CN112904420A - Data acquisition method, device and equipment based on mobile equipment - Google Patents
Data acquisition method, device and equipment based on mobile equipment Download PDFInfo
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- CN112904420A CN112904420A CN202110121596.0A CN202110121596A CN112904420A CN 112904420 A CN112904420 A CN 112904420A CN 202110121596 A CN202110121596 A CN 202110121596A CN 112904420 A CN112904420 A CN 112904420A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
Abstract
The embodiment of the invention provides a data acquisition method, a device and equipment based on mobile equipment, and belongs to the technical field of data acquisition. The data acquisition method based on the mobile equipment comprises the following steps: based on hardware information and a stable state of the mobile equipment, carrying out availability measurement on the mobile equipment to obtain a measurement result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to the motion state and the placement state of the mobile device; and determining the data uploading authority of the data collected by the mobile equipment based on the measurement result. Meanwhile, the corresponding data acquisition device based on the mobile equipment and the data acquisition equipment based on the mobile equipment are also provided. The implementation mode provided by the invention can improve the data acquisition quality of the mobile equipment as a data acquisition terminal and solve the problem of transmission of mass data.
Description
Technical Field
The invention relates to the technical field of data acquisition, in particular to a data acquisition method based on mobile equipment and data acquisition equipment based on the mobile equipment.
Background
As mobile terminals become more powerful, they are able to perceive more and more external data. The data collected by the mobile devices through their various sensors has been used in a number of applications in the prior art. The current trend is that mobile devices, as important nodes for distributed sensing and edge computing, need to collect and process specific data in different fields. Taking the application of the mobile terminal to the field of earthquake monitoring and early warning as an example, the prior art does not provide effective processing of specific types of vibration data of the mobile device terminal, and does not find a method for selecting the mobile device as a vibration sensing node.
Disclosure of Invention
The invention aims to provide a data acquisition method based on mobile equipment, and aims to solve the problems of overlarge data volume when the existing mobile equipment is used as a sensing terminal, communication cost and processing pressure of a service terminal caused by the overlarge data volume, and uneven data quality.
In a first aspect of the present invention, a data acquisition method based on a mobile device is provided, the method comprising: based on hardware information and a stable state of the mobile equipment, carrying out availability measurement on the mobile equipment to obtain a measurement result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device; and determining the data uploading authority of the data collected by the mobile equipment based on the measurement result.
Preferably, the hardware information includes: the model of the mobile device, the usage information, the model of the shock and location related sensor, and the detection performance of the shock related sensor.
Preferably, the steady state comprises: a frequency with which the mobile device enters or exits a stationary state and a horizontally disposed state, and a duration for which the mobile device remains in the stationary state and the horizontally disposed state.
Preferably, the mobile device is in a stationary state determined by: in the acceleration data corresponding to the mobile equipment in the static state, the measurement in the short time window and the measurement in the long time window accord with the configured static state measurement; the mobile device is determined to be in a horizontal placement state by: in the acceleration data corresponding to the mobile device in the horizontally placed state, the measure of the acceleration component with respect to the vertical direction conforms to the configured horizontally placed state measure.
Preferably, the performing the usability measurement on the mobile device to obtain the measurement result includes: scoring hardware information of the mobile device and each data dimension of the steady state; calculating a weighted sum as the metric result based on the score and corresponding weight value for each data dimension; the metric results are updated as the scores or weight values change.
Preferably, the mobile device is tagged with a steady state identification when the mobile device maintains a duration metric having the static state and the horizontally disposed state, consistent with a configured steady state time metric.
Preferably, the data dimensions include: data processing capabilities related to a model of the mobile device and a model of a sensor of the mobile device; a sensor detection performance related to a self-noise level and a sampling rate performance of a shock related sensor of the mobile device; the equipment aging degree is related to the total use duration or the charging and discharging times of the mobile equipment; a steady-state time ratio, which is a time ratio of the mobile device having a steady-state identifier in a preset statistical period; and the steady state change frequency is the change times of the mobile equipment with the steady state identification in the statistic period.
Preferably, the data dimension further comprises: and the relative height is the ground height of the mobile equipment relative to the position.
Preferably, the scores of steady-state time fraction, steady-state change frequency and relative height in the data dimension are updated at the end of the statistical period.
Preferably, the method further comprises: determining that the mobile equipment has a reporting history of the collected data; correcting the measurement result corresponding to the mobile equipment based on the accuracy score of the reported historical record relative to the final confirmation data corresponding to the reported historical record; and taking the corrected measurement result as the measurement result of the mobile equipment.
Preferably, the determining the data uploading authority of the data collected by the sensor of the mobile device based on the measurement result includes: determining that a metric result of the mobile device is above a configured metric result threshold; and determining whether the mobile equipment has a data uploading authority identification, and if so, the mobile equipment has the data uploading authority.
Preferably, the determining whether the mobile device has the data uploading right identifier includes: assigning a selected probability corresponding to a metric result based on the metric result of the mobile device; selecting an alternative mobile device from the grid based on the selected probability; and randomly determining mobile equipment corresponding to the number of the data uploading right identifications from the alternative mobile equipment, wherein the determined mobile equipment has the data uploading right identifications.
Preferably, the determining whether the mobile device has the data uploading right identifier includes: determining a mobile device with a metric result in the grid higher than the configured metric result threshold as an alternative mobile device; determining the selected probability of the alternative mobile devices based on the number of the alternative mobile devices in the grid, the number of the data uploading weight identifications to be distributed and a measurement result; the candidate mobile device is determined whether to have the data upload right identification based on the selected probability.
Preferably, the grid is one of a plurality of grids into which the geographical range of the preset monitoring area is divided.
Preferably, the selected probability is updated under the following preset conditions, and the preset conditions include: a change in a number of mobile devices within the grid exceeding a configured number change threshold; the number of the data uploading right identifiers to be distributed in the grid is configured and updated; and reaching the updating period of the preset selected probability.
In a second aspect of the present invention, there is also provided a data acquisition apparatus based on a mobile device, the apparatus comprising: the data acquisition module is used for acquiring hardware information and a stable state of the mobile equipment; a metric calculation module, configured to perform usability metric on the mobile device based on the hardware information and the stable state to obtain a metric result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device; and the permission determining module is used for determining the data uploading permission of the data collected by the mobile equipment based on the measurement result.
In a third aspect of the present invention, there is also provided a data acquisition device based on a mobile device, the device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the aforementioned data acquisition method based on a mobile device when executing the computer program.
In a fourth aspect of the invention, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements the method as described above.
In a fifth aspect of the present invention, there is also provided a computer readable storage medium storing computer instructions which, when run on a computer, cause the computer to perform the aforementioned method.
The technical scheme provided by the invention adopts the modes of mobile equipment state definition, statistics and the like, and can select the mobile equipment which accords with the specific characteristics from a large number of mobile equipment, so as to avoid the problems of overlarge data volume when the large number of mobile equipment is used as a sensing terminal, communication cost and processing pressure of a service terminal caused by the overlarge data volume, and uneven data quality. By adopting the implementation mode provided by the invention, the data collection quality of the selected mobile equipment can be preferentially selected from a large number of mobile equipment and improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 is a schematic flow chart illustrating a data collection method based on a mobile device according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a step of determining that a mobile device has a data upload right identifier according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a step of determining that a mobile device has a data upload right identifier according to another embodiment of the present invention;
fig. 4 is a block diagram of a data acquisition apparatus based on a mobile device according to another embodiment of the present invention.
Detailed Description
In addition, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a schematic flow chart of a data collection method based on a mobile device in an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides a data acquisition method based on a mobile device, where the method includes:
s01, carrying out usability measurement on the mobile equipment based on the hardware information and the stable state of the mobile equipment to obtain a measurement result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device;
the mobile device as a data acquisition terminal of the whole system is influenced by various factors of the mobile device. In order to measure the influence of the factors on the data acquisition quality, the embodiment performs availability measurement on the hardware information and the stable state of the mobile equipment. Wherein the selected hardware information is limited to data collection capabilities including sensor performance evaluation and processor performance evaluation. The stable state is defined as a motion state and a placement state, wherein the motion state is mainly a stationary state of the mobile device, and the placement state is mainly the stability of the mobile device after placement. The selection of the above factors is beneficial for the mobile device to better collect external data, especially vibration data.
And S02, determining the data uploading authority of the data collected by the mobile equipment based on the measurement result.
After the availability measurement is performed on the hardware information and the stable state selected in step S01, the mobile device whose measurement result satisfies the preset condition is selected from the hardware information and the stable state, and the data upload right is given to the mobile device. And uploading the acquired data by the mobile equipment with the data uploading authority.
In the above embodiment, the mobile device in the better state can be selected from a large number of mobile devices to perform data acquisition and upload, so that the excessive data volume when a large number of mobile devices are used as the sensing terminal, and the communication cost and the processing pressure of the service terminal caused by the excessive data volume are avoided. Meanwhile, the embodiment reduces the influence and interference of the mobile equipment on the acquired data to the greatest extent, thereby solving the problem of uneven data quality.
In one embodiment of the present invention, the hardware information includes: the model of the mobile device, the usage information, the model of the shock and location related sensor, and the detection performance of the shock related sensor. The mobile equipment model reflects the performance of the mobile equipment, the use information reflects the aging degree of the mobile equipment, and the sensor related to the vibration and the positioning comprises an acceleration sensor and a positioning module, and the model reflects the corresponding acquisition capacity and acquisition precision. The detection performance of the sensor related to the vibration comprises the self-noise level, the acquisition precision, the sampling rate and the like. Through the specific selection of the hardware information, the acquisition precision and the processing capacity of the vibration data of the mobile equipment can be improved.
In one embodiment of the present invention, the steady state comprises: a frequency with which the mobile device enters or exits a stationary state and a horizontally disposed state, and a duration for which the mobile device remains in the stationary state and the horizontally disposed state. When the mobile device is not in a static state, the mobile device is greatly influenced by the outside, and is not suitable to be used as an acquisition terminal. Similarly, when the mobile device is not placed horizontally, the mobile device is easy to move due to slight shaking, and is not suitable to be used as a collection terminal. The present embodiment thus performs the determination of the steady state using the static state and the horizontally placed state. When the mobile device frequently enters or exits the static state and the horizontal placement state, and the duration of keeping the static state and the horizontal placement state is too short, the stable state of the mobile device is considered to be poor.
In one embodiment of the present invention, the mobile device is determined to be in a stationary state by: in the acceleration data corresponding to the mobile equipment in the static state, the measurement in the short time window and the measurement in the long time window accord with the configured static state measurement; for example, the STA/LTA algorithm is adopted to identify the static/moving state; the mobile device is determined to be in a horizontal placement state by: in the acceleration data corresponding to the mobile device in the horizontally placed state, the measurement of the acceleration component in the vertical direction relative to the acceleration corresponds to the configured horizontally placed state measurement, for example, the three-directional acceleration monitored by the MEMS acceleration sensor is analyzed and calculated to obtain the placed state of the mobile device and the tilt degree thereof, which is the prior art and is not described herein again.
In one embodiment of the present invention, performing an availability metric on the mobile device to obtain a metric result includes: scoring hardware information of the mobile device and each data dimension of the steady state; calculating a weighted sum as the metric result based on the score and corresponding weight value for each data dimension; the metric results are updated as the scores or weight values change. Specifically, the measurement result is evaluated by using a plurality of data dimensions, and the evaluation is preferably quantitative score evaluation, so that a data basis is provided for calculating the subsequent measurement result. When a plurality of data dimensions exist, the importance and the influence of each data dimension are different, so that different weights are given to each data dimension to embody the influence of each data dimension on the measurement result. Calculating an overall score of the mobile device usability assessment, wherein the overall score is weighted and averagedX1*P1/(P1+P2+P3+……+Pn)+X2*P2/(P1+P2+P3+……Pn)+……Xn*Pn/(P1+P2+P3+……+Pn). Wherein XnFor scoring of the nth data dimension, PnAnd the weight corresponding to the nth data dimension.
To facilitate statistics and define a mobile device as a required specific state, the mobile device is marked with a steady state identification when the mobile device maintains a duration metric having the static state and the horizontally disposed state, consistent with a configured steady state time metric. To better identify that the mobile device is in a particular steady state and to facilitate statistics, the present embodiment defines a steady state identification.
In the foregoing manner of calculating the metric result, the selected data dimension in this embodiment may include: data processing capabilities related to a model of the mobile device and a model of a sensor of the mobile device; the better the model performance, the higher the score. A sensor detection performance related to a self-noise level and a sampling rate performance of a shock related sensor of the mobile device; the lower the noise level, the higher the score, the higher the sampling rate performance, and the higher the score, which can be evaluated separately in a real scenario. The equipment aging degree is related to the total use duration or the charging and discharging times of the mobile equipment; the longer the total usage time, the lower the score. A steady-state time fraction, which is a time fraction of the mobile device having a steady-state flag within the statistical period; the higher the specific time, the higher the score. And the steady state change frequency is the change times of the mobile equipment with the steady state identification in the statistic period. The higher the frequency of steady state changes, the lower the score.
The effects of certain vibrations, particularly those induced by earthquakes, on the various floors of a high-rise building vary. Thus, in some usage scenarios, the data dimension also includes a relative height, which is the ground height of the mobile device relative to the location. Which is obtained by subtracting the altitude at which the mobile device is located from the base ground altitude. The height of the foundation ground is obtained by inquiring the service end in combination with the topographic data.
In the data dimensions listed in the above embodiments, some data dimensions do not change much or even change in a period of time, such as data processing performance, sensor detection performance, and the like, and the device aging degree does not change for a short period of time. While some data dimensions are changed in real time, such as steady-state time ratio, steady-state change frequency and relative altitude, etc. The scores of these frequently changing data dimensions need to be updated in a timely manner. Therefore, the data dimensions can be divided into two types, namely non-time-interval evaluation classification and time-interval evaluation classification, wherein the data processing performance, the sensor detection performance and the equipment aging degree are almost unchanged within a certain time, so that time-interval evaluation is not needed; the steady state time ratio, the steady state change frequency and the relative height may change all the time, and time-interval scoring is needed to reflect the real-time state of the mobile device. It is therefore desirable to set the steady-state time fraction, steady-state change frequency and relative altitude scores in the data dimension to be updated at the end of the preset statistical period.
In one embodiment provided by the present invention, the method further comprises: determining that the mobile equipment has a reporting history of the collected data; correcting the measurement result corresponding to the mobile equipment based on the accuracy score of the reported historical record relative to the final confirmation data corresponding to the reported historical record; and taking the corrected measurement result as the measurement result of the mobile equipment. And scoring according to deviation values of the monitoring data and final confirmation data (also called formal data) which are reported by the mobile equipment in history. Specifically, if the mobile device does not have a reporting history of the collected data, the item does not participate in scoring. If there is a reporting history, then the scoring can be based on: and (3) calculating the average value of the absolute values of the deviation percentages of the latest 3 times of uploaded data according to the deviation percentages of the seismic monitoring data uploaded each time and the finally confirmed seismic data: if the average value is more than 50%, the score is-10; if the weight is 30-50%, the rating is 5; if the weight is 20-30%, the rating is 0; if the weight is 10-20%, 5 points are scored; if less than 10%, the rating is 10. The scoring of this data dimension takes into account the metric result based on the corresponding weight.
In one embodiment of the present invention, the determining, based on the measurement result, a data uploading authority of data collected by a sensor of the mobile device includes: determining that a metric result of the mobile device is above a configured metric result threshold; and determining whether the mobile equipment has a data uploading authority identification, and if so, the mobile equipment has the data uploading authority. In this embodiment, mobile devices with lower metric results need to be excluded, but when the number of mobile devices above the configured metric result threshold is too large, a selection needs to be made among them to avoid transmission congestion and processing overload. In particular, in some application scenarios requiring real-time data transmission and processing, such as seismic sensing scenarios, the timeliness of transmission and processing is very important.
Fig. 2 is a schematic diagram illustrating a step of determining that a mobile device has a data upload right identifier according to an embodiment of the present invention, as shown in fig. 2. In this embodiment, determining whether the mobile device has the data upload right identifier includes: assigning a selected probability corresponding to a metric result based on the metric result of the mobile device; selecting candidate mobile devices from the grid based on the selected probability, and randomly determining the mobile devices corresponding to the number of the data uploading right identifications from the candidate mobile devices, wherein the determined mobile devices have the data uploading right identifications. The method comprises the following specific steps:
the probability of being selected is different for mobile devices of different metrics in the grid: for example, the selection probability below 5 is 0, the selection probability of the mobile devices from 5 to 7 is 0.3, the selection probability of the mobile devices from 7 to 9 is 0.5, and the selection probability above 9 is 0.7, and the candidate mobile devices are randomly screened out; in order to keep the total number of mobile devices in each grid authorized to upload at a certain number, a second decimation is required. The number of the extractions needs to meet the requirement of the server for earthquake analysis, and data waste is not caused, for example, 500-1000 data are extracted. Therefore, 500 mobile devices are randomly selected from the alternative mobile devices as final authorized uploading devices, and the data uploading authority is embodied by having the data uploading authorized identification.
Fig. 3 is a schematic diagram illustrating a step of determining that a mobile device has a data upload right identifier according to another embodiment of the present invention, as shown in fig. 3. In this embodiment, determining whether the mobile device has the data upload right identifier includes: determining a mobile device with a metric result in the grid higher than the configured metric result threshold as an alternative mobile device; determining the selected probability of the alternative mobile devices based on the number of the alternative mobile devices in the grid, the number of the data uploading weight identifications to be distributed and a measurement result; the candidate mobile device is determined whether to have the data upload right identification based on the selected probability. Specifically, the average selection probability may be obtained by dividing the number of mobile devices required to be selected in each grid by the number of available mobile devices (i.e., alternative mobile devices) in the current grid in the current time period. For example, if the number of the mobile devices to be selected is 500 and the number of the candidate mobile devices is 1000, the average selection probability is 50%. And then dynamically adjusting the selection probability according to the measurement result, wherein the selection probability of the mobile equipment with higher measurement result is higher than the average selection probability. And issuing the selected probability corresponding to the adjusted different measurement results to corresponding mobile equipment, judging whether to upload or not by the mobile equipment according to the selected probability, and informing the server.
In one embodiment of the present invention, the grid is one of a plurality of grids into which a geographical range of the preset monitoring area is divided. The grid mobile equipment which divides the early warning area evenly uploads the self positioning to the server at regular time, and the server updates the equipment distribution condition in each grid in time. For example, a certain seismic plateau is divided into rectangular or cellular grids of 10km x 10km, and mobile devices with turn-on monitoring functions within each grid upload their own location to the server every 10 minutes.
In an embodiment provided by the present invention, the selected probability is updated under the following preset conditions, where the preset conditions include:
(1) a change in a number of mobile devices within the grid exceeding a configured number change threshold; if the mobile equipment quantity change in a certain grid exceeds a quantity change threshold value, for example 20%, the server immediately updates the uploading strategy of the corresponding grid and reselects the mobile equipment which is authorized to be uploaded according to the strategy;
(2) the number of the data uploading right identifiers to be distributed in the grid is configured and updated; in consideration of further optimization of an uploading strategy, grids corresponding to areas needing important attention, such as earthquake fracture zones and the like, allow more uploading devices.
(3) And reaching the updating period of the preset selected probability. The update period here may be 1 hour, and is consistent with the aforementioned statistical period. By adopting the scheme of periodic updating, the selected mobile equipment can be kept in a required state at any time. By the embodiment, the selection probability of the mobile equipment in the grid can be dynamically and timely updated.
Fig. 4 is a block diagram of a data acquisition apparatus based on a mobile device according to an embodiment of the present invention, as shown in fig. 4. In this embodiment, a data acquisition apparatus based on a mobile device is provided, the apparatus including: the data acquisition module is used for acquiring hardware information and a stable state of the mobile equipment; a metric calculation module, configured to perform usability metric on the mobile device based on the hardware information and the stable state to obtain a metric result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device; and the permission determining module is used for determining the data uploading permission of the data collected by the mobile equipment based on the measurement result.
For specific limitations of the mobile device-based data acquisition apparatus, reference may be made to the above limitations of the mobile device-based data acquisition method, which are not described herein again. The various modules in the above-described apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, the present invention provides a data acquisition device based on a mobile device, where the device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the aforementioned data acquisition method based on a mobile device when executing the computer program.
The data collection device herein may be a computing device such as a mobile device and/or a cloud server. When the terminal equipment is mobile equipment, the data acquisition method based on the above operates at the mobile equipment end, acquires hardware information and a stable state of the terminal equipment, and automatically determines whether the terminal equipment has data uploading authority, and the accuracy score of the reporting history record which the terminal equipment does not have, the number of the standby mobile equipment in the grid and the number of the data uploading authority identification are acquired from the outside in a wireless mode. In another case, when the terminal device is a cloud server, the hardware information and the stable state of the mobile device are collected to the cloud server, and the cloud server executes the data collection method based on the mobile device and issues the selected probability to the mobile device, or even directly issues the data uploading right identifier. In addition, the data acquisition method based on the mobile device can be implemented by the mobile device or the cloud server in a matching manner, and the steps of the method are executed in the mobile device or the cloud server after being decomposed.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may be an internal storage unit of the data acquisition device, such as a hard disk or a memory of the data acquisition device. The memory may also be an external storage device of the data acquisition device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the data acquisition device. Further, the memory may also include both an internal storage unit of the data acquisition device and an external storage device. The memory is used for storing the computer program and other programs and data required by the data acquisition device. The memory may also be used to temporarily store data that has been output or is to be output.
In an embodiment provided by the invention, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements the aforementioned method.
In one embodiment of the present invention, a computer-readable storage medium is further provided, which stores computer instructions, and when the computer instructions are executed on a computer, the computer is caused to execute the foregoing method.
While the invention has been described in detail with reference to the drawings, the invention is not limited to the details of the embodiments, and various simple modifications can be made within the technical spirit of the embodiments of the invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention will not be described separately for the various possible combinations.
Those skilled in the art will appreciate that all or part of the steps in the method according to the above embodiments may be implemented by a program, which is stored in a storage medium and includes instructions for causing a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as the disclosure of the present invention as long as it does not depart from the idea of the embodiments of the present invention.
Claims (19)
1. A data acquisition method based on a mobile device, the method comprising:
based on hardware information and a stable state of the mobile equipment, carrying out availability measurement on the mobile equipment to obtain a measurement result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device;
and determining the data uploading authority of the data collected by the mobile equipment based on the measurement result.
2. The method of claim 1, wherein the hardware information comprises:
the model of the mobile device, the usage information, the model of the shock and location related sensor, and the detection performance of the shock related sensor.
3. The method of claim 1, wherein the steady state comprises:
a frequency with which the mobile device enters or exits a stationary state and a horizontally disposed state, and a duration for which the mobile device remains in the stationary state and the horizontally disposed state.
4. The method of claim 3,
the mobile device is determined to be in a stationary state by: in the acceleration data corresponding to the mobile equipment in the static state, the measurement in the short time window and the measurement in the long time window accord with the configured static state measurement;
the mobile device is determined to be in a horizontal placement state by: in the acceleration data corresponding to the mobile device in the horizontally placed state, the measure of the acceleration component with respect to the vertical direction conforms to the configured horizontally placed state measure.
5. The method of claim 1, wherein performing an availability metric for the mobile device, resulting in a metric result, comprises:
scoring hardware information of the mobile device and each data dimension of the steady state;
calculating a weighted sum as the metric result based on the score and corresponding weight value for each data dimension;
the metric results are updated as the scores or weight values change.
6. The method of claim 5, wherein the mobile device is tagged with a steady state identification when the mobile device remains having a duration metric of the stationary state and the horizontally disposed state that conforms to a configured steady state time metric.
7. The method of claim 6, wherein the data dimension comprises:
data processing capabilities related to a model of the mobile device and a model of a sensor of the mobile device;
a sensor detection performance related to a self-noise level and a sampling rate performance of a shock related sensor of the mobile device;
the equipment aging degree is related to the total use duration or the charging and discharging times of the mobile equipment;
a steady-state time ratio, which is a time ratio of the mobile device having a steady-state identifier in a preset statistical period; and
and the steady state change frequency is the change times of the mobile equipment with the steady state identification in the statistic period.
8. The method of claim 7, wherein the data dimension further comprises:
and the relative height is the ground height of the mobile equipment relative to the position.
9. The method of claim 8, wherein the scores for steady-state time fraction, steady-state change frequency, and relative height in the data dimension are updated at the end of the statistical period.
10. The method of claim 9, further comprising:
determining that the mobile equipment has a reporting history of the collected data;
correcting the measurement result corresponding to the mobile equipment based on the accuracy score of the reported historical record relative to the final confirmation data corresponding to the reported historical record;
and taking the corrected measurement result as the measurement result of the mobile equipment.
11. The method of claim 10, wherein the determining data upload permission for data collected by a sensor of the mobile device based on the metric result comprises:
determining that a metric result of the mobile device is above a configured metric result threshold;
and determining whether the mobile equipment has a data uploading authority identification, and if so, the mobile equipment has the data uploading authority.
12. The method of claim 10, wherein determining whether the mobile device has a data upload right identifier comprises:
assigning a selected probability corresponding to a metric result based on the metric result of the mobile device;
selecting an alternative mobile device from the grid based on the selected probability;
and randomly determining mobile equipment corresponding to the number of the data uploading right identifications from the alternative mobile equipment, wherein the determined mobile equipment has the data uploading right identifications.
13. The method of claim 10, wherein determining whether the mobile device has a data upload right identifier comprises:
determining a mobile device with a metric result in the grid higher than the configured metric result threshold as an alternative mobile device;
determining the selected probability of the alternative mobile devices based on the number of the alternative mobile devices in the grid, the number of the data uploading weight identifications to be distributed and a measurement result;
the candidate mobile device is determined whether to have the data upload right identification based on the selected probability.
14. The method according to claim 12 or 13, wherein the grid is one of a plurality of grids into which the geographical range of the preset monitoring area is divided.
15. The method of claim 14, wherein the selected probabilities are updated under preset conditions comprising:
a change in a number of mobile devices within the grid exceeding a configured number change threshold;
the number of the data uploading right identifiers to be distributed in the grid is configured and updated;
and reaching the updating period of the preset selected probability.
16. A data collection apparatus based on a mobile device, the apparatus comprising:
the data acquisition module is used for acquiring hardware information and a stable state of the mobile equipment;
a metric calculation module, configured to perform usability metric on the mobile device based on the hardware information and the stable state to obtain a metric result; wherein the hardware information is related to data acquisition capabilities of the mobile device; the stable state is related to a motion state and a placement state of the mobile device; and
and the permission determining module is used for determining the data uploading permission of the data collected by the mobile equipment based on the measurement result.
17. A mobile device based data acquisition device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor when executing the computer program realizes the steps of the mobile device based data acquisition method of any of claims 1 to 15.
18. A computer program product comprising a computer program which, when executed by a processor, implements the method of any one of claims 1 to 15.
19. A computer readable storage medium storing computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 15.
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