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A forest fire monitoring system node effective dynamic coverage method based on the Internet of Things

A forest fire and monitoring node technology, applied in the field of forest fire monitoring system, can solve the problems of high cost of effective coverage calculation and low efficiency, achieve good node deployment effect, improve efficiency, and reduce calculation cost

Inactive Publication Date: 2019-05-21
YANAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide an effective dynamic coverage method for forest fire monitoring system nodes based on the Internet of Things, which solves the problems of high cost and low efficiency in the effective coverage calculation of forest fire monitoring Internet of Things nodes existing in the prior art

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  • A forest fire monitoring system node effective dynamic coverage method based on the Internet of Things
  • A forest fire monitoring system node effective dynamic coverage method based on the Internet of Things
  • A forest fire monitoring system node effective dynamic coverage method based on the Internet of Things

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Embodiment Construction

[0064] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0065] According to the different coverage target areas of the Internet of Things, the deployment of Internet of Things node coverage can generally be divided into three types: area coverage, point coverage, and fence coverage.

[0066] The Internet of Things area coverage is based on a certain area. In the target area, the number of IoT nodes is as small as possible to cover every point in the target area, so as to ensure reliable communication between nodes in the area and realize the target area. Maximize coverage, reduce network construction costs and expenses. Regional coverage requires large coverage and high quality requirements, and is generally used in key areas, or occasions that have high requirements for monitoring quality. figure 1 It is a schematic diagram of regional coverage, and 6 IoT nodes are required to complete the cover...

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Abstract

The invention discloses a forest fire monitoring system node effective dynamic coverage method based on Internet of Things. The method comprises the following steps: setting parameters: a population size NP, a scale factor F, a cross probability CR and a maximum evolution algebra Gmax; Randomly generating an initial population with a population size of NP, and solving a fitness value of an NP individual; Judging whether a termination criterion is met or not, and performing DE variation operation, DE crossover operation and DE selection operation on the current population individual; Executinga local search algorithm SQI; And finally outputting the obtained best result. According to the invention, the problems of high calculation cost and low efficiency of effective coverage of forest firemonitoring Internet of Things nodes in the prior art are solved.

Description

technical field [0001] The invention belongs to the technical field of forest fire monitoring systems, and in particular relates to an effective dynamic coverage method for forest fire monitoring system nodes based on the Internet of Things. Background technique [0002] With the continuous advancement of MEMS, sensor technology and communication technology, the Internet of Things is increasingly connected with modern industrial production and daily life. Especially for large-scale monitoring such as disaster environment monitoring and forest fire early warning, the Internet of Things node coverage has become an important indicator to measure the normal working range of the Internet of Things in the monitoring area. [0003] Forest fire monitoring IoT coverage strategy can be divided into deterministic coverage and random coverage according to whether the monitoring environment or area is known. When the monitoring environment or area is known, the Internet of Things covera...

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Application Information

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IPC IPC(8): G06N3/00G06N3/12G06F17/16
Inventor 雷文礼张鑫聂宏伟高瑞薛晶晶张玉强杨延宁王箫扬崔巍
Owner YANAN UNIV
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