A Data Fusion Method for Sensor Networks Based on Data Uniformity Weighting

Abstract

The invention relates to a sensor network data fusion method based on data uniformity weighting, which is implemented according to the following steps: determining the distance weighted value Omega(di) of each sensor node i according to the distance from an actuator; generating a node association relation diagram according to the geographical location of each sensor node in a scene to describe the adjacent relation around each node; calculating the smoothness weighted value Omega(si) of each node i according to the node association relation diagram; calculating the pre-estimated result De according to the distance weighted value Omega(di) and the smoothness weighted value Omega(si); calculating the amount of weighting fine-tuning Delta Omega(i); and after getting the amount of weighting fine-tuning, calculating the final data fusion result D. According to the sensor network data fusion method based on data uniformity weighting put forward by the invention, the influence of error nodes on the final result is weakened by adopting different weighted values, and an accurate sensing result can be obtained.

Description

technical field [0001] The invention relates to the technical field of detection, in particular to a sensor network data fusion method based on data uniformity weighting. Background technique [0002] Environmental control plays an important role in industrial and agricultural production. For example, the adjustment of greenhouse temperature, humidity, light, and carbon dioxide concentration can significantly affect the growth of plants. The basis of environmental control is to obtain on-site parameter values ​​accurately and fairly, so as to correctly control the actuator for compensation control. However, due to the complexity of the field environment, each part of a large area has slightly different parameter values, and a single sensor may also obtain inaccurate data due to errors or equipment failures during collection, or even obtain errors due to damage. The data. In this case, arranging multiple sensors and interconnecting them into a network form, thereby increasi...

AI Technical Summary

Problems solved by technology

After a large number of sensors are used, the problem of data fusion is brought. How to obtain a more accurate result through comprehensive calculation of data from a large number of sensors has become a problem to be solved by the data fusion algorithm.

In actual production practice, due to the different locations of the sensor nodes, the reliability of the collected data also varies. For example, when the sensor node next to the heater is working, the air temperature is higher than the average temperature of the entire greenhouse, the value may have a large deviation, and the reliability is poor

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