As the basic work of accurate poverty alleviation, the accuracy of poverty alleviation information is very important. Guizhou fully relies on big data and cloud computing to innovate poverty alleviation and development means, and explores a new poverty alleviation model of "internet plus" by building a "poverty alleviation cloud" platform in the province. "Poverty Alleviation Cloud" aims at different reasons and different types of poor people, and provides the right medicine, precise poverty alleviation and precise poverty alleviation. For regional poor people, it vigorously implements the ecological transfer project for poverty alleviation, fundamentally helps solve livelihood problems, and enhances the endogenous motivation for the development of poor areas and poor people.
Transparency of poverty alleviation information
In the flower base of Yangliu Community, Xiehe Town, qianxi county City, Guizhou Province, more than 150 mu of Gerbera jamesonii blooms brilliantly, and 61-year-old Zhou Xuefen is bending over and picking one by one. "More than 10 mu of Gerbera jamesonii is transferred to the base with guaranteed dividends, and there is still 1,200 yuan for work every month. My wife and I have 2,400 yuan, and we saved more than 20,000 yuan last year."
Zhou Xuefen’s family was identified as a poor household in 2014. The old couple were unable to serve these ten acres of land. In addition, his wife Wang Kaifu was sick before, and he owed more than 10,000 yuan in debt just for seeing a doctor. Last year, the poverty alleviation cloud management platform was built in the province. The system shows that through the evaluation of housing, labor and other indicators, the causes of poverty in his family are disease and lack of development funds.
At the beginning of 2015, the village introduced enterprises to engage in flower planting, and the Zhou Xuefen family was first included. With industrial coverage, the hand is getting richer. At the end of the year, Zhou Xuefen’s family took off the hat of poor households. However, the information of Zhou Xuefen’s family can still be found on the "Poverty Alleviation Cloud" system led by Guizhou Poverty Alleviation Office. The system shows that his family scored 69 points through various indicators evaluation, which has reached the poverty alleviation standard.
"A temporary increase in income does not mean that poor households can completely say goodbye to poverty, help the horse to send a ride, and keep abreast of their industries, diseases, education and other conditions through systematic dynamic monitoring to prevent them from returning to poverty due to accidental factors." Zhou Xing, chief agronomist of Guizhou Poverty Alleviation Office, said.
Not only Zhou Xuefen, but also the information of 6.23 million poor people in Guizhou province (statistics as of the end of 2014, including more than 1.2 million people who have been lifted out of poverty) is clearly displayed on the "Poverty Alleviation Cloud" system. Click on the system, from the poverty situation in the whole province to the topography, industrial distribution of a village, and even the housing, population and income of a poor household, with pictures and texts, it is clear at a glance.
Relying on big data and cloud computing, in December 2015, the "Poverty Alleviation Cloud" was launched, realizing the precise management, dynamic management and scientific management of big data for poverty alleviation and development in Guizhou, and the poverty alleviation information was open and transparent.
A display screen, a map of Guizhou, and jumping data show the information of migrant workers, poverty status and causes of poverty in the region in real time … … Guizhou put the breakthrough point of accurate poverty alleviation on accurate identification, found out the number and situation of poor people, and set up a file on the "poverty alleviation cloud" management system to realize the quantification of poverty identification and the visualization of poverty level.
According to the real-time display of the system, as of June 17th, there were still about 4.93 million poor people in Guizhou, and the incidence of poverty was 14.37%. The per capita disposable income of poor farmers was 6681.68 yuan, with 66 poverty-stricken counties, 928 poverty-stricken towns and 9000 poverty-stricken villages.
Visualization of poverty assessment
"To carry out poverty alleviation work, we must first identify the poor, and identifying the poor through big data is the first step of accurate identification." Zhou Xing said that the biggest feature of the "poverty alleviation cloud" is to collect information on poor households through household visits and surveys, and form a scientific and reasonable poverty assessment system based on the "four views".
According to reports, this four-view evaluation system — — Looking at the house, the grain, the labor force and the reader, a total of more than 80 indicators, showing the situation of provinces, cities, counties, towns and villages in the form of pie charts. Among them, the pie chart composition of housing includes: per capita housing is more than 30 square meters, 10-mdash; 30 square meters and less than 10 square meters; The pie chart composition of grain includes: more than 2 mu of cultivated land, 1-mdash; 2 mu, less than 1 mu, no arable land; The composition of the pie chart of the labor force includes: the labor force accounts for more than 50%, 40% and less than 20% of the family population, and there is no labor force; The pie chart of Reading Lang includes: no education debt, less than 5,000 yuan, 5000— 10000 yuan, more than 10000 yuan. Show the poverty score and distribution of poor people (households) through four views, and what kind of assistance measures are taken to further position the poor people.
Zhou Xing said that the "Poverty Alleviation Cloud" integrates various indicators through big data to form a poverty alleviation index, and those below 60 points are real poor households, 60-mdash; 80 points are poor households who reach the poverty alleviation standard but are easy to return to poverty, and more than 80 points are poor households who are stable out of poverty, which is used as a standard to assist in identifying poor households. "In the past, the exit of poor households was only a simple investigation of their income, housing and whether they had dropped out of school, mainly based on qualitative analysis. Now it is more scientific and reasonable to visualize all indicators through the system."
In addition, through the "Poverty Alleviation Cloud", we can supervise the responsibility chain, task chain and project capital chain in real time, do a good job in the implementation of each link, and achieve accurate poverty alleviation.
At present, there are about 5 billion yuan of project funds in Guizhou every year, and there are 10 thousand to 15 thousand projects in the village. How to ensure these projects are implemented is a difficult problem. Zhaowei, development manager of Inspur Group, the technology developer of "Poverty Alleviation Cloud", said that "Poverty Alleviation Cloud" is based on GIS (Geographic Information System) and takes mobile terminals as the carrier to build a mobile inspection system for poverty alleviation work focusing on establishing poverty-stricken households and project funds. "The electronic map of poverty alleviation cloud vector model has been expanded to 16 floors, reaching a scale of 1: 5000, and the positioning of poor households and poverty alleviation projects has been accurate to the village level, realizing random inspection and poverty alleviation projects at any time.
Dynamic assistance measures
Through the data extraction and analysis, the "Poverty Alleviation Cloud" can also show the poverty-causing reasons of the poor, including: illness, disability, school, disaster, lack of land, water, technology, labor, capital, backward traffic conditions, lack of self-development motivation, etc. Through the analysis of the poverty-causing reasons, it can help to formulate accurate poverty alleviation measures.
Systematic data show that the top three causes of poverty are lack of funds, lack of skills and poverty caused by learning, accounting for 30.0%, 17.2% and 14.7% respectively.
Zhaowei said that the "Poverty Alleviation Cloud" aims to expand information collection channels, improve data processing capacity and efficiency, deeply tap the value of data, provide real, reliable, timely and comprehensive decision-making data for poverty alleviation, and escort the final realization of precise poverty alleviation and precise poverty alleviation.
The purpose of accurate identification is to accurately help out of poverty.
"Through big data technology, after mastering the information of the poor population and the causes of poverty, we will monitor the implementation of pairing, assistance plans, implementation of assistance plans and assistance measures for provinces, cities, counties, towns and villages, respectively, identify the distribution of the poor population that has been implemented and not implemented, and display relevant information such as people or units that have been assisted. Through the analysis of the assistance situation, we can clearly understand the actual assistance of the poor people in provinces, cities, counties, towns and villages and assist in the implementation of the assistance task. " Zhou Xing said.
Liu Yuankun, vice governor of Guizhou Province, said that using big data to implement precise poverty alleviation and building a "poverty alleviation cloud" can really make the target precise, make the reasons clear, standardize the management, and make policies according to households and people. The system shows that 1,554,196 poor households and 4,888,885 poor people in Guizhou have all been included in the assistance plan, achieving the right medicine, precise drip irrigation and targeted treatment.
Cartography: Cai Huawei