CN112508466A

CN112508466A - Position identification method and device, computer readable storage medium and electronic equipment

Info

Publication number: CN112508466A
Application number: CN201910789503.4A
Authority: CN
Inventors: 孙铭; 马超逸; 邢轲; 高久翀
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2019-08-26
Filing date: 2019-08-26
Publication date: 2021-03-16

Abstract

The specification discloses a method, a device, a computer-readable storage medium and an electronic device for identifying a location, which can determine a feature vector of a wireless environment of an assigned address according to wireless environment parameters of the assigned address for the assigned address, and when the location of a user needs to be identified, determine the feature vector of the wireless environment of the location of the current user by acquiring the wireless environment parameters acquired by a terminal of the current user, and then identify whether the current user reaches the assigned address according to the wireless environment parameters of the assigned address and the feature vector of the wireless environment of the location of the current user. The rider can determine whether the rider reaches the designated address or not through the wireless environment parameters acquired by the terminal without actively reporting the position. The condition that the rider violates the operation to cause wrong judgment is avoided, and whether the rider reaches the designated address can be determined more accurately and efficiently.

Description

Position identification method and device, computer readable storage medium and electronic equipment

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for identifying a location, a computer-readable storage medium, and an electronic device.

Background

Currently, in order to improve distribution efficiency, a take-out distribution platform determines to which rider an order is assigned according to the matching degree of the order and the rider. Wherein the higher the matching degree of the order with the rider, the more efficiently the rider executes the order. For example, when the rider has a short meal time after the rider arrives at the store, the promised meal delivery time promised to the user in the immediate vicinity of the expected meal delivery time, the "way around" between orders on the delivery route, and so on. In addition, in order to facilitate the rider to more effectively execute the distribution service, when the platform assigns the order to the rider, the platform sends the corresponding path plan to the rider. The path planning includes information such as the delivery path of the rider, the order of taking and delivering the food in each order, and the like.

Of course, failure of the rider to plan delivery according to the path given by the platform often results in reduced delivery efficiency and even customer complaints. In order to adjust subsequent order assignments in time when the rider cannot plan delivery according to the route, the platform generally requires the rider to report the situation when the rider reaches a designated address. For example, the rider needs to report the order being delivered and the current delivery progress to the platform by clicking keys such as "go to store", "get meal", and "deliver meal" on the client. Actually, the progress of each order is monitored, so that abnormality is found in time, and larger loss is avoided.

It can be seen that in the prior art, the progress of the distribution service executed by the rider is monitored and determined according to the information actively sent by the rider through the client, and the method mainly depends on the self-perception of the rider, so that whether the rider reaches the specified address or not is difficult to accurately determine and execute the corresponding service. The rider can operate in violation inevitably, so that the platform can judge the delivery progress of the rider mistakenly. For example, the rider clicks the "to shop" button when he or she has not arrived at a restaurant, and the platform determines that the rider has arrived at the designated address.

Disclosure of Invention

The method, the device, the computer-readable storage medium and the electronic device for position identification provided by the embodiments of the present specification are used to partially solve the problems in the prior art.

The embodiment of the specification adopts the following technical scheme:

the method for identifying the position provided by the specification comprises the following steps:

acquiring wireless environment parameters acquired by a terminal of a current user, and determining a feature vector of a wireless environment of a position where the current user is located according to the acquired wireless environment parameters;

and identifying whether the current user reaches the specified address according to the characteristic vector of the wireless environment of the position of the current user and the characteristic vector of the wireless environment of the specified address, wherein the characteristic vector of the wireless environment of the specified address is determined according to the wireless environment parameters of the specified address.

Optionally, determining a feature vector of the wireless environment of the specified address includes:

aiming at least one historical order, determining at least one signal source corresponding to data acquired by a terminal of a historical user when the historical user reaches a target address corresponding to the historical order, and determining the at least one signal source as the signal source corresponding to the target address;

aiming at least one signal source corresponding to the target address, determining a characteristic value of the signal source according to data which is collected by the terminal of the history user and is sent by the signal source;

and determining the characteristic vector of the wireless environment of the designated address according to the characteristic value of each signal source of which the corresponding target address is the designated address.

Optionally, the determining a characteristic value of the signal source according to the data sent by the signal source and collected by the terminal of the history user includes:

for at least one signal source, determining the order quantity of a historical order corresponding to the signal source according to data which is acquired by a terminal of the historical user and is sent by the signal source;

determining the inverse document frequency of the signal source according to the order quantity of the historical orders corresponding to the signal source and the total quantity of the historical orders;

and determining the characteristic value of the signal source according to the inverse document frequency of the signal source.

aiming at least one signal source, determining the signal intensity of the signal source according to the data which is collected by the terminal of the history user and is sent by the signal source;

and determining the characteristic value of the signal source according to the signal strength of the signal source.

Optionally, the determining, according to the feature value of each signal source of which the corresponding target address is the designated address, a feature vector of a wireless environment of the designated address includes:

clustering characteristic values of signal sources with target addresses as the designated addresses to obtain a plurality of clusters;

aiming at least one cluster, selecting a specified number of characteristic values according to the sequence of the characteristic values from large to small;

determining a characteristic vector corresponding to the cluster according to the selected characteristic value and the identifier of the signal source corresponding to the selected characteristic value;

and taking the characteristic vector corresponding to at least one cluster as the characteristic vector of the wireless environment corresponding to the specified address.

Optionally, the identifying whether the current user arrives at the designated address according to the feature vector of the wireless environment of the location where the current user is located and the feature vector of the wireless environment of the designated address includes:

similarity calculation is carried out on the characteristic vector of the wireless environment of the position where the current user is located and the characteristic vector of the wireless environment of the designated address;

and identifying whether the current user reaches the specified address according to a calculation result.

Optionally, if the calculation result satisfies at least one of the following conditions, determining that the current user arrives at the designated address; the conditions include:

the similarity between the feature vector of the wireless environment of the current user position and any feature vector of the wireless environment of the designated address is greater than a first threshold value;

the similarity between the characteristic vector of the wireless environment of the current user position and at least two characteristic vectors of the wireless environment of the designated address is greater than a second threshold;

wherein the first threshold is higher than the second threshold.

The position recognition device provided by the specification comprises:

the determining module is configured to acquire wireless environment parameters acquired by a terminal of a current user and determine a feature vector of a wireless environment of a position where the current user is located according to the acquired wireless environment parameters;

and the identification module is configured to identify whether the current user reaches the specified address according to the characteristic vector of the wireless environment of the position where the current user is located and the characteristic vector of the wireless environment of the specified address, wherein the characteristic vector of the wireless environment of the specified address is determined according to the wireless environment parameters of the specified address.

The present specification provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program, when executed by a processor, implements the above-described method of position identification.

The electronic device provided by the present specification includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above location identification method when executing the program.

The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:

the method comprises the steps that a characteristic vector of a wireless environment of an appointed address can be determined according to wireless environment parameters of the appointed address in advance, when the position of a user needs to be identified, the characteristic vector of the wireless environment of the position of the current user is determined by obtaining the wireless environment parameters collected by a terminal of the current user, and then whether the current user reaches the appointed address or not is identified according to the wireless environment parameters of the appointed address and the characteristic vector of the wireless environment of the position of the current user. The rider can determine whether the rider reaches the designated address or not through the wireless environment parameters acquired by the terminal without actively reporting the position. The condition that the rider violates the operation to cause wrong judgment is avoided, and whether the rider reaches the designated address can be determined more accurately and efficiently.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a schematic flowchart of a location identification method provided in an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a feature vector process for determining a wireless environment for a specified address provided by an embodiment of the present description;

FIG. 3 is a schematic diagram of signal strength provided by an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a device for location identification provided in an embodiment of the present disclosure;

fig. 5 is a schematic view of an electronic device implementing a location identification method according to an embodiment of the present disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the present disclosure more apparent, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step are within the scope of the present application.

The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a location identification method provided in an embodiment of the present specification, which may specifically include one or more of the following steps:

s102: acquiring wireless environment parameters acquired by a terminal of a current user, and determining a feature vector of a wireless environment of a position where the current user is located according to the acquired wireless environment parameters.

In this specification, it is described by taking an example that the delivery platform recognizes whether a rider reaches a task point, the device for performing the position recognition may be a server of the delivery platform, and the current user specifies an address of a task point (e.g., an address of a pickup position, an address of a delivery position, etc.) on a delivery path of the rider for the rider who needs to recognize whether the rider reaches the task point at present.

When the rider is on an open area (e.g., a highway), the server may determine the current rider's location by establishing a communication connection with the rider's terminal, obtaining GPS data provided by a Global Positioning System (GPS) chip of the rider's terminal. When the rider enters a building or the rider is on a complex terrain (e.g., a building complex, an underlying square), the accuracy of the GPS data is degraded, making it difficult to accurately identify the rider's location.

The server can determine the characteristic vector of the wireless environment of the current position of the rider so as to accurately monitor the progress of the rider in executing the distribution task by the distribution platform in order to more accurately identify whether the rider reaches the task point.

Specifically, since the server of the current distribution platform maintains communication with the terminal of the rider during the period when the rider executes the distribution task to support the completion of the distribution service, the server can obtain the wireless environment parameters currently collected by the terminal of the rider through communication with the terminal of the rider. The Wireless environment parameter may specifically be a parameter corresponding to a signal transmitted by a Wireless Fidelity (WiFi) signal source received by the rider terminal. For example, a signal of a WiFi hotspot of a router, a signal of a WiFi hotspot of a mobile terminal. The wireless environment parameter is a parameter of the WiFi signal, including data transmitted by the WiFi hotspot received by the rider's terminal, the strength of the received WiFi signal, and so on. The data transmitted by the WiFi hotspot may be data broadcasted by the WiFi hotspot, for example, the WiFi signal includes information such as an identifier of the WiFi hotspot, whether the WiFi hotspot needs a password, a Media Access Control Address (MAC Address) of the WiFi hotspot, and the like.

Then, the server can determine the feature vector of the wireless environment of the current position of the rider according to the acquired wireless environment parameters. Therefore, in the subsequent step, whether the rider reaches the specified address can be identified according to the feature vector of the wireless environment and the feature vector of the wireless environment of the specified address.

In addition, in this specification, since the wireless environment of the position where the rider is located may be very complex, the number of signal sources corresponding to the acquired wireless environment parameters may be many, but for a signal source with weak signal strength, the function of the parameter of the WiFi signal provided by the signal source on identifying the position of the rider is small, so when determining the feature vector of the wireless environment, the server may select the parameter of the WiFi signal of the signal source with the preset first number from the signal sources corresponding to the acquired wireless environment parameters according to the sequence of the signal strength from large to small, and determine the feature vector of the wireless environment. Specifically, the terminal of the rider may determine parameters of WiFi signals of the wireless environment according to a preset time interval, select parameters of WiFi signals of the signal sources of the preset first number from the parameters, and determine a feature vector of the wireless environment. The parameters of the WiFi signal of the signal source contained in the feature vector of the wireless environment may be arranged from large to small according to the signal strength of the signal source.

The preset first number may be set as required, and the description is not limited. However, the signal source with weak signal strength has a small effect on identifying the position of the rider, and one of the main reasons is that the signal strength may be weak, which may cause the signal of the signal source to be received in some cases but not received in the same place, and thus the signal source with weak signal strength is not suitable for determining the feature vector of the wireless environment of the designated address. And the subsequent step is used for comparing the characteristic vectors with the characteristic vectors of the wireless environment of the designated address and identifying whether the rider reaches the designated address, so that the characteristic vectors of the wireless environment of the designated address can be determined according to the parameters of the WiFi signals of the signal sources with the preset second number from large to small in strength. In this specification, the preset second number may be set as needed, and the first number and the second number may be the same, which is not limited in this specification. Because the signal sources with weak signal intensity are filtered, the number of the signal sources needing to be processed subsequently is reduced, the complexity of the subsequent steps can be reduced, and the efficiency is improved.

Further, since what needs to be solved in this specification is that when the rider enters a location where the accuracy of GPS data is degraded, the problem that whether the rider reaches a designated address cannot be accurately identified is solved, the server may perform the location identification method provided in this specification when it is determined that the task point of the rider that performs the distribution task is located at the location where the accuracy of GPS data is degraded. Alternatively, the rider position may be determined from GPS data when the rider position cannot be identified by the method provided in the present specification.

S104: and identifying whether the current user reaches the specified address or not according to the characteristic vector of the wireless environment of the position where the current user is located and the characteristic vector of the wireless environment of the specified address.

In this specification, after determining the feature vector of the wireless environment at the current position of the rider, the server may identify whether the current rider arrives at the specified address according to the feature vector of the wireless environment at the specified address. The designated address is the address of the task point which needs to be reached most recently when the rider executes the distribution task according to the distribution path. The designated address can thus be determined according to the current progress of the rider in performing the delivery task. For example, the order in which the rider executes the delivery tasks is task point 1, task point 2, and task point 3, and if the current rider has completed the task from task point 1 and then proceeds to task point 2, the designated address of the current rider is the address of task point 2. Alternatively, since the rider does not necessarily execute the delivery tasks along the delivery route, the rider may set each task point in the delivery route of the rider as the designated address regardless of the delivery order of the rider. And aiming at each designated address, identifying whether the current rider reaches the designated address or not according to the characteristic vector of the wireless environment of the designated address and the characteristic vector of the wireless environment of the current rider position.

In order to identify whether the current rider arrives at the specified address according to the feature vector of the wireless environment of the specified address, the server needs to determine the feature vector of the wireless environment of the specified address first. And, the feature vector of the wireless environment of the specified address may be determined by the server in advance based on the history data.

Specifically, since the wireless environment is complex at present, the wireless environment of the designated address may change over time, but not be constant. Therefore, in order to more accurately determine the feature vector of the wireless environment of the designated address, the server needs to determine the feature vector of the wireless environment that can be used for identifying the designated address according to the data collected for multiple times. The accidental data are eliminated through a large amount of data acquired for many times, and the robustness of the identification process is improved.

Fig. 2 is a schematic diagram of the process for determining the feature vector of the wireless environment with a specific address provided in the present specification, which specifically includes the following steps:

s1042: and aiming at least one historical order, determining at least one signal source corresponding to data acquired by a terminal of the historical user when the historical user reaches a target address corresponding to the historical order, and determining the at least one signal source as the signal source corresponding to the target address.

In this specification, the feature vector of the wireless environment for determining the designated address is a feature vector that can be used to uniquely identify the wireless environment of the designated address, and since the distances between different addresses may be relatively close in a region with dense people (e.g., a business district or an office building), it is easy to happen that signals transmitted by the same signal source may be relatively strong at multiple addresses. It is difficult to distinguish different addresses based on the signals transmitted from such signal sources, and it is impossible to determine the eigenvector uniquely identifying the wireless environment of the specified address.

Therefore, in the present specification, the feature vector of the wireless environment of the designated address cannot be determined based only on the history data of the history order in which the task point is the designated address. The server needs to finally determine the feature vector of the wireless environment capable of distinguishing each target address by acquiring the wireless environment parameters of a large number of target addresses and determining the wireless environment parameters of each target address.

Therefore, the server can use the signals collected by the terminal at the target address as the signal source of the target address when the rider executes the distribution task historically. So as to finally determine the characteristic vector of the wireless environment of each target address through the subsequent steps according to the data transmitted by each signal source, and then determine the characteristic vector of the wireless environment of the designated address.

The target address is a task point corresponding to the order, namely one of a pickup position or a delivery position. It should be noted that, in this specification, the designated address is one of the destination addresses, the address of any task point included in the order may be the destination address, and the designated address is the destination address of the feature vector of the wireless environment that needs to be determined in step S104.

S1044: the server can determine the characteristic value of the signal source according to the data, collected by the terminal of the history user and sent by the signal source, of at least one signal source corresponding to the target address.

In this specification, the server may determine, for each destination address, data transmitted from each signal source received at the destination address, and determine, for each signal source, a characteristic value of the signal source. Since the data of the signal source is determined to determine the radio environment parameter, the main purpose is to distinguish different addresses, when determining the characteristic value of the signal source, what is determined is the characteristic value of the signal source for distinguishing the degrees of different addresses.

Specifically, the server may determine, for at least one signal source, the order number of the history order corresponding to the signal source according to the data sent by the signal source and collected by the terminal of the history user. That is, the server can determine how many times the data sent by the source was collected by the rider when executing the historical order. For example, if data transmitted from a signal source is collected by a terminal when a plurality of riders distribute historical orders at different positions, the data transmitted from the signal source is difficult to be used for distinguishing different addresses.

Thereafter, the server may continue to determine an Inverse Document Frequency (IDF) of the signal source according to the order quantity of the historical order corresponding to the signal source and the total quantity of the historical order. Specifically, the server may obtain the IDF by dividing the total amount of the historical orders by the quotient of the order number of the historical order corresponding to the signal source and taking a base-10 logarithm of the obtained quotient. The IDF may be used to characterize the source's ability to uniquely identify the destination address.

In addition, the IDF of the signal source can be used to distinguish different addresses, but it needs the feature vector of the wireless environment when the rider reaches the designated address, so the strength of the signal transmitted by the signal source is also important, as shown in fig. 3. Fig. 3 is a schematic diagram of signal strength provided in this specification, where it can be seen that there are a target address a, a target address B and a signal source C in the diagram, and assuming that there is only the signal source C in the environment and the transmitted signal has two levels of strong and weak (for example, a dark circle indicates a coverage range of a strong signal and a light circle indicates a coverage range of a weak signal), when a rider arrives near the target address a and the target address B, only data transmitted by the signal source C can be collected, so that it may be difficult to distinguish different addresses only by the IDF of the signal source, and it may be easy to determine whether the rider is located at the target address a or the target address B according to the signal strength of the signal source.

Specifically, the server may determine, for at least one signal source, the signal strength of the signal source according to the data sent by the signal source and collected by the terminal of the history user, and then determine the characteristic value of the signal source according to the signal strength of the signal source. The signal strength may be specific decibel relative to one milliwatt (dBm), a commonly used parameter for indicating the signal strength.

Further, the server may determine, for each signal source, a characteristic value of the signal source according to the determined signal strength of the signal source and the determined IDF of the signal source. Specifically, the calculation and determination can be performed according to a formula IDF × (dBM +10)0, wherein, since the value range of dBM is usually 30 to-100, in order to ensure that the eigenvalue is positively correlated with both IDF and signal strength, the signal strength term is a positive number in the formula.

In addition, in this specification, the characteristic value of the signal source, that is, the parameter contributed by the signal source in the radio environment parameter of the destination address. For example, assuming that there are 3 WiFi hotspots near a certain destination address, the wireless environment parameter of the destination address is composed of characteristic values corresponding to data sent by the 3 WiFi hotspots.

S1046: the server can determine the characteristic vector of the wireless environment of the designated address according to the characteristic value of each signal source of the designated address corresponding to the target address.

In this specification, after passing through steps S1040 and S1046, the server may determine, according to the historical order, a characteristic value of each signal source corresponding to each destination address. The characteristic value of the signal source can be used for distinguishing different target addresses, so when the server needs to determine the characteristic vector of the wireless environment of the designated address, firstly, the designated address can be determined from each target address, and the characteristic value of each signal source corresponding to the target address is determined.

Secondly, clustering the characteristic values of the signal sources corresponding to the designated address to obtain a plurality of clusters. The server can adopt a k-means clustering method for clustering, and the number of clusters can be preset. For example, if the k value is set to 2, 2 clusters can be determined by clustering with the k-means clustering method.

Then, for at least one cluster, a specified number of eigenvalues are selected in descending order of the eigenvalues. The selected feature value may be regarded as a feature value representing the cluster because the selected feature value is closer to the center of the cluster, where the designated number may not be completely consistent with the preset first number in step S102, and may be set as needed, which is not limited in this specification.

And then, determining the eigenvector corresponding to the cluster according to the selected eigenvalue and the identifier of the signal source corresponding to the selected eigenvalue.

After selecting a plurality of eigenvalues from each cluster, the server can further determine the identifier of the signal source corresponding to the selected eigenvalue, and then determine the eigenvector corresponding to the cluster according to each selected eigenvalue and the identifier of the signal source corresponding to the eigenvalue. The feature vector consists of a specified number of feature values and the identity of the signal source. For example, assuming that the specified number is 3, the characteristic values and the signal source identifications determined by the server are shown in table 1.

Characteristic value	Identification of signal source
		X	C
Y	D
		Z	E

TABLE 1

The feature vector corresponding to the cluster can be represented by (C ═ X, D ═ Y, E ═ Z). It should be noted that the elements (i.e., the eigenvalues and the identifiers) in the eigenvector may be arranged according to a preset arrangement order (e.g., arranged according to an identifier a-Z) or randomly ordered, as long as the correspondence between the eigenvalue and the identifier of each signal source in the eigenvector is ensured.

And finally, taking the characteristic vector corresponding to at least one cluster as the characteristic vector of the wireless environment corresponding to the specified address. It should be noted that, when the feature vector is subsequently used to perform similarity calculation, the feature vector of the wireless environment at the current position of the rider does not include an IDF item, so that when determining the feature vector, the IDF corresponding to each signal source may be determined and stored according to the identifier of each signal source in the feature vector. Therefore, when the characteristic vector of the wireless environment of the current position of the rider is determined subsequently, the characteristic vector of the wireless environment of the current position of the rider can be determined according to the signal intensity of each signal source collected by the terminal of the rider and the pre-stored IDF of the signal source. Thus, for each signal source, the server may also store the IDF of that signal source when it is determined. Or when the IDF of the signal source is updated, the stored IDF of the signal source is updated.

In this specification, after determining the feature vector of the wireless environment of the designated address, the server may perform similarity calculation on the feature vector of the wireless environment of the current rider position determined in step S102 and the feature vector of the wireless environment of the designated address. To determine whether the rider reaches the specified position according to the calculation result.

Specifically, since the server may determine, for the specific address, a feature vector corresponding to at least one cluster as a feature vector of a wireless environment corresponding to the specific address, the specific address may correspond to feature vectors of multiple wireless environments. Therefore, the server can respectively calculate the similarity of the feature vector of the wireless environment at the current position of the rider and the feature vector of each wireless environment corresponding to the designated address.

And if the similarity between the feature vector of the wireless environment of the current rider position and any feature vector of the wireless environment of the designated address is greater than a first threshold value in the calculation result, determining that the current rider reaches the designated address. Or, if the similarity between the feature vector of the wireless environment of the current rider position and at least two feature vectors of the wireless environment of the designated address is greater than the second threshold, it may also be determined that the current rider reaches the designated address.

The specific calculation process may be determined according to the number of the elements with the same identifier in the two feature vectors and the difference between the feature values corresponding to the elements with the same identifier. For example, the feature vector of the wireless environment of the designated address includes the feature values of the identifiers of 100 signal sources, the feature vector of the wireless environment of the current rider position covers the identifiers of 90 signal sources, the feature value in the feature vector of the wireless environment of the designated address is calculated for each signal source identifier, and after the similarity between the feature value in the feature vector of the wireless environment of the current rider position and the feature value in the feature vector of the wireless environment of the designated address is determined, the similarity between the feature values of the 90 signal sources is determined to be more than 90%, and then the similarity is determined to be greater than the first threshold.

Or, the server may also determine the similarity between the feature vector of the wireless environment at the current rider position and the feature vector of the wireless environment at the specified address by using a method of calculating cosine similarity. Of course, the specific method for calculating the similarity is not limited in this specification, and may be set as needed.

In addition, in this specification, the first threshold is higher than the second threshold, because the result determined by two feature vectors is generally more accurate, and therefore, if it is determined whether the rider reaches the designated address only from one feature vector, the requirement for the determination condition needs to be increased.

Based on the location identification method shown in fig. 1, due to the current development of wireless communication technology, people usually have various wireless signal coverage in their daily life areas. Especially in densely populated areas (e.g., residential areas, shopping malls, office buildings, etc.), the composition of the wireless signals in the environment is further complicated due to the large number and variety of devices transmitting the wireless signals. Moreover, wireless signals transmitted by different devices are not completely consistent, so that the geographic location usually corresponds to a feature vector of the wireless environment. That is, in a certain geographic location, the feature vector of the wireless environment corresponding to the geographic location may be determined, and the geographic location of the acquired feature vector of the wireless environment may be reversely deduced by determining the feature vector of the certain acquired wireless environment. In this specification, the IDF and the signal strength of the signal source corresponding to the destination address are determined by acquiring a large amount of data from the history data corresponding to the history order, so as to determine the feature vector of the wireless environment for distinguishing the destination addresses. When the position of a user needs to be identified, firstly, the wireless environment parameters acquired by the terminal of the current user are acquired, the characteristic vector of the wireless environment of the position where the current user is located is determined, and then whether the current user reaches the specified address is identified according to the wireless environment parameters of the specified address and the characteristic vector of the wireless environment of the position where the current user is located. Through the position identification process provided by the specification, the server can determine whether the rider reaches the designated address or not through the wireless environment parameters acquired by the terminal without waiting for the rider to actively report the position. That is, even if the rider does not actively report the position, whether the rider reaches the designated address can be determined by the wireless environment parameters acquired by the terminal. The situation that misjudgment is caused by illegal operation when the rider actively reports the position is avoided, and whether the rider reaches the designated address can be determined more accurately and efficiently.

In addition, because the wireless environment is more complex at present, the wireless environment is not only reflected in more signal sources, but also reflected in the increase of mobile signal sources (for example, a personal hotspot of a mobile phone moves along with the movement of a holder of the mobile phone, a wireless hotspot carried by a vehicle driving recorder of a vehicle moves along with the movement of the vehicle, and the like). Also, there are cases where the user modifies the WiFi name for network security, or there are WiFi hotspots that are temporarily started. Therefore, in step S1040 in this specification, when the server acquires data collected by the terminal for at least one historical order, to avoid such interference of the WiFi hotspot which occurs accidentally, the server may also screen the WiFi signal source.

In this specification, first, the server may determine, according to a history order within a period of time, at least one signal source corresponding to data collected by a terminal of a history user when the history user arrives at a destination address corresponding to the history order. The period of time may be one week, one month, or the like, and this specification does not limit the period of time. And aiming at each target address, determining a signal source with the ratio of the occurrence frequency to the number of corresponding target address historical orders being smaller than a third threshold value from signal sources corresponding to the target address acquired in the period of time, taking the signal source as an abnormal signal source, and in the subsequent steps, not taking the signal source as a signal source for determining the characteristic vector of the target address any more. For example, if the number of orders needed to reach the destination address a in a week is 100, the number of times a certain signal source b appears is 2, and the third threshold is 70%, the signal source b is not used as a signal source for determining the feature vector of the destination address a. Or, for each target address, determining signal sources with the occurrence frequency not greater than a third number from the signal sources corresponding to the target address acquired in the period of time, and taking the signal sources as abnormal signal sources, wherein the signal sources are not used as signal sources for determining the feature vectors of the target address in the subsequent steps. For example, assuming that the third number is 1 and the number of times a certain signal source b is received at the target address a within one week is 1, it is determined that the signal source b is an abnormal signal source.

Further, since the terminal can acquire the signal sent by the signal source in real time, the server can acquire the data of the signal source received by the terminal in the whole period of the delivery task executed by the rider. However, it is necessary to determine that the rider is getting the data of the signal source at the destination address when executing the housekeeping order, so the server can determine that the rider's terminal receives the data of the signal source for a while before and after the rider reports the arrival at the destination address.

For example, assuming that the rider reports his status both when he is required to reach the target position and when he leaves the target position, the server may obtain the data of the signal source received by the rider's terminal 120s before the rider reaches the target position until the rider leaves the target position.

Furthermore, in order to reduce the amount of data to be acquired and the probability of acquiring the data of the passing mobile signal source, the server may acquire the data of the signal source received by the rider's terminal at a predetermined frequency for a period of time before and after the rider arrives at the destination address.

Continuing with the above example, assume that the rider is at 10: 00a.m. to a target position, and leaving the target position at 10:05a.m., the server can acquire the data of the signal source received by the rider terminal in the period from 10:03a.m. to 10:05a.m., and can determine the signal source corresponding to the target position in a manner of acquiring the data once every 20 s.

In addition, when the signal strength of the signal source is weak as described in step S102, it is difficult to apply because of instability. Similarly, in step S1040, when determining the signal sources of the destination address corresponding to the historical order, the server may also select a second number of preset signal sources as the signal sources corresponding to the destination address according to the sequence from the large signal intensity to the small signal intensity when acquiring the data of the signal sources received by the terminal of the rider according to the preset frequency. The first and second numbers may not be identical, and may be set as required, and the description is not limited.

Further, in this specification, since some public WiFi hotspots have the same identifier, and signals of the WiFi hotspots of the WiFi identifier can be received in many places, so that the identifier set of the WiFi hotspots can be preset manually according to the identifiers of the common public WiFi hotspots in order to reduce the workload of the IDF, and the server can select a signal source that does not belong to the identifier set as the signal source corresponding to the destination address according to the identifier set.

Furthermore, the time from the rider to the target address restricts the time period for the server to determine the signal source, and a similar server can also determine the signal source corresponding to the target address according to the distance between the rider and the target address.

Specifically, since the rider may perform distribution tasks between multiple floors of a moving high-rise building, there may be omissions as to the determination of the signal source based only on the rider arrival time. In addition, since the problem of how to identify whether the rider reaches the designated address after the accuracy of the GPS data is lowered is dealt with in this specification, when the signal source corresponding to the target address is acquired, the server may determine the signal source corresponding to the target address according to the data of the signal source received when the rider is within the designated distance from the target address.

The specified distance may be determined according to the position offset range of the GPS data in the complex environment, for example, the position offset range of the GPS data in the complex environment is usually within 100 meters, and the specified distance may be set to 100 meters. That is, when the GPS data indicates that the rider is within the GPS data positional offset range from the target address, it can be determined that the rider is likely to have reached the target address, and therefore, acquisition of data of the signal source can be started to determine the signal source corresponding to the target address.

Based on the position identification method shown in fig. 1, the embodiment of the present specification further corresponds to a schematic structural diagram of an apparatus for providing position identification, as shown in fig. 4.

Fig. 4 is a schematic structural diagram of an apparatus for location identification provided in an embodiment of the present specification, where the apparatus includes:

the determining module 200 is configured to acquire wireless environment parameters acquired by a terminal of a current user, and determine a feature vector of a wireless environment of a position where the current user is located according to the acquired wireless environment parameters;

an identifying module 202, configured to identify whether the current user arrives at the specified address according to a feature vector of a wireless environment of a location where the current user is located and a feature vector of a wireless environment of the specified address, where the feature vector of the wireless environment of the specified address is determined according to a wireless environment parameter of the specified address.

Optionally, the identifying module 202 is configured to determine, for at least one historical order, at least one signal source corresponding to data collected by a terminal of the historical user when the historical user arrives at a destination address corresponding to the historical order, determine the at least one signal source as a signal source corresponding to the destination address, determine, for the at least one signal source corresponding to the destination address, a feature value of the signal source according to the data collected by the terminal of the historical user and sent by the signal source, and determine, according to the feature value of each signal source whose corresponding destination address is the designated address, a feature vector of a wireless environment of the designated address.

Optionally, the identification module 202 is configured to, for at least one signal source, determine an order quantity of a historical order corresponding to the signal source according to data, which is collected by a terminal of the historical user and sent by the signal source, determine an inverse document frequency of the signal source according to the order quantity of the historical order corresponding to the signal source and a total amount of the historical order, and determine a characteristic value of the signal source according to the inverse document frequency of the signal source.

Optionally, the identifying module 202 is configured to determine, for at least one signal source, a signal strength of the signal source according to the data, collected by the terminal of the history user and sent by the signal source, and determine a characteristic value of the signal source according to the signal strength of the signal source.

Optionally, the identifying module 202 is configured to cluster feature values of signal sources whose target addresses are the designated addresses to obtain a plurality of clusters, select a designated number of feature values according to a descending order of the feature values for at least one cluster, determine a feature vector corresponding to the cluster according to the selected feature values and the identifiers of the signal sources corresponding to the selected feature values, and use the feature vector corresponding to at least one cluster as the feature vector of the wireless environment corresponding to the designated address.

Optionally, the identifying module 202 is configured to perform similarity calculation on the feature vector of the wireless environment of the location where the current user is located and the feature vector of the wireless environment of the specified address, and identify whether the current user reaches the specified address according to a calculation result.

Optionally, the identifying module 202 is configured to use that a similarity between the feature vector of the wireless environment of the current location of the user and any feature vector of the wireless environment of the designated address is greater than a first threshold, and similarities between the feature vector of the wireless environment of the current location of the user and at least two feature vectors of the wireless environment of the designated address are both greater than a second threshold, where the first threshold is higher than the second threshold.

Based on the location identification device shown in fig. 5, the IDF and the signal strength of the signal source corresponding to the destination address are determined by acquiring a large amount of data from the historical data corresponding to the historical order, so as to determine the feature vector of the wireless environment for distinguishing the destination addresses. When the position of a user needs to be identified, firstly, the wireless environment parameters acquired by the terminal of the current user are acquired, the characteristic vector of the wireless environment of the position where the current user is located is determined, and then whether the current user reaches the specified address is identified according to the wireless environment parameters of the specified address and the characteristic vector of the wireless environment of the position where the current user is located. Through the position identification process provided by the specification, the server can determine whether the rider reaches the designated address or not through the wireless environment parameters acquired by the terminal without waiting for the rider to actively report the position. The situation that misjudgment is caused by illegal operation when the rider actively reports the position is avoided, and whether the rider reaches the designated address can be determined more accurately and efficiently.

Embodiments of the present specification also provide a computer-readable storage medium storing a computer program, which can be used to execute any one of the above-mentioned methods of position identification.

Based on the method for location identification shown in fig. 1, the embodiment of the present specification further proposes a schematic structural diagram of the electronic device shown in fig. 5. As shown in fig. 5, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, but may also include hardware required for other services. The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to realize any one of the above location identification methods.

Of course, besides the software implementation, the present specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may be hardware or logic devices.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, 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 apparatus 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 apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. 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 apparatus that comprises the element.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.

Claims

1. A method of location identification, comprising:

2. The method of claim 1, wherein determining the feature vector for the wireless environment for the specified address comprises:

3. The method of claim 2, wherein the determining the characteristic value of the signal source according to the data collected by the terminals of the history users and transmitted by the signal source comprises:

4. The method of claim 2, wherein the determining the characteristic value of the signal source according to the data collected by the terminals of the history users and transmitted by the signal source comprises:

5. The method of claim 2, wherein the determining the eigenvector of the wireless environment of the designated address according to the eigenvalue of each signal source of which the corresponding destination address is the designated address comprises:

6. The method as claimed in claim 5, wherein said identifying whether the current user arrives at the designated address according to the feature vector of the wireless environment of the current user location and the feature vector of the wireless environment of the designated address comprises:

7. The method according to claim 6, wherein it is determined that the current user arrives at the specified address if the calculation result satisfies at least one of the following conditions; the conditions include:

wherein the first threshold is higher than the second threshold.

8. An apparatus for location identification, the apparatus comprising:

9. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-7.

10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-7 when executing the program.