Deployment method of low-energy ecological environment monitoring nodes based on sensor network

Abstract

The invention discloses a sensor-network-based low-energy-consumption ecological environment monitoring node deploying method and relates to the Internet of Things. The method comprises the following steps: firstly determining factors to be monitored and key points with relative factors; building an optimal mathematic monitoring model according to the monitored factors and the key points; then solving the mathematic model and finding a key point with most attributes and taking the key point as a pre-selection point; invoking an attribute optimizing method for selecting the key points with all the attributes which are close to an attribute mean value if the number of the pre-selection points is greater than 1; invoking a crop growth factor weighing method for determining monitoring points if more than two pre-selection points exist after the treatment; randomly determining that the pre-selection points processed by the crop growth factor weighing method are taken as the monitoring points by using a random algorithm; finally processing a matrix T formed by the key points and the attributes by using a matrix optimizing method of the key points and the attributes to obtain the number of the final monitoring nodes and the distribution positions of the monitoring nodes.

Description

technical field [0001] The invention relates to the Internet of Things, in particular to a sensor network-based low-energy ecological environment monitoring node deployment method. Background technique [0002] The land on which crops grow is a non-growable natural resource. How to improve production efficiency, economic benefits and environmental benefits on the basis of limited resources with the help of advanced technology has become a major problem to be solved urgently. At present, "agricultural informatization" characterized by the integration of information technology and agricultural technology has become one of the key supporting technologies to solve the above problems. The reasons for the spatial differences in the growth and yield of crops, and make decisions for each plot, and accurately perform irrigation, fertilization, spraying, etc. on each plot, so that traditional agricultural production can be refined to maximize The use efficiency of water, fertilizer a...

AI Technical Summary

Problems solved by technology

[0004] In the traditional ecological environment monitoring method, the selection of monitoring nodes is very subjective and arbitrary, and lacks relevant quantitative mathematical models, so it is difficult to save construction costs while ensuring the monitoring effect in actual work

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