Monitoring method and system for massive farmland data

Abstract

The invention provides a monitoring method and system for massive farmland data, belonging to the technical field of computers. The method for monitoring massive farmland data includes: collecting farmland data of different attributes in real time through micro wireless sensor nodes; calculating the degree of influence of farmland data of different attributes on the farmland through cloud computing and using it as the calculation result; displaying the calculation results through the network to the user. This method calculates the impact of farmland data with different attributes on farmland through cloud computing, solves the problem of computing efficiency for massive farmland data, expands the scale of data input, and improves the mining efficiency of farmland data.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a monitoring method and system for massive farmland data. Background technique [0002] my country is a large agricultural country with a vast territory, numerous soil types, and complex crop varieties. my country has conducted many agricultural censuses, and scientific and technological personnel have accumulated a large amount of attribute data and spatial data closely related to agricultural production through various methods. These data have multidimensional , dynamic, uncertain, incomplete, strong spatio-temporal variability and other characteristics, which can specifically reflect the real situation of agricultural production operations. Sensors are a common method for agricultural scientists to collect field information and obtain data. In addition to the above characteristics, these data also have the characteristics of a large number, concentration and persistence. The...

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Problems solved by technology

[0004] The current farmland data system can efficiently realize data entry, query, and statistical functions, but it cannot predict based on existing data, and cannot discover the relationship between data, and data mining technology can discover the relationship between data, so it can solve agricultural problems. The phenomenon of "data rich knowledge poor" in the field

The traditional decision tree algorithm is popular because of its fast construction speed, simple generation model, and high precision. It is an important classification method in data mining. Data calculation must be in memory at the same time, and can only be run on a single machine, so it can only be applied to small-scale data input. When the object of data mining is a huge data set, the speed often slows down due to the increase in the amount of calculation. Slow or even impossible to run, greatly affecting the scalability of the algorithm, which is the bottleneck of the algorithm

[0005] To sum up, the existing farmland data analysis methods cannot complete the calculation of huge data, making the farmland information collection systems independent of each other, closed operation, and difficult to integrate, analyze and share information. How to effectively integrate and analyze data is the key to the current agricultural information important issues in the process of

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