Large-scale wireless sensor network data collection method based on unmanned aerial vehicle

A wireless sensor, network data technology, applied in specific environment-based services, network topology, wireless communication, etc., can solve the problem of low value of data information

Active Publication Date: 2020-02-28
SOUTHEAST UNIV
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  • Large-scale wireless sensor network data collection method based on unmanned aerial vehicle
  • Large-scale wireless sensor network data collection method based on unmanned aerial vehicle
  • Large-scale wireless sensor network data collection method based on unmanned aerial vehicle

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Embodiment Construction

[0041] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0042] In the present embodiment, the method of the present invention is applied to UAV-assisted wireless sensor networks (UAV-aidedWSNs), and the DFP (Direct Future Prediction) model is applied to the UAV path planning problem, such as figure 1 As shown, the scenario considered in this embodiment consists of a group of sensor nodes S={s i |i=1,2,...,n}, composed of a drone, base station and charging station. The sensor nodes are randomly deployed to the target area, and the drone acts as a mobile sink node to collect data and send the data back to the base station. When the battery runs low during collection, it flies to a charging station to recharge.

[0043] In the scenario of a large-scale wireless sensor network based on drones, it is obviously unrealistic for drones to collect data from each node. So in order to reduce the spatio-temp...

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Abstract

The invention discloses a large-scale wireless sensor network data collection method based on an unmanned aerial vehicle. The method comprises the following steps that sensor nodes collect surroundinginformation in an event-driven mode; dividing the target area according to a grid type, and forming a cluster by the sensor nodes in the same grid; counting node energy in each cluster, and selectingthe node with the most residual energy in the cluster as a cluster head node; calculating an information value of a non-cluster head node in the grid at the moment t; if a threshold function is given, forwarding the node data to the cluster head nodes in the same grid, otherwise, returning; training the unmanned aerial vehicle on line according to the DFP model, and planning an unmanned aerial vehicle path; and the unmanned aerial vehicle collects data of the sensor nodes according to the planned path and transmits the data back to the base station. According to the invention, the DFP model is applied to unmanned aerial vehicle path planning, so that the unmanned aerial vehicle can maximize the collected total information value and ensure charging at a low electric quantity, and the method is very suitable for animal monitoring, forest fire, earthquake rescue and other scenes.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and in particular relates to a large-scale wireless sensor network data collection method based on an unmanned aerial vehicle. Background technique [0002] Data collection in wireless sensor networks is an active research topic, and scheduling UAVs to acquire sensor data from distributed sensors is expected to significantly improve the data collection efficiency of traditional wireless sensor networks. It has been widely used in disaster rescue, animal tracking, forest monitoring and other fields. The communication methods of wireless sensor networks can be divided into three main types: query-driven, event-driven and clock-driven. In an event-driven sensor network, only when certain specific events (such as earthquakes, fires, temperature / humidity, etc. reach a certain threshold) occur, the sensors are woken up for data transmission, and remain in low-power sleep at other time...

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Application Information

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IPC IPC(8): H04W4/38H04W4/44H04W40/10H04W40/22H04W40/32H04W52/02H04W84/18G05D1/10
CPCH04W4/38H04W4/44H04W40/10H04W40/22H04W40/32H04W52/0225H04W84/18G05D1/101Y02D30/70
Inventor 燕锋陈佳慧茅珅珅夏玮玮沈连丰胡静宋铁成
Owner SOUTHEAST UNIV
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