Method, device and computer readable storage medium for state recognition

Abstract

This application discloses a method, apparatus, device, and computer-readable storage medium for state identification, belonging to the field of positioning technology. The method includes: acquiring a first Bluetooth signal received by a device of a target object; determining Bluetooth fingerprint information matching the first Bluetooth signal in a Bluetooth fingerprint database, the Bluetooth fingerprint database including multiple Bluetooth fingerprint information, each Bluetooth fingerprint information corresponding to a location, and the Bluetooth fingerprint information including at least one of the Bluetooth name identifier and manufacturer information corresponding to the Bluetooth fingerprint information; and determining the state identification result of the target object based on the location corresponding to the Bluetooth fingerprint information matching the first Bluetooth signal. This method avoids the need to virtualize a Bluetooth beacon on the merchant's app to help identify the state of the target object, thus making the state identification of the target object not limited by the usage rate of the merchant's app, and improving the reliability of state identification.

Description

Technical Field

[0001] This application relates to the field of positioning technology, and in particular to a method, apparatus, device, and computer-readable storage medium for state recognition. Background Technology

[0002] Location technology is typically used to identify the status of a located object. Taking goods delivery as an example, related technologies use a virtual Bluetooth beacon within the merchant's app (application) to determine if the delivery object is at the pickup location. This beacon emits a Bluetooth signal. Because the effective range of Bluetooth signals is typically short (usually no more than 15 meters under unobstructed conditions), when the delivery object's device receives this Bluetooth signal, it assumes the delivery object is within a certain range of the merchant's pickup location. In this case, the delivery object's status is identified as being at the pickup location; otherwise, it is considered not to be at the pickup location.

[0003] Of the aforementioned technologies, the method of using a virtual Bluetooth beacon in the merchant app to help identify whether the delivery recipient is at the pickup location is limited by the usage rate of the merchant app. Since whether merchants use the merchant app is uncontrollable, this method is easily restricted in its application and has low reliability. Summary of the Invention

[0004] This application provides a method, apparatus, device, and computer-readable storage medium for state identification, which can be used to solve problems in related technologies. The technical solution is as follows:

[0005] On one hand, embodiments of this application provide a method for state recognition, the method comprising:

[0006] Acquire the first Bluetooth signal received by the target device;

[0007] In the Bluetooth fingerprint database, a Bluetooth fingerprint information matching the first Bluetooth signal is determined. The Bluetooth fingerprint database includes multiple Bluetooth fingerprint information, each Bluetooth fingerprint information corresponding to a location. The Bluetooth fingerprint information includes at least one of the Bluetooth name identifier and manufacturer information corresponding to the Bluetooth fingerprint information.

[0008] Based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal, the state recognition result of the target object is determined.

[0009] In one possible implementation, before determining the Bluetooth fingerprint information matching the first Bluetooth signal in the Bluetooth fingerprint database, the method further includes: acquiring a second Bluetooth signal received by the first device; removing Bluetooth signals that do not meet the requirements from the second Bluetooth signal to obtain a third Bluetooth signal; acquiring the Bluetooth fingerprint information corresponding to the third Bluetooth signal; and establishing the Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

[0010] In one possible implementation, the Bluetooth signals that do not meet the requirements in the second Bluetooth signal include at least one of the following: unresolved Bluetooth signals, Bluetooth signals with mobility, and Bluetooth signals that the second device cannot obtain; the second device has a different operating system than the first device, and the third Bluetooth signal is applicable to the operating systems of both the first device and the second device.

[0011] In one possible implementation, establishing the Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal includes: selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal, wherein the target Bluetooth fingerprint information corresponds to a target Bluetooth signal, and the target Bluetooth signal is a Bluetooth signal obtained within a range threshold of the location from the third Bluetooth signal; and establishing the Bluetooth fingerprint database based on the target Bluetooth fingerprint information.

[0012] In one possible implementation, selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal includes: selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on the Wi-Fi fingerprint corresponding to the location; or, clustering the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on a clustering algorithm, and selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on the clustering results.

[0013] In one possible implementation, after establishing the Bluetooth fingerprint database based on the target Bluetooth fingerprint information, the method further includes: updating the Bluetooth fingerprint database at first intervals, wherein the update includes adding new target Bluetooth fingerprint information obtained during the Bluetooth fingerprint database update to the Bluetooth fingerprint database, and removing Bluetooth fingerprint information that is determined to be invalid from the target Bluetooth fingerprint information from the Bluetooth fingerprint database.

[0014] In one possible implementation, removing Bluetooth fingerprint information determined to be invalid from the target Bluetooth fingerprint information from the Bluetooth fingerprint database includes: counting at least two locations where each Bluetooth device appears in the Bluetooth device corresponding to the target Bluetooth fingerprint information; removing Bluetooth fingerprint information where the distance between two of the at least two locations is greater than a distance threshold; generating a polygon corresponding to each target Bluetooth fingerprint information based on a polygon generation algorithm and the at least two locations; and removing target Bluetooth fingerprint information where the area of ​​the polygon is greater than an area threshold during the Bluetooth fingerprint database update.

[0015] In one possible implementation, after determining the state identification result of the target object based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal, the method further includes: after a reference time, reacquiring the Bluetooth signal received by the device of the target object; and in response to the reacquiring Bluetooth signal being different from the first Bluetooth signal, determining the state of the target object based on the reacquiring Bluetooth signal.

[0016] On the other hand, a state recognition device is provided, the device comprising:

[0017] The first acquisition module is used to acquire the first Bluetooth signal received by the target device.

[0018] The first determining module is used to determine Bluetooth fingerprint information that matches the first Bluetooth signal in the Bluetooth fingerprint database. The Bluetooth fingerprint database includes multiple Bluetooth fingerprint information, each Bluetooth fingerprint information corresponds to a location, and the Bluetooth fingerprint information includes at least one of the Bluetooth name identifier and manufacturer information corresponding to the Bluetooth fingerprint information.

[0019] The second determining module is used to determine the state recognition result of the target object based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal.

[0020] In one possible implementation, the device further includes:

[0021] The second acquisition module is used to acquire the second Bluetooth signal received by the first device;

[0022] The removal module is used to remove Bluetooth signals that do not meet the requirements from the second Bluetooth signal to obtain the third Bluetooth signal;

[0023] The third acquisition module is used to acquire the Bluetooth fingerprint information corresponding to the third Bluetooth signal;

[0024] A module is established to build the Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

[0025] In one possible implementation, the Bluetooth signals that do not meet the requirements in the second Bluetooth signal include at least one of the following: unresolved Bluetooth signals, Bluetooth signals with mobility, and Bluetooth signals that the second device cannot obtain; the second device has a different operating system than the first device, and the third Bluetooth signal is applicable to the operating systems of both the first device and the second device.

[0026] In one possible implementation, the establishing module is used to select target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal, wherein the target Bluetooth fingerprint information corresponds to a target Bluetooth signal, and the target Bluetooth signal is a Bluetooth signal obtained within a range threshold of the location from the third Bluetooth signal; and to establish the Bluetooth fingerprint database based on the target Bluetooth fingerprint information.

[0027] In one possible implementation, the establishment module is configured to select the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on the Wi-Fi fingerprint corresponding to the location; or, to cluster the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on a clustering algorithm, and select the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal according to the clustering result.

[0028] In one possible implementation, the device further includes:

[0029] An update module is used to update the Bluetooth fingerprint database at a first time interval. The update includes adding new target Bluetooth fingerprint information obtained during the update of the Bluetooth fingerprint database into the Bluetooth fingerprint database, and removing Bluetooth fingerprint information that is determined to be invalid from the target Bluetooth fingerprint information from the Bluetooth fingerprint database.

[0030] In one possible implementation, the update module is configured to: count at least two locations where each Bluetooth device appears in the Bluetooth devices corresponding to the target Bluetooth fingerprint information; remove Bluetooth fingerprint information where the distance between two of the at least two locations is greater than a distance threshold; generate a polygon corresponding to each target Bluetooth fingerprint information based on a polygon generation algorithm and the at least two locations; and remove target Bluetooth fingerprint information where the area of ​​the polygon is greater than an area threshold during the Bluetooth fingerprint database update.

[0031] In one possible implementation, the second determining module is further configured to reacquire the Bluetooth signal received by the device of the target object after a reference duration; and to determine the state of the target object based on the reacquired Bluetooth signal if the reacquired Bluetooth signal is different from the first Bluetooth signal.

[0032] On the other hand, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor to enable the computer device to implement any of the above-described state recognition methods.

[0033] On the other hand, a computer-readable storage medium is also provided, wherein at least one computer program is stored therein, the at least one computer program being loaded and executed by a processor to enable a computer to implement any of the above-described methods for state recognition.

[0034] On the other hand, a computer program product or computer program is also provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium, a processor of a computer device reading the computer instructions from the computer-readable storage medium, and the processor executing the computer instructions, causing the computer device to perform any of the above-described state recognition methods.

[0035] The technical solution provided in this application has at least the following beneficial effects:

[0036] The technical solution provided in this application obtains the first Bluetooth signal received by the target object's device, then determines the Bluetooth fingerprint information matching the first Bluetooth signal in the Bluetooth fingerprint database. Subsequently, based on the location corresponding to the Bluetooth fingerprint information matching the first Bluetooth signal, the status identification result of the target object is determined. This method avoids the need to create a virtual Bluetooth beacon on the merchant's app to help identify the target object's status, thus making the status identification of the target object unrestricted by the merchant's app usage rate and improving the accuracy of status identification. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of the implementation environment of a state recognition method provided in an embodiment of this application;

[0039] Figure 2 This is a flowchart of a state recognition method provided in an embodiment of this application;

[0040] Figure 3 This is a schematic diagram illustrating the distribution of Bluetooth fingerprint information provided in an embodiment of this application;

[0041] Figure 4 This is a flowchart illustrating how to select target Bluetooth fingerprint information from Bluetooth fingerprint information corresponding to a third Bluetooth signal based on WiFi fingerprinting, as provided in an embodiment of this application.

[0042] Figure 5 This is a schematic diagram illustrating various time periods of goods delivery provided in an embodiment of this application;

[0043] Figure 6 This is a schematic diagram of a Bluetooth list provided in an embodiment of this application;

[0044] Figure 7 This is an overall framework diagram of Bluetooth fingerprint generation and Bluetooth fingerprint matching provided in an embodiment of this application;

[0045] Figure 8 This is a schematic diagram of a state recognition device provided in an embodiment of this application;

[0046] Figure 9 This is a schematic diagram of the structure of a server provided in an embodiment of this application;

[0047] Figure 10 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0049] It should be noted that the terms "first," "second," etc. (if applicable) in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0050] In goods delivery, especially on-demand delivery, the recipient often needs to complete the fulfillment of the order (or delivery order) within a certain timeframe, including arriving at the pickup location, picking up the goods, and delivering them. During this process, the recipient typically needs to travel between multiple shopping malls and residential buildings, and even make multiple trips between the same mall and building. Therefore, identifying the recipient's current status has a significant impact on delivery efficiency. For example, when assigning a new order, it's necessary to consider whether the recipient's current status is suitable for receiving the new order.

[0051] Taking goods delivery as an example, the methods provided in related technologies for identifying the status of delivery objects include: Method 1, GPS (Global Positioning System) positioning + delivery object actively reporting; Method 2, WiFi (Wireless Fidelity) fingerprint recognition of the status of delivery objects; Method 3, virtual Bluetooth beacon in the merchant's App to help identify the status of delivery objects.

[0052] When identifying the status of delivery objects using Method 1, the poor accuracy of GPS positioning indoors and its inability to represent three-dimensional space mean that determining the status of delivery objects relies heavily on their proactive reporting. However, whether or not the delivery object proactively reports its status is uncontrollable. Therefore, identifying the status of delivery objects using Method 1 is limited by whether the delivery object reports its status and by the accuracy of GPS positioning indoors.

[0053] Method 2, which identifies the status of the delivery recipient, somewhat compensates for the shortcomings of Method 1. Based on WiFi fingerprinting, it can effectively identify whether the delivery recipient is at the pickup location or destination. Therefore, the status of the delivery recipient can be determined directly based on whether the device used to receive the waybill receives a specific WiFi signal. For example, if the device receives a WiFi signal specific to the pickup location, it can be determined that the delivery recipient is within a certain range of the pickup location, thus identifying the delivery recipient's status as being at the pickup location. However, Method 2 also has certain drawbacks. Devices running different operating systems have different restrictions on WiFi signal scanning. This means that a second device using an operating system with higher WiFi signal scanning restrictions cannot determine its location based on WiFi fingerprinting. Therefore, when the delivery recipient uses a second device to receive the waybill, Method 2 cannot identify the delivery recipient's status.

[0054] The principle behind identifying the delivery recipient's status using Method 3 is as follows: A Bluetooth signal is emitted via a Bluetooth beacon. If the device used to receive the delivery order receives this signal, it indicates that the delivery recipient is within a certain range of the merchant's device (the device on which the merchant's app is installed). When this merchant's device is at the pickup location, the delivery recipient's status can be considered to be at the pickup location. Method 3 avoids the problems of Methods 1 and 2, but it also has its own limitations. For example, it is restricted by the merchant's app usage rate. Whether a merchant uses the app is uncontrollable, and even if the delivery recipient's device receives the Bluetooth signal when the merchant's device is not at the pickup location, it only indicates that the delivery recipient is near the merchant's device, not that it is at the pickup location. Therefore, Method 3 is easily limited. Furthermore, only about 30% of merchants actually use the merchant app.

[0055] In addition to the three methods mentioned above for identifying the status of delivery recipients, there is also a method of identifying whether the delivery recipient is at the pickup location by directly deploying Bluetooth devices at the pickup location. The drawback of this method is its high cost.

[0056] To address this issue, this application provides a method for state recognition that eliminates the need for direct deployment of Bluetooth devices, thus saving on the cost of implementing state recognition and avoiding the problems associated with methods 1, 2, and 3 provided by related technologies. Please refer to... Figure 1 The diagram illustrates the implementation environment of the method provided in this embodiment. This implementation environment may include: terminal 11 and server 12.

[0057] Terminal 11 can acquire Bluetooth and WiFi signals and upload them to server 12. Terminal 11 can also filter the acquired Bluetooth signals, save the target Bluetooth fingerprint information corresponding to the filtered target Bluetooth signals, and upload it to server 12. Server 12 can save the Bluetooth signals uploaded by terminal 11, filter the Bluetooth signals, save the target Bluetooth fingerprint information corresponding to the filtered target Bluetooth signals, and send it to terminal 11. Server 12 can also directly acquire Bluetooth and WiFi signals.

[0058] Optionally, terminal 11 can be any electronic product capable of human-computer interaction with the user through one or more methods such as a keyboard, touchpad, touchscreen, remote control, voice interaction, or handwriting device, such as PC (Personal Computer), mobile phone, smartphone, PDA (Personal Digital Assistant), wearable device, PPC (Pocket PC), tablet computer, smart car system, smart TV, smart speaker, etc. Server 12 can be a single server, a server cluster consisting of multiple servers, or a cloud computing service center. Terminal 11 and server 12 establish a communication connection through wired or wireless network.

[0059] Those skilled in the art should understand that the terminal 11 and server 12 described above are merely examples. Other existing or future terminals or servers that are applicable to this application should also be included within the scope of protection of this application, and are hereby incorporated by reference. Furthermore, it should be noted that all actions involving the acquisition of signals, information, or data in this application are performed with the authorization of the respective device owner.

[0060] Based on the above Figure 1 The implementation environment shown in this application embodiment provides a state recognition method, which is executed by a computer device, which can be a server 12 or a terminal 11, and this application embodiment does not limit it. Figure 2 As shown, the method provided in this application embodiment may include steps 201 and 202.

[0061] In step 201, the first Bluetooth signal received by the target object's device is acquired. A Bluetooth fingerprint matching the first Bluetooth signal is determined from a Bluetooth fingerprint database. The Bluetooth fingerprint database includes multiple Bluetooth fingerprints, each corresponding to a location. Each Bluetooth fingerprint includes at least one of the Bluetooth name identifier and manufacturer information. The target object is the object to be identified, such as a delivery object used to receive and deliver waybills. Acquiring the first Bluetooth signal received by the target object's device is equivalent to acquiring the first Bluetooth signal received by the device of the object to be identified. The number of first Bluetooth signals may be one or more; this embodiment does not limit this.

[0062] In an exemplary embodiment, when identifying the state of a target object, the number of first Bluetooth signals received by the target object's device needs to be no less than a first preset value. If the number of first Bluetooth signals is less than the first preset value, the number of first Bluetooth signals that match the Bluetooth fingerprint information in the Bluetooth fingerprint database will also be less. A smaller number of matches makes it easier to be interfered with when using the matching results to determine the state of the target object, resulting in an inaccurate determination of the state.

[0063] Before explaining why the number of first Bluetooth signals being less than a first set value leads to inaccurate determination of the target object's status, it's necessary to first introduce the principle of Bluetooth fingerprint-based target object status recognition. Typically, the effective range of Bluetooth signals emitted by Bluetooth devices is relatively short, for example, generally not exceeding 15 meters. Therefore, when a device receives a Bluetooth signal, it's assumed that the distance between the user corresponding to that device and the device itself is no more than 15 meters. In this case, the user can be considered to be within a certain distance (15 meters) of the device. Thus, when the Bluetooth device is fixed in one location, and the user's personal device receives the Bluetooth signal emitted by that device, it's assumed that the user is within a certain distance of that location. At this point, the user's status can be determined as being at that location.

[0064] After clarifying the principle of Bluetooth fingerprint recognition for identifying the status of a target object, it is necessary to explain different scenarios. For example, when the target object is required to be within 50 meters of location A, the target object is considered to be at location A. There are 10 Bluetooth fingerprint records within 50 meters of location A, and the distribution of these 10 Bluetooth fingerprint records is as follows: Figure 3 As shown. From Figure 3 As can be seen, the distance from Bluetooth fingerprint information M to location A is 45 meters. This means that the target object can receive Bluetooth fingerprint information M when it is 60 meters away from location A (assuming the effective range of the Bluetooth signal is 15 meters). Therefore, it is unreasonable to determine that the target object is within 50 meters of location A if the first Bluetooth signal received by the target object's device matches one of the 10 Bluetooth fingerprint information.

[0065] Therefore, in the exemplary embodiment, the reason why the number of first Bluetooth signals received by the target object's device is not less than a first preset value when identifying the state of the target object is that: the more first Bluetooth signals there are, the more first Bluetooth signals will match the Bluetooth fingerprint information included in the Bluetooth fingerprint database, and the more first Bluetooth signals and Bluetooth fingerprint information match, the more accurate the state identification result of the target object will be. The size of the first preset value is an empirical setting or may be adjusted based on the application scenario; this embodiment does not limit it.

[0066] In another exemplary embodiment, to avoid wasting computing resources due to a small number of first Bluetooth signals, after acquiring the first Bluetooth signal received by the target device, the number of first Bluetooth signals is first identified. If the number of first Bluetooth signals is less than a first preset value, subsequent state identification steps are not performed, thereby avoiding waste of computing resources. If the number of first Bluetooth signals is not less than the first preset value, subsequent steps are performed. The accuracy of the result obtained by identifying the state of the target object based on the first Bluetooth signals at this time is high.

[0067] In an exemplary embodiment, the Bluetooth fingerprint database includes multiple Bluetooth fingerprint information entries, each corresponding to a location. Bluetooth fingerprint information entries corresponding to the same location can be grouped into the same group within the Bluetooth fingerprint database, which can be called a Bluetooth fingerprint sub-database. Since the Bluetooth fingerprint information entries in the sub-database correspond to the same location, one sub-database corresponds to one location. The Bluetooth fingerprint information included in the Bluetooth fingerprint database is information that can uniquely identify a Bluetooth signal; that is, one Bluetooth fingerprint entry corresponds to one Bluetooth signal. In an exemplary embodiment, the Bluetooth fingerprint information can be at least one of the following: manufacturer information and name identifier corresponding to the Bluetooth signal, which can uniquely identify the Bluetooth signal. In an exemplary embodiment, before determining the Bluetooth fingerprint information matching the first Bluetooth signal in the Bluetooth fingerprint database, the Bluetooth fingerprint database needs to be established first. The process of establishing the Bluetooth fingerprint database includes steps 2011 to 2013.

[0068] Step 2011: Obtain the second Bluetooth signal received by the first device, remove the Bluetooth signals in the second Bluetooth signal that do not meet the requirements, and obtain the third Bluetooth signal.

[0069] For example, the first device is a device that can be located using WiFi fingerprinting. In an exemplary embodiment, acquiring the second Bluetooth signal received by the first device includes: acquiring the Bluetooth signal received by the first device at regular intervals to obtain a second Bluetooth signal, wherein there are multiple second Bluetooth signals. In an exemplary embodiment, Bluetooth signals that do not meet the requirements among the second Bluetooth signals include at least one of the following: unresolvable Bluetooth signals, mobile Bluetooth signals, and Bluetooth signals that the second device cannot acquire. For example, whether the second Bluetooth signal has mobility is determined by the name in the first device when the second Bluetooth signal is received by the first device.

[0070] In an exemplary embodiment, the second device operates a different operating system than the first device, resulting in different limitations on WiFi signal scanning between the two devices. In this exemplary embodiment, the first device has fewer limitations on WiFi signal scanning than the second device; for example, the first device can receive more WiFi signals than the second device. In one possible implementation, the target device can belong to either the first or the second device; this embodiment does not impose any restrictions on this.

[0071] It should be noted that among devices corresponding to different operating systems, all devices other than the first type are classified as second type devices. For example, if operating system 1 corresponds to one type of device, operating system 2 to another, and operating system 3 to yet another, when determining which type of device is the first type, the device corresponding to operating systems 1-3 that has the fewest restrictions on WiFi signal scanning and can be located using WiFi fingerprinting can be selected as the first type. Devices corresponding to the other two operating systems are considered second type devices. For another example, if the device corresponding to operating system 1 has the fewest restrictions on WiFi signal scanning and can be located using WiFi fingerprinting, then the device corresponding to operating system 1 is selected as the first type, and devices corresponding to operating systems 2 and 3 are both considered second type devices.

[0072] In an exemplary embodiment, unresolvable Bluetooth signals in the second Bluetooth signal include: Bluetooth information in the second Bluetooth signal from which identifying information cannot be extracted. The reason for removing unresolvable Bluetooth signals is that when an unresolvable Bluetooth signal changes its name, it will be considered a different Bluetooth signal, leading to misidentification and inaccurate identification when using that signal to determine the state of a target object.

[0073] In an exemplary embodiment, the inclusion of mobile Bluetooth signals in the second Bluetooth signal includes: when the second Bluetooth signal is received by the first device, determining that the Bluetooth signal is mobile based on the name displayed on the first device. For example, if a Bluetooth signal is displayed on the first device as "XXX Bluetooth Headset," this name indicates that the Bluetooth device corresponding to the signal is mobile, thus confirming the mobility of the Bluetooth signal. In practice, removing mobile Bluetooth signals by their names on the first device can filter out approximately 40% of the Bluetooth signals in the second Bluetooth signal. The Bluetooth devices corresponding to the filtered signals include, but are not limited to, Bluetooth headsets, Bluetooth wristbands, bicycles, etc.

[0074] In an exemplary embodiment, the second Bluetooth signal includes Bluetooth signals that the second device can acquire. Therefore, after removing Bluetooth signals that the second device cannot acquire from the second Bluetooth signal, the resulting third Bluetooth signal is not empty. The advantage of removing these unacquired Bluetooth signals from the second Bluetooth signal is that it makes the state recognition result of the target object independent of the type of device used by the target object. If the unacquired Bluetooth signals from the second Bluetooth signal are not removed, the third Bluetooth signal may contain unacquired Bluetooth signals. Consequently, the Bluetooth fingerprint database established based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal may contain Bluetooth fingerprint information that the second device cannot acquire. Therefore, when performing state recognition on a target object, the result may differ depending on the type of device used by the target object.

[0075] For example, when a third Bluetooth signal is received, Bluetooth signals that the second device cannot obtain are not removed from the second Bluetooth signal. If the target device is the first device, the number of Bluetooth fingerprints matching the third Bluetooth signal in the Bluetooth fingerprint database is 4. If the target device is the second device, the number of Bluetooth fingerprints matching the third Bluetooth signal in the Bluetooth fingerprint database is 3. If the required number of matches is less than 4, the target is considered not at the target location; if the number of matches is not less than 4, the target is considered at the target location. In this case, the result of the target's status identification varies depending on the target device type.

[0076] In the exemplary embodiment, the third Bluetooth signal is applicable to the operating systems of both the first and second devices. Since the third Bluetooth signal is the Bluetooth signal remaining after removing Bluetooth signals that do not meet the conditions from the second Bluetooth signal, and the second Bluetooth signal is acquired by the first device, the third Bluetooth signal is applicable to the first device. However, whether the third Bluetooth signal is applicable to the second device requires consideration on a case-by-case basis. If the second Bluetooth signal does not contain Bluetooth signals that the second device cannot acquire, then even without removing the unacquired Bluetooth signals, the resulting third Bluetooth signal is also applicable to the second device. If the second Bluetooth signal includes Bluetooth signals that the second device cannot acquire, then the third Bluetooth signal obtained by removing the unacquired Bluetooth signals from the second Bluetooth signal is also applicable to the second device.

[0077] It should be noted that the embodiments of this application do not limit the relationship between the Bluetooth signals obtainable by the first device and the Bluetooth signals obtainable by the second device. Optionally, the Bluetooth signals obtainable by the first device include the Bluetooth signals obtainable by the second device. Optionally, the Bluetooth signals obtainable by the second device include the Bluetooth signals obtainable by the first device. In this case, when removing the Bluetooth signals in the second Bluetooth signal that do not meet the requirements to obtain the third Bluetooth signal, even if the Bluetooth signals that the second device cannot obtain are removed, the third Bluetooth signal is still applicable to the second device. Optionally, the Bluetooth signals obtainable by the first device and the Bluetooth signals obtainable by the second device may have overlap and differences.

[0078] Step 2012: Obtain the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

[0079] In an exemplary embodiment, after obtaining the third Bluetooth signal, it needs to be converted into Bluetooth fingerprint information that uniquely identifies the third Bluetooth signal. The name of the third Bluetooth signal can be changed, but the Bluetooth fingerprint information of the third Bluetooth signal will not change. Exemplarily, obtaining the Bluetooth fingerprint information corresponding to the third Bluetooth signal includes: parsing the third Bluetooth signal to obtain the Bluetooth fingerprint information that uniquely identifies the third Bluetooth signal. This application embodiment does not limit the content of the third Bluetooth signal that the Bluetooth fingerprint information is; any content that can uniquely identify the third Bluetooth signal can be used as the Bluetooth fingerprint information. Optionally, the Bluetooth fingerprint information includes at least one of the Bluetooth name identifier and manufacturer information corresponding to the third Bluetooth signal.

[0080] Step 2013: Establish a Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

[0081] In an exemplary embodiment, the process of establishing a Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal includes: selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal; and then establishing a Bluetooth fingerprint database based on the target Bluetooth fingerprint information. In an exemplary embodiment, the methods for selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal include: Method 1, selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on a Wi-Fi fingerprint corresponding to a location; Method 2, clustering the Bluetooth fingerprint information corresponding to the third Bluetooth signal using a clustering algorithm, and selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on the clustering results. Wherein, as... Figure 4 As shown, the process of selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on method 1 includes steps 201A to 201C.

[0082] Step 201A: Classify the second Bluetooth signal based on the Wi-Fi fingerprint corresponding to the location to obtain the first Bluetooth set and the second Bluetooth set.

[0083] In an exemplary embodiment, between a first time point and a second time point, a Bluetooth set is acquired from the first device at regular intervals, and the Bluetooth signals included in all the obtained Bluetooth sets are the second Bluetooth signals. For example... Figure 5 As shown, taking goods delivery as an example, the first time point is the time when the delivery recipient accepts the order, and the second time point is the time when the delivery recipient delivers the goods to the customer (customer delivery). The Bluetooth signals included in different Bluetooth sets can overlap. For example, consider two consecutively acquired Bluetooth sets, Bluetooth set A and Bluetooth set B. Bluetooth set A includes 20 Bluetooth signals: Bluetooth signal 1 to Bluetooth signal 20, and Bluetooth set B includes 20 Bluetooth signals: Bluetooth signal 1 to Bluetooth signal 19, and Bluetooth signal 21. It can be seen that Bluetooth set A and Bluetooth set B have 19 overlapping Bluetooth signals.

[0084] In an exemplary embodiment, the WiFi fingerprint is used to locate the first device, and each WiFi fingerprint information included in the WiFi fingerprint corresponds to a location. When the WiFi signal received by the first device matches the WiFi fingerprint information included in the WiFi fingerprint, the first device is considered to be at the location corresponding to that WiFi fingerprint information.

[0085] In an exemplary embodiment, classifying the second Bluetooth signal based on the WiFi fingerprint to obtain a first Bluetooth set and a second Bluetooth set includes: binary classification of the second Bluetooth signal based on the WiFi fingerprint; the first Bluetooth set includes second Bluetooth signals acquired within a range threshold of the target location, and the second Bluetooth set includes second Bluetooth signals acquired outside the range threshold of the target location. The second Bluetooth signals acquired within the range threshold of the target location may exist in only one first Bluetooth set or may exist in different first Bluetooth sets. That is, the number of first Bluetooth sets can be one or more, and the number of first Bluetooth sets is determined by the number of Bluetooth sets corresponding to the second Bluetooth signals acquired within the range threshold of the target location.

[0086] Similarly, the second Bluetooth signal acquired outside the range threshold of the target location may exist in only one second Bluetooth set, or it may exist in different second Bluetooth sets. That is to say, the number of second Bluetooth sets can be one or more, and the number of second Bluetooth sets is determined by the number of Bluetooth sets corresponding to the second Bluetooth signal acquired outside the range threshold of the target location. Here, the range threshold is a set value, and this application does not limit it.

[0087] Taking goods delivery as an example, if the pickup location is the target location for delivery, then the first Bluetooth set is the set of Bluetooth signals corresponding to the second Bluetooth signals obtained within a threshold range of the pickup location, based on WiFi fingerprint classification. In other words, when the delivery object appears within the threshold range of the pickup location, the Bluetooth set corresponding to the Bluetooth signal obtained from the first device of the delivery object is the first Bluetooth set. Figure 5 As shown, the time period corresponding to the delivery object appearing within the pickup location's range threshold is the pickup location time period. The second Bluetooth set is the Bluetooth set corresponding to the second Bluetooth signal obtained outside the pickup location's range threshold based on WiFi fingerprint classification. That is, when the delivery object appears outside the pickup location's range threshold, the Bluetooth set corresponding to the Bluetooth signal obtained from the delivery object's first device is the second Bluetooth set. For example... Figure 5 As shown, the time period corresponding to the delivery object appearing outside the range threshold of the pickup location is the time period when the delivery is not at the pickup location.

[0088] It should be noted that the set of Bluetooth signals obtained from the device each time is called a Bluetooth set, and the Bluetooth set can be represented in the device as a Bluetooth list. One type of Bluetooth list is as follows: Figure 6 As shown.

[0089] Step 2011 mentions that the device's restrictions on WiFi signal scanning affect the establishment of a Bluetooth fingerprint database. This impact includes: if the device's restrictions on WiFi signal scanning are too significant, making it impossible for the device to locate itself based on WiFi fingerprints, then a Bluetooth fingerprint database cannot be established based on that device. In the exemplary embodiment, because the second device's restrictions on WiFi signal scanning are greater than those of the first device, this application embodiment establishes the Bluetooth fingerprint database based on the first device.

[0090] Step 201B: Determine the first frequency at which each Bluetooth fingerprint information corresponding to the third Bluetooth signal appears in the first Bluetooth set and the second frequency at which it appears in the second Bluetooth set.

[0091] In an exemplary embodiment, any third Bluetooth signal may appear in multiple Bluetooth sets. Taking goods delivery as an example, after the delivery object arrives at the pickup location, it stays there for a period of time. During this period, the first device of the delivery object is sampled multiple times, corresponding to multiple Bluetooth sets. Since the distance the delivery object moves is negligible compared to the effective range of the Bluetooth signal, the repetition rate of Bluetooth signals obtained from different samplings is high during the time the delivery object stays at the pickup location. For example, two adjacent samplings of Bluetooth signals correspond to two Bluetooth sets, namely Bluetooth set A and Bluetooth set B. Bluetooth set A includes 25 Bluetooth signals, and Bluetooth set B includes 26 Bluetooth signals. The Bluetooth signals contained in Bluetooth set B include the Bluetooth signals contained in Bluetooth set A.

[0092] In one possible implementation, there are multiple first Bluetooth sets and multiple second Bluetooth sets. Determining the first frequency at which each Bluetooth fingerprint information corresponding to a third Bluetooth signal appears in the first Bluetooth set includes: calculating the ratio of the number of times each Bluetooth fingerprint information corresponding to the third Bluetooth signal appears in the first Bluetooth set to the number of first Bluetooth sets. For example, if one Bluetooth fingerprint information corresponding to the third Bluetooth signal is Bluetooth fingerprint information A, and there are 30 first Bluetooth sets, and Bluetooth fingerprint information A appears in 15 of them, then the frequency of Bluetooth fingerprint information A appearing in the first Bluetooth sets is 0.5. For example, if there are 30 first Bluetooth sets and 30 Bluetooth sets appearing with Bluetooth fingerprint information A, then the frequency of Bluetooth fingerprint information A appearing in the first Bluetooth sets is 1, that is, the first frequency corresponding to Bluetooth fingerprint information A is 1.

[0093] In one possible implementation, determining the second frequency at which each Bluetooth fingerprint information corresponding to a third Bluetooth signal appears in a second Bluetooth set includes: calculating the ratio of the number of times the Bluetooth fingerprint information corresponding to each third Bluetooth signal appears in the second Bluetooth set to the number of second Bluetooth sets. For example, if there are 100 second Bluetooth sets, and Bluetooth fingerprint information A appears in 2 of them, then the frequency of Bluetooth fingerprint information A appearing in the second Bluetooth sets is 0.02, meaning the second frequency corresponding to Bluetooth fingerprint information A is 0.02.

[0094] Step 201C: Select the Bluetooth fingerprint information in the Bluetooth fingerprint information corresponding to the third Bluetooth signal whose first frequency exceeds the second frequency by a value greater than the frequency threshold as the target Bluetooth fingerprint information.

[0095] In an exemplary embodiment, when establishing the Bluetooth fingerprint database, Bluetooth fingerprint information that can effectively distinguish the state of a target object should be included in the Bluetooth fingerprint database, that is, the target Bluetooth fingerprint information should be included in the Bluetooth fingerprint database. When the value of the first frequency exceeding the second frequency in the Bluetooth fingerprint information corresponding to the third Bluetooth signal is greater than a frequency threshold, it is considered that the Bluetooth fingerprint information can effectively identify whether the target object is within the range threshold of the target location. Therefore, it is considered that the Bluetooth fingerprint information can effectively distinguish the state of the target object, that is, the Bluetooth fingerprint information is the target Bluetooth fingerprint information. Here, the frequency threshold is a set value, and this embodiment of the application does not limit it.

[0096] For example, one of the Bluetooth fingerprint information corresponding to the third Bluetooth signal is Bluetooth fingerprint information B. The first frequency of Bluetooth fingerprint information B is 0.6, the second frequency is 0.01, and the frequency threshold is 0.5. After calculation, Bluetooth fingerprint information B can be used as the target Bluetooth fingerprint information.

[0097] In another exemplary embodiment, selecting target Bluetooth fingerprint information from Bluetooth fingerprint information corresponding to the third Bluetooth signal based on method 2 includes: selecting target Bluetooth fingerprint information from Bluetooth fingerprint information corresponding to the third Bluetooth signal based on clustering algorithm, wherein steps 2011A to 2011E are steps of the process of selecting target Bluetooth fingerprint information in method 2.

[0098] Step 2011A: Vectorize the Bluetooth fingerprint information corresponding to the third Bluetooth signal to obtain a fingerprint vector set. Select two base fingerprint vectors from the fingerprint vector set as the first initial cluster center and the second initial cluster center of the fingerprint vector set.

[0099] When clustering the third Bluetooth signal using a clustering algorithm, this application embodiment does not limit the specific clustering algorithm; for example, it can use the K-means clustering algorithm. When using K-means clustering, it is necessary to determine the location of the Bluetooth fingerprint information corresponding to the third Bluetooth signal. Typically, the effective range of a Bluetooth signal is small; when devices are not compatible, the effective range of a Bluetooth signal generally does not exceed 15 meters. Therefore, it can be considered that the location of the device that collected the Bluetooth signal is the location of the Bluetooth signal itself. Since the location of the third Bluetooth signal is the same as the location of the corresponding Bluetooth fingerprint information, the location of the Bluetooth fingerprint information corresponding to the third Bluetooth signal is considered to be the location of the first device that collected the third Bluetooth signal.

[0100] In one possible implementation, the Bluetooth fingerprint information corresponding to the third Bluetooth signal is vectorized to obtain a fingerprint vector set. This includes: using one-hot encoding to vectorize the Bluetooth fingerprint information corresponding to the third Bluetooth signal, resulting in the same number of fingerprint vectors as the Bluetooth fingerprint information corresponding to the third Bluetooth signal. This set of fingerprint vectors is called the fingerprint vector set. Two base fingerprint vectors are selected from the fingerprint vector set as the first and second initial cluster centers. This includes: randomly selecting two fingerprint vectors from all fingerprint vectors included in the fingerprint vector set as base fingerprint vectors, and using these two base fingerprint vectors as the two initial cluster centers for K-means clustering, i.e., the first initial cluster center and the second initial cluster center.

[0101] It should be noted that there can be multiple initial cluster centers (two or more). That is, when selecting the base fingerprint vector, multiple fingerprint vectors can be selected as cluster centers. This application does not limit the number of cluster centers, and can be set according to experience.

[0102] Step 2011B: Calculate the distance x from each fingerprint vector in the fingerprint vector set to the first initial cluster center. 1i and the distance x to the second initial cluster center 2i And classify each fingerprint vector in the fingerprint vector set into x. 1i and x 2i In the class corresponding to the smaller median value.

[0103] Since one cluster center corresponds to one cluster, selecting two base fingerprint vectors as initial cluster centers in step 2011A results in two corresponding clusters: the first initial cluster and the second initial cluster. In one possible implementation, the distance x from each fingerprint vector in the fingerprint vector set to the first initial cluster center is calculated. 1i and the distance x to the second initial cluster center 2i This includes: calculating the position of each target Bluetooth fingerprint in the target Bluetooth fingerprint information corresponding to the fingerprint vector set, and the distance x to the position of the target Bluetooth fingerprint information corresponding to the first initial cluster center. 1i And the distance x to the location of the target Bluetooth fingerprint information corresponding to the second initial cluster center. 2i The location of the target Bluetooth fingerprint information has already been described in step 2011A and will not be repeated here. For example, the distances from the fingerprint vectors in the fingerprint vector set to the first initial cluster center are respectively: x 11 x 12 x 13 …x 1n The distances to the second initial cluster centers are: x 21 x 22 x 23 …x2n .

[0104] In one possible implementation, each fingerprint vector in the fingerprint vector set is classified into x. 1i and x 2i The classes corresponding to smaller median values ​​include: when x 1i >x 2i When x..., the fingerprint vector obtained at that distance is classified into the second initial class corresponding to the second initial cluster center. 1i <x 2i When the distance is obtained, the fingerprint vector is classified into the first initial class corresponding to the first initial cluster center. For example, the distance from a fingerprint vector 1 in the fingerprint vector set to the first initial cluster center is x. 11 The distance to the second initial cluster center is x. 21 When x 11 <x 21 When x..., fingerprint vector 1 is classified into the first initial class corresponding to the first initial cluster center. 11 >x 21 At that time, fingerprint vector 1 is classified into the second initial class corresponding to the second initial cluster center.

[0105] Step 2011C: Recalculate the cluster center of the class such that the sum of the distances from the positions corresponding to the fingerprint vectors in the class to the cluster center is minimized.

[0106] In one possible implementation, the cluster centers of the classes are recalculated, including reselecting cluster centers from the first and second initial classes based on the classification of fingerprint vectors in the fingerprint vector set into the first and second initial classes in step 2011B. The reselected clusters should satisfy the condition that the sum of the distances from the positions of all fingerprint vectors in the class containing the cluster center to the cluster center is minimized.

[0107] Step 2011D: Repeat steps 2011B and 2011C. When the termination condition is met, take the cluster center that is closer to the target location from the cluster center's location as the target class.

[0108] In one possible implementation, steps 2011B and 2011C are repeated, including: based on the new cluster centers obtained in step 2011C, the fingerprint vector set is clustered again based on the new cluster centers. After clustering is completed, step 2011C is repeated to select a new round of cluster centers, until a termination condition is met, at which point the loop of steps 2011B and 2011C stops. In another possible implementation, the termination condition is that the fingerprint vectors contained in each class no longer change, or steps 2011B and 2011C are repeated for a certain number of rounds. Fingerprint vectors within the target location's range threshold have the characteristic of being geographically close to the target location. Due to this characteristic, fingerprint vectors within the target location's range threshold will eventually be clustered into the same class, and the cluster center of this class is geographically closer to the target location than the cluster center of another class. After determining the cluster center that is geographically closer to the target location, the class corresponding to this cluster center is taken as the target class.

[0109] Step 2011E: Select the Bluetooth fingerprint information corresponding to the first second set value fingerprint vectors in the target class as the target Bluetooth fingerprint information.

[0110] The reason for selecting the Bluetooth fingerprint information corresponding to the second-to-first set number of fingerprint vectors in the target class as the target Bluetooth fingerprint information is that the second-to-first set number of fingerprint vectors in the target class can more effectively distinguish whether the target object is near the target location. In the classes obtained based on K-means clustering, the earlier samples have more obvious common features. In the fingerprint vector set, the fingerprint vectors are distributed around the target location and show a certain degree of clustering near the target location. Therefore, selecting the Bluetooth fingerprint information corresponding to the second-to-first set number of fingerprint vectors is to select Bluetooth fingerprint information that is closer to the target location. The second set value is an empirical value, and this embodiment does not limit it; it can be set based on experience.

[0111] In an exemplary embodiment, after obtaining the target Bluetooth fingerprint information, the process of establishing a Bluetooth fingerprint database based on the target Bluetooth fingerprint information includes: establishing the Bluetooth fingerprint database; and adding the target Bluetooth fingerprint information into the Bluetooth fingerprint database. The Bluetooth fingerprint database needs to be established once. If the Bluetooth fingerprint database already exists, the target Bluetooth fingerprint information can be directly added to it. In an exemplary embodiment, when adding the target Bluetooth fingerprint information, if no Bluetooth fingerprint sub-databases for different locations are established in the Bluetooth fingerprint database, the target Bluetooth fingerprint information is directly added to the Bluetooth fingerprint database; if Bluetooth fingerprint sub-databases for different locations are established in the Bluetooth fingerprint database, the target Bluetooth fingerprint information is added to the corresponding Bluetooth fingerprint sub-database.

[0112] In an exemplary embodiment, after establishing a Bluetooth fingerprint database based on the target Bluetooth fingerprint information, the Bluetooth fingerprint database also needs to be updated. The update of the Bluetooth fingerprint database occurs every first time interval. The update includes adding new target Bluetooth fingerprint information obtained during the update period to the Bluetooth fingerprint database, and removing Bluetooth fingerprint information deemed invalid from the target Bluetooth fingerprint information from the Bluetooth fingerprint database. The first time interval is a set value; the shorter the first time interval, the higher the update frequency of the Bluetooth fingerprint database. A higher update frequency means that invalid Bluetooth fingerprint information can be removed promptly, thus resulting in higher accuracy of the state recognition results obtained from a Bluetooth fingerprint database with a high update frequency. However, a high update frequency also means that more computing resources are required. Therefore, this embodiment does not limit the specific value of the first time interval and can set it according to a balance between the effectiveness of the Bluetooth fingerprint database model and the consumption of computing resources.

[0113] In an exemplary embodiment, removing Bluetooth fingerprint information deemed invalid during Bluetooth fingerprint database updates includes: counting at least two locations where each Bluetooth device appears in the Bluetooth devices corresponding to the target Bluetooth fingerprint information; removing Bluetooth fingerprint information where the distance between two of the at least two locations is greater than a distance threshold; generating a polygon corresponding to each target Bluetooth fingerprint information based on a polygon generation algorithm and the at least two locations; and removing target Bluetooth fingerprint information where the area of ​​the polygon is greater than an area threshold during Bluetooth fingerprint database updates. The distance threshold and area threshold are preset values, and this embodiment does not impose limitations on them.

[0114] In one possible implementation, based on a polygon generation algorithm and the at least two locations, a polygon corresponding to each target Bluetooth fingerprint is generated. Target Bluetooth fingerprints whose polygon area exceeds a threshold during Bluetooth fingerprint database updates are removed. This includes: using the polygon generation algorithm, each location where a target Bluetooth fingerprint has appeared is delineated into a polygon. When the area of ​​the delineated polygon exceeds the area threshold, the target Bluetooth fingerprint corresponding to that polygon is removed from the Bluetooth fingerprint database. The reason for removing target Bluetooth fingerprints whose polygon area exceeds the area threshold during Bluetooth fingerprint database updates is that when the area of ​​the polygon delineated from the locations where the Bluetooth fingerprint has appeared exceeds the area threshold, the Bluetooth device corresponding to that fingerprint is considered to have a large mobility range, i.e., the Bluetooth fingerprint is mobile. The polygon generation algorithm can be any polygon generation algorithm, and this application embodiment does not limit it. Optionally, the polygon generation algorithm is the Delaunay triangulation algorithm.

[0115] It should be noted that if the Bluetooth fingerprint database contains sub-databases for different locations, updates to the Bluetooth fingerprint database can be performed on a per-sub-database basis. In other words, each sub-database can be updated independently.

[0116] After obtaining the Bluetooth fingerprint database, the process of matching the Bluetooth fingerprint database with the first Bluetooth signal obtained in step 201 includes: parsing the first Bluetooth signal to obtain Bluetooth fingerprint information corresponding to the first Bluetooth signal; and matching the Bluetooth fingerprint information corresponding to the first Bluetooth signal with the Bluetooth fingerprint information included in the Bluetooth fingerprint database to obtain the Bluetooth fingerprint information in the Bluetooth fingerprint database that matches the first Bluetooth signal. For example, the Bluetooth fingerprint information that matches the first Bluetooth signal includes: Bluetooth fingerprint information E, Bluetooth fingerprint information R, and Bluetooth fingerprint information T. These three Bluetooth fingerprint information can correspond to the same location or different locations; this embodiment does not impose any limitations on this.

[0117] In step 202, the status recognition result of the target object is determined based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal.

[0118] In one possible implementation, determining the state identification result of the target object based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal includes: if the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal includes one location, then the state identification result of the target object is determined to be at that location; or, determining the number of Bluetooth fingerprint information matched by the first Bluetooth signal and determining the state identification result of the target object based on the number. If the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal includes at least two locations, then the state identification result of the target object is determined to be at those at least two locations; or, determining the number of Bluetooth fingerprint information matched by the first Bluetooth signal corresponding to each of the at least two locations and determining the state identification result of the target object based on the number.

[0119] In one possible implementation, the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal includes a location. The number of Bluetooth fingerprints matched with the first Bluetooth signal is determined, and the state identification result of the target object is determined based on this number. This includes: if the number exceeds a third preset value, then the state identification result of the target object is confirmed to be at that location; otherwise, the state identification result of the target object is determined to be not at that location. The third preset value is an empirical value, and this application embodiment does not impose any limitations on it.

[0120] Taking goods delivery as an example, the target location includes a pickup location and a third setting value of 3. When the number of times the first Bluetooth signal received by the delivery object's device matches the Bluetooth fingerprint information corresponding to the pickup location is greater than 3, the status of the delivery object is determined to be at the pickup location; otherwise, the status of the delivery object is determined to be not at the pickup location.

[0121] In one possible implementation, the target location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal includes at least two locations. The number of Bluetooth fingerprint information matching the first Bluetooth signal corresponding to these at least two locations is determined, and the state identification result of the target object is determined based on this number. This includes: if the number of Bluetooth fingerprint information matching the first Bluetooth signal corresponding to either of the at least two locations is greater than a fourth preset value, then the state identification result of the target object is determined to be at that location; if the number of Bluetooth fingerprint information matching the first Bluetooth signal corresponding to either location is not greater than the fourth preset value, then the state identification result of the target object is determined to be not at that location. The fourth preset value is an empirical value, and this embodiment does not impose any limitations on it.

[0122] In one possible implementation, the identification of the target object's state is performed in real time. Therefore, after determining the target object's state identification result at the location corresponding to the Bluetooth fingerprint information matched based on the first Bluetooth signal, the method further includes: after a reference duration, reacquiring the Bluetooth signal received by the target object's device; and, in response to the reacquiring Bluetooth signal being different from the first Bluetooth signal, determining the target object's state based on the reacquiring Bluetooth signal. Here, the reference duration is a set value, and this application embodiment does not limit it. For example, the reference duration is 5 minutes.

[0123] In another exemplary embodiment, such as Figure 7 As shown, the Bluetooth fingerprint generation process can be achieved by training a real-time model based on the Bluetooth signal obtained from the first device with the delivery app installed on the delivery recipient, and then uploading this real-time Bluetooth fingerprint database to the cloud platform. When identifying the delivery recipient's status at the pickup location, the Bluetooth signal obtained from the first or second device with the delivery app installed on the delivery recipient is parsed to obtain the corresponding Bluetooth fingerprint information, which is then matched with the Bluetooth fingerprint database. Afterwards, the matching result determines whether the delivery recipient's status is at the pickup location. The status recognition method provided in this application embodiment can achieve an accuracy of 33 meters for identifying the delivery recipient's status at the pickup location, improving the accuracy from the hundreds of meters to the tens of meters level, and increasing the success rate of identifying the delivery recipient's status at the pickup location from 30% to 70%.

[0124] In this embodiment, the first Bluetooth signal received by the target object's device is acquired, and then Bluetooth fingerprint information matching the first Bluetooth signal is determined in the Bluetooth fingerprint database. Subsequently, based on the location corresponding to the Bluetooth fingerprint information matching the first Bluetooth signal, the state recognition result of the target object is determined. This method avoids the need to virtualize a Bluetooth beacon on the merchant's app to help identify the target object's state, thus making the state recognition of the target object unrestricted by the merchant's app usage rate and improving the reliability of state recognition.

[0125] See Figure 8 This application provides a state recognition device, which includes:

[0126] The first acquisition module 801 is used to acquire the first Bluetooth signal received by the target device.

[0127] The first determining module 802 is used to determine Bluetooth fingerprint information that matches the first Bluetooth signal in the Bluetooth fingerprint database. The Bluetooth fingerprint database includes multiple Bluetooth fingerprint information, each Bluetooth fingerprint information corresponds to a location, and the Bluetooth fingerprint information includes at least one of the Bluetooth name identifier and manufacturer information corresponding to the Bluetooth fingerprint information.

[0128] The second determining module 803 is used to determine the state recognition result of the target object based on the location corresponding to the Bluetooth fingerprint information matched by the first Bluetooth signal.

[0129] In one possible implementation, the device further includes: a second acquisition module for acquiring a second Bluetooth signal received by the first device; a removal module for removing Bluetooth signals that do not meet the requirements from the second Bluetooth signal to obtain a third Bluetooth signal; a third acquisition module for acquiring Bluetooth fingerprint information corresponding to the third Bluetooth signal; and an establishment module for establishing a Bluetooth fingerprint database based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

[0130] In one possible implementation, the Bluetooth signals that do not meet the requirements in the second Bluetooth signal include at least one of the following: unresolved Bluetooth signals, Bluetooth signals with mobility, and Bluetooth signals that the second device cannot obtain; the second device has a different operating system than the first device, and the third Bluetooth signal is applicable to the operating systems of both the first and second devices.

[0131] In one possible implementation, a module is established to select target Bluetooth fingerprint information from Bluetooth fingerprint information corresponding to a third Bluetooth signal. The target Bluetooth fingerprint information corresponds to a target Bluetooth signal, which is a Bluetooth signal obtained within a range threshold of the third Bluetooth signal at that location. Based on the target Bluetooth fingerprint information, a Bluetooth fingerprint database is established.

[0132] In one possible implementation, a module is established to select target Bluetooth fingerprint information from Bluetooth fingerprint information corresponding to a third Bluetooth signal based on the Wi-Fi fingerprint corresponding to the location; or, clustering the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on a clustering algorithm, and selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on the clustering results.

[0133] In one possible implementation, the device further includes:

[0134] The update module is used to update the Bluetooth fingerprint database at a first time interval. The update includes adding new target Bluetooth fingerprint information obtained during the Bluetooth fingerprint database update into the Bluetooth fingerprint database, and removing Bluetooth fingerprint information that has been determined to be invalid from the target Bluetooth fingerprint information in the Bluetooth fingerprint database.

[0135] In one possible implementation, the update module is used to count at least two locations where each Bluetooth device appears in the Bluetooth device corresponding to the target Bluetooth fingerprint information; remove Bluetooth fingerprint information where the distance between two of the at least two locations is greater than a distance threshold; generate a polygon corresponding to each target Bluetooth fingerprint information based on a polygon generation algorithm and the at least two locations; and remove target Bluetooth fingerprint information whose polygon area is greater than an area threshold during the Bluetooth fingerprint database update.

[0136] In one possible implementation, the second determining module 803 is further configured to reacquire the Bluetooth signal received by the target object's device after a reference duration; and determine the state of the target object based on the reacquired Bluetooth signal in response to the reacquired Bluetooth signal being different from the first Bluetooth signal.

[0137] In this embodiment, the first Bluetooth signal received by the target object's device is acquired, and then Bluetooth fingerprint information matching the first Bluetooth signal is determined in the Bluetooth fingerprint database. Subsequently, based on the location corresponding to the Bluetooth fingerprint information matching the first Bluetooth signal, the state recognition result of the target object is determined. This method avoids the need to virtualize a Bluetooth beacon on the merchant's app to help identify the target object's state, thus making the state recognition of the target object unrestricted by the merchant's app usage rate and improving the reliability of state recognition.

[0138] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0139] Figure 9 This is a schematic diagram of a server structure provided in an embodiment of this application. The server can vary significantly due to differences in configuration or performance. It may include one or more Central Processing Units (CPUs) 901 and one or more memories 902. The one or more memories 902 store at least one computer program, which is loaded and executed by the one or more processors 901 to enable the server to implement the state recognition methods provided in the various method embodiments described above. Of course, the server may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server may also include other components for implementing device functions, which will not be elaborated upon here.

[0140] Figure 10 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application. The terminal can be: a smartphone, a tablet computer, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, or a desktop computer. The terminal may also be referred to as user equipment, a portable terminal, a laptop terminal, a desktop terminal, or other names.

[0141] Typically, a terminal includes a processor 1501 and a memory 1502.

[0142] Processor 1501 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1501 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1501 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1501 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, processor 1501 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0143] The memory 1502 may include one or more computer-readable storage media, which may be non-transitory. The memory 1502 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1502 are used to store at least one instruction, which is executed by the processor 1501 to cause the terminal to implement the state recognition method provided in the method embodiments of this application.

[0144] In some embodiments, the terminal may also optionally include: a peripheral device interface 1503 and at least one peripheral device. The processor 1501, memory 1502, and peripheral device interface 1503 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 1503 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of: a radio frequency circuit 1504, a display screen 1505, a camera assembly 1506, an audio circuit 1507, a positioning assembly 1508, and a power supply 1509.

[0145] Peripheral interface 1503 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1501 and memory 1502. In some embodiments, processor 1501, memory 1502 and peripheral interface 1503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1501, memory 1502 and peripheral interface 1503 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0146] The radio frequency (RF) circuit 1504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1504 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1504 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 1504 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 1504 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: metropolitan area networks (MANs), various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks (WLANs), and / or WiFi networks. In some embodiments, the RF circuit 1504 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0147] Display screen 1505 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1505 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 1501 for processing. In this case, display screen 1505 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, display screen 1505 can be a single screen, located on the front panel of the terminal; in other embodiments, display screen 1505 can be at least two screens, respectively located on different surfaces of the terminal or in a folded design; in other embodiments, display screen 1505 can be a flexible display screen, located on a curved or folded surface of the terminal. Furthermore, display screen 1505 can be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. Display screen 1505 can be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0148] The camera assembly 1506 is used to acquire images or videos. Optionally, the camera assembly 1506 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 1506 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0149] The audio circuit 1507 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 1501 for processing, or input to the radio frequency circuit 1504 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each positioned at a different location on the terminal. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 1501 or the radio frequency circuit 1504 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 1507 may also include a headphone jack.

[0150] Positioning component 1508 is used to determine the current geographic location of the terminal for navigation or LBS (Location Based Service). Positioning component 1508 can be a positioning component based on the US GPS (Global Positioning System), China's BeiDou system, Russia's Granas system, or the EU's Galileo system.

[0151] Power supply 1509 is used to power the various components in the terminal. Power supply 1509 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1509 includes a rechargeable battery, the rechargeable battery can support wired or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0152] In some embodiments, the terminal further includes one or more sensors 1510. The one or more sensors 1510 include, but are not limited to: an acceleration sensor 1511, a gyroscope sensor 1512, a pressure sensor 1513, an optical sensor 1514, and a proximity sensor 1515.

[0153] Accelerometer 1511 can detect the magnitude of acceleration along the three coordinate axes of a coordinate system established by the terminal. For example, accelerometer 1511 can be used to detect the components of gravitational acceleration along the three coordinate axes. Processor 1501 can control display screen 1505 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 1511. Accelerometer 1511 can also be used for games or for acquiring user motion data.

[0154] The gyroscope sensor 1512 can detect the terminal's orientation and rotation angle. The gyroscope sensor 1512, in conjunction with the accelerometer sensor 1511, can collect the user's 3D movements on the terminal. Based on the data collected by the gyroscope sensor 1512, the processor 1501 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0155] The pressure sensor 1513 can be disposed on the side bezel of the terminal and / or the lower layer of the display screen 1505. When the pressure sensor 1513 is disposed on the side bezel of the terminal, it can detect the user's grip signal on the terminal, and the processor 1501 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 1513. When the pressure sensor 1513 is disposed on the lower layer of the display screen 1505, the processor 1501 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 1505. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0156] Optical sensor 1514 is used to collect ambient light intensity. In one embodiment, processor 1501 can control the display brightness of display screen 1505 based on the ambient light intensity collected by optical sensor 1514. Specifically, when the ambient light intensity is high, the display brightness of display screen 1505 is increased; when the ambient light intensity is low, the display brightness of display screen 1505 is decreased. In another embodiment, processor 1501 can also dynamically adjust the shooting parameters of camera assembly 1506 based on the ambient light intensity collected by optical sensor 1514.

[0157] The proximity sensor 1515, also known as a distance sensor, is typically installed on the front panel of the terminal. The proximity sensor 1515 is used to detect the distance between the user and the front of the terminal. In one embodiment, when the proximity sensor 1515 detects that the distance between the user and the front of the terminal is gradually decreasing, the processor 1501 controls the display screen 1505 to switch from a screen-on state to a screen-off state; when the proximity sensor 1515 detects that the distance between the user and the front of the terminal is gradually increasing, the processor 1501 controls the display screen 1505 to switch from a screen-off state to a screen-on state.

[0158] Those skilled in the art will understand that Figure 10 The structure shown does not constitute a limitation on the terminal and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0159] In an exemplary embodiment, a computer device is also provided, comprising a processor and a memory storing at least one computer program. The at least one computer program is loaded and executed by one or more processors to enable the computer device to implement any of the aforementioned state recognition methods.

[0160] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one computer program that is loaded and executed by a processor of a computer device to enable the computer to implement any of the aforementioned state recognition methods. In one possible implementation, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, or optical data storage device, etc.

[0161] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the aforementioned state recognition methods.

[0162] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0163] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method of state recognition, characterized in that, The method comprises: acquiring a first Bluetooth signal received by a device of a target object; determining Bluetooth fingerprint information matched with the first Bluetooth signal in a Bluetooth fingerprint library, the Bluetooth fingerprint library comprising a plurality of Bluetooth fingerprint information, each Bluetooth fingerprint information corresponding to a location, the Bluetooth fingerprint information comprising at least one of a name identifier and manufacturer information of a Bluetooth corresponding to the Bluetooth fingerprint information; determining a state recognition result of the target object based on a location corresponding to the Bluetooth fingerprint information matched with the first Bluetooth signal; updating the Bluetooth fingerprint library, counting at least two positions where a Bluetooth device corresponding to target Bluetooth fingerprint information corresponding to a target Bluetooth signal appears, and removing Bluetooth fingerprint information where a distance between two positions is greater than a distance threshold value among the at least two positions; generating a polygon corresponding to each target Bluetooth fingerprint information based on a polygon generation algorithm and the at least two positions, and removing target Bluetooth fingerprint information where an area of the polygon is greater than an area threshold value during the updating of the Bluetooth fingerprint library.

2. The method of claim 1, wherein, Before the determining Bluetooth fingerprint information matched with the first Bluetooth signal in the Bluetooth fingerprint library, the method further comprises: acquiring a second Bluetooth signal received by a first device; removing Bluetooth signals that do not meet requirements in the second Bluetooth signal to obtain a third Bluetooth signal; acquiring Bluetooth fingerprint information corresponding to the third Bluetooth signal; establishing the Bluetooth fingerprint library based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal.

3. The method of claim 2, wherein, The Bluetooth signals that do not meet requirements in the second Bluetooth signal comprise at least one of unresolvable Bluetooth signals, Bluetooth signals with mobility, and Bluetooth signals that cannot be acquired by a second device; The second device has a different operating system from the first device, and the third Bluetooth signal is suitable for the operating systems of the first device and the second device.

4. The method of claim 2, wherein, The establishing the Bluetooth fingerprint library based on the Bluetooth fingerprint information corresponding to the third Bluetooth signal comprises: selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal, the target Bluetooth fingerprint information corresponding to a target Bluetooth signal, and the target Bluetooth signal being a Bluetooth signal acquired within a range threshold value of the location in the third Bluetooth signal; establishing the Bluetooth fingerprint library based on the target Bluetooth fingerprint information.

5. The method of claim 4, wherein, The selecting target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal comprises: selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on wireless fidelity (WiFi) fingerprint corresponding to the location; or performing clustering on the Bluetooth fingerprint information corresponding to the third Bluetooth signal based on a clustering algorithm, and selecting the target Bluetooth fingerprint information from the Bluetooth fingerprint information corresponding to the third Bluetooth signal according to a clustering result.

6. The method of claim 4, wherein, After the establishing the Bluetooth fingerprint library based on the target Bluetooth fingerprint information, the method further comprises: The Bluetooth fingerprint library is updated every first time length, and the updating includes including new target Bluetooth fingerprint information obtained during the Bluetooth fingerprint library updating into the Bluetooth fingerprint library, and removing Bluetooth fingerprint information determined as invalid from the Bluetooth fingerprint library.

7. The method according to any of claims 1 to 6, characterized in that After determining the state recognition result of the target object based on the location corresponding to the Bluetooth fingerprint information matched with the first Bluetooth signal, the method further includes: After a reference time length, reacquiring Bluetooth signals received by a device of the target object; In response to the reacquired Bluetooth signals being different from the first Bluetooth signal, determining the state of the target object based on the reacquired Bluetooth signals.

8. An apparatus for state recognition, characterized by The device includes: A first acquiring module configured to acquire a first Bluetooth signal received by a device of a target object; A first determining module configured to determine Bluetooth fingerprint information matched with the first Bluetooth signal in a Bluetooth fingerprint library, the Bluetooth fingerprint library including a plurality of Bluetooth fingerprint information, each Bluetooth fingerprint information corresponding to a location, the Bluetooth fingerprint information including at least one of a name identifier and manufacturer information of a Bluetooth corresponding to the Bluetooth fingerprint information, updating the Bluetooth fingerprint library, and counting at least two positions where a Bluetooth device corresponding to target Bluetooth fingerprint information corresponding to target Bluetooth signal appears; Based on a polygon generation algorithm and the at least two positions, generating a polygon corresponding to each target Bluetooth fingerprint information; removing target Bluetooth fingerprint information whose polygon has an area greater than an area threshold during the Bluetooth fingerprint library updating; A second determining module configured to determine a state recognition result of the target object based on a location corresponding to the Bluetooth fingerprint information matched with the first Bluetooth signal.

9. A computer device, comprising: The computer device includes a processor and a memory, and the memory stores at least one computer program, the at least one computer program is loaded and executed by the processor, so that the computer device implements the state recognition method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one computer program, and the at least one computer program is loaded and executed by the processor, so that the computer implements the state recognition method of any one of claims 1 to 7.

11. A computer program product, the computer program product includes computer instructions stored in a computer readable storage medium, a processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device implement the state recognition method of any one of claims 1 to 7.

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