CN114828217B - Site personnel positioning and alarming method based on base station positioning technology - Google Patents
Site personnel positioning and alarming method based on base station positioning technology Download PDFInfo
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Abstract
The invention belongs to the technical field of base station positioning, and discloses a site personnel positioning alarm method based on a base station positioning technology, which specifically comprises the following steps of S1: acquiring the personnel number, longitude, latitude, unix timestamp T and instantaneous speed value of a construction worker at the time T; s2: transmitting the data acquired at the moment to a background server, and extracting a plurality of groups of unix time stamps and historical data of speed data of the personnel by the background server according to the personnel number; s3: generating a prediction model by using polynomial fitting according to historical data, predicting the running speed at the current moment by using the prediction model, and correcting the actually detected coordinate position according to the proportion between the predicted speed and the actual speed; s4: and judging whether the point position exceeds the electronic fence or not according to the predicted longitude and latitude, and giving an alarm if the point position exceeds the electronic fence. The positioning technology disclosed by the invention reduces the high false alarm rate caused by poor positioning precision of the base station.
Description
Technical Field
The invention belongs to the technical field of base station positioning, and particularly relates to a site personnel positioning alarm method based on a base station positioning technology.
Background
The positioning technology mainly includes base station positioning, GPS positioning, UWB positioning, and the most common technology at present is base station positioning. According to different communication technologies, each positioning technology has different positioning accuracy, for example, the positioning accuracy of a 4G base station is about 10 meters, and the positioning accuracy of a 5G base station is about 5 meters. Compared with other positioning technologies, the accuracy of base station positioning is poor. At present, in order to facilitate centralized management, building workers are positioned in a construction process by marking electronic fences on a construction site on a map, using mobile phone equipment to position base stations of the building workers (mobile phones of most building workers do not have GPS modules), and alarming workers outside the range of the electronic fences, but due to the fact that the positioning accuracy of the base stations is not high, many false reports and false reports are caused.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a construction site personnel positioning alarm method based on a base station positioning technology, which predicts the longitude and latitude of a real-time point location through historical data and an operation speed, and detects whether the longitude and latitude data exceeds the range of an electronic fence or not by using the predicted longitude and latitude data, thereby reducing the problems of misinformation and failure in reporting.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for site personnel positioning and alarming based on base station positioning technology comprises the following steps,
s1: acquiring the personnel number ID and the longitude LONG of the construction worker at the current moment T LAT, latitude T Unix timestamp, instantaneous speed S T ；
S2: s2: the personnel number ID and longitude LONG of the construction worker at the moment T LAT, latitude T Unix timestamp, instantaneous speed S T Transmitting to a background server, and extracting historical data of a plurality of groups of unix time stamps and speed data of the construction worker according to the personnel number ID of the construction worker by the background server, such as [ (T) T-n ,S T-n ),(T T-n-1 ,S T-n-1 ),……,(T T-2 ,S T-2 ),(T T-1 ,S T-1 )]The time interval between two adjacent groups of data is set according to the actual condition;
s3: generating a prediction model by using polynomial fitting according to the historical data, and predicting the prediction-S of the running speed at the current moment by using the prediction model T Correcting the coordinate position actually detected, i.e. longitude and latitude Predict-LONG, according to the ratio between the predicted speed and the actual speed T ，Predict-LAT T ；
S4: judging the corrected longitude and latitude Predict-LONG T ，Predict-LAT T If the longitude and latitude is beyond the electronic fence, if the longitude and latitude after correction is predicted-LONG T ，Predict-LAT T And if the alarm exceeds the electronic fence, the alarm is given.
Further, the step S2 also comprises the steps of setting a movement speed range [0-20] km/h of a construction worker; cleaning historical data of a plurality of groups of unix time stamps and speed data of the construction workers extracted by the background server according to the personnel number ID, wherein the selected historical data of the plurality of groups of unix time stamps and speed data is 100 groups of data which are selected from the current moment, and less than 100 groups of data are calculated according to actual data quantity; selecting a group of data with the unix time stamps farthest from the current time in the historical data of a plurality of groups of unix time stamps and speed data as data of a time zero point; the time of each group of data in the historical data of the plurality of groups of the unix time stamps and the speed data is the difference value of the unix time stamp in each group of data minus the unix time stamp in the data of the time zero point, and the unit is converted into the second.
Further, the specific steps of generating the prediction model in step S3 are:
for a given data set (T) i ,S i )，i＝1,2,……,n，n<=100 to solve a polynomial of degree 5,
by fitting this polynomial by the least square method, (a) is calculated 0 ，a 1 ，a 2 ，a 3 ，a 4 ，a 5 )。
Further, the operation speed at the present time predicted by using the prediction model is predicted as previous-S in step S3 T And the instantaneous speed S T The method comprises the following steps of (1) correcting the actually detected coordinate position according to the ratio of the coordinate position to the coordinate position, and specifically: s31: calculating the point location at time T (LONG) by using Haverine formula T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) Is greater than the distance d of (a),
wherein R is the radius of the earth, the average value is 6371km,
respectively representing the point of time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) And Δ λ represents a point at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) A difference of (d);
s32: according to the predicted current running speed Presect-S T Correcting the location of the point at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) The distance of (d) is, specifically,
if Presect-S T >＝S T
Predict-d＝d*(1+Predict-S T /S T )
If Presect-S T <S T
Predict-d＝d*(1-Predict-S T /S T )；
Wherein, the point location at time T (LONG) T ，LAT T ) Indicating the location of a construction worker at time T; point of time T-1 (LONG) T-1 ，LAT T-1 ) Indicating the location of a construction worker at time T-1;
s33: according to (LONG) T 、LAT T ) And (LONG) T-1 、LAT T-1 ) Determining a point location at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) The azimuth angle a therebetween, specifically,
a＝arcsin((LONG T -LONG T-1 )*ARC*cos(LAT T-1 )*2π/360/d)
wherein ARC =6371.393 x 1000 (meters);
s34: determining corrected longitude and latitude coordinate Predict-LONG T ，Predict-LAT T The method specifically comprises the following steps:
Predict-LONG T ＝LONG T-1 +Predict-d*sin(a)/(ARC*cos(LAT T-1 )*2π/360)
Predict-LAT T ＝LAT T-1 +Predict-d*cos(a)/(ARC*2π/360)
wherein ARC =6371.393 x 1000 (meters).
The invention has the beneficial effects that: according to the invention, through a base station positioning technology, the time interval of data acquisition is set, an operation speed prediction model is established according to the acquired historical data, the speed at the current moment is predicted, the coordinate position actually detected is corrected according to the ratio between the predicted speed and the actual speed, and the high false alarm rate caused by poor base station positioning accuracy is reduced.
Drawings
FIG. 1 is an overall flow diagram of the process of the present invention;
FIG. 2 is a logic diagram of a base station location data prediction algorithm in accordance with the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and the detailed description below:
a method for site personnel positioning and alarming based on base station positioning technology comprises the following steps,
s1: acquiring the personnel number ID and the longitude LONG of the construction worker at the current moment T LAT, latitude T Unix timestamp, instantaneous speed S T (ii) a unix timestamp is the number of seconds elapsed since 1/1970, i.e., midnight for UTC/GMT;
s2: the personnel number ID and longitude LONG of the construction worker at the moment T LAT, latitude T Unix timestamp, instantaneous speed S T Transmitting to a background server, and extracting a plurality of groups of historical data of unix time stamps and speed data of the construction worker by the background server according to the personnel number ID, such as [ (T) T-n ,S T-n ),(T T-n-1 ,S T-n-1 ),……,(T T-2 ,S T-2 ),(T T-1 ,S T-1 )]The time interval between two adjacent groups of data is set according to the actual condition;
s3: generating a prediction model from the historical data using polynomial fittingAnd predicting the current-time operating speed Predict-S using the prediction model T Based on the current-time operating speed predicted by using the prediction model T And the instantaneous speed S T The actual detected coordinate position, i.e. longitude and latitude Predict-LONG, is corrected T ，Predict-LAT T ；
S4: judging the corrected longitude and latitude Predict-LONG T ，Predict-LAT T If the longitude and latitude exceed the electronic fence, if the longitude and latitude are corrected, predict-LONG T ，Predict-LAT T And if the electronic fence is exceeded, an alarm is given.
Step S2 also comprises setting a movement speed range [0-20] km/h of the construction worker; cleaning historical data of a plurality of groups of unix time stamps and speed data of the construction workers extracted by the background server according to the personnel number ID, wherein the selected historical data of the plurality of groups of unix time stamps and speed data is 100 groups of data which are selected from the current moment, and less than 100 groups of data are calculated according to actual data quantity; selecting a group of data with the unix timestamp farthest from the current moment in the historical data of a plurality of groups of unix timestamps and speed data as data of a time zero point; the time of each group of data in the historical data of the plurality of groups of the unix time stamps and the speed data is the difference value of the unix time stamp in each group of data minus the unix time stamp in the data of the time zero point, and the unit is converted into the second.
The specific steps of generating the prediction model in step S3 are:
for a given data set (T) i ,S i )，i＝1,2,……,n，n<=100 solving for 5 th degree polynomial, S i ＝a 0 T i 5 +a 1 T i 4 +a 2 T i 3 +a 3 T i 2 +a 4 T i 1 +a 5
By fitting this polynomial by the least square method, (a) is calculated 0 ，a 1 ，a 2 ，a 3 ，a 4 ，a 5 )。
Operation at the present time predicted by using the prediction model in step S3Velocity Predict-S T And the instantaneous speed S T The method comprises the following steps of (1) correcting the actually detected coordinate position according to the ratio of the coordinate position to the coordinate position, and specifically:
s31: calculating the point location at time T (LONG) by using Haverine formula T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) Is greater than the distance d of (a),
wherein R is the radius of the earth, the average value is 6371km,
respectively representing the point of time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) And Δ λ represents a point at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) Difference of (2)
S32: according to the predicted current running speed Presect-S T Correcting latitude and Longitude (LONG) at time T T ，LAT T ) And latitude and Longitude (LONG) at time T-1 T-1 ，LAT T-1 ) The distance of (d) is, specifically,
if Presect-S T >＝S T
Predict-d＝d*(1+Predict-S T /S T )
If Presect-S T <S T
Predict-d＝d*(1-Predict-S T /S T )；
S33: according to (LONG) T 、LAT T ) And (LONG) T-1 、LAT T-1 ) Determining a point location at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) The azimuth angle a therebetween, specifically,
a＝arcsin((LONG T -LONG T-1 )*ARC*cos(LAT T-1 )*2π/360/d)
wherein ARC =6371.393 x 1000 (meters);
s34: determining corrected longitude and latitude coordinate Predict-LONG T ，Predict-LAT T The method specifically comprises the following steps:
Predict-LONG T ＝LONG T-1 +Predict-d*sin(a)/(ARC*cos(LAT T-1 )*2π/360)
Predict-LAT T ＝LAT T-1 +Predict-d*cos(a)/(ARC*2π/360)
wherein ARC =6371.393 x 1000 (meters).
Example one
As shown in figure 1 and as shown in figure 2,
the first step is as follows: setting the effective range of the running speed data of the personnel to be [0,20] km/h, and defining four points of the electronic fence:
point 1 (36.658022588860135,117.06813454627991),
point 2 (36.65805701611133,117.06478714942932),
point 3 (36.65482078720795,117.06473350524902),
point 4 (36.65485521589088,117.06822037696838;
and a second step of collecting data of the construction worker at time T using a base station location technology, and assigning the collected data to a personnel number ID =5301, a longitude LONG =36.6581430841719,
latitude LAT =117.06724405288696, unix timestamp T =1654494418481, and instantaneous speed S =8km/h to the backend server;
fourthly, after the background server receives the data, historical data are inquired according to the personnel number ID, the latest 100 pieces of valid data are taken, the data are cleaned according to the valid range of the electronic fence in the first step, and if the number of the data is less than 100, the actual number of the data is used as the standard; the historical data acquisition time interval is 1 second, and it is assumed that the data acquired each time are successfully received and stored by the background server;
taking a point, farthest from a unix timestamp at the time T, of the unix timestamp in the historical data as a time zero point, subtracting a difference value obtained by the unix timestamp at the time zero point from the unix timestamp at the time T, and converting a unit of the difference value into a second to be used as a time value at the time T; for example: the unix time stamp of the zero point data is (1654494318763,4.6), the data acquired at the time T in the second step is modified to be the personnel number ID =5301, the longitude LONG =36.6581430841719, the latitude LAT =117.06724405288696, T =100, and S =8km/h;
fourthly, according to the 100 pieces of extracted effective data, a prediction model is built for the speed and time relation, the speed of T =100 moment is predicted to be 4.5km/h according to the prediction model, the actually measured speed is S =8km/h, the longitude and latitude (LONG, LAT) uploaded by the base station positioning technology is adjusted according to the ratio of the predicted speed of 4.5km/h to the actual speed of 8km/h, the adjusted longitude and latitude is (36.65779881135225,117.06704020500183), and the adjusted longitude and latitude is inside the electronic fence, so that an alarm does not need to be sent.
The method for acquiring data of construction workers by using the base station positioning technology can be realized by using the existing base station positioning software, and belongs to the prior art. According to the invention, through a base station positioning technology, the time interval of data acquisition is set, an operation speed prediction model is established according to the acquired historical data, the speed at the current moment is predicted, the coordinate position actually detected is corrected according to the ratio between the predicted speed and the actual speed, and the high false alarm rate caused by poor base station positioning accuracy is reduced.
Various other modifications and changes may be made by those skilled in the art based on the above-described technical solutions and concepts, and all such modifications and changes should fall within the scope of the claims of the present invention.
Claims (1)
1. A method for site personnel positioning and alarming based on base station positioning technology is characterized in that the method comprises the following steps,
s1: acquiring the personnel number ID and the longitude LONG of the construction worker at the current moment T LAT, latitude T Unix timestamp, instantaneous speed S T ；
S2: the personnel number ID and longitude LONG of the construction worker at the moment T LAT, latitude T Unix timestamp, instantaneous speed S T Transmitting the data to a background server, and extracting a plurality of groups of unix time stamps and historical data of speed data of the construction worker by the background server according to the personnel number ID of the construction worker;
the step S2 also comprises the steps of setting a movement speed range [0-20] km/h of a construction worker; cleaning historical data of a plurality of groups of unix time stamps and speed data of the construction workers extracted by the background server according to the personnel number ID, wherein the selected historical data of the plurality of groups of unix time stamps and speed data is 100 groups of data which are selected from the current moment, and less than 100 groups of data are calculated according to actual data quantity; selecting a group of data with the unix time stamps farthest from the current time in the historical data of a plurality of groups of unix time stamps and speed data as data of a time zero point; the time of each group of data in the historical data of the plurality of groups of unix time stamps and the speed data is the difference value of the unix time stamp in each group of data minus the unix time stamp in the data of the time zero point, and the unit is converted into the second;
s3: generating a prediction model by using polynomial fitting according to the historical data, and predicting the prediction-S of the running speed at the current moment by using the prediction model T Based on the current-time operating speed predicted by using the prediction model T And the instantaneous speed S T The coordinate position actually detected is corrected according to the ratio of the longitude and the latitude, and the corrected coordinate position is marked as longitude and latitude Predict-LONG T ，Predict-LAT T ；
The specific steps of generating the prediction model in step S3 are:
for a given data set (T) i ,S i )，i＝1,2,……,n，n<=100 to solve a polynomial of degree 5,
S i ＝a 0 T i 5 +a 1 T i 4 +a 2 T i 3 +a 3 T i 2 +a 4 T i 1 +a 5
fitting by least squaresCombining the polynomials to calculate (a) 0 ,a 1 ,a 2 ,a 3 ,a 4 ,a 5 )；
S4: judging the corrected longitude and latitude Predict-LONG T ，Predict-LAT T If the longitude and latitude exceed the electronic fence, if the longitude and latitude are corrected, predict-LONG T ，Predict-LAT T If the alarm exceeds the electronic fence, the alarm is given;
the operation speed Predict-S at the present time predicted by using the prediction model in the step S3 T And the instantaneous speed S T The method comprises the following steps of (1) correcting the actually detected coordinate position according to the ratio of the coordinate position to the coordinate position, and specifically:
s31: calculating the point location at time T (LONG) by using Haverine formula T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) Is greater than the distance d of (a),
wherein R is the radius of the earth, the average value is 6371km,
s32: according to the predicted current running speed Presect-S T Correcting the location of the point at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) The distance of (d) is, specifically,
if Presect-S T >＝S T
Predict-d＝d*(1+Predict-S T /S T )
If Presect-S T <S T
Predict-d＝d*(1-Predict-S T /S T )；
S33: according to (LONG) T 、LAT T ) And (LONG) T-1 、LAT T-1 ) Determining a point location at time T (LONG) T ，LAT T ) And point of time T-1 (LONG) T-1 ，LAT T-1 ) The azimuth angle a therebetween, specifically,
a＝arcsin((LONG T -LONG T-1 )*ARC*cos(LAT T-1 )*2π/360/d)
wherein ARC =6371.393 x 1000 (meters);
s34: determining corrected longitude and latitude Predict-LONG T ，Predict-LAT T The method specifically comprises the following steps:
Predict-LONG T ＝LONG T-1 +Predict-d*sin(a)/(ARC*cos(LAT T-1 )*2π/360)
Predict-LAT T ＝LAT T-1 +Predict-d*cos(a)/(ARC*2π/360)
wherein ARC =6371.393 x 1000 (meters).
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| CN109564726A (en) * | 2016-10-19 | 2019-04-02 | 华为技术有限公司 | A kind of localization method and mobile device |
| CN108391236A (en) * | 2018-04-04 | 2018-08-10 | 浙江中诚工程管理科技有限公司 | Positioning system in a kind of construction site construction personnel based on UWB |
| EP3971525A1 (en) * | 2019-05-15 | 2022-03-23 | Nissan Motor Co., Ltd. | Self-positioning correction method and self-positioning correction device |
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