A wireless sensor network data collection method for environmental emergencies

Abstract

The invention discloses a wireless sensor network data collection method for environmental emergencies. The method comprises the following steps: classifying nodes in a wireless sensor network according to event relevance, comprising an event correlation node, an event edge node and a sleep node; when an environmental emergency occurs, selecting any event correlation node as a starting point, completing initialization, and notifying a neighbor node to perform environmental event sensing; when the neighbor node completes the sensing, judging a fuzzy domain, and when a correlation coefficient exceeds a set threshold, storing the node in an event correlation node set; for the newly selected event correlation node set, notifying the neighbor node to perform the environmental event sensing in the same method; repeating the above steps until the nodes in the event correlation node set is not increased anymore; and transmitting the collected data to a remote server. By adoption of the wireless sensor network data collection method disclosed by the invention, the correlation between the data sending node and the event is improved, and the accuracy of a sensing strategy and the data qualityare improved.

Description

technical field [0001] The invention belongs to the technical field of environmental monitoring, and relates to a wireless sensor network data acquisition method oriented to environmental emergencies. Background technique [0002] Wireless networking, intelligence, miniaturization, and integration are important trends in the development of environmental monitoring systems, which can automate and remoteize environmental monitoring. Therefore, with the rapid development of semiconductors, wireless communication technology, micro-electromechanical systems and other disciplines, wireless sensor networks have become one of the research hotspots in the field of environmental monitoring. Wireless sensor network comprehensively uses a number of technologies, it is a collection of various technologies, including wireless communication technology, embedded computer technology, sensor technology and distributed information processing technology. It can monitor the monitoring object in...

AI Technical Summary

Problems solved by technology

When the current wireless sensor network environmental monitoring system collects key parameter data in response to unexpected environmental events, there are deficiencies such as low quality of wireless sensor network parameter collection data, poor correlation with environmental events, large data transmission volume, and high network delay.

[0003] In the existing environmental monitoring data acquisition system, the wireless node sensors have a single type, and the correlation between the collected data and environmental events is poor; it is usually assumed that the environmental events are static and the occurrence area is fixed

Based on the above description and analysis, the existing technology has the following deficiencies: First, the current data collection method of the wireless sensor network for environmental monitoring is that the wireless network drives all the wireless sensor nodes in the network to collect data, and a single node collects the data of all sensors, and then perceives through A certain routing path transmits the data to the remote server; obviously, the current wireless sensor network data acquisition strategy has shortcomings such as large amount of collected data, low network transmission efficiency, large energy consumption, and high data transmission delay

Secondly, the current data collection method is the data of all sensors in each node, which has the disadvantages of low quality of collected data and low correlation between collected data and events.

Finally, when the current wireless sensor network for environmental emergencies collects data, it assumes that the environmental events are static, which is obviously different from the actual engineering application, and it is not suitable for practical applications; the environmental monitoring data collection based on this assumption The method obviously cannot adapt to dynamically changing environmental emergencies, and there are shortcomings such as incomplete monitoring data in practical applications.

Images