A high-performance electronic fence method, device and equipment based on communication big data

Abstract

The present invention provides a high-performance electronic fence method based on communication big data, including spatial grid division, encoding each spatial grid to construct an operator network side database, constructing an electronic fence database, storing and quickly retrieving the spatial boundaries, attribute information and a list of people allowed to enter the fence of the demarcated electronic fence, establishing an electronic fence management system to create, delete and modify the electronic fence in the database, quickly demarcating the initial population within the electronic fence, real-time operator network side data processing, parallel calculation of people currently within the electronic fence and people not within the fence, parallel calculation of events of abnormal entry and exit of the electronic fence for more than a certain time, and timely reporting to the electronic fence management system. It can realize real-time detection of people prohibited from entering and leaving the demarcated electronic fence from massive operator network side data in a megacity.

Description

Technical Field

[0001] The present invention belongs to the field of mobile object data processing, and in particular relates to a high-performance electronic fence method, device and equipment based on communication big data. Background Art

[0002] Electronic fencing was first implemented by deploying electronic detection networks around key areas such as museums and schools to detect unauthorized entry into these areas. However, the construction of these electronic detection networks is time-consuming and costly, especially for controlling large areas. Furthermore, once deployed, these fences are difficult to modify and lack flexibility. With the advancement of communication and positioning technologies, new information-based electronic fencing technologies have emerged, supporting large-scale, multi-dimensional, and customizable perimeters. These technologies are being used in areas such as communication base station signal management and vehicle management. These new information-based electronic fencing technologies detect entry based on whether a communication connection has been established with a base station within the fence, or based on whether the GNSS positioning signal (such as GPS or Beidou) from a device (such as a shared bike or car) exceeds the spatial range of the fence.

[0003] Currently, mobile phones are widely used, and the coverage density of communication base stations is increasing. The interaction and communication between mobile phones and base stations generates a large amount of signaling data. This signaling data is processed in real time on the operator network side to generate location data. In theory, this operator network data contains users' spatiotemporal information, is highly fresh, and covers a large population, making it suitable for crowd management within electronic fences designated in key areas. However, base stations typically collect signaling data every five seconds. For a city with a population of tens of millions, the operator network data accumulated daily can reach several terabytes, exceeding a trillion points. Defining electronic fences in key areas based on such a large amount of data and detecting and reporting abnormal entries and exits in real time is extremely time-consuming and difficult. Therefore, currently, there is no efficient electronic fence method in China or abroad that uses communication big data to control multiple key areas within a city. Existing electronic fence technologies in areas such as base station signal management and vehicle management are not suitable for this problem due to the different data and management targets. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the purpose of the present invention is to provide a high-performance electronic fence method, device and equipment based on communication big data, which can realize real-time detection of people prohibited from entering and leaving the designated electronic fence from the massive operator network side data in megacities, and support the determination of the initial people within the fence, and can be used for access management of key places in megacities.

[0005] The present invention is achieved through the following technical solutions:

[0006] A high-performance electronic fence method based on communication big data includes the following steps:

[0007] Step 1: spatial grid division: divide the spatial range of the designated city or region into n spatial grids and encode each spatial grid;

[0008] Step 2: Build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong;

[0009] Step 3: Build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information, and a list of people allowed to enter the electronic fence;

[0010] Step 4: Establishing an electronic fence management system, which is used to create, delete and modify electronic fences in the database;

[0011] Step 5: Quickly delineate the initial population within the electronic fence based on the index of the spatial grid;

[0012] Step 6: Real-time operator network-side data access, preprocessing, and coarse screening;

[0013] Step 7: Parallel calculation of the persons currently inside the electronic fence and the persons not inside the fence;

[0014] Step 8: Parallel calculation of abnormal entry and exit events exceeding a certain time period of the geo-fence, and timely reporting to the geo-fence management system.

[0015] Furthermore, in step 2, it is assumed that in the operator network side database, a piece of operator network side data is organized as follows:

[0016] o ={"LONGITUDE": double, "LATITUDE": double, "TIME": int64, "IMSI":int64}

[0017] Where "IMSI" is the International Mobile Subscriber Identity, "TIME" is the Unix timestamp, and "LONGITUDE" and "LATITUDE" are the longitude and latitude.

[0018] Calculate the code "GRID_ID" of the spatial grid to which it belongs based on the "LONGITUDE" and "LATITUDE" of o, establish a database to store each o and its "GRID_ID" field, and create an index for the "GRID_ID" and "TIME" fields of each o.

[0019] Furthermore, in step 4, in the electronic fence management system, the polygonal boundary point "POLYGON", the name "NAME", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" of the input fence e are obtained, and the electronic fence is created in the electronic fence database; the name of the input fence is obtained, and the electronic fence with "NAME" as the name is deleted in the electronic fence database; the input name and one or more of the polygonal boundary point "POLYGON", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" are obtained, and the electronic fence "NAME" is modified to the relevant information of the name in the electronic fence database.

[0020] Furthermore, in step 5, when creating an electronic fence e, if the identification code set "I" of people allowed to enter the electronic fence e is not determined, or if it is desired to use people in the time period t_1-t_2 in e as the identification code set "I" of people allowed to enter e, the communication big data is used to efficiently calculate the set of people in e in a certain time period, and the "I_A" or "I_B" of e in the electronic fence database is updated to "I": the coding set "L_GRID_ID" of the spatial grid spanned by e is quickly retrieved using the electronic fence database, and the identification code set L_IMSI of all people in the spatial grid corresponding to each "GRID_ID" in the set "L_GRID_ID" within the time period t_1-t_2 is quickly retrieved using the operator network side database. For ∀imsi∈L_IMSI, the time when the person corresponding to each imsi is within the boundary of e is calculated. If the time is greater than t_3, the person is regarded as a person allowed to enter e.

[0021] Furthermore, in step 6, the operator network data collected and generated each time for the entire city or region from the operator network is accessed and preprocessed, such as filtering for invalid values, to obtain a set O_1T. Based on the spatial index, a network data set O_F that may be located within the electronic fence set L_E stored in the electronic fence database is preliminarily screened out. Also, a set I_OUT_ALL of identification codes for persons not in L_E is preliminarily screened out based on the spatial index. Network data far from L_E is filtered out, thereby significantly reducing the amount of subsequent computation. Communication flow data from the operator network is parsed and accessed in real time. For each data item, the "IMSI", "TIME", "LONGITUDE", and "LATITUDE" fields are extracted to form o. o items containing invalid or incomplete field values ​​are eliminated. Then, the "GRID_ID" field value gid is calculated based on the "LONGITUDE" and "LATITUDE" fields of each o item. The electronic fence data is used to quickly retrieve whether the "L_GRID_ID" of the fence in the database contains gid. If not, the o item is filtered out; otherwise, the o item is added to O_F.

[0022] Furthermore, in step 7, for ∀e∈L_E, based on the O_F and I_OUT_ALL, the identification code set I_IN_E of the persons currently within the fence and the identification code set I_OUT_E of the persons not within the fence are calculated in parallel: let I_OUT_E=I_OUT_ALL, for ∀o∈O_F, determine whether the spatial point formed by the "LONGITUDE" and "LATITUDE" fields of o is in the closed polygon formed by the "POLYGON" field of e. If so, add the "IMSI" field value of o to I_IN_E, otherwise add it to I_OUT_E.

[0023] Furthermore, in step 8, for ∀e∈L_E, based on the "I_A", "I_B", I_OUT_E and I_IN_E of said e, the events of abnormal entry and exit of fence e exceeding time t_4 are calculated in parallel and reported in a timely manner: for each operator network-side data collected and generated for the entire city or region, first, the set of personnel identification codes of abnormal entry in I_IN_E is calculated in parallel, that is, I_IN_E_ILLEGAL = I_IN_E \ (I_A∪I_B), and then the set of personnel identification codes of abnormal exit in I_OUT_E is calculated in parallel, that is, I_OUT_E_ILLEGAL = I_B∩I_OUT_E. If the duration of the identification codes in I_IN_E_ILLEGAL and I_OUT_E_ILLEGAL exceeds t_4, the event and the corresponding personnel identification code are reported. After the event is reported, the operator network side data set O_1T is inserted into the operator network side database.

[0024] A high-performance electronic fence device based on communication big data, comprising:

[0025] The spatial grid division module is used for spatial grid division. Based on the specified spatial grid division method and spatial grid resolution r, the spatial range of the specified city or region is divided into n spatial grids, and each spatial grid is encoded;

[0026] An operator network side database module is used to build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong;

[0027] An electronic fence database module is used to build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information and the list of people allowed to enter the electronic fence;

[0028] The electronic fence management module is used to establish an electronic fence management system, which is used to create, delete and modify electronic fences in the database:

[0029] The module for quickly defining the initial population of the electronic fence is used to quickly define the initial population within the electronic fence;

[0030] Real-time operator network side data processing module, used for real-time operator network side data access, pre-processing, and coarse screening;

[0031] The module for calculating the entry and exit of the electronic fence is used to calculate the number of people currently inside the electronic fence and those outside the fence in parallel;

[0032] The abnormal entry and exit fence detection and reporting module is used to parallelly calculate the events of abnormal entry and exit of the electronic fence for more than a certain period of time, and report them to the electronic fence management system in a timely manner.

[0033] A high-performance electronic fence device based on communication big data, the device includes a distributed memory, a processor, and a computer program in the memory and executable in the processor. When the processor executes the computer program, the steps of the high-performance electronic fence method based on communication big data are implemented.

[0034] A storage medium stores a computer program, which, when executed by a processor, implements the steps of the high-performance electronic fence method based on communication big data.

[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0036] (1) The present invention proposes a high-performance electronic fence method, device and equipment based on communication big data, which realizes the electronic fence management in key areas of megacities with a population of tens of millions. Compared with physical electronic fences and GNSS-based electronic fence methods, the present invention uses communication big data with high temporal freshness and high population coverage, and has the advantages of low cost and high population coverage. It can be used in the protection and management of key areas such as museums, schools, and wildlife reserves.

[0037] (2) The present invention proposes a high-performance electronic fence method, device and equipment based on communication big data, which supports the demarcation and management of a large number of electronic fences. It can automatically extract a list of people allowed to enter the fence from the communication big data according to the time range and fence boundary specified by the user. Moreover, for each demarcated electronic fence, the present invention can detect and report two types of events and people: abnormal entry into the fence and abnormal exit from the fence.

[0038] (3) The present invention proposes a high-performance electronic fence method, device and equipment based on communication big data, which uses spatial index to roughly screen the communication big data, and then uses parallel technology to perform rapid event detection of abnormal entry and exit of the electronic fence. It has the advantages of high performance and high efficiency, and can quickly detect and report people who abnormally enter and exit the electronic fence from tens of millions of real-time communication flow data per second, without causing the accumulation of communication big data when it is stored in the warehouse. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0040] Figure 1This is a flowchart of a high-performance electronic fence method based on communication big data provided by an embodiment of the present invention.

[0041] Figure 2 This is a structural diagram of a high-performance electronic fence device based on communication big data provided by an embodiment of the present invention.

[0042] Figure 3 This is a schematic diagram of an event of abnormal entry and exit of an electronic fence detected and reported by a high-performance electronic fence device based on communication big data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0044] A high-performance electronic fence method based on communication big data, such as Figure 1 As shown, the following steps are included:

[0045] Step 1: spatial grid division: divide the spatial range of the designated city or region into n spatial grids and encode each spatial grid;

[0046] Step 2: Build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong;

[0047] Step 3: Build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information, and a list of people allowed to enter the electronic fence;

[0048] Step 4: Establishing an electronic fence management system, which is used to create, delete and modify electronic fences in the database;

[0049] Step 5: Quickly delineate the initial population within the electronic fence based on the index of the spatial grid;

[0050] Step 6: Real-time operator network-side data access, preprocessing, and coarse screening;

[0051] Step 7: Parallel calculation of the persons currently inside the electronic fence and the persons not inside the fence;

[0052] Step 8: Parallel calculation of abnormal entry and exit events exceeding a certain time period of the geo-fence, and timely reporting to the geo-fence management system.

[0053] The present invention provides a high-performance electronic fencing method based on communication big data, which realizes electronic fencing management in key areas of megacities with a population of tens of millions. Compared with physical electronic fencing and GNSS-based electronic fencing methods, the present invention uses communication big data with high temporal freshness and high population coverage, and has the advantages of low cost and high population coverage. It can be used for the protection and management of key areas such as schools and museums, and the closed management of wildlife reserves.

[0054] The present invention provides a high-performance electronic fence method based on communication big data, which supports the demarcation and management of a large number of electronic fences. It can automatically extract a list of people allowed to enter the fence from the communication big data according to the time range and fence boundaries specified by the user. For each demarcated electronic fence, the present invention can detect and report two types of events and people: abnormal entry into the fence and abnormal exit from the fence.

[0055] The present invention provides a high-performance electronic fence method based on communication big data. It uses spatial indexing to roughly screen the communication big data, and then uses parallel technology to perform rapid event detection of abnormal entry and exit of the electronic fence. It has the advantages of high performance and high efficiency. It can quickly detect and report people who abnormally enter and exit the electronic fence from tens of millions of real-time communication flow data per second, and will not cause the accumulation of communication big data when it is stored.

[0056] In the present invention, in step 1, the space grid division method adopts regular quadrilaterals, regular hexagons or regular triangles to perform uniform space grid division, and the encoding method adopts row and column number encoding.

[0057] In step 2, it is assumed that in the operator network side database, a piece of operator network side data is organized as follows:

[0058] o ={"LONGITUDE": double, "LATITUDE": double, "TIME": int64, "IMSI":int64}

[0059] Where "IMSI" is the International Mobile Subscriber Identity, "TIME" is the Unix timestamp, and "LONGITUDE" and "LATITUDE" are the longitude and latitude.

[0060] Calculate the code "GRID_ID" of the spatial grid to which it belongs based on the "LONGITUDE" and "LATITUDE" of o, establish a database to store each o and its "GRID_ID" field, and create an index for the "GRID_ID" and "TIME" fields of each o.

[0061] In step 2, the operator network side database uses HBase, MongoDB or CouchDB distributed database, and the index uses RTree, Hash or BTree index structure.

[0062] In step 3, each electronic fence e is a closed polygon "POLYGON" consisting of a series of spatial points. The attributes of each e include the fence name "NAME", the start time "START_T", the end time "END_T", etc., and the identification code set "I" of people allowed to enter the fence. The "I" of each fence is divided into the identification code set "I_A" of people allowed to leave the fence and the identification code list "I_B" of people prohibited from leaving the fence. Based on the "POLYGON" of each e, the coding set "L_GRID_ID" of the spatial grid it spans is calculated. A database is established to store the "POLYGON", "I_A", "I_B", attribute information and "GRID_ID" of each e, and an index is established for the "GRID_ID" and "NAME" of each e.

[0063] In step 3, the electronic fence database uses HBase, MongoDB or CouchDB distributed database, and the index uses RTree, Hash or BTree index structure.

[0064] In step 4, in the electronic fence management system, the polygonal boundary point "POLYGON", the name "NAME", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" of the input fence e are obtained, and the electronic fence is created in the electronic fence database; the name of the input fence is obtained, and the electronic fence with "NAME" as the name is deleted in the electronic fence database; the input name and one or more of the polygonal boundary point "POLYGON", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" are obtained, and the electronic fence "NAME" is modified in the electronic fence database to the relevant information of the name.

[0065] In step 5, when creating an electronic fence e, if the identification code set "I" of persons allowed to enter the electronic fence e is uncertain, or if it is desired to use persons within the time period t_1-t_2 in e as the identification code set "I" of persons allowed to enter e, the communication big data is used to efficiently calculate the set of persons within e in a certain time period, and the "I_A" or "I_B" of e in the electronic fence database is updated to "I": the coding set "L_GRID_ID" of the spatial grid spanned by e is quickly retrieved using the electronic fence database, and the identification code set L_IMSI of all persons in the spatial grid corresponding to each "GRID_ID" in the set "L_GRID_ID" within the time period t_1-t_2 is quickly retrieved using the operator network side database. For ∀imsi∈L_IMSI, the time when the person corresponding to each imsi is within the boundary of e is calculated. If the time is greater than t_3, the person is regarded as a person allowed to enter e.

[0066] Through step 5, the high temporal sampling frequency and high population coverage characteristics of communication big data are fully utilized. When creating an electronic fence, according to the spatial area of ​​the electronic fence and the specified time range, the spatial grid index can be used to quickly find the people corresponding to the communication big data within the specified spatial range and time range, so as to serve as the initial population of the electronic fence, avoiding the time-consuming and costly manual census work.

[0067] In step 6, the operator network data collected and generated for the entire city or region is accessed and pre-processed, such as filtering for invalid values, to obtain a set O_1T. A spatial index is then used to preliminarily filter out the network data set O_F that may be located within the electronic fence set L_E stored in the electronic fence database. Furthermore, a spatial index is used to preliminarily filter out the identification code set I_OUT_ALL for individuals not within L_E. This filter eliminates network data far from L_E, significantly reducing subsequent computational complexity. Communication flow data from the operator network is parsed and accessed in real time. For each data entry, the "IMSI," "TIME," "LONGITUDE," and "LATITUDE" fields are extracted to form an o. o entries containing invalid or incomplete field values ​​are then removed. Next, the "GRID_ID" value gid is calculated based on the "LONGITUDE" and "LATITUDE" fields of each o entry. The electronic fence data is then used to quickly determine whether the "L_GRID_ID" of a fence in the database contains gid. If not, the o entry is filtered out; otherwise, the o entry is added to O_F.

[0068] Through step 6, the operator network side data is accessed in real time, and during the access process, preliminary screening is first performed based on the spatial grid index to eliminate invalid data and data far away from the electronic fence, thereby greatly reducing the subsequent calculation amount.

[0069] In step 7, for ∀e∈L_E, based on the O_F and I_OUT_ALL, the identification code set I_IN_E of the people currently inside the fence and the identification code set I_OUT_E of the people not inside the fence are calculated in parallel: let I_OUT_E=I_OUT_ALL, for ∀o∈O_F, determine whether the spatial point formed by the "LONGITUDE" and "LATITUDE" fields of o is in the closed polygon formed by the "POLYGON" field of e. If so, add the "IMSI" field value of o to I_IN_E, otherwise add it to I_OUT_E.

[0070] In step 7, whether the spatial point is in the closed polygon formed by the "POLYGON" field of e is determined by using a dichotomy method, a crossing number, or a winding number.

[0071] In step 7, whether the spatial point is in the closed polygon formed by the "POLYGON" field of e is determined by using a dichotomy method, a crossing number, or a winding number.

[0072] Through step 7, a parallel method is used to quickly calculate the persons inside the fence and outside the fence from the current data, so as to further distinguish the persons who abnormally enter the fence and those who abnormally leave the fence at the current moment.

[0073] Specifically, step 7 includes:

[0074] Step 701: For ∀e∈L_E, based on O_F and I_OUT_ALL, Spark distributed parallel computing is used to calculate the identification code set I_IN_E of the people currently inside the fence and the identification code set I_OUT_E of the people outside the fence: Let I_OUT_E = I_OUT_ALL. For ∀o∈O_F, use the intersection number method to determine whether the spatial point formed by the "LONGITUDE" and "LATITUDE" fields of o is within the closed polygon formed by the "POLYGON" field of e. If so, add the value of the "IMSI" field of o to I_IN_E; otherwise, add it to I_OUT_E.

[0075] Step 702: For ∀e∈L_E, based on "I_A", "I_B", I_OUT_E, and I_IN_E of e, Spark distributed parallel computing is used to calculate events of abnormal entry and exit of fence e exceeding 5 minutes, and timely report them: For each operator network-side data collected and generated for the entire city or region, first, in parallel, the set of personnel identification codes of abnormal entry in I_IN_E is calculated, I_IN_E_ILLEGAL, i.e., I_IN_E_ILLEGAL = I_IN_E \ (I_A∪I_B). Then, the set of personnel identification codes of abnormal exit in I_OUT_E is calculated, I_OUT_E_ILLEGAL = I_B∩I_OUT_E. If the duration of the identification codes in I_IN_E_ILLEGAL and I_OUT_E_ILLEGAL exceeds t_4, the event and the corresponding personnel identification code are reported;

[0076] Step 703: After the abnormal event is reported, O_1T is inserted into the operator network side database.

[0077] In step 8, for ∀e∈L_E, based on e's "I_A," "I_B," I_OUT_E, and I_IN_E, events of abnormal entry and exit of fence e exceeding time t_4 are calculated in parallel and reported promptly: For each instance of operator network-side data collected and generated for the entire city or region, first, in parallel, the set of person identification codes for abnormal entries in I_IN_E, I_IN_E_ILLEGAL, is calculated, i.e., I_IN_E_ILLEGAL = I_IN_E \ (I_A∪I_B). Next, the set of person identification codes for abnormal exits in I_OUT_E, I_OUT_E_ILLEGAL, is calculated, i.e., I_OUT_E_ILLEGAL = I_B∩I_OUT_E. If the duration of the identification codes in I_IN_E_ILLEGAL and I_OUT_E_ILLEGAL exceeds t_4, the event and the corresponding person identification code are reported. After the event is reported, the operator network side data set O_1T is inserted into the operator network side database.

[0078] In step 8, t_4 is a time threshold specified by the user.

[0079] In step 8, the parallel computing method adopts OpenMP, POSIX Threads single-node multi-threaded parallel mode, or adopts MPI, Hadoop, Spark distributed parallel mode.

[0080] Through step 8, the number of people who abnormally enter and exit the electronic fence can be quickly calculated from the communication big data with high time sampling frequency and high population coverage, and reported in a timely manner.

[0081] In one embodiment of the present invention, taking the abnormal entry and exit detection of a school in a certain city as an example, a high-performance electronic fence method based on communication big data provided by the present invention is implemented to obtain events of abnormal entry and exit of the electronic fence for more than a certain time. In step 1, the school space grid is divided. Based on the uniform space grid division method and the space grid resolution of 500×500 meters, the school space range is divided into 34276 space grids, and the divided space grids are encoded using row and column number coding. In step 5, taking January 1, 2022, 13:00-January 1, 2022, 13:05 as the time period, the communication big data can be used to efficiently calculate the set of people in the electronic fence e from January 1, 2022, 13:00-January 1, 2022, 13:05, and the "I_A" or "I_B" of e in the electronic fence database is updated to " I": First, use the electronic fence database to quickly retrieve the code set "L_GRID_ID" of the spatial grid spanned by e, and use the operator network side database to quickly retrieve the identification code set L_IMSI of all people in the spatial grid corresponding to each "GRID_ID" in the set "L_GRID_ID" between 13:00 on January 1, 2022 and 13:05 on January 1, 2022. For ∀imsi∈L_IMSI, based on the "LONGITUDE" and "LATITUDE" field values, accurately calculate whether o with "IMSI" as imsi is within the boundary of e. The time that the person corresponding to each imsi is within the boundary of e is the cumulative continuous time length of all o with "IMSI" as imsi located within the boundary of e. If this time is greater than 3 minutes, the person is allowed to enter e, such as Figure 3 As shown, an electronic fence 652 is established, wherein a solid circle represents an abnormal entry event, and a solid square represents an abnormal exit event, which proves that the present invention can effectively realize real-time detection of persons prohibited from entering and leaving the designated electronic fence from the massive operator network-side data of a megacity, and supports the determination of the initial persons within the fence, and can be used for access management of key places in a megacity.

[0082] The present invention also provides a high-performance electronic fence device based on communication big data, such as Figure 2 Shown, including:

[0083] The spatial grid division module is used for spatial grid division. Based on the specified spatial grid division method and spatial grid resolution r, the spatial range of the specified city or region is divided into n spatial grids, and each spatial grid is encoded;

[0084] An operator network side database module is used to build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong;

[0085] An electronic fence database module is used to build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information and the list of people allowed to enter the electronic fence;

[0086] The electronic fence management module is used to establish an electronic fence management system, which is used to create, delete and modify electronic fences in the database:

[0087] The module for quickly defining the initial population of the electronic fence is used to quickly define the initial population within the electronic fence;

[0088] Real-time operator network side data processing module, used for real-time operator network side data access, pre-processing, and coarse screening;

[0089] The module for calculating the entry and exit of the electronic fence is used to calculate the number of people currently inside the electronic fence and those outside the fence in parallel;

[0090] The abnormal entry and exit fence detection and reporting module is used to parallelly calculate the events of abnormal entry and exit of the electronic fence for more than a certain period of time, and report them to the electronic fence management system in a timely manner.

[0091] In one embodiment of the present invention, the grid division module is used to divide the spatial range of a specified city or region into grids and encode the divided grids;

[0092] The carrier network database module is used to store massive, high-frequency, and high-fresh carrier network data and the codes of the grids to which it belongs. It provides high-performance insertion and retrieval of carrier network data and supports multi-node redundancy and horizontal expansion.

[0093] The electronic fence database module is used to store the spatial boundaries and attribute information of the electronic fence and the list of people allowed to enter the fence. It provides high-performance electronic fence insertion and retrieval, and supports multi-node redundancy and horizontal expansion.

[0094] Electronic fence management module, used to create, delete and modify electronic fences in the database;

[0095] The electronic fence management module can obtain the polygonal boundary points, name, set of identification codes for people allowed to enter the fence, start time and end time of the input fence e, and call the fence database module's API to create the electronic fence; can obtain the name of the input fence and call the electronic fence database module's search API to delete the electronic fence with the input name "NAME"; can obtain the input name and one or more of the polygonal boundary points, set of identification codes for people allowed to enter the fence, start time and end time, and call the electronic fence database module's API to modify the information related to the electronic fence "NAME" to the input name;

[0096] The initial population rapid demarcation module for the fence uses communication big data to efficiently calculate the set of identification codes of people within the specified electronic fence e and a certain time period. This set of identification codes serves as the set of identification codes for people allowed to enter the fence e and updates the electronic fence database module.

[0097] The data access, preprocessing, and coarse screening module is used to access the operator network-side data collected and generated every time in the entire city or region, perform preprocessing such as filtering invalid values, and then preliminarily screen out the network-side data set O_F that may be located in the electronic fence set L_E stored in the electronic fence database module based on the spatial index, as well as the identification code set I_OUT_ALL of people not in L_E;

[0098] Fence entry and exit calculation module: for ∀e∈L_E, after calling the real-time operator network-side data access, preprocessing, and coarse screening modules, it obtains OF and I_OUT_ALL, and concurrently calculates the identification code set I_IN_E of the people currently inside fence e and the identification code set I_OUT_E of the people outside the fence.

[0099] Abnormal entry and exit fence detection and reporting module: for ∀e∈L_E, call the entry and exit fence calculation module to obtain I_OUT_E and I_IN_E, parallelly calculate the events of abnormal entry and exit of fence e exceeding time t_4, and report them in time.

[0100] A high-performance electronic fence device based on communication big data, the device includes a distributed memory, a processor, and a computer program in the memory and executable in the processor. When the processor executes the computer program, the steps of the high-performance electronic fence method based on communication big data are implemented.

[0101] It should be noted that the high-performance electronic fence device based on communication big data provided in the above embodiment is only illustrated by the division of the above-mentioned program modules when performing high-performance electronic fencing based on communication big data. In actual applications, the above-mentioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the high-performance electronic fence device based on communication big data provided in the above embodiment and the high-performance electronic fence method embodiment based on communication big data belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0102] The memory in the embodiment of the present invention is used to store various types of data to support the operation of the high-performance electronic fence device based on communication big data. Examples of such data include any computer program used to operate on the high-performance electronic fence device based on communication big data.

[0103] The high-performance electronic fence method based on communication big data disclosed in the embodiments of the present invention can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, the various steps of the high-performance electronic fence method based on communication big data can be completed by hardware integrated logic circuits or software instructions in the processor. The processor may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium located in a memory. The processor reads information from the memory and, in conjunction with its hardware, completes the steps of the high-performance electronic fence method based on communication big data provided in the embodiments of the present invention.

[0104] In an exemplary embodiment, a high-performance electronic fence device based on communication big data can be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to execute the aforementioned method.

[0105] It is understood that the memory can be volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. Among them, the non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disk, or compact disc read-only memory (CD-ROM); magnetic surface memory can be magnetic disk memory or tape memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM). The memory described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0106] In an exemplary embodiment, the present invention further provides a storage medium, namely, a computer storage medium, specifically a computer-readable storage medium, such as a memory storing a computer program. The computer program can be executed by a processor of a high-performance electronic fence device based on communication big data, and the steps of the high-performance electronic fence method based on communication big data are described. The computer-readable storage medium can be a memory such as ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0107] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A high-performance electronic fence method based on communication big data, characterized in that: The following steps are involved: Step 1: spatial grid division: divide the spatial range of the designated city or region into n spatial grids and encode each spatial grid; Step 2: Build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong; Step 3: Build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information, and a list of people allowed to enter the electronic fence; Step 4: Establishing an electronic fence management system, which is used to create, delete and modify electronic fences in the database; Step 5: Quickly delineate the initial population within the electronic fence based on the index of the spatial grid; Step 6: Real-time operator network-side data access, preprocessing, and coarse screening; Step 7: Parallel calculation of the persons currently inside the electronic fence and the persons not inside the fence; Step 8: Parallel calculation of abnormal entry and exit events exceeding a certain time limit, and timely reporting to the electronic fence management system; In step 2, it is assumed that in the operator network side database, a piece of operator network side data is organized as follows: o ={"LONGITUDE": double, "LATITUDE": double, "TIME": int64, "IMSI":int64} Where "IMSI" is the International Mobile Subscriber Identity, "TIME" is the Unix timestamp, and "LONGITUDE" and "LATITUDE" are the longitude and latitude. Calculate the code "GRID_ID" of the spatial grid to which it belongs based on the "LONGITUDE" and "LATITUDE" of o, establish a database to store each o and its "GRID_ID" field, and create an index for the "GRID_ID" and "TIME" fields of each o.

2. The high-performance electronic fence method based on communication big data according to claim 1 is characterized by: In step 4, in the electronic fence management system, the polygonal boundary point "POLYGON", the name "NAME", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" of the input fence e are obtained, and the electronic fence is created in the electronic fence database; the name of the input fence is obtained, and the electronic fence with "NAME" as the name is deleted in the electronic fence database; the input name and one or more of the polygonal boundary point "POLYGON", the identification code set "I" of the personnel allowed to enter the fence, the start time "START_T" and the end time "END_T" are obtained, and the electronic fence "NAME" is modified in the electronic fence database to the relevant information of the name.

3. The high-performance electronic fence method based on communication big data according to claim 1 is characterized in that: In step 5, when creating an electronic fence e, if the set of identification codes "I" of persons allowed to enter the electronic fence e is uncertain, or if it is desired to use persons within the time period t_1-t_2 of e as the set of identification codes "I" of persons allowed to enter e, the communication big data is used to efficiently calculate the set of persons within e for a certain time period, and "I_A" or "I_B" of e in the electronic fence database is updated to "I": the set of codes "L_GRID_ID" of the spatial grids spanned by e is quickly retrieved using the electronic fence database, and the set of identification codes L_IMSI of all persons in the spatial grid corresponding to each "GRID_ID" in the set "L_GRID_ID" within the time period t_1-t_2 is quickly retrieved using the operator network-side database. For ∀imsi∈L_IMSI, the time that the person corresponding to each imsi is within the boundary of e is calculated. If the time is greater than t_3, the person is considered to be allowed to enter e. Wherein, "I_A" represents the set of identification codes of persons allowed to leave the fence, and "I_B" represents the set of identification codes of persons prohibited from leaving the fence.

4. The high-performance electronic fence method based on communication big data according to claim 3 is characterized by: In step 6, the operator network data collected and generated for the entire city or region from the operator network is accessed, pre-processed by filtering out invalid values ​​to obtain a set O_1T, and a network data set O_F that may be located within the electronic fence set L_E stored in the electronic fence database is preliminarily screened based on the spatial index. Also, a set I_OUT_ALL of identification codes for individuals not within L_E is preliminarily screened based on the spatial index, thereby filtering out network data far from L_E, thereby significantly reducing the amount of subsequent computation. Communication flow data from the operator network is parsed and accessed in real time. For each data item, the "IMSI", "TIME", "LONGITUDE", and "LATITUDE" fields are extracted to form o. o items containing invalid or incomplete field values ​​are eliminated. Then, the "GRID_ID" field value gid is calculated based on the "LONGITUDE" and "LATITUDE" fields of each o item. The electronic fence data is used to quickly retrieve whether the "L_GRID_ID" of a fence in the database contains gid. If not, the o item is filtered out; otherwise, the o item is added to O_F.

5. The high-performance electronic fence method based on communication big data according to claim 4 is characterized in that: In step 7, for ∀e∈L_E, based on the O_F and I_OUT_ALL, the identification code set I_IN_E of the people currently inside the fence and the identification code set I_OUT_E of the people not inside the fence are calculated in parallel: let I_OUT_E=I_OUT_ALL. For ∀o∈O_F, determine whether the spatial point formed by the "LONGITUDE" and "LATITUDE" fields of o is in the closed polygon formed by the "POLYGON" field of e. If so, The "IMSI" field value of o is added to I_IN_E, and vice versa, it is added to I_OUT_E.

6. The high-performance electronic fence method based on communication big data according to claim 5, characterized in that: In step 8, for ∀e∈L_E, based on the "I_A", "I_B", I_OUT_E and I_IN_E of said e, the events of abnormal entry and exit of fence e exceeding time t_4 are calculated in parallel and reported in a timely manner: for each operator network-side data collected and generated for the entire city or region, first, the set of personnel identification codes of abnormal entry in I_IN_E is calculated in parallel, that is, I_IN_E_ILLEGAL = I_IN_E \ (I_A∪I_B), and then the set of personnel identification codes of abnormal exit in I_OUT_E is calculated in parallel, that is, I_OUT_E_ILLEGAL = I_B∩I_OUT_E. If the duration of the identification codes in I_IN_E_ILLEGAL and I_OUT_E_ILLEGAL exceeds t_4, the event and the corresponding personnel identification code are reported. After the event is reported, the operator network side data set O_1T is inserted into the operator network side database.

7. A high-performance electronic fence device based on communication big data, characterized in that: include: The spatial grid division module is used for spatial grid division. Based on the specified spatial grid division method and spatial grid resolution r, the spatial range of the specified city or region is divided into n spatial grids, and each spatial grid is encoded; An operator network side database module is used to build an operator network side database, which is used to store and quickly retrieve massive amounts of operator network side data and the codes of the spatial grids to which they belong; An electronic fence database module is used to build an electronic fence database, which is used to store and quickly retrieve the spatial boundaries, attribute information and the list of people allowed to enter the electronic fence; The electronic fence management module is used to establish an electronic fence management system, which is used to create, delete and modify electronic fences in the database: The module for quickly defining the initial population of the electronic fence is used to quickly define the initial population within the electronic fence; Real-time operator network side data processing module, used for real-time operator network side data access, pre-processing, and coarse screening; The module for calculating the entry and exit of the electronic fence is used to calculate the number of people currently inside the electronic fence and those outside the fence in parallel; Abnormal entry and exit fence detection and reporting module, used to parallelly calculate the events of abnormal entry and exit of the electronic fence for more than a certain period of time, and report them to the electronic fence management system in a timely manner; In the operator network side database, it is assumed that a piece of operator network side data is organized as follows: o ={"LONGITUDE": double, "LATITUDE": double, "TIME": int64, "IMSI":int64} Where "IMSI" is the International Mobile Subscriber Identity, "TIME" is the Unix timestamp, and "LONGITUDE" and "LATITUDE" are the longitude and latitude. Calculate the code "GRID_ID" of the spatial grid to which it belongs based on the "LONGITUDE" and "LATITUDE" of o, establish a database to store each o and its "GRID_ID" field, and create an index for the "GRID_ID" and "TIME" fields of each o.

8. A high-performance electronic fence device based on communication big data, characterized by: The device includes a distributed memory, a processor, and a computer program in the memory and executable in the processor. When the processor executes the computer program, the steps of the high-performance electronic fence method based on communication big data described in any one of claims 1 to 6 are implemented.

9. A storage medium storing a computer program, wherein: When the computer program is executed by a processor, the steps of the high-performance electronic fence method based on communication big data described in any one of claims 1 to 6 are implemented.

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