Generation method, monitoring method, device, electronic equipment and readable medium
阅读说明：本技术 生成方法、监测方法、装置、电子设备以及可读介质 (Generation method, monitoring method, device, electronic equipment and readable medium ) 是由 陶震 王�华 成进 罗嵩 董帅甫 刘禹轩 于 2020-06-28 设计创作，主要内容包括：本申请实施例提供了一种生成方法、监测方法、装置、电子设备以及计算机存储介质,所述生成方法包括：通过获取移动对象的定位点,定位点可以包括第一定位点以及与第一定位点相邻的至少一个第二定位点,接着确定两个定位点之间的位置关系,并根据该位置关系,对第一定位点进行异常检测,生成第一定位点的检测结果,然后根据移动对象在移动过程中,所采集的各个定位点的检测结果,生成移动对象的移动轨迹,从而通过确定相邻定位点之间的位置关系,可以有效地识别出采样定位点的状态,以便在剔除影响移动对象的移动轨迹的异常点后,可以得到可信的定位点,进而使得移动轨迹更符合实际的情况,保证了定位数据的准确性,提高了定位精度。(The embodiment of the application provides a generation method, a monitoring device, electronic equipment and a computer storage medium, wherein the generation method comprises the following steps: the positioning points of the moving object are obtained, wherein the positioning points can comprise a first positioning point and at least one second positioning point adjacent to the first positioning point, the position relationship between the two positioning points is determined, the first positioning point is subjected to abnormal detection according to the position relationship to generate a detection result of the first positioning point, then the moving track of the moving object is generated according to the detection result of each positioning point acquired in the moving process of the moving object, and therefore, the state of the sampling positioning point can be effectively identified by determining the position relationship between the adjacent positioning points, so that after the abnormal point influencing the moving track of the moving object is eliminated, a credible positioning point can be obtained, the moving track positioning data can better meet the actual condition, the accuracy of the positioning data is ensured, and the positioning precision is improved.)
1. A method for generating a movement trajectory is characterized by comprising the following steps:
acquiring positioning points of a moving object, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
determining the position relation between the first positioning point and the second positioning point;
according to the position relation, carrying out abnormity detection on the first fixed position point to generate a detection result of the first fixed position point;
and generating a moving track of the moving object according to the detection results of the positioning points.
2. The method according to claim 1, wherein the positional relationship at least includes a distance value between the first positioning point and the second positioning point, and the performing anomaly detection on the first positioning point according to the positional relationship to generate the detection result of the first positioning point includes:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
3. The method according to claim 2, wherein the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point comprises:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the mobile object to generate a detection result of the first positioning point.
4. The method according to claim 3, wherein the environment information includes a forbidden area, and the performing anomaly detection on the first positioning point by using at least one distance value and the environment information where the mobile object is located to generate the detection result of the first positioning point includes:
if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
5. The method according to claim 4, wherein the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point comprises:
and if the distance value between the first positioning point and the second positioning point is smaller than or equal to a preset distance threshold, generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point.
6. The method according to claim 5, wherein the second anchor point comprises a historical anchor point before the first anchor point, and the performing anomaly detection on the first anchor point by using at least one distance value to generate a detection result of the first anchor point further comprises:
and if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold, generating a third detection result of the first positioning point.
7. The method according to claim 6, wherein the second anchor point comprises a target anchor point after the first anchor point, and the performing anomaly detection on the first anchor point by using at least one distance value to generate a detection result of the first anchor point further comprises:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
8. The method according to claim 6, wherein the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further comprises:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
9. The method according to any one of claims 4 to 8, wherein the detection result comprises a result of adding the first fixed point to a preset sampling point set, wherein the sampling point set comprises a credible point set, a suspicious point set and an unreliable point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the generating the moving track of the moving object according to the detection results of the plurality of positioning points includes:
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
10. The method according to any one of claims 4 to 8, wherein the detection result comprises a confidence value of a positioning point, different detection results correspond to different confidence values, and the generating the movement trajectory of the moving object according to the detection results of a plurality of positioning points comprises:
using the positioning point with the credibility value being greater than or equal to the preset credibility threshold value and successfully matched as a credible positioning point;
and generating a moving track of the moving object by adopting the credible positioning point.
11. The method according to claim 10, wherein the generating of the moving trajectory of the moving object according to the detection results of the plurality of positioning points comprises:
acquiring a credibility level aiming at a preset sampling point set, wherein the sampling point set comprises a credibility point set;
adding the positioning point with the credible value meeting the credible grade to the credible point set;
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
12. A monitoring method for a logistics process is characterized by comprising the following steps:
acquiring positioning points of a moving object in a logistics area, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
determining the position relation between the first positioning point and the second positioning point;
according to the position relation, carrying out abnormity detection on the first fixed position point to generate a detection result of the first fixed position point;
and generating a moving track of the moving object according to the detection results of the positioning points.
13. An apparatus for generating a movement trajectory, comprising:
the positioning point acquisition module is used for acquiring positioning points of a mobile object, and the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
the position relation determining module is used for determining the position relation between the first positioning point and the second positioning point;
the detection result generation module is used for carrying out abnormity detection on the first fixed position point according to the position relation and generating a detection result of the first fixed position point;
and the moving track generating module is used for generating the moving track of the moving object according to the detection results of the positioning points.
14. A monitoring device for logistics processes, comprising:
the positioning point acquisition module is used for acquiring positioning points of the mobile object in the logistics area, and the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
the position relation determining module is used for determining the position relation between the first positioning point and the second positioning point;
the detection result generation module is used for carrying out abnormity detection on the first fixed position point according to the position relation and generating a detection result of the first fixed position point;
and the moving track generating module is used for generating the moving track of the moving object according to the detection results of the positioning points.
15. An electronic device, comprising:
one or more processors; and
one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the electronic device to perform the method of any of claims 1-11 or 12.
16. One or more machine readable media having instructions stored thereon that, when executed by one or more processors, cause the processors to perform the method of any of claims 1-11 or 12.
Technical Field
The application relates to the technical field of logistics transportation, in particular to a moving track generation method and a moving track generation device, and a logistics process monitoring method and a logistics process monitoring device.
Background
In the process of logistics management, the logistics management system can comprise links of transportation, storage, packaging, handling, processing, distribution and related logistics information of goods. In the transportation process, the moving track of a moving object (including a person, a carrying device, and the like) for transporting goods needs to be located. In general, the moving track of the moving object is formed by connecting the positioning sampling points. However, not every sample point is accurately and confident, and abnormal data sometimes occurs, and the occurrence of the abnormal data influences the correct presentation of the track.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present application is to provide a method for generating a moving trajectory, so as to solve the problem that the existing technology cannot identify abnormal positioning data of a moving object.
Correspondingly, the embodiment of the application also provides a device for generating the movement track, so as to ensure the realization and the application of the method.
In order to solve the above problem, an embodiment of the present application discloses a method for generating a movement trajectory, including:
acquiring positioning points of a moving object, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
determining the position relation between the first positioning point and the second positioning point;
according to the position relation, carrying out abnormity detection on the first fixed position point to generate a detection result of the first fixed position point;
and generating a moving track of the moving object according to the detection results of the positioning points.
Optionally, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the performing, according to the position relationship, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the mobile object to generate a detection result of the first positioning point.
Optionally, the environment information includes a forbidden area, and the performing anomaly detection on the first positioning point by using at least one distance value and the environment information where the moving object is located to generate a detection result of the first positioning point includes:
if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and if the distance value between the first positioning point and the second positioning point is smaller than or equal to a preset distance threshold, generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point.
Optionally, the second positioning point includes a historical positioning point before the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold, generating a third detection result of the first positioning point.
Optionally, the second positioning point includes a target positioning point after the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
Optionally, the detection result includes a result of adding the first fixed point to a preset sampling point set, where the sampling point set includes a credible point set, a suspicious point set, and an unreliable point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the generating the moving track of the moving object according to the detection results of the plurality of positioning points includes:
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
Optionally, the generating the moving trajectory of the moving object according to the detection results of the multiple positioning points includes:
using the positioning point with the credibility value being greater than or equal to the preset credibility threshold value and successfully matched as a credible positioning point;
and generating a moving track of the moving object by adopting the credible positioning point.
Optionally, the generating a moving trajectory of the moving object according to the detection results of the plurality of positioning points includes:
acquiring a credibility level aiming at a preset sampling point set, wherein the sampling point set comprises a credibility point set;
adding the positioning point with the credible value meeting the credible grade to the credible point set;
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
The embodiment of the application also discloses a method for monitoring the logistics process, which comprises the following steps:
acquiring positioning points of a moving object in a logistics area, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
determining the position relation between the first positioning point and the second positioning point;
according to the position relation, carrying out abnormity detection on the first fixed position point to generate a detection result of the first fixed position point;
and generating a moving track of the moving object according to the detection results of the positioning points.
Optionally, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the performing, according to the position relationship, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the logistics object to generate a detection result of the first positioning point.
Optionally, the environment information includes a forbidden area, and the performing anomaly detection on the first location point by using at least one distance value and the environment information where the logistics object is located to generate a detection result of the first location point includes:
if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and if the distance value between the first positioning point and the second positioning point is smaller than or equal to a preset distance threshold, generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point.
Optionally, the second positioning point includes a historical positioning point before the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold, generating a third detection result of the first positioning point.
Optionally, the second positioning point includes a target positioning point after the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
Optionally, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
Optionally, the detection result includes a result of adding the first fixed point to a preset sampling point set, where the sampling point set includes a credible point set, a suspicious point set, and an unreliable point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the generating the moving track of the moving object according to the detection results of the plurality of positioning points includes:
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
Optionally, the generating the moving trajectory of the moving object according to the detection results of the multiple positioning points includes:
using the positioning point with the credibility value being greater than or equal to the preset credibility threshold value and successfully matched as a credible positioning point;
and generating a moving track of the logistics object by adopting the credible positioning point.
Optionally, the generating a moving trajectory of the moving object according to the detection results of the plurality of positioning points includes:
acquiring a credibility level aiming at a preset sampling point set, wherein the sampling point set comprises a credibility point set;
adding the positioning point with the credible value meeting the credible grade to the credible point set;
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
The embodiment of the present application further discloses a device for generating a movement trajectory, including:
the positioning point acquisition module is used for acquiring positioning points of a mobile object, and the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
the position relation determining module is used for determining the position relation between the first positioning point and the second positioning point;
the detection result generation module is used for carrying out abnormity detection on the first fixed position point according to the position relation and generating a detection result of the first fixed position point;
and the moving track generating module is used for generating the moving track of the moving object according to the detection results of the positioning points.
Optionally, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the detection result generation module is specifically configured to:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
Optionally, the detection result generating module is specifically configured to:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the mobile object to generate a detection result of the first positioning point.
Optionally, the environment information includes a forbidden area, and the detection result generating module includes:
a first detection result generation submodule for: if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
Optionally, the detection result generating module further includes:
and the second detection result generation submodule is used for generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point if the distance value between the first positioning point and the second positioning point is less than or equal to a preset distance threshold value.
Optionally, the second positioning point includes a historical positioning point before the first positioning point, and the detection result generating module further includes:
and the third detection result generation submodule is used for generating a third detection result of the first positioning point if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold value.
Optionally, the second positioning point includes a target positioning point after the first positioning point, and the first detection result generation submodule is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
Optionally, the second detection result generation sub-module is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
Optionally, the detection result includes a result of adding the first fixed point to a preset sampling point set, where the sampling point set includes a credible point set, a suspicious point set, and an unreliable point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the movement track generation module is specifically configured to:
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
Optionally, the detection result includes a credible value of the locating point, and different detection results correspond to different credible values, and the movement trajectory generation module includes:
the credible locating point determining submodule is used for matching the locating point with the credible value being greater than or equal to the preset credible threshold value successfully as the credible locating point;
and the first movement track generation submodule is used for generating the movement track of the mobile object by adopting the credible positioning point.
Optionally, the movement trajectory generating module includes:
the credibility level acquisition sub-module is used for acquiring credibility levels aiming at a preset sampling point set, and the sampling point set comprises a credibility point set;
the positioning point adding submodule is used for adding the positioning point of which the credible value meets the credible grade to the credible point set;
and the second movement track generation submodule is used for generating the movement track of the mobile object by adopting the positioning points in the credible point set.
The embodiment of the application also discloses a monitoring devices of commodity circulation process includes:
the positioning point acquisition module is used for acquiring positioning points of the mobile object in the logistics area, and the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
the position relation determining module is used for determining the position relation between the first positioning point and the second positioning point;
the detection result generation module is used for carrying out abnormity detection on the first fixed position point according to the position relation and generating a detection result of the first fixed position point;
and the moving track generating module is used for generating the moving track of the moving object according to the detection results of the positioning points.
Optionally, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the detection result generation module is specifically configured to:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
Optionally, the detection result generating module is specifically configured to:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the logistics object to generate a detection result of the first positioning point.
Optionally, the environment information includes a forbidden area, and the detection result generating module includes:
a first detection result generation submodule for: if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
Optionally, the detection result generating module further includes:
and the second detection result generation submodule is used for generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point if the distance value between the first positioning point and the second positioning point is less than or equal to a preset distance threshold value.
Optionally, the second positioning point includes a historical positioning point before the first positioning point, and the detection result generating module further includes:
and the third detection result generation submodule is used for generating a third detection result of the first positioning point if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold value.
Optionally, the second positioning point includes a target positioning point after the first positioning point, and the first detection result generation submodule is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
Optionally, the second detection result generation sub-module is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
Optionally, the detection result includes a result of adding the first fixed point to a preset sampling point set, where the sampling point set includes a credible point set, a suspicious point set, and an unreliable point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the movement track generation module is specifically configured to:
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
Optionally, the detection result includes a credible value of the locating point, and different detection results correspond to different credible values, and the movement trajectory generation module includes:
the credible locating point determining submodule is used for matching the locating point with the credible value being greater than or equal to the preset credible threshold value successfully as the credible locating point;
and the first movement track generation submodule is used for generating the movement track of the logistics object by adopting the credible positioning point.
Optionally, the movement trajectory generating module includes:
the credibility level acquisition sub-module is used for acquiring credibility levels aiming at a preset sampling point set, and the sampling point set comprises a credibility point set;
the positioning point adding submodule is used for adding the positioning point of which the credible value meets the credible grade to the credible point set;
and the second movement track generation submodule is used for generating the movement track of the logistics object by adopting the positioning points in the credible point set.
The embodiment of the application also discloses an electronic device, which comprises:
one or more processors; and
one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the electronic device to perform the method as described above.
One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause the processors to perform the methods described above, are also disclosed.
The embodiment of the application has the following advantages:
in the embodiment of the present application, the positioning points of the moving object may be obtained, where the positioning points may include a first positioning point and at least one second positioning point adjacent to the first positioning point, and then a position relationship between the two positioning points is determined, and according to the position relationship, carrying out abnormity detection on the first positioning point to generate a detection result of the first positioning point, then generating a moving track of the moving object according to the detection result of each positioning point acquired in the moving process of the moving object, therefore, by determining the position relation between the adjacent positioning points, the state of the sampling positioning point can be effectively identified, so that after the abnormal points influencing the moving track of the moving object are removed, a credible positioning point can be obtained, and then make the movement track more accord with the actual condition, guaranteed the accuracy of location data, improved positioning accuracy.
Drawings
Fig. 1 is a flowchart illustrating a first step of a first embodiment of a method for generating a movement track according to the present application;
FIG. 2 is a flowchart illustrating steps of a second embodiment of a method for generating a movement trajectory according to the present application;
FIG. 3 is a flow chart illustrating steps of an embodiment of a method for monitoring a logistics process of the present application;
FIG. 4 is a schematic diagram of anchor points in an embodiment of the present application;
FIG. 5 is a schematic view of a scene of mobile object monitoring in an embodiment of the present application;
FIG. 6 is a schematic diagram of a set of sampling points in an embodiment of the present application;
FIG. 7 is a block diagram of an embodiment of a device for generating a movement trajectory according to the present application;
fig. 8 is a block diagram of an embodiment of a monitoring device for a logistics process according to the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
The Mobile Object Management (Mobile Object Management) covers the fields of traffic, aviation/aerospace/navigation, security monitoring, ecological environment protection, logistics, disaster prevention and control and the like, and is an important leading-edge application field of information technology in the era of the internet of things. Mainly embodied as monitoring the track of a moving object. In general, mobile objects can be classified into three categories according to behavior patterns:
1. restricted moving object: the behavior of the limited moving object is constrained by external conditions, the whole object has certain regularity, the individual moves in a relatively fixed mode, and the behavior mode of the object has relatively large constraint no matter on a macroscopic level or a microscopic level; urban traffic is a restricted moving object with typical representatives. Vehicle behavior patterns and trajectories in this area are constrained by urban road networks.
2. Semi-constrained moving object: semi-constrained moving objects have freedom to some extent under external constraints; the behavior individuals are large in non-restraint on the microscopic level; the groups under the macro level present certain regularity; aviation/navigation is a semi-confined moving object with typical representativeness. In this field the aircraft/vessel moves generally according to a course and the individual has a certain freedom during the movement.
3. Unrestricted moving object: the unrestricted moving object has smaller external constraint conditions, and the individual behavior of the unrestricted moving object has larger freedom; meanwhile, the group behavior is random; an open-space personnel monitoring room has typically representative non-restricted moving objects. In this field, individuals move freely in open space, and the movement of the population is random.
Behavior analysis and mining based on the moving track are core links of moving object track monitoring. The behavior patterns of the moving objects under specific constraint conditions can be identified and extracted through classification-clustering of the moving tracks, and the method has important application value for monitoring and management and abnormal identification of specific groups. In the process of identifying the moving track, the positioning sampling points of the moving object need to be collected, and then the plurality of positioning sampling points are connected to obtain the moving track of the moving object. In the process, abnormal data sometimes occur, and the occurrence of the abnormal data easily affects the correct presentation of the movement track.
Therefore, one of the core ideas of the embodiment of the present application is to obtain the positioning points of the moving object, determine the position relationship between the adjacent positioning points of the moving object, and perform anomaly detection on the positioning points of the moving object by combining the relationship between the positioning points and the environment, thereby eliminating the abnormal points affecting the moving track, so that the moving track of the moving object more conforms to the actual situation, the accuracy of the positioning data is ensured, and the positioning accuracy is improved.
Referring to fig. 1, a flowchart illustrating a first step of a first embodiment of a method for generating a movement trajectory according to the present application is shown, which may specifically include the following steps:
step 101, acquiring positioning points of a mobile object, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
in the embodiment of the present application, the moving object may include a person, a logistics carrying object (such as an automated guided vehicle), a vehicle, a ship, an aircraft, and the like, and since the positioning track of the moving object may be composed of a plurality of positioning points of the moving object, the positioning points of the moving object may be acquired in a preset sampling manner.
In one example, a positioning device may be disposed on the mobile object, so that the positioning system may acquire the current position (i.e., the positioning point) of the mobile object in real time through the positioning device. In addition, a metal tag, such as an active tag and a passive tag, may be set on the mobile object in a manner including, but not limited to, spraying, printing, pasting, and stamping, and by setting the metal tag, a tag reader in the positioning system may also obtain the current position of the mobile object in real time, so as to obtain a positioning point of the mobile object. Wherein the second anchor point may comprise an anchor point before the first anchor point and an anchor point after the first anchor point.
Step 102, determining the position relation between the first positioning point and the second positioning point;
in an example, the position relationship may be a distance value between two positioning points, and the distance value between two adjacent positioning points may be determined according to the sampling time of the positioning system and the moving speed of the moving object, so that after the two sampling positioning points are obtained, the distance value between the two positioning points may be calculated, so as to determine the reliability of the current positioning point according to the distance relationship between the two positioning points.
It should be noted that, regarding the position relationship between the positioning points, the position between the two positioning points, the position of the two positioning points in the environment, and the like may also be used, and the application is not limited thereto.
103, performing anomaly detection on the first fixed position point according to the position relation to generate a detection result of the first fixed position point;
after the positioning system collects the positioning points of the mobile object, the positioning points can be subjected to abnormal detection according to the position relation between two adjacent positioning points, so that the abnormal positioning points in the moving process of the mobile object can be identified, the moving track is more in line with the actual condition, the accuracy of the positioning data is ensured, and the positioning precision is improved.
In a specific implementation, the second positioning point may include a positioning point before the first positioning point and a positioning point after the first positioning point, and the first positioning point may be subjected to anomaly detection according to a position relationship between the first positioning point and the second positioning point, so as to determine a reliability of the first positioning point, so as to identify an anomalous positioning point in a moving process of the moving object, so that a moving track better conforms to an actual situation, accuracy of positioning data is ensured, and positioning accuracy is improved.
The reliability may be used to determine whether the anchor point is reliable. In one example, the confidence level may be a score value, with different score values representing different confidence levels, e.g., 0 indicating that the anchor point is not trusted, 1 indicating that the anchor point is suspicious, 2 identifying that the anchor point is trusted, etc. In another example, the credibility may be which type of set of sampling points the anchor point belongs to, and different sets of sampling points represent different credibility, for example, an anchor point in the set of trusted points is a trusted anchor point, i.e. a normal anchor point; the positioning points in the suspicious point set may be credible positioning points and also may be incredible positioning points, and further identification is needed; the anchor points in the set of untrusted points are untrusted anchor points, i.e. abnormal anchor points, etc. It is understood that, under the guidance of the idea of the embodiment of the present application, a person skilled in the art may also set the confidence level in other ways, and the present application is not limited to this.
And 104, generating a moving track of the moving object according to the detection results of the positioning points.
Through carrying out anomaly detection on each positioning point, the anomaly positioning points acquired by the positioning system in the moving process of the moving object can be effectively identified, so that effective and credible positioning points are obtained after the anomaly points influencing the moving track of the moving object are eliminated, the moving track is more in line with the actual condition, the accuracy of positioning data is ensured, and the positioning precision is improved.
In the embodiment of the application, by obtaining the positioning points of the mobile object, the positioning points may include a first positioning point and at least one second positioning point adjacent to the first positioning point, and then determining a position relationship between the two positioning points, and performing anomaly detection on the first positioning point according to the position relationship to generate a detection result of the first positioning point, and then generating a moving track of the mobile object according to the detection result of each acquired positioning point in the moving process of the mobile object, so that by determining the position relationship between the adjacent positioning points, the state of the sampling positioning point can be effectively identified, and after eliminating the abnormal points affecting the moving track of the mobile object, a credible positioning point can be obtained, so that the moving track is more in line with the actual situation, the accuracy of the positioning data is ensured, and the positioning accuracy is improved.
Referring to fig. 2, a flowchart illustrating steps of a second embodiment of the method for generating a movement trajectory according to the present application is shown, and specifically, the method may include the following steps:
step 201, acquiring positioning points of a mobile object, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
in a specific implementation, the timing acquisition of the positioning point of the moving object can be performed by setting the sampling time. For a moving object with a relatively fixed moving track and moving mode, a relatively long sampling time can be set to acquire positioning points of the moving object, for example, the positioning points are acquired once at a time, or the positioning points are acquired once every 30 minutes, and the like; for a moving object with a relatively flexible moving track and a relatively flexible moving mode, relatively short sampling time can be set, for example, the sampling time is acquired every 5 minutes or every 3 minutes, so that the positioning system can acquire positioning points of the moving object in real time according to the sampling time, obtain a plurality of positioning points of the moving object, and judge the reliability of the positioning points in real time.
Step 202, determining a distance value between the first positioning point and the second positioning point;
in specific implementation, different sampling times can be set for different moving objects, and different moving objects can correspond to different moving speeds, so that a distance value between two adjacent positioning points of the moving object can be obtained according to the sampling times and the moving speeds of the moving objects.
Step 203, performing anomaly detection on the first positioning point by using at least one distance value or at least one distance value and environment information where the moving object is located, and generating a detection result of the first positioning point;
in this embodiment of the present application, an abnormal state of the first positioning point may be detected according to a distance value between the first positioning point and a positioning point before the first positioning point. When the abnormal state of the first positioning point cannot be determined, the abnormal state of the positioning point can be determined in an auxiliary manner by combining the positioning points behind the first positioning point, the distance relation between the positioning points before and after combination is realized, the positioning data of the moving object is accurately detected, and the accuracy of the positioning data is ensured. In addition, the positioning points can be subjected to abnormal detection according to the distance values between the positioning points and the environment information where the moving object is located, so that the detection effect of the positioning points is improved by combining the environment information, and the accuracy of the positioning data is further improved.
In a specific implementation, the second locating point may include a historical locating point before the first locating point and a target locating point after the first locating point, it should be noted that, when it is not possible to identify whether the first locating point is reliable through a distance relationship between the historical locating point and the first locating point, it may be combined with a distance relationship between the first locating point and two locating points before and after the first locating point to identify whether the first locating point is abnormal, so as to generate a detection result of the first locating point, so as to identify an abnormal locating point in a moving process of a moving object according to the detection result, so that a moving track more conforms to an actual situation, accuracy of locating data is ensured, and locating accuracy is improved.
The environmental information of the mobile object may include a moving area, a forbidden area, and the like, where the moving of the mobile object in the moving area is legal, and the forbidden area is an area that the mobile object cannot reach, and if the anchor point falls into the forbidden area, the anchor point is an abnormal anchor point and needs to be removed.
In an optional embodiment of the present application, if a distance value between the first positioning point and the second positioning point is less than or equal to a preset distance threshold, and the first positioning point falls into a forbidden area, a first detection result of the first positioning point is generated; and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
In another optional embodiment of the present application, if a first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold, a third detection result of the first positioning point is generated.
The distance threshold may be a maximum predicted distance between two adjacent positioning points corresponding to the moving speed of the moving object, and different moving objects may correspond to different maximum predicted distances. By comparing the distance value between two positioning points of the moving object with the maximum prediction distance, an abnormal positioning point can be identified.
It should be noted that different detection results may represent different credibility of the anchor point, wherein the first detection result may represent that the anchor point is not credible, that is, the anchor point is an abnormal anchor point; the second detection result may indicate that the anchor point is trusted, i.e. the anchor point is a normal anchor point; the third detection result indicates that the positioning point has a certain suspicious property and needs to be further judged, and the like, which is not limited in the present application.
In a specific implementation, in order to ensure the accuracy of the detection of the abnormality of the positioning point, the reliability of the first positioning point needs to be determined by combining the distance relationship between the first positioning point and the positioning points before and after the first positioning point. If the distance value between the first positioning point and the historical positioning point is greater than the distance threshold value, it indicates that the first positioning point has certain suspicion at the moment, and the reliability of the first positioning point needs to be further determined, and the first positioning point corresponds to a third detection result. Specifically, when the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, the third detection result of the first positioning point may be changed into the first detection result, that is, the first positioning point is treated as an abnormal positioning point; when the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold value, the third detection result of the first positioning point can be changed into the second detection result, namely the first positioning point is used as a normal positioning point to be processed, so that the state of the sampling positioning point can be effectively identified by determining the position relation between adjacent positioning points, and a credible positioning point can be obtained after an abnormal point influencing the moving track of the moving object is removed.
In addition, when the distance value between the first positioning point and the second positioning point is smaller than or equal to the preset distance threshold, the first positioning point and the second positioning point correspond to a second detection result, or the first positioning point corresponds to the second detection result.
In one example, the detection result may be a result of adding the first fixed point to a preset set of sampling points, the set of sampling points including a set of trustworthy points, a set of suspect points, and a set of untrustworthy points. Wherein the first detection result is the result of adding the first fixed position point to the set of unreliable points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point with the credible point set; the third detection result is the result of adding the first fixed point to the suspicious point set.
For a positioning point of a mobile object, a plurality of different sampling point sets can be set, the sampling point sets can include a credible point set, a suspicious point set and an untrustworthy point set, and for all positioning points, whether the positioning points are credible or not, the sampling point sets can be added into the positioning point sets.
In the complete moving process of the moving object, the positioning point set is all the positioning points of the moving object acquired by the positioning system; the credible point set is a normal positioning point of the mobile object identified by the positioning system; the suspicious point set is a suspicious positioning point of the mobile object identified by the positioning system, in one case, the positioning point in the suspicious point set can be converted into a credible positioning point, and in the other case, the positioning point in the suspicious point set can be converted into an incredible positioning point; the set of untrusted points is an abnormal positioning point which is identified by the positioning system and influences the moving track of the moving object.
In a specific implementation, in order to ensure the accuracy of the detection of the abnormality of the positioning point, the reliability of the first positioning point needs to be determined by combining the distance relationship between the first positioning point and the positioning points before and after the first positioning point. If the distance value between the first positioning point and the historical positioning point is greater than the distance threshold value, it indicates that the first positioning point has certain suspicion at the moment, and the reliability of the first positioning point needs to be further determined. Specifically, when a second distance value between the first positioning point and the target positioning point is greater than a distance threshold, the first positioning point is moved from the suspicious point set to the untrusted point set; when the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold value, the first positioning point is moved into the credible point set from the suspicious point set, so that the state of the sampling positioning point can be effectively identified by determining the position relation between adjacent positioning points, and the credible positioning point can be obtained after the abnormal point influencing the moving track of the moving object is removed.
In addition, when the distance value between the first positioning point and the second positioning point is smaller than or equal to the preset distance threshold, the first positioning point and the second positioning point, or the first positioning point, are added to the set of trusted points.
For example, if the first positioning point is P (n), n represents the nth positioning point of the moving object acquired by the positioning system, the historical positioning point may be P (n-1), the target positioning point may be P (n +1), the distance value between the historical positioning point and the first positioning point may be d (n-1, n), and the distance value between the first positioning point and the target positioning point may be d (n, n + 1).
Specifically, when d (n-1, n) is less than or equal to dmax (n-1, n), P (n) may be added to the set of trust points, or both P (n) and P (n +1) may be added to the set of trust points; when d (n-1, n) is greater than dmax (n-1, n), P (n) is in an abnormal position, a certain suspicious state exists, at this time, the true speed of the moving object may be greater than the set maximum speed, or a reasonable error occurs in the test data, so that P (n) is added to the suspicious point set, the acquisition of the locating points of the moving object is continued, P (n +1) is obtained, if d (n, n +1) is less than or equal to dmax (n, n +1), the suspicious state that P (n) occurs is a reasonable error, the data of the locating points still is reliable, P (n) can be moved into the suspicious point set, if d (n, n +1) is greater than dmax (n, n +1), the moving of the moving object can be represented as an abnormal state, and the moving speed of the moving object can exceed the maximum moving speed stored in the system, or a moving object has a large displacement deviation, or a positioning system acquires wrong positioning data due to sampling errors, and the like, and if the positioning point is recorded in a moving track, the accuracy of the moving track is easily affected, so that p (n) needs to be moved from a suspicious point set to an untrusted point set to remove the positioning point.
In addition, if the positioning system identifies that P (n) is located in the forbidden area, the P (n) can be directly added to the untrusted point set to remove the abnormal points, so that the state of the sampling positioning points can be effectively identified by calculating the position relationship between adjacent positioning points and comparing the relationship between the positioning points and the environment, and after the abnormal points influencing the movement track of the moving object are removed, the finally obtained movement track of the moving object can better accord with the actual condition, the accuracy of the positioning data is ensured, and the positioning precision is improved.
In another example, the detection result may be a credible value of the locating point, and different credible values indicate different credibility of the locating point, so that the locating system can identify the abnormal situation of the locating according to the credible value of the locating point, so as to effectively identify the state of the sampling locating point, and after the abnormal point affecting the moving track of the moving object is removed, the finally obtained moving track of the moving object is more in line with the actual situation, thereby ensuring the accuracy of the locating data and improving the locating precision.
And 204, generating a moving track of the moving object according to the detection results of the positioning points.
When the moving object completes one-time complete movement, and the positioning system acquires all positioning points of the moving object and performs exception identification on the positioning points, the normal positioning points can be connected according to the detection results of the plurality of positioning points to generate a moving track of the moving object moving at the same time, and the moving track is displayed, so that the behavior of the moving object can be analyzed and mined based on the moving track, and monitoring, management and exception identification on the moving object are facilitated.
In an example, assuming that the detection result is a result of adding the first positioning point to the preset sampling point set, the positioning points in the trusted point set may be adopted to generate the moving track of the mobile object, so that the behavior of the mobile object may be analyzed and mined based on the moving track, which is beneficial to monitoring and managing the mobile object and performing anomaly identification.
In another example, assuming that the detection result is a credible value of the anchor point, different detection results correspond to different credible values, for example, the first detection result may correspond to a first credible value, the second detection result may correspond to a second credible value, and the third detection result may correspond to a third credible value.
In one case, the credible value of each locating point can be compared with a preset credible threshold, the locating points which are greater than or equal to the credible threshold are used as credible locating points, then all the credible locating points are connected according to a sampling sequence, and therefore the moving track of the moving object is obtained, the behavior of the moving object can be analyzed and mined based on the moving track, and monitoring, management and abnormal recognition of the moving object are facilitated. . For the calculation of the credible value, the calculation may be determined according to a difference between a distance value between two adjacent positioning points and a preset distance value, for example, if the difference is positive, the larger the difference is, the lower the credible value is; if the difference is negative, the smaller the difference is, the higher the confidence value is, and the like, and in addition, when the fixed point falls into the forbidden zone, the confidence value may be 0, which is not limited in this application.
In another case, the confidence value may be a fixed value, for example, the first detection result may correspond to a first confidence value (0), the second detection result may correspond to a second confidence value (2), the third detection result may correspond to a third confidence value (1), 0 represents that the localization point is not trusted, 1 represents that the localization point is suspicious, 2 identifies that the localization point is trusted, and so on. The credibility levels of the preset sampling point sets can be obtained, different sets correspond to different credibility levels, the credibility of the non-credible point set corresponds to the first-level credibility, the credibility of the suspicious point set corresponds to the second-level credibility, the credibility of the credible point set corresponds to the third-level credibility, and along with the improvement of the levels, the higher the credibility is, so that the positioning points can be added into the collection point sets of the corresponding levels according to the credibility values, the positioning system can generate the moving track of the moving object by adopting the positioning points in the credible point sets, the behavior analysis and the mining of the moving object can be based on the moving track, and the monitoring, the management and the abnormal recognition of the moving object are facilitated.
In the embodiment of the application, by obtaining the positioning points of the mobile object, the positioning points may include a first positioning point and at least one second positioning point adjacent to the first positioning point, and then determining a position relationship between the two positioning points, and performing anomaly detection on the first positioning point according to the position relationship to generate a detection result of the first positioning point, and then generating a moving track of the mobile object according to the detection result of each acquired positioning point in the moving process of the mobile object, so that by determining the position relationship between the adjacent positioning points, the state of the sampling positioning point can be effectively identified, and after eliminating the abnormal points affecting the moving track of the mobile object, a credible positioning point can be obtained, so that the moving track is more in line with the actual situation, the accuracy of the positioning data is ensured, and the positioning accuracy is improved.
For a mobile object, which may be a logistics object, the detection of the logistics object may be to detect the logistics warehouse in a logistics scene, for example, in a warehouse logistics scene, a flow change of the logistics object in the warehouse may be monitored. The logistics object may include goods, packages, carriers, and the like, and the surface of the logistics object may be provided with metal tags, such as active tags, passive tags, and the like, in a manner including, but not limited to, spraying, printing, sticking, and stamping. The metal label can have a design of a pattern, a shape, a color or a combination thereof, and the information of the logistics object can be expressed through the design of the metal label, so that the positioning point of the logistics object in the logistics warehouse can be obtained through the identification label through the positioning system, and the logistics object can be monitored. In addition, the moving object can also be a worker (user object) moving in the logistics warehouse, and the flow change of the worker in the logistics warehouse can be monitored to obtain the moving track of the worker in the warehouse, so that the behavior analysis and mining of the moving object based on the moving track can be realized, and the monitoring, management and abnormal recognition of the moving object are facilitated.
Specifically, referring to fig. 3, a flowchart of a third step of the monitoring method for a logistics process according to the embodiment of the present application is shown, which specifically includes the following steps:
step 301, acquiring positioning points of a moving object in a logistics area, wherein the positioning points comprise a first positioning point and at least one second positioning point adjacent to the first positioning point;
step 302, determining the position relation between the first positioning point and the second positioning point;
step 303, performing anomaly detection on the first fixed position point according to the position relationship to generate a detection result of the first fixed position point;
and 304, generating a moving track of the moving object according to the detection results of the positioning points.
In an optional embodiment of the present application, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the performing, according to the position relationship, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
In an optional embodiment of the present application, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the logistics object to generate a detection result of the first positioning point.
In an optional embodiment of the present application, the environment information includes a forbidden area, and the performing anomaly detection on the first positioning point by using at least one distance value and the environment information where the logistics object is located to generate the detection result of the first positioning point includes:
if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
In an optional embodiment of the present application, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point includes:
and if the distance value between the first positioning point and the second positioning point is smaller than or equal to a preset distance threshold, generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point.
In an optional embodiment of the present application, the second positioning point includes a historical positioning point before the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold, generating a third detection result of the first positioning point.
In an optional embodiment of the present application, the second positioning point includes a target positioning point after the first positioning point, and the performing anomaly detection on the first positioning point by using at least one distance value to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
In an optional embodiment of the present application, the performing, by using at least one distance value, an anomaly detection on the first positioning point to generate a detection result of the first positioning point further includes:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
In an optional embodiment of the present application, the detection result includes a result of adding the first positioning point to a preset sampling point set, where the sampling point set includes a trusted point set, a suspicious point set, and an untrusted point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the generating the moving track of the moving object according to the detection results of the plurality of positioning points includes:
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
In an optional embodiment of the present application, the generating a movement trajectory of the mobile object according to the detection results of the multiple positioning points includes:
using the positioning point with the credibility value being greater than or equal to the preset credibility threshold value and successfully matched as a credible positioning point;
and generating a moving track of the logistics object by adopting the credible positioning point.
In an optional embodiment of the present application, the generating a movement trajectory of the moving object according to the detection results of the plurality of positioning points includes:
acquiring a credibility level aiming at a preset sampling point set, wherein the sampling point set comprises a credibility point set;
adding the positioning point with the credible value meeting the credible grade to the credible point set;
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
In the embodiment of the present application, by obtaining the positioning points of the moving object in the logistics area, the positioning points may include a first positioning point and at least one second positioning point adjacent to the first positioning point, then determining the position relationship between the two positioning points, and according to the position relationship, carrying out abnormity detection on the first positioning point to generate a detection result of the first positioning point, then generating a moving track of the logistics object according to the detection result of each positioning point acquired in the moving process of the logistics object, therefore, by determining the position relation between the adjacent positioning points, the state of the sampling positioning point can be effectively identified, after the abnormal points influencing the moving track of the logistics object are removed, the credible positioning points can be obtained, and then make the movement track more accord with the actual condition, guaranteed the accuracy of location data, improved positioning accuracy.
In order to enable those skilled in the art to better understand the embodiments of the present application, the following description is given by way of an example:
as shown in fig. 4, a schematic diagram of a location point in the embodiment of the present application is shown, and as shown in fig. 5, a schematic diagram of a scene of monitoring a moving object in the embodiment of the present application is shown, assuming that the moving object is a user object (i.e., a person), the moving scene is a transportation of goods in a logistics warehouse, the maximum moving speed is 9 km/h, and the sampling time is every 5 minutes/time. In a complete movement process, the positioning system acquires 11 positioning points comprising 1-11 and the like.
In the process of acquiring positioning points of a user object in real time, the process of identifying the state of each positioning point of the user object by a positioning system comprises the following steps:
p (1): since the starting point of the mobile object is the default of the starting positioning point as the credible point, P (1) is added to the credible point set;
p (2): d (1, 2) is less than or equal to dmax (1, 2), and P (2) is added to the set of trust points;
p (3): recognizing that P (3) is located in a forbidden zone, and directly adding P (3) to an untrusted point set;
p (4): since P (3) has been added to the set of untrusted points, for P (4), the distance relationship to P (2) can be calculated, resulting in d (2, 4) being less than or equal to dmax (2, 4), adding P (4) to the set of trusted points;
p (5): d (4, 5) is less than or equal to dmax (4, 5), and P (5) is added to the set of trust points;
p (6): d (5, 6) is greater than dmax (5, 6), adding P (6) to the suspicious point set, further identifying P (6) at the moment, continuously collecting P (7), calculating a distance value between P (6) and P (7), and obtaining that d (6, 7) is greater than dmax (6, 7), so that by calculating the distance relationship between P (6) and P (5) and P (7), P (6) can be identified as an abnormal point, P (6) is moved from the suspicious point set to the untrusted point set, and meanwhile, P (7) can be added to the suspicious point set;
p (7): since P (6) is an abnormal point, it is necessary to determine the state of P (7) by combining the distance relationship between P (5) and P (7) and the distance relationship between P (7) and P (8), and then d (5, 7) is less than or equal to dmax (5, 7) and d (7, 8) is less than or equal to dmax (7, 8) are obtained by calculation, so P (7) can be added from the suspicious point set to the credible point set;
p (8): d (7, 8) is less than or equal to dmax (7, 8), and P (8) is added to the set of trust points;
p (9): d (8, 9) is larger than dmax (8, 9), adding P (9) to the set of suspicious points, further identifying P (9) at the moment, continuing to collect P (10), calculating the distance value between P (9) and P (10), and moving P (9) from the set of suspicious points to the set of credible points if d (9, 10) is smaller than or equal to dmax (9, 10);
p (10): d (9, 10) is less than or equal to dmax (9, 10), P (10) is added to the set of trust points;
p (11): d (10, 11) is less than or equal to dmax (10, 11), and P (11) is added to the set of trust points.
As shown in fig. 6, which shows a schematic diagram of a set of sampling points in the embodiment of the present application, anchor points in set a are all anchor points of a user object, and for anchor points in set a, a set B (a set of trusted points), a set C (a set of suspicious points), and a set D (a set of untrusted points) may be moved in; the anchor points in set C may be moved into set B or set D. According to the positioning points and the moving environment of the user object, the state of the sampling positioning points can be effectively identified according to the distance relation between the current positioning point and the front and back positioning points, after the abnormal points influencing the moving track of the moving object are eliminated, the moving track can better meet the actual condition, the accuracy of the positioning data is ensured, and the positioning precision is improved.
It should be noted that, in the embodiment of the present application, an exemplary description is performed on a sampling point set, and it can be understood that a reliability of a positioning point acquired by a user object in a moving process can also be determined by using a reliability value, which is not limited in the present application.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.
Referring to fig. 7, a block diagram of an embodiment of a device for generating a movement track according to the present application is shown, and specifically, the device may include the following modules:
the positioning point obtaining module 701 is configured to obtain a positioning point of a mobile object, where the positioning point includes a first positioning point and at least one second positioning point adjacent to the first positioning point;
a position relation determining module 702, configured to determine a position relation between the first positioning point and the second positioning point;
a detection result generating module 703, configured to perform anomaly detection on the first positioning point according to the position relationship, and generate a detection result of the first positioning point;
a moving track generating module 704, configured to generate a moving track of the moving object according to the detection results of the multiple positioning points.
In an optional embodiment of the present application, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the detection result generating module 703 is specifically configured to:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
In an optional embodiment of the present application, the detection result generating module 703 is specifically configured to:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the mobile object to generate a detection result of the first positioning point.
In an optional embodiment of the present application, the environment information includes a forbidden area, and the detection result generating module 703 includes:
a first detection result generation submodule for: if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
In an optional embodiment of the present application, the detection result generating module 703 further includes:
and the second detection result generation submodule is used for generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point if the distance value between the first positioning point and the second positioning point is less than or equal to a preset distance threshold value.
In an optional embodiment of the present application, the second positioning point includes a historical positioning point before the first positioning point, and the detection result generating module 703 further includes:
and the third detection result generation submodule is used for generating a third detection result of the first positioning point if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold value.
In an optional embodiment of the present application, the second anchor point includes a target anchor point after the first anchor point, and the first detection result generation submodule is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
In an optional embodiment of the present application, the second detection result generation sub-module is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
In an optional embodiment of the present application, the detection result includes a result of adding the first positioning point to a preset sampling point set, where the sampling point set includes a trusted point set, a suspicious point set, and an untrusted point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the movement track generation module 704 is specifically configured to:
and generating a moving track of the moving object by adopting the positioning points in the credible point set.
In an optional embodiment of the present application, the detection result includes a confidence value of the positioning point, and different detection results correspond to different confidence values, and the movement track generating module 704 includes:
the credible locating point determining submodule is used for matching the locating point with the credible value being greater than or equal to the preset credible threshold value successfully as the credible locating point;
and the first movement track generation submodule is used for generating the movement track of the mobile object by adopting the credible positioning point.
In an optional embodiment of the present application, the movement trace generating module 704 includes:
the credibility level acquisition sub-module is used for acquiring credibility levels aiming at a preset sampling point set, and the sampling point set comprises a credibility point set;
the positioning point adding submodule is used for adding the positioning point of which the credible value meets the credible grade to the credible point set;
and the second movement track generation submodule is used for generating the movement track of the mobile object by adopting the positioning points in the credible point set.
Referring to fig. 8, a block diagram of a monitoring apparatus of a logistics process according to an embodiment of the present application is shown, and specifically, the monitoring apparatus may include the following modules:
the locating point acquiring module 801 is configured to acquire a locating point of a mobile object in a logistics area, where the locating point includes a first locating point and at least one second locating point adjacent to the first locating point;
a position relation determining module 802, configured to determine a position relation between the first positioning point and the second positioning point;
a detection result generation module 803, configured to perform anomaly detection on the first fixed location according to the position relationship, and generate a detection result of the first fixed location;
a moving track generating module 804, configured to generate a moving track of the moving object according to the detection results of the multiple positioning points.
In an optional embodiment of the present application, the position relationship at least includes a distance value between the first positioning point and the second positioning point, and the detection result generating module 803 is specifically configured to:
and carrying out anomaly detection on the first fixed position point by adopting at least one distance value to generate a detection result of the first fixed position point.
In an optional embodiment of the present application, the detection result generating module 803 is specifically configured to:
and carrying out anomaly detection on the first positioning point by adopting at least one distance value or at least one distance value and the environmental information of the logistics object to generate a detection result of the first positioning point.
In an optional embodiment of the present application, the environment information includes a forbidden area, and the detection result generating module 803 includes:
a first detection result generation submodule for: if the distance value is smaller than or equal to a preset distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point;
and if the distance value is greater than the distance threshold value and the first positioning point falls into the forbidden region, generating a first detection result of the first positioning point.
In an optional embodiment of the present application, the detection result generating module 803 further includes:
and the second detection result generation submodule is used for generating a third detection result of the first positioning point or a second detection result of the first positioning point and the second positioning point if the distance value between the first positioning point and the second positioning point is less than or equal to a preset distance threshold value.
In an optional embodiment of the present application, the second positioning point includes a historical positioning point before the first positioning point, and the detection result generating module 803 further includes:
and the third detection result generation submodule is used for generating a third detection result of the first positioning point if the first distance value between the first positioning point and the historical positioning point is greater than a preset distance threshold value.
In an optional embodiment of the present application, the second anchor point includes a target anchor point after the first anchor point, and the first detection result generation submodule is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is greater than the distance threshold, changing the second detection result of the first positioning point into the first detection result.
In an optional embodiment of the present application, the second detection result generation sub-module is specifically configured to:
and if the second distance value between the first positioning point and the target positioning point is smaller than or equal to the distance threshold, changing the third detection result of the first positioning point into the second detection result.
In an optional embodiment of the present application, the detection result includes a result of adding the first positioning point to a preset sampling point set, where the sampling point set includes a trusted point set, a suspicious point set, and an untrusted point combination;
wherein the first detection result is a result of adding the first localization point to the set of untrusted points; the second detection result is the result of adding the first positioning point and the second positioning point or the first positioning point to the set of trusted points; the third detection result is the result of adding the first localization point to the suspicious point set;
the movement track generation module 804 is specifically configured to:
and generating a moving track of the logistics object by adopting the positioning points in the credible point set.
In an optional embodiment of the present application, the detection result includes a confidence value of the anchor point, and different detection results correspond to different confidence values, and the movement trajectory generating module 804 includes:
the credible locating point determining submodule is used for matching the locating point with the credible value being greater than or equal to the preset credible threshold value successfully as the credible locating point;
and the first movement track generation submodule is used for generating the movement track of the logistics object by adopting the credible positioning point.
In an optional embodiment of the present application, the movement trace generating module 804 includes:
the credibility level acquisition sub-module is used for acquiring credibility levels aiming at a preset sampling point set, and the sampling point set comprises a credibility point set;
the positioning point adding submodule is used for adding the positioning point of which the credible value meets the credible grade to the credible point set;
and the second movement track generation submodule is used for generating the movement track of the logistics object by adopting the positioning points in the credible point set.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
An embodiment of the present application further provides an electronic device, including:
one or more processors; and
one or more machine-readable media having instructions stored thereon, which when executed by the one or more processors, cause the electronic device to perform the methods of embodiments of the present application.
Embodiments of the present application also provide one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause the processors to perform the methods of embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more machine-readable media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The method for generating a movement track and the device for generating a movement track provided by the present application are introduced in detail above, and a specific example is applied in the present application to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
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