CN-122002210-A - Information acquisition method and device based on big data

CN122002210ACN 122002210 ACN122002210 ACN 122002210ACN-122002210-A

Abstract

The application provides an information acquisition method and device based on big data, which are characterized by acquiring position information, signal transmission power and signal quality detection data of first devices in a preset area, analyzing the signal quality detection data by utilizing a big data model, determining channel loss of wireless signals transmitted in the preset area according to analysis results and the position information, determining signal to noise ratio corresponding to each first device according to the channel loss and the signal transmission power, judging whether each first device meets the information acquisition quality requirement according to the signal to noise ratio and a preset signal to noise ratio threshold, if the number of the first devices meeting the requirement is greater than or equal to the preset threshold, transmitting an information acquisition instruction to at least one first device, otherwise, transmitting a power adjustment instruction to at least one first device, and recalculated signal to noise ratio after adjustment until the number of the first devices meeting the requirement is greater than or equal to the preset threshold.

Inventors

YUE HAO

Assignees

南京市医疗保障综合服务中心(南京市医药集中采购保障中心)

Dates

Publication Date: 20260508
Application Date: 20231212

Claims (10)

1. An information acquisition method based on big data is characterized by comprising the following steps: analyzing the signal quality detection data by utilizing a big data model, and determining the channel loss of wireless signals transmitted in the preset area according to the analysis result and the position information; Determining a signal-to-noise ratio corresponding to each first device according to the channel loss and each signal transmission power; judging whether each first device meets the information acquisition quality requirement according to each signal-to-noise ratio and a preset signal-to-noise ratio threshold; If the number of the first devices meeting the information acquisition quality requirement is greater than or equal to a preset threshold, sending an information acquisition instruction to at least one first device, wherein the information acquisition instruction is used for indicating the first device to establish wireless communication with at least one second device and receiving information sent by the second device; Otherwise, sending a power adjustment instruction to at least one first device, and recalculating the adjusted signal-to-noise ratio until the number is greater than or equal to the preset threshold.
2. The method of claim 1, wherein the channel loss comprises a first channel loss comprising loss in signal transmission between each of the first devices and a second channel loss comprising an average loss in signal transmission between each of the first devices and at least one second device; And determining a signal-to-noise ratio corresponding to each first device according to the channel loss and each signal transmission power, including: Calculating a total interference value of each first device interfered by other first devices according to each first channel loss and each signal transmission power; and determining the signal to noise ratio corresponding to each first device according to each signal transmission power, each second channel loss and the total interference value.
3. The big data based information collection method according to claim 2, wherein the calculating the total interference value of each first device interfered by other first devices according to each first channel loss and each signal transmission power comprises: interfere i ＝ω i ∑Lost1 i,j ·P i (i,j∈N) Wherein interfere i is the total interference value of the ith first device, lost1 i,j is the first channel loss between the ith first device and the jth first device, P i is the signal transmission power of the ith first device, ω i is a weight, and N is a set formed by the first devices.
4. The big data based information collection method according to claim 2, wherein the determining the signal-to-noise ratio corresponding to each of the first devices according to each of the signal transmission power, the respective second channel loss, and the total interference value comprises: Wherein interfere i is the total interference value of the ith first device, lost2 i is the second channel loss of the ith first device and at least one second device in the information acquisition range of the ith first device, P i is the signal transmission power of the ith first device, To adjust the coefficients.
5. The big data based information collection method according to any of claims 1-4, wherein said sending a power adjustment instruction to at least one of said first devices comprises: Acquiring a current power distribution diagram of the preset area, wherein the power distribution diagram is used for representing the distribution situation of the signal transmission power of all the first devices in the preset area; Determining the power adjustment instructions for one or more of the first devices based on the respective total interference values and the power profile.
6. The big data based information collection method of claim 5, wherein said determining said power adjustment instructions for one or more of said first devices based on each of said total interference values and said power profile comprises: acquiring the current information acquisition range of each first device; modeling and analyzing each information acquisition range and the power distribution map through the big data model to obtain an information acquisition probability distribution function corresponding to each first device and a power distribution probability density function corresponding to the power distribution map; Determining shape control parameters of the power distribution probability density function according to each information acquisition probability distribution function and each total interference value; and calculating an adjustment value of the shape control parameter through the big data model, and determining the power adjustment instruction according to the adjustment value.
7. The big data based information collection method of claim 6, wherein the determining the shape control parameter of the power distribution probability density function according to each of the information collection probability distribution functions and each of the total interference values comprises: S C ＝h(F(r i ),interfere i ) Wherein S C is the shape control parameter, F (r i ) is the information acquisition probability distribution function, interfere i is the total interference value, and h (x) is the power distribution probability density function.
8. The method of claim 6, wherein the shape control parameters include a first parameter α and a second parameter β when the power distribution probability density function is a probability density function that follows a beta distribution.
9. An information acquisition device based on big data, characterized by comprising: The acquisition module is used for acquiring the position information, the signal transmission power and the signal quality detection data of each first device in the preset area; a processing module for: Analyzing each signal quality detection data by utilizing a big data model, and determining the channel loss of the wireless signal transmitted in the preset area according to the analysis result and each position information; determining a signal-to-noise ratio corresponding to each first device according to the channel loss and each signal transmission power; judging whether each first device meets the information acquisition quality requirement according to each signal-to-noise ratio and a preset signal-to-noise ratio threshold; If the number of the first devices meeting the information acquisition quality requirement is greater than or equal to a preset threshold, sending an information acquisition instruction to at least one first device, wherein the information acquisition instruction is used for indicating the first device to establish wireless communication with at least one second device and receiving information sent by the second device; Otherwise, sending a power adjustment instruction to at least one first device, and recalculating the adjusted signal-to-noise ratio until the number is greater than or equal to the preset threshold.
10. An electronic device comprising a processor and a memory communicatively coupled to the processor; The memory stores computer-executable instructions; the processor executes computer-executable instructions stored in the memory to implement the big data based information collection method of any of claims 1 to 8.

Description

Information acquisition method and device based on big data Technical Field The application relates to the technical field of transformer monitoring, in particular to an information acquisition method and device based on big data. Background Information collection is the basis of information technology, and along with the development of internet of things technology, more and more electronic devices need to read or send information data, so that mutual interference exists between wireless signals. The interference can be divided into two aspects, namely, interference between transmission signals caused by a plurality of transmission terminals transmitting information data to the same receiving terminal, and interference between solicited signals caused by a plurality of receiving terminals soliciting information data from the same transmitting terminal. Currently, in order to suppress the above two kinds of interference, two modes are generally adopted, that is, signals are transmitted through different channels and signals are transmitted through the same channel at different times. However, with the advent of large explosion of information and large data age, the demand of signal transmission has also presented explosive growth, but the wireless channel resource is limited, and many time-sharing multiplexing channels also reduce the utilization rate of the channels, so that the wireless signal transmission has delay, and the information acquisition requirement of the large data age cannot be met more and more. Therefore, how to reduce the mutual interference between signals during information acquisition and improve the channel communication utilization rate at the same time becomes a technical problem to be solved urgently. Disclosure of Invention The application provides an information acquisition method and device based on big data, which are used for solving the technical problems of reducing mutual interference between signals during information acquisition and improving the communication utilization rate of a channel. In a first aspect, the present application provides an information acquisition method based on big data, including: Analyzing the signal quality detection data by utilizing a big data model, and determining the channel loss of wireless signals transmitted in the preset area according to the analysis result and the position information; Determining a signal-to-noise ratio corresponding to each first device according to the channel loss and the signal transmission power of each first device; If the number of the first devices meeting the information acquisition quality requirement is greater than or equal to a preset threshold, sending an information acquisition instruction to at least one first device, wherein the information acquisition instruction is used for indicating the first device to establish wireless communication with at least one second device and receiving information sent by the second device; Otherwise, a power adjustment instruction is sent to at least one first device, and the adjusted signal to noise ratio is recalculated until the number of the first devices meeting the information acquisition quality requirement is greater than or equal to a preset threshold. In one possible design, the channel loss includes a first channel loss including loss in signal transmission between the respective first devices and a second channel loss including an average loss in signal transmission between each first device and at least one second device; determining a signal to noise ratio corresponding to each first device according to the channel loss and each signal transmission power, including: According to the loss of each first channel and the transmission power of each signal, calculating the total interference value of each first device interfered by other first devices; And determining the signal-to-noise ratio corresponding to each first device according to the transmission power of each signal, the loss of each second channel and the total interference value. In one possible design, calculating the total interference value of each first device interfered by other first devices according to the respective first channel loss and the respective signal transmission power includes: interrerei＝ωi∑Lost1i,j·Pi(i,j∈N) Wherein interfere i is the total interference value of the ith first device, lost1 i,j is the first channel loss between the ith first device and the jth first device, P i is the signal transmission power of the ith first device, ω i is the weight, and N is the set formed by each first device. In one possible design, determining a signal-to-noise ratio corresponding to each first device based on each signal transmit power, the respective second channel loss, and the total interference value includes: Wherein interfere i is the total interference value of the ith first device, lost2 i is the second channel loss with at least one second device in the information acquisition