Trajectory tracking method, device, electronic device and storage medium

Abstract

The present invention provides a trajectory tracking method, device, electronic device, and storage medium. The method includes: determining the location parameter information of a target user through fused positioning; generating the target user's trajectory fingerprint based on the location parameter information; and determining the target user's close contacts based on the target user's trajectory fingerprint. The trajectory tracking method, device, electronic device, and storage medium provided by the present invention determine the user's location parameter information through fused positioning, generate the user's trajectory fingerprint based on the user's location parameter information determined by fused positioning, and determine close contacts based on the user's trajectory fingerprint, making the tracking of close contacts more accurate.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a trajectory tracking method, device, electronic device and storage medium. Background Art

[0002] In terms of infectious disease prevention and control, the most effective way to control infectious diseases is to track the close contacts of infectious disease patients and isolate and observe close contacts.

[0003] The existing solution uses an app called TraceTogether for tracking. TraceTogether works by exchanging short-range Bluetooth signals between phones to closely detect other TraceTogether users. These raw records of close contact are encrypted and stored on each user's phone and never uploaded online. If a user is diagnosed with the virus, all the data they provide can be used to track down those who had close contact with them.

[0004] However, existing technical solutions rely on the search range of Bluetooth. Currently, the maximum search range of Bluetooth is between 10 and 20 meters, and there is also a large prediction error, estimated to be 3 to 5 meters. Therefore, the close contacts tracked using the solutions in existing technology are not accurate. Summary of the Invention

[0005] The present invention provides a trajectory tracking method, device, electronic device and storage medium to solve the technical problem that the close contacts tracked by the solutions in the prior art are not accurate.

[0006] In a first aspect, the present invention provides a trajectory tracking method, characterized by comprising:

[0007] Determine the location parameter information of the target user through fusion positioning;

[0008] generating a trajectory fingerprint of the target user based on the location parameter information;

[0009] Determine close contacts of the target user based on the trajectory fingerprint of the target user.

[0010] In one embodiment, determining the location parameter information of the target user through fusion positioning includes:

[0011] Obtain positioning results from multiple positioning systems; the multiple positioning systems include at least one of a 4G / 5G in-band positioning system, a co-band positioning system, a WiFi positioning system, a Bluetooth positioning system, and a GPS positioning system;

[0012] Perform position fusion on the positioning results of multiple positioning systems;

[0013] Combine indoor and outdoor maps to perform path fitting and make predictions based on the position fusion results;

[0014] The location parameter information of the target user is determined according to the location fusion result, the prediction estimation result and the path fitting result.

[0015] In one embodiment, the location parameter information includes: a dense closed index, a ranging distance, and a relative motion trend.

[0016] In one embodiment, generating the target user's trajectory fingerprint based on the location parameter information includes:

[0017] When the target user exchanges information with other users, the temporary identification codes of the target user and other users are recorded in pairs; and whether the other users are users that the target user has contacted before is determined. If so, the latest contact information is updated and retained;

[0018] Perform risk assessment based on the location parameter information to determine a close contact risk probability index;

[0019] Read the contact information that meets the conditions and the corresponding close contact risk probability index in all close contact records of the target user to generate the trajectory fingerprint of the target user.

[0020] In one embodiment, the mapping relationship between the temporary identification code of the target user and the user identification code of the target user is stored on an application server;

[0021] The temporary identification code of the target user is encrypted by a public key allocated to the target user by a third party and decrypted using a corresponding private key.

[0022] In one embodiment, determining close contacts of the target user based on the target user's trajectory fingerprint includes:

[0023] Generate the user's health code based on the user's trajectory fingerprint;

[0024] The tested user determines whether the tested user is a close contact of the target user by scanning the monitoring code of the target user;

[0025] If it is preliminarily verified that the user being tested is a close contact of the target user, a third-party verification platform is used as the verifier to determine again whether the user being tested is a close contact of the target user based on a zero-knowledge proof protocol.

[0026] In one embodiment, after determining the close contacts of the target user based on the target user's trajectory fingerprint, the method further includes:

[0027] A blockchain is constructed based on the target user and his / her close contacts; the blockchain includes a main chain, a first side chain, and a second side chain; the main chain is composed of confirmed users; the first side chain is composed of undiagnosed close contacts of the confirmed users in the main chain; the second side chain is composed of healthy close contacts, confirmed and cured close contacts, and deceased close contacts of the confirmed users in the main chain.

[0028] In a second aspect, the present invention provides a trajectory tracking device, comprising:

[0029] A first determination module is used to determine the location parameter information of the target user through fusion positioning;

[0030] A generating module, configured to generate a trajectory fingerprint of the target user based on the location parameter information;

[0031] The second determination module is used to determine the close contacts of the target user based on the trajectory fingerprint of the target user.

[0032] In a third aspect, the present invention provides an electronic device comprising a memory and a memory storing a computer program, wherein the processor implements the steps of the trajectory tracking method described in the first aspect when executing the program.

[0033] In a fourth aspect, the present invention provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the steps of the trajectory tracking method described in the first aspect.

[0034] The trajectory tracking method, device, electronic device and storage medium provided by the present invention determine the user's location parameter information through fusion positioning, generate the user's trajectory fingerprint based on the user's location parameter information determined by fusion positioning, and determine close contacts based on the user's trajectory fingerprint, making the tracked close contacts more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 It is a flow chart of the trajectory tracking method provided by the present invention;

[0037] Figure 2 This is a schematic diagram of the personal health information code system embedded with trajectory tracking provided by the present invention;

[0038] Figure 3 This is a schematic diagram of the positioning and ranging module provided by the present invention;

[0039] Figure 4 This is a schematic diagram of the contact information exchange process provided by the present invention;

[0040] Figure 5 This is a schematic diagram of the main chain-side chain structure based on blockchain provided by the present invention;

[0041] Figure 6 This is a schematic diagram of the tracking process based on trajectory fingerprint provided by the present invention;

[0042] Figure 7 It is a structural schematic diagram of the trajectory tracking device provided by the present invention;

[0043] Figure 8 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0044] Imagine three people, A, B, and C. Person A has a history of contact with an epidemic area and is scattered across the country, making him easy to locate. During their travels, Person A encounters Person B, a person they have never met before and who they don't know. A is unaware of Person B, and neither is Person B. Upon arrival, Person A comes into contact with Person C. Regardless of how many Person Cs they have come into contact with, all of them can be found and isolated. The biggest hidden danger now is Person B, who is impossible to find. No one knows who Person B is, and they themselves don't even know they are Person B. Therefore, the goal of isolating everyone is to buy time to identify Person B. The incubation period is two weeks, and within that time, Person Bs will develop symptoms, revealing the true identity. Only when all Person Bs have developed symptoms can the epidemic be over. Therefore, all current epidemic prevention and control measures are aimed at reducing the risk of new Person Bs. Tracking and identifying close contacts of Person Bs, allowing for early detection and isolation, is the most effective way to control the epidemic. It helps flatten the infection curve and, in turn, reduces the burden on the healthcare system.

[0045] The currently known technology involves a personal health information code. Real-name code holders scan the code when entering and exiting public places, leaving a personal track record. When a case occurs, close contacts and quarantined individuals are identified and verified. This solution relies on manual verification, which has low automation and accuracy, and can easily lead to the expansion of close contacts and omissions.

[0046] In addition, an application called TraceTogether has also been used for trajectory tracking during the epidemic. TraceTogether works by exchanging short-range Bluetooth signals between mobile phones to detect other users using TraceTogether at close range. These original records of close contact are encrypted and stored on each user's mobile phone and will not be uploaded over the network. If a user is diagnosed with the infection, the confirmed user can provide all data in order to track people who have had close contact with the user. TraceTogether states that it does not collect or use any type of user location data, nor does it access the user's contacts or address information. It only uses Bluetooth data to establish contact and does not store information about where the contact occurred.

[0047] However, using the TraceTogether app for tracing and identifying close contacts has the following disadvantages:

[0048] 1. Inaccurate close contact predictions. TraceTogether relies on Bluetooth's search range, which is roughly 10 to 20 meters. This also results in a significant prediction error, estimated at 3 to 5 meters. Determining close contact based solely on distance ignores the fact that the probability of close contact is related to factors such as relative movement speed, ambient ventilation (indoors / outdoors), and contact time and distance. Clearly, unilaterally basing close contact determinations on imprecise physical distance, rather than accurately predicting risk levels based on a comprehensive assessment of multiple factors, can easily lead to an increase in the number of close contacts and omissions.

[0049] 2. Inadequate privacy protection. TraceTogether's close contact records are stored on each user's phone. Although this data is encrypted, it still carries a high risk of being leaked. This is especially true if a user is diagnosed with the virus. This will leak the user's historical contact data and easily infringe on the user's privacy.

[0050] 3. Insufficient tamper-proofing of contact data. TraceTogether stores data locally and does not upload it, so there is a possibility of local data tampering.

[0051] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0052] Figure 1It is a flow chart of the trajectory tracking method provided by the present invention, such as Figure 1 As shown, the present invention provides a trajectory tracking method, comprising:

[0053] Step 101: Determine the location parameter information of the target user through fusion positioning.

[0054] The determining of the location parameter information of the target user by fusion positioning includes:

[0055] Obtain positioning results from multiple positioning systems; the multiple positioning systems include at least one of a 4G / 5G in-band positioning system, a co-band positioning system, a WiFi positioning system, a Bluetooth positioning system, and a GPS positioning system;

[0056] Perform position fusion on the positioning results of multiple positioning systems;

[0057] Combine indoor and outdoor maps to perform path fitting and make predictions based on the position fusion results;

[0058] The location parameter information of the target user is determined according to the location fusion result, the prediction estimation result and the path fitting result.

[0059] The location parameter information includes: dense closed index, ranging distance and relative movement trend.

[0060] Specifically, Figure 2 This is a schematic diagram of the personal health information code system embedded with trajectory tracking provided by the present invention, such as Figure 2 As shown, the trajectory tracking of close contacts is achieved by embedding trajectory fingerprints into personal health information codes. The trajectory fingerprint engine is used to generate hierarchical and classified trajectory fingerprints of close contacts; the epidemic data platform, based on blockchain technology, builds a sharing platform including epidemic data by putting epidemic data on the chain; the health code engine is used to generate health codes (health codes including trajectory fingerprints) and verify the health information of the code holder (including whether he is a close contact of a certain user).

[0061] The track tracking application platform provides account management and positioning and ranging functions.

[0062] The client form of the embodiment of the present application is a mobile application, and the trajectory tracking application platform assigns a unique user identification number to each client. The data exchange of contacts is based on the improved In order to prevent users from being tracked by third parties, data exchange uses a temporary identification number. (The format is as follows, the first three fields use encryption). and The mapping relationship is stored on the application server of the trajectory tracking application platform. At a certain moment, Use a trusted third party to User-assigned public key Encrypt using the corresponding private key Decrypt.

[0063] Another important function of the trajectory tracking application platform is to provide users with positioning and ranging capabilities based on the MEC location service open capability, which is implemented by the positioning and ranging module. The output parameter of this module is the dense closed index. , ranging distance , relative movement trend (Estimated distance estimate for the next cycle).

[0064] Estimating the distance between contacts is a key factor in accurate tracking. Compared to estimation based solely on the user client's Bluetooth RSSI, high-precision fused positioning methods based on 4G / 5G networks, if supported by the application client and the network environment (if available), can provide more accurate location estimation and achieve precise tracking.

[0065] Figure 3 This is a schematic diagram of the positioning and ranging module provided by the present invention. Figure 3 As shown in the figure, the positioning and ranging module includes the following layers: the signal test layer, which is the basic settings, chips, sensors, etc. of various positioning systems supported in the current environment, and collects the information required for positioning; the basic position estimation layer, which mainly obtains the positioning results of each positioning system through some positioning algorithms, and mainly selects 4G / 5G in-band positioning, common frequency band positioning, WiFi positioning, Bluetooth, GPS positioning and other basic indoor / outdoor positioning subsystems for high-precision measurement and positioning; the fusion position estimation layer, which performs position fusion based on the positioning results of multiple positioning systems to reduce errors and obtain higher positioning accuracy; the position prediction layer, which mainly combines indoor and outdoor maps for path fitting, and makes predictions and estimates based on the position fusion results; the decision and feedback layer, based on the fusion of position results, prediction estimation, and path fitting results, combines other positioning systems to obtain a dense closed index , ranging distance , relative movement trend .

[0066] According to the geographic location standard and the number of times the current location is matched, the dense enclosure type can be divided into indoor dense, indoor sparse, outdoor dense, and outdoor sparse. The corresponding values ​​are: 、 、 and The indoor / outdoor judgment is based on geographical matching or whether it is an indoor base station access judgment; the sparse and dense judgment refers to the human density, and the number of matching attempts currently occurring can be used to determine whether the number of matches exceeds times can be judged as dense. Movement trend It is an estimate of the possible next distance based on the previous distance and two intervals.

[0067] Step 102: Generate a trajectory fingerprint of the target user based on the location parameter information.

[0068] Generating the target user's trajectory fingerprint based on the location parameter information includes:

[0069] When the target user exchanges information with other users, the temporary identification codes of the target user and other users are recorded in pairs; and whether the other users are users that the target user has contacted before is determined. If so, the latest contact information is updated and retained;

[0070] Perform risk assessment based on the location parameter information to determine a close contact risk probability index;

[0071] Read the contact information that meets the conditions and the corresponding close contact risk probability index in all close contact records of the target user to generate the trajectory fingerprint of the target user.

[0072] The mapping relationship between the temporary identification code of the target user and the user identification code of the target user is stored on the application server;

[0073] The temporary identification code of the target user is encrypted by a public key allocated to the target user by a third party and decrypted using a corresponding private key.

[0074] Specifically, the core functions of the trajectory fingerprint engine are to record and track close contacts, predict their risk levels, and generate trajectory fingerprints for close contacts. The trajectory fingerprint engine can be divided into the following functional modules: contact trigger module, risk prediction module, and trajectory compression module.

[0075] 1. Contact trigger module

[0076] Assume that there is a user and , for each ,user Generate a pair of keys for yourself and ,user As When information exchange occurs, the public key Km and the contact message are sent to the contact. , keep the private key yourself , and All keep records of previous contacts. Initiate When making a contact request with the user, attach all temporary contacts that have been in contact with the user within a specific time (e.g. 2 hours). A list composed of It is encrypted by the public key of the other party, and the public key is also attached to In the case of new contact, the private key is used to decrypt the contact and determine whether it is a user that has been contacted before. If it is an update, the latest contact information is retained and the previous ones are deleted.

[0077] The exchange information format is as follows:

[0078] { / / JSON format of contact records of central devices

[0079] "id":"Fj5jfbTtDySw8JoVsCmeul0wsoIcJKRPV0HtEFUlNvNg6C3wyGj8R1utPbw+Iz8tqAdpbxR1nSvr+ILXPG==",

[0080] "st":1545299299910

[0081] "mc": "hwp30",

[0082] "rs":-60

[0083] "location":"cn_xa",

[0084] "pr":1,

[0085] "class":"H",

[0086] "not":3,

[0087] "rssi":-60,

[0088] "n":23

[0089] }

[0090] { / / JSON format of contact records of peripheral devices

[0091] "id":"Fj5jfbTtDySw8JoVsCmeul0wsoIcJKRPV0HtEFUlNvNg6C3wyGj8R1utPbw+Iz8tqAdpbxR1nSvr+ILXPG==",

[0092] "st":1545299299910

[0093] "mp": "hwp30",

[0094] "location":"cn_xa",

[0095] "pr":1,

[0096] "class":"H"

[0097] "not":3,

[0098] "rssi":-60,

[0099] "n":23

[0100] }

[0101] in, That is ; is the phone model; Indicates the area where the contact occurred (city level); timestamp ; Bluetooth power; close contact risk index , represents the risk probability, ranging from 0 to 1, the larger the value, the higher the risk; close contact type (High risk , medium risk , low risk and No risk); Cumulative number of contacts , that is, the cumulative number of contacts between the two; Cumulative effective interactions of users .

[0102] The contact trigger module is used to track contacts and output a pair of contact matches. ,Right now .

[0103] Figure 4 This is a schematic diagram of the contact information exchange process provided by the present invention, such as Figure 4As shown, contact information exchange is based on the existing BLE (Bluetooth Low Energy) protocol. Each device can have two roles: Peripheral and Central. Peripheral terminals issue Service notifications, and Central terminals scan for notification messages from all Peripheral terminals and connect to Services. Services are collections of data exchanged between devices, with the Central terminal performing read and write operations.

[0104] Assume that there is a user A who has a record of his / her usage in the past period of time (usually set to 2 hours). List of users you have contacted In one contact, user A issues a public key to the person who has been in contact with him, allowing him to check the If the other party is a former contact of user A, the contact information is read and the following logic is used to perform the operation:

[0105] (1) The Is it in user A's blacklist? (The blacklist includes those who have been identified as high-risk close contacts, including custom acquaintances), update contact data information, etc., and exit all processes directly;

[0106] (2) If the contact history shows that the contact type is not high-risk, update the timestamp and RSSI, set the previous contact record to the pending update state, and jump to (4);

[0107] (3) If it is the first contact, create a new contact record, write the timestamp and RSSI, set the contact record status to pending update, and jump to (4);

[0108] (4) Output the paired device to the next level positioning and ranging module. Output in pairs .

[0109] 2. Risk prediction module

[0110] The risk prediction module conducts risk assessment based on positioning and ranging results (close contact probability index, indoor and outdoor closure index, function of distance and time, etc.), classifies and tracks trajectories, and defines three levels of close contact risk: high risk, medium risk, and low risk.

[0111] For example, in a user and Occurrence The close contact risk probability index at this time is recorded as , according to the dense closure index ,distance , relative movement trend Factors such as the close contact risk between contacts are used to predict the risk. The close contact risk index is positively correlated with the intensive isolation index, positively correlated with the duration of contact, and negatively correlated with the contact distance. It can be formalized as follows:

[0112]

[0113] According to the close contact risk probability index Contacts are defined as three categories:

[0114] High-risk close contacts are defined as , now correct , that is, the close contact risk probability index is updated to 1; medium-risk close contacts are defined as ; Low-risk close contacts are defined as .

[0115] After completing the risk prediction, the system will update the contact information items, including: location ; Close contact risk index ; Close contact type (High risk , medium risk , low risk ); and the Cumulative number of contacts ; This temporary The cumulative number of effective interactions Etc. After the update is completed, the information is stored between devices.

[0116] 3. Trajectory Compression Module

[0117] In the close contact list of user A, a collection of information about all close contacts within a specific period is maintained, including And risk level. For a certain user C, if he wants to determine whether he is a close contact of A, the existing solution is that A directly discloses or semi-discloses his close contact set, and lets C verify it directly or through a third-party organization. The typical problem of this method is that the search efficiency is low, and all the tracks and contact information of A and C need to be checked, which leaks the user's privacy. This embodiment of the application proposes a method based on The zero-knowledge proof solution can quickly screen whether C is a suspected close contact of A without leaking the privacy information of A and C.

[0118] The embodiment of the present application proposes a trajectory fingerprint, which is generated by all the contact records of the user that meet specific time conditions and risk levels, and is used to identify whether a user is a close contact of the user. is Hash functions ( ) is generated, which is essentially a bit-long bit string, this set of Hash functions can satisfy Randomly distributed to Full space.

[0119] Confirmed user A reads all close contact records that meet the conditions , extract each record in Composition set ; Then, traverse For all elements in Seek their ,Update trajectory fingerprint , which is a bitwise OR operation. The expression is as follows:

[0120] .

[0121] Step 103: Determine close contacts of the target user based on the target user's trajectory fingerprint.

[0122] The determining the close contacts of the target user based on the trajectory fingerprint of the target user includes:

[0123] Generate the user's health code based on the user's trajectory fingerprint;

[0124] The tested user determines whether the tested user is a close contact of the target user by scanning the monitoring code of the target user;

[0125] If it is preliminarily verified that the user being tested is a close contact of the target user, a third-party verification platform is used as the verifier to determine again whether the user being tested is a close contact of the target user based on a zero-knowledge proof protocol.

[0126] After determining the close contacts of the target user based on the trajectory fingerprint of the target user, the method further includes:

[0127] A blockchain is constructed based on the target user and his / her close contacts; the blockchain includes a main chain, a first side chain, and a second side chain; the main chain is composed of confirmed users; the first side chain is composed of undiagnosed close contacts of the confirmed users in the main chain; the second side chain is composed of healthy close contacts, confirmed and cured close contacts, and deceased close contacts of the confirmed users in the main chain.

[0128] Specifically, the health code engine is used to generate a health code (a health code that includes a trajectory fingerprint) and verify the health information of the code holder (including whether he or she is a close contact of a user). It includes a health code generation module, a suspected screening module and a precise screening module.

[0129] 1. Health code generation module

[0130] Existing personal health information code data includes: (1) basic personal information; (2) personal health information; (3) travel information; and (4) health certificate information. The so-called travel information refers to the location information of the subject of personal health information who has lived or stayed in a certain market in the recent period. This includes the province / city / district where the subject currently resides or has stayed and the verification status of travel information.

[0131] Based on this, this proposal adds trajectory contact information carried by trajectory fingerprints to the health code. The generation of the QR code of the personal health information code containing the trajectory fingerprint follows the national standard GB / T 27766-2011.

[0132] 2. Suspected screening module

[0133] Suspected screening is combined with trajectory fingerprinting Trajectory fingerprints are very suitable for tracking the trajectory of the epidemic. Although there is a certain probability of false positive rate, it ensures that there will be no false negative, that is, no close contact will be missed by mistake, so suspected screening can be carried out.

[0134] The suspected screening module consists of two parts: active screening and passive screening. In actual application, it can be presented to the public in the form of a QR code. The so-called active screening means that when someone is diagnosed and needs to disclose information, in addition to the textual descriptive trajectory information, it also includes his trajectory fingerprint. In addition to confirming based on trajectory information, any user can also actively scan the trajectory fingerprint QR code of the confirmed person to determine whether they are a close contact of the user. If yes, they will enter the precise confirmation module; if not, it means that the user is definitely not a close contact, so it can quickly determine whether close contact is met.

[0135] The specific process can be as follows: suppose user A is diagnosed with a patient, and user B follows user A's publicly available motion trajectory description and finds that he or she may have partially overlapped with A's trajectory. At this time, user B scans A's publicly available trajectory fingerprint. , do the following:

[0136] Step 1: B extracts the local stored history for a certain period of time (such as 14 days or 21 days) , recorded as ;

[0137] Step 2: Randomly extract an untested identifier from , and then calculate the hash values ​​locally one by one ;

[0138] Step 3: Judgment The corresponding position is Are they both 1? If so, exit. B is a suspected close contact of A. If not, Mark as tested and jump to step 2 until All the logos in the test are completed.

[0139] Passive screening is similar to active screening in principle. The user becomes a passive screener, but the application scenario has changed, such as entering or leaving a residential area, a public place, or a sentry checkpoint. Assume that user C is the screened person and presents his / her personal track fingerprint to the inspector. The QR code of the confirmed user is used by the inspectors. Go match.

[0140] For scenarios where active screening is performed, a passive screening can be performed once, and in scenarios where passive screening is performed, an active screening can be performed again, that is, the trajectory fingerprints of the two people are matched with each other. Only if both are suspected close contacts will they be listed as suspected close contacts, otherwise they are not close contacts.

[0141] 3. Accurate confirmation module

[0142] Whether it is active screening or passive screening, there is a possibility of false positives. In order to more accurately confirm whether suspected close contacts are true close contacts, close contacts can prove their innocence.

[0143] Both suspected close contacts are paired according to the existing stored pairings, but neither knows which pair constitutes a close contact pair. First, suspected close contacts A and B pair their respective history for a specific period of time. and Calculate separately and , and sent to the trajectory tracking application platform, the trajectory tracking application platform will find the same Yes, using a third-party verification platform as a verifier, based on Zero-knowledge proof protocol, proves that of and Also satisfied, and , that is, the two are indeed a pair of close contacts; otherwise, they are judged as not close contacts.

[0144] The most important point in epidemic prevention and control based on trajectory tracking is to quickly and accurately identify close contacts and isolate them. Currently, the main method is manual confirmation, and close contacts and their stakeholders are prone to subjective fraud and evasion. In order to avoid the authenticity and effectiveness of trajectory tracking, the embodiment of this application proposes an implementation plan based on the main chain-side chain structure of blockchain. In this solution, both the main chain and the side chain adopt the form of permission chain.

[0145] Figure 5 This is a schematic diagram of the main chain-side chain structure based on blockchain provided by the present invention, such as Figure 5 As shown, the main chain consists of confirmed users, all Generated digital summary , contact information in original trajectory tracking Generated digital summary And the user's trajectory fingerprint .

[0146] Sidechain 1 consists of close contacts of confirmed users in the main chain. For each close contact, the confirmed patient in the main chain that caused him to enter Sidechain 1 is chained. The digital summary generated by the set , which I have used before Numerical summary of the collection , Numerical summary of contact information in raw trajectory tracking and other information.

[0147] Side chain 2 consists of healthy close contacts, cured confirmed patients and deceased patients. Identify these three states, in addition to the ones that have been used Numerical summary of the collection , Numerical summary of contact information in raw trajectory tracking and other information.

[0148] Sidechain 1 and Sidechain 2 are essentially a cross-chain solution for the epidemic alliance chain formed around the core main chain. Through this solution, two-way anchoring can be achieved, and epidemic data can be transferred efficiently, quickly and securely between the main chain and the side chain. The specific process is as follows:

[0149] When a user conducts active self-examination or passive screening (by querying on the main chain), if he is found to be a close contact, the smart contract C1 on side chain 1 will be triggered first to determine whether it is necessary to confirm and upload the required information. If so, the information will be automatically triggered for upload; if the close contact on side chain 1 is confirmed as a confirmed patient after testing, when the medical institution submits the confirmed information, smart contract 2 will be executed, so that the close contact information on the side chain will be transmitted across the chain; when the confirmed person is cured or dies, smart contract C3 will be triggered, and information will be transmitted from the main chain to side chain 2; when the close contact has passed the quarantine period, information will be transmitted from side chain 1 to side chain 2.

[0150] Figure 6 This is a schematic diagram of the tracking process based on trajectory fingerprint provided by the present invention, such as Figure 6 As shown in Figure 2, the tracking process based on trajectory fingerprint is as follows:

[0151] 1. Users A and B enter the contact trigger distance range, and determine whether to trigger the trajectory tracking between A and B.

[0152] Assume that there is a user A who has a record of his / her usage in the past period of time (usually set to 2 hours). List of users you have contacted In one contact, user A issues a public key to the person who has been in contact with him, allowing him to check the If the other party is a former contact of user A, the contact information is read and the following logic is used to perform the operation:

[0153] 1-1. Check whether the ID is on user A's blacklist (the blacklist includes those who have been identified as high-risk close contacts, including custom acquaintances). Update contact data information, etc., and exit all processes directly;

[0154] 1-2 If the contact history shows that the contact type is not high-risk, update the timestamp and RSSI, set the previous contact record to the pending update state, and jump to 1-4;

[0155] If 1-3 is the first contact, create a new contact record, write the timestamp and RSSI, set the contact record status to pending update, and jump to 1-4;

[0156] 1-4. Output the paired device to the next level positioning and ranging module. Output in pairs .

[0157] 2. Based on the open capabilities of location services deployed at the edge of the mobile network, determine the relevant parameters between A and B: dense closed index , ranging distance , relative movement trend (Estimated distance estimation for the next cycle) etc.

[0158] 3. After predicting the contact risk based on the parameters between A and B given in step 2, the system will update the contact information entry.

[0159] 3-1. Based on the dense closure index , ranging distance , relative movement trend etc. to calculate exposure risk;

[0160] 3-2. Update the contact content information of A and B, and complete the storage of the contact content by the devices corresponding to A and B, including the location ; Close contact risk index ; Close contact type (High risk , medium risk , low risk ); and the Cumulative number of contacts ; This temporary The cumulative number of effective interactions wait.

[0161] 4. Close contact screening based on trajectory fingerprints:

[0162] 4-1. When user B is confirmed to be infected, his / her track fingerprint will be made public. All users who are suspected of having the same track as B can scan B's track fingerprint. The generated QR code is actively screened to preliminarily predict whether the person is a close contact of B.

[0163] 4-2. A's track fingerprint serves as his health certificate. When entering or leaving a public place, inspectors can scan A's track fingerprint. The generated QR code is passively screened to determine whether the person is a suspected close contact of a recently confirmed case.

[0164] 4-3. For scenarios where active screening is performed, a passive screening can be performed once, and an active screening can be performed again in scenarios where passive screening is performed, that is, the trajectory fingerprints of the two people are matched with each other. Only if both are suspected close contacts will they be listed as suspected close contacts, otherwise they are not close contacts.

[0165] 5. Determine whether a suspected close contact is a true close contact through the precise prediction module.

[0166] The embodiments of the present application provide a trajectory tracking method, which uses multi-factor hierarchical classification to confirm close contacts based on fused positioning, implements user privacy protection based on cryptographic algorithms such as zero-knowledge proof, and provides tamper-proof capabilities for close contact data based on blockchain technology. This method solves problems such as insufficient accuracy of close contacts, insufficient privacy protection, and insufficient tamper-proof capabilities for contact data, and enables close contact tracking to be more accurate, with better privacy protection, and more complete and authentic data.

[0167] The trajectory tracking device provided by the present invention is described below. The trajectory tracking device described below and the trajectory tracking method described above can be referenced to each other.

[0168] Figure 7 Schematic diagram of the structure of the trajectory tracking device provided by the present invention, such as Figure 7 As shown, the embodiment of the present application discloses a trajectory tracking device, including a first determination module 701, a generation module 702, and a second determination module 703, wherein:

[0169] The first determination module 701 is used to determine the location parameter information of the target user through fusion positioning; the generation module 702 is used to generate the trajectory fingerprint of the target user based on the location parameter information; the second determination module 703 is used to determine the close contacts of the target user based on the trajectory fingerprint of the target user.

[0170] Specifically, the above-mentioned trajectory tracking device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned trajectory tracking method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0171] Figure 8 Schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 8 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call a computer program in the memory 830 to execute the steps of the trajectory tracking method, for example, including:

[0172] Determine the location parameter information of the target user through fusion positioning;

[0173] generating a trajectory fingerprint of the target user based on the location parameter information;

[0174] Determine close contacts of the target user based on the trajectory fingerprint of the target user.

[0175] Furthermore, the logic instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0176] On the other hand, the present invention further provides a computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions. When the program instructions are executed by a computer, the computer can perform the steps of the trajectory tracking method provided by the above methods, for example, including:

[0177] Determine the location parameter information of the target user through fusion positioning;

[0178] generating a trajectory fingerprint of the target user based on the location parameter information;

[0179] Determine close contacts of the target user based on the trajectory fingerprint of the target user.

[0180] On the other hand, an embodiment of the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, wherein the computer program is configured to cause the processor to execute the steps of the methods provided in the above embodiments, for example, including:

[0181] Determine the location parameter information of the target user through fusion positioning;

[0182] generating a trajectory fingerprint of the target user based on the location parameter information;

[0183] Determine close contacts of the target user based on the trajectory fingerprint of the target user.

[0184] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROMs, EPROMs, EEPROMs, non-volatile memories (NANDFLASH), solid-state drives (SSDs)), etc.

[0185] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0186] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0187] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A trajectory tracking method, characterized in that: include: Determine the location parameter information of the target user through fusion positioning; generating a trajectory fingerprint of the target user based on the location parameter information; Determine close contacts of the target user based on the trajectory fingerprint of the target user; The determining of the location parameter information of the target user by fusion positioning includes: Obtain positioning results from multiple positioning systems; the multiple positioning systems include 4G / 5G in-band positioning systems, co-band positioning systems, WiFi positioning systems, Bluetooth positioning systems, and GPS positioning systems; Perform position fusion on the positioning results of multiple positioning systems; Combine indoor and outdoor maps to perform path fitting and make predictions based on the position fusion results; Determine the location parameter information of the target user according to the location fusion result, the prediction estimation result and the path fitting result; The position parameter information includes: dense closed index, ranging distance and relative movement trend; Generating the target user's trajectory fingerprint based on the location parameter information includes: When the target user exchanges information with other users, the temporary identification codes of the target user and other users are recorded in pairs; and whether the other users are users that the target user has contacted before is determined. If so, the latest contact information is updated and retained; Performing a risk assessment based on the location parameter information to determine a close contact risk probability index; the close contact risk probability index is positively correlated with the dense enclosure index, positively correlated with the continuous contact time, and inversely correlated with the ranging distance; Read the contact information that meets the conditions and the corresponding close contact risk probability index in all close contact records of the target user to generate the trajectory fingerprint of the target user.

2. The trajectory tracking method according to claim 1, characterized in that: The mapping relationship between the temporary identification code of the target user and the user identification code of the target user is stored on the application server; The temporary identification code of the target user is encrypted by a public key allocated to the target user by a third party and decrypted using a corresponding private key.

3. The trajectory tracking method according to claim 1, characterized in that: The determining the close contacts of the target user based on the trajectory fingerprint of the target user includes: Generate the user's health code based on the user's trajectory fingerprint; The tested user determines whether the tested user is a close contact of the target user by scanning the monitoring code of the target user; If it is preliminarily verified that the user being tested is a close contact of the target user, a third-party verification platform is used as the verifier to determine again whether the user being tested is a close contact of the target user based on a zero-knowledge proof protocol.

4. The trajectory tracking method according to claim 1, characterized in that: After determining the close contacts of the target user based on the trajectory fingerprint of the target user, the method further includes: A blockchain is constructed based on the target user and his / her close contacts; the blockchain includes a main chain, a first side chain, and a second side chain; the main chain is composed of confirmed users; the first side chain is composed of undiagnosed close contacts of the confirmed users in the main chain; the second side chain is composed of healthy close contacts, confirmed and cured close contacts, and deceased close contacts of the confirmed users in the main chain.

5. A trajectory tracking device, characterized in that: include: A first determination module is used to determine the location parameter information of the target user through fusion positioning; A generating module, configured to generate a trajectory fingerprint of the target user based on the location parameter information; A second determination module is configured to determine close contacts of the target user based on the trajectory fingerprint of the target user; Determining the location parameter information of the target user through fusion positioning includes: obtaining positioning results of multiple positioning systems; the multiple positioning systems include a 4G / 5G in-band positioning system, a co-band positioning system, a WiFi positioning system, a Bluetooth positioning system, and a GPS positioning system; performing location fusing on the positioning results of the multiple positioning systems; performing path fitting in combination with indoor and outdoor maps and performing prediction estimation based on the location fusion results; and determining the location parameter information of the target user based on the location fusion results, the prediction estimation results, and the path fitting results. The position parameter information includes: dense closed index, ranging distance and relative movement trend; The generating of the trajectory fingerprint of the target user based on the position parameter information includes: when the target user exchanges information with other users, recording the temporary identification codes of the target user and other users in pairs; and determining whether the other users are users that the target user has contacted before, and if so, updating and retaining the latest contact information; performing risk assessment based on the position parameter information to determine a close contact risk probability index; the close contact risk probability index is positively correlated with the dense closure index, positively correlated with the continuous contact time, and inversely correlated with the ranging distance; reading the contact information that meets the conditions and the corresponding close contact risk probability index in all close contact records of the target user to generate the trajectory fingerprint of the target user.

6. An electronic device comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the trajectory tracking method according to any one of claims 1 to 4 are implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the trajectory tracking method according to any one of claims 1 to 4 are implemented.

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