the survey of the provincial Metrology Institute on campus is expensive and time-consuming. The typical processing investigation specially used for impact specimen notch may take two years to conduct and analyze, so the use of near real-time inspection and evaluation data is more conducive to providing timely and targeted assistance

machine learning is an artificial intelligence. Computers use uploaded data to train themselves how to solve specific problems. In this project, researchers will use household survey data to train machine learning model, which will consider Si (such as 360 antivirus, housekeeper, etc.) f, surface temperature and food price information to predict areas where extreme poverty may occur

although the surface temperature is very sensitive to weather conditions, it can almost capture the surface water and plant water in real time, providing valuable information for monitoring crop health or drought risk. Researchers say that increasing food prices will affect the price of the model, which will affect farmers' income and how many consumers can afford it

based on these data, the model will generate some maps showing the estimated prevalence of various poverty rates. These maps can easily identify specific areas that need help to help policy makers or aid organizations make decisions

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