Sensing detection method, apparatus, and processor-readable storage medium

Abstract

The present disclosure provides a sensing detection method, an apparatus, and a processor-readable storage medium. The method comprises: receiving sensing data of a target area sent by a second network element; and determining a sensing detection result on the basis of the sensing data, wherein the sensing detection result is used for indicating sensing target related information in the target area.

Description

Sensing and detection methods, devices, and processors; readable storage media

[0001] This disclosure claims priority to Chinese Patent Application No. 202411799929.5, filed with the Chinese Patent Office on December 09, 2024, entitled "Sensing and Detection Method, Apparatus and Processor-Readable Storage Medium", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of communication technology, and in particular to a sensing and detection method, apparatus, and processor-readable storage medium. Background Technology

[0003] Communication sensing technology is one of the key technologies in current mobile communications and future networks, playing a significant role in vertical fields such as intelligent transportation, drone surveillance, national railway perimeter security detection, smart homes, public safety, health monitoring, and environmental monitoring. Target detection in air traffic control is one of its primary application scenarios. For example, it involves determining whether unauthorized targets (those that do not meet security requirements) are intruding into a target area based on the sensing and detection behavior of targets, or whether there are conflicts between different targets. However, current network technologies lack specific procedures for identifying targets within a target area. Summary of the Invention

[0004] This disclosure provides a sensing detection method, apparatus, and processor-readable storage medium, which solves the problem that current network technologies lack relevant processes for determining sensing targets within a target area.

[0005] Embodiments of this disclosure provide a sensing and detection method, applied to a first network element, comprising:

[0006] Receive sensing data of the target area sent by the second network element;

[0007] Based on the perception data, a perception detection result is determined; wherein the perception detection result is used to indicate relevant information about the perception target within the target area.

[0008] In some embodiments, the perception detection result includes at least one of the following:

[0009] The target area may contain a sensing target or the target area may not contain a sensing target.

[0010] The sensing targets in the target area meet the safety conditions, or the sensing targets in the target area do not meet the safety conditions;

[0011] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0012] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0013] The time information of conflicts occurring between different sensing targets within the target area;

[0014] The location information of conflicts between different sensing targets within the target area.

[0015] In some embodiments, the first type of perceived target information includes at least one of the following:

[0016] The identification information of the first type of perceived target;

[0017] The type of the first type of perceived target;

[0018] Size information of the first type of perceived target;

[0019] Material information of the first type of perceived target.

[0020] In some embodiments, the perceived data includes at least one of the following:

[0021] Perceive target information;

[0022] Analyze the mobility of the target;

[0023] Analyze and predict the movement trajectory of the perceived target;

[0024] Analyzing the perception accuracy of the target;

[0025] Information on the perceived credibility of the target.

[0026] In some embodiments, the perceived target information includes at least one of the following:

[0027] Perceive the identification information of the target;

[0028] Perceive the material information of the target;

[0029] Perceive the size information of the target;

[0030] Perceive the image information of the target.

[0031] In some embodiments, determining the perception detection result based on the perception data includes at least one of the following:

[0032] Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, it is determined whether the sensing target meets the safety conditions or whether the sensing target does not meet the safety conditions.

[0033] The type of the perceived target is determined based on at least one of the following: material information of the perceived target, size information of the perceived target, identification information of the perceived target, and image information of the perceived target contained in the perceived data;

[0034] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, it is determined that there is a conflict between different perceived targets in the target area or that there is no conflict between different perceived targets in the target area.

[0035] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine the time information of the conflict between different perceived targets in the target area;

[0036] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, the location information of the conflict between different perceived targets in the target area is determined.

[0037] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0038] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0039] In some embodiments, before receiving the sensing data of the target area sent by the second network element, the method further includes:

[0040] Send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

[0041] In some embodiments, the perception detection method further includes:

[0042] The system receives a second request message sent by a third network element; wherein the second request message is used to request the detection of sensing target-related information within the target area.

[0043] In some embodiments, the second request message carries at least one of the following:

[0044] The second type of perceived target information; wherein, the second type of perceived target is a perceived target that meets the security conditions;

[0045] Perceive the business type;

[0046] Perceive business requirements;

[0047] The triggering conditions for sensing business processes.

[0048] In some embodiments, the perception detection method further includes:

[0049] Send a third request message to the third network element;

[0050] A response message is received from the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

[0051] In some embodiments, the perception detection method further includes:

[0052] Authorization verification is performed on the third network element;

[0053] If the authorization verification of the third network element is successful, a first request message is sent to the second network element.

[0054] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, application data analytics enablement service (ADAES) network element, artificial intelligence / machine learning enablement service (AIMLE) network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0055] In some embodiments, the perception detection method further includes:

[0056] The sensing and detection results are sent to the third network element.

[0057] In some embodiments, the third network element includes at least one of the following: an application server, a terminal device, and a terminal internal perception management client.

[0058] This disclosure provides a sensing and detection method, wherein the method is applied to a second network element and includes:

[0059] The first network element sends sensing data of the target area to the first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

[0060] In some embodiments, the perception detection result includes at least one of the following:

[0061] The target area may contain a sensing target or the target area may not contain a sensing target.

[0062] The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions;

[0063] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0064] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0065] The time information of conflicts occurring between different sensing targets within the target area;

[0066] The location information of conflicts between different sensing targets within the target area.

[0067] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0068] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0069] In some embodiments, the perceived data includes at least one of the following:

[0070] Perceive target information;

[0071] Analyze the mobility of the target;

[0072] Analyze and predict the movement trajectory of the perceived target;

[0073] Analyzing the perception accuracy of the target;

[0074] Information on the perceived credibility of the target.

[0075] In some embodiments, the perceived target information includes at least one of the following:

[0076] Perceive the identification information of the target;

[0077] Perceive the material information of the target;

[0078] Perceive the size information of the target;

[0079] Perceive the image information of the target.

[0080] In some embodiments, sending the sensing data of the target area to the first network element includes:

[0081] Receive the first request message sent by the first network element;

[0082] Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

[0083] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0084] This disclosure provides a sensing and detection device, including a memory, a transceiver, and a processor;

[0085] The memory stores computer programs; the transceiver, under the control of the processor, sends and receives data; the processor reads the computer programs from the memory and performs the following operations:

[0086] Receive sensing data of the target area sent by the second network element;

[0087] Based on the perception data, a perception detection result is determined; wherein the perception detection result is used to indicate relevant information about the perception target within the target area.

[0088] In some embodiments, the perception detection result includes at least one of the following:

[0089] The target area may contain a sensing target or the target area may not contain a sensing target.

[0090] The sensing targets in the target area meet the safety conditions, or the sensing targets in the target area do not meet the safety conditions;

[0091] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0092] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0093] The time information of conflicts occurring between different sensing targets within the target area;

[0094] The location information of conflicts between different sensing targets within the target area.

[0095] In some embodiments, the first type of perceived target information includes at least one of the following:

[0096] The identification information of the first type of perceived target;

[0097] The type of the first type of perceived target;

[0098] Size information of the first type of perceived target;

[0099] Material information of the first type of perceived target.

[0100] In some embodiments, the perceived data includes at least one of the following:

[0101] Perceive target information;

[0102] Analyze the mobility of the target;

[0103] Analyze and predict the movement trajectory of the perceived target;

[0104] Analyzing the perception accuracy of the target;

[0105] Information on the perceived credibility of the target.

[0106] In some embodiments, the perceived target information includes at least one of the following:

[0107] Perceive the identification information of the target;

[0108] Perceive the material information of the target;

[0109] Perceive the size information of the target;

[0110] Perceive the image information of the target.

[0111] In some embodiments, the processor is configured to read a computer program from the memory and perform at least one of the following operations:

[0112] Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, it is determined whether the sensing target meets the safety conditions or whether the sensing target does not meet the safety conditions.

[0113] The type of the perceived target is determined based on at least one of the following: material information of the perceived target, size information of the perceived target, identification information of the perceived target, and image information of the perceived target contained in the perceived data;

[0114] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, it is determined that there is a conflict between different perceived targets in the target area or that there is no conflict between different perceived targets in the target area.

[0115] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine the time information of the conflict between different perceived targets in the target area;

[0116] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, the location information of the conflict between different perceived targets in the target area is determined.

[0117] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0118] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0119] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0120] Send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

[0121] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0122] The system receives a second request message sent by a third network element; wherein the second request message is used to request the detection of sensing target-related information within the target area.

[0123] In some embodiments, the second request message carries at least one of the following:

[0124] The second type of perceived target information; wherein, the second type of perceived target is a perceived target that meets the security conditions;

[0125] Perceive the business type;

[0126] Perceive business requirements;

[0127] The triggering conditions for sensing business processes.

[0128] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0129] Send a third request message to the third network element;

[0130] A response message is received from the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

[0131] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0132] Authorization verification is performed on the third network element;

[0133] If the authorization verification of the third network element is successful, a first request message is sent to the second network element.

[0134] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0135] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0136] The sensing and detection results are sent to the third network element.

[0137] In some embodiments, the third network element includes at least one of the following: an application server, a terminal device, and a terminal internal perception management client.

[0138] This disclosure provides a sensing and detection device, including:

[0139] The first receiving unit is used to receive sensing data of the target area sent by the second network element;

[0140] The processing unit is configured to determine a perception detection result based on the perception data; wherein the perception detection result is used to indicate information related to the perception target within the target area.

[0141] This disclosure provides a sensing and detection device that operates on a second network element, including a memory, a transceiver, and a processor;

[0142] The memory stores computer programs; the transceiver, under the control of the processor, sends and receives data; the processor reads the computer programs from the memory and performs the following operations:

[0143] The first network element sends sensing data of the target area to the first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

[0144] In some embodiments, the perception detection result includes at least one of the following:

[0145] The target area may contain a sensing target or the target area may not contain a sensing target.

[0146] The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions;

[0147] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0148] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0149] The time information of conflicts occurring between different sensing targets within the target area;

[0150] The location information of conflicts between different sensing targets within the target area.

[0151] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0152] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0153] In some embodiments, the perceived data includes at least one of the following:

[0154] Perceive target information;

[0155] Analyze the mobility of the target;

[0156] Analyze and predict the movement trajectory of the perceived target;

[0157] Analyzing the perception accuracy of the target;

[0158] Information on the perceived credibility of the target.

[0159] In some embodiments, the perceived target information includes at least one of the following:

[0160] Perceive the identification information of the target;

[0161] Perceive the material information of the target;

[0162] Perceive the size information of the target;

[0163] Perceive the image information of the target.

[0164] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0165] Receive the first request message sent by the first network element;

[0166] Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

[0167] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0168] This disclosure provides a sensing and detection device, including:

[0169] A transmitting unit is used to transmit sensing data of a target area to a first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target-related information within the target area.

[0170] This disclosure provides a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the perception detection method described above.

[0171] The beneficial effects of the above-mentioned technical solution disclosed herein are:

[0172] In this embodiment of the present disclosure, the second network element can provide the first network element with the perception data of the target area. When the first network element receives the perception data of the target area sent by the second network element, it can determine the relevant information of the perception target in the target area based on the perception data. That is, the first network element can determine the perception target in the target area through the interaction between the first network element and the second network element, thereby solving the problem that there is no relevant process in the current network technology to determine the perception target in the target area. Attached Figure Description

[0173] Figure 1 shows a flowchart of the sensing and detection method on the first network element side according to an embodiment of the present disclosure;

[0174] Figure 2 shows a flowchart of the sensing and detection method on the second network element side according to an embodiment of the present disclosure;

[0175] Figure 3 shows one of the interactive flow diagrams of the perception detection method according to an embodiment of this disclosure;

[0176] Figure 4 shows a second interactive flowchart of the perception detection method according to an embodiment of this disclosure;

[0177] Figure 5 illustrates the third interactive flow diagram of the perception detection method according to an embodiment of this disclosure;

[0178] Figure 6 shows one of the block diagrams of a sensing and detection device on the first network element side according to an embodiment of the present disclosure;

[0179] Figure 7 shows a second block diagram of the sensing and detection device on the first network element side according to an embodiment of the present disclosure;

[0180] Figure 8 shows a block diagram of one of the sensing and detection devices on the second network element side according to an embodiment of the present disclosure;

[0181] Figure 9 shows a second block diagram of a sensing and detection device on the second network element side according to an embodiment of the present disclosure. Detailed Implementation

[0182] To make the technical problems, solutions, and advantages of this disclosure clearer, a detailed description will be provided below in conjunction with the accompanying drawings and specific embodiments. In the following description, specific details such as particular configurations and components are provided merely to aid in a comprehensive understanding of the embodiments of this disclosure. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Furthermore, for clarity and brevity, descriptions of known functions and structures have been omitted.

[0183] It should be understood that the phrase "an embodiment" or "one embodiment" throughout the specification means that a particular feature, structure, or characteristic relating to an embodiment is included in at least one embodiment of this disclosure. Therefore, "in one embodiment" or "one embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0184] In the various embodiments of this disclosure, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure.

[0185] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0186] The technical solutions provided in this disclosure can be applied to a variety of systems. For example, applicable systems include Global System for Mobile Communication (GSM), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), General Packet Radio Service (GPRS), Long Term Evolution (LTE), LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), Long Term Evolution Advanced (LTE-A), Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX), 4th Generation Mobile Communication Technology (4G), 5th Generation Mobile Communication Technology (5G), New Radio (NR) and its evolution systems, and 6th Generation Mobile Communication Technology (6G), etc. These systems can include terminal devices and network devices. The system may also include a core network component, such as the Evolved Packet Core (EPC) or the 5G Core (5GC).

[0187] Network devices and terminal devices can each use one or more antennas for Multiple Input Multiple Output (MIMO) transmission. MIMO transmission can be Single User MIMO (SU-MIMO) or Multiple User MIMO (MU-MIMO). Depending on the configuration and number of antenna combinations, MIMO transmission can be 2D MIMO, 3D MIMO, Full Dimension MIMO (FD-MIMO), or Massive MIMO, or it can be diversity transmission, pre-coded transmission, or beamforming transmission, etc.

[0188] In this disclosure, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0189] In this disclosure, the term "multiple" refers to two or more, and other quantifiers are similar.

[0190] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0191] The following describes the relevant technologies involved in this disclosure:

[0192] I. Definition of Communication Sensing

[0193] In a narrow sense, perception refers to a system with the ability to locate targets (range, velocity, angle), image targets, detect targets, track targets, and identify targets. In a broad sense, perception refers to a system that can perceive the attributes and states of all services, networks, users and terminals, as well as environmental objects.

[0194] Communication-sensing fusion achieves a unified design of communication and sensing functions through signal joint design and / or hardware sharing. In this fusion, "sensing" can be understood as a wireless sensing technology based on a communication system. It involves transmitting wireless signals to a target area or object and analyzing the received signals to obtain corresponding sensing measurement information. Therefore, wireless communication networks possess wireless sensing capabilities, and base stations and user equipment (UEs) will simultaneously possess both communication and sensing capabilities, enabling them to provide sensing services for applications including intelligent transportation, drone surveillance, national railway perimeter security monitoring, smart homes, public safety, health monitoring, and environmental monitoring.

[0195] II. Perceiving Scenarios and Needs

[0196] Perceptual needs are prevalent across various industries and can be broadly categorized into per-area perception and per-object perception. Per-area perception primarily targets objects within a specific geographical area. For example, monitoring unmanned aerial vehicles (UAVs) at airports requires sensing and detecting a large area of ​​airspace to identify illegal UAV intrusions, or sensing and detecting specific areas around and along railway lines to identify obstacles or unauthorized entry by people or animals. Per-object perception, on the other hand, focuses on sensing a single target object and may even require continuous tracking of that object. Examples include continuously tracking suspicious vehicles or UAVs, or detecting human breathing and heartbeats through the collaboration of base stations and terminal devices. Target objects can lack UE (User Equipment) identification (e.g., animals, buildings); they can also possess UE identification, including the object itself and the UE identification (e.g., a car with a UE module), as well as the coupling relationship between the object and the UE identification (e.g., a person carrying a mobile phone).

[0197] III. Non-3GPP Drone Detection Technologies

[0198] Unmanned aerial vehicle (UAV) detection and identification is a multidisciplinary application technology that can be used to detect, track, and identify UAVs through one or more technologies such as radar detection, radio signal monitoring, and photoelectric identification and tracking.

[0199] Radar detection involves a radar system emitting electromagnetic waves and utilizing the principle of electromagnetic wave reflection from the drone's fuselage to detect and measure its position. By receiving and analyzing the reflected radar waves, the target's distance, altitude, azimuth, and speed information can be obtained. Due to the "low, slow, and small" characteristics of drones, traditional radars are not very effective at detecting them.

[0200] Radio signal monitoring utilizes the spectral characteristics of flight control and image transmission signals to detect and identify unmanned aerial vehicles (UAVs). Single-station direction finding technology can monitor and calculate the UAV's azimuth information, while also using received signal strength to roughly estimate the UAV's distance. Multi-station time difference positioning technology can calculate the target's position information by analyzing the signal delays relative to multiple receiving stations.

[0201] Visible light recognition and tracking utilizes a visible light camera to detect video images of the target drone, thereby identifying and tracking the target. This technology is suitable for daytime use, has relatively low equipment cost, and is widely used. Infrared recognition and tracking utilizes an infrared camera to detect infrared images of the target drone, thereby identifying and tracking the drone.

[0202] The above non-3GPP technologies have problems such as high deployment costs and susceptibility to weather and environmental factors. For example, radar has difficulty detecting hovering or low-speed drones, and optoelectronic systems are greatly affected by weather and may confuse drones with birds or airplanes.

[0203] This disclosure provides a sensing detection method, apparatus, and processor-readable storage medium, addressing the problem that current network technologies lack relevant processes for determining sensing targets within a target area. The method and apparatus are based on the same concept, and since their problem-solving principles are similar, implementations of the apparatus and method can be mutually referenced; repeated details will not be elaborated further.

[0204] As shown in Figure 1, an embodiment of this disclosure provides a sensing and detection method applied to a first network element, comprising the following steps:

[0205] Step 11: Receive the sensing data of the target area sent by the second network element;

[0206] Step 12: Determine the perception detection result based on the perception data; wherein the perception detection result is used to indicate the perception target information in the target area.

[0207] In this embodiment of the present disclosure, the second network element can provide the first network element with the perception data of the target area. When the first network element receives the perception data of the target area sent by the second network element, it can determine the relevant information of the perception target in the target area based on the perception data. That is, the first network element can determine the perception target in the target area through the interaction between the first network element and the second network element, thereby solving the problem that there is no relevant process in the current network technology to determine the perception target in the target area.

[0208] In some embodiments, the first network element may be a network element for performing Sensing Management (SM). For example, the first network element may be a server (SM server) deployed in the application enablement layer for performing sensing management. It may be an independent network element or function, or it may be a network element or function co-located with other functions of the application enablement layer. The embodiments disclosed herein are not limited thereto.

[0209] In some embodiments, the second network element may be a device, network element, or function capable of sensing or obtaining sensing data. For example, the second network element may include, but is not limited to, at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, third-party network function, etc.

[0210] For example, a core network element or core network function can acquire sensing data through a Radio Access Network (RAN) device and provide it to the first network element. Alternatively, a core network element or core network function can acquire sensing data through a Network Data Analytics Function (NWDAF) and send it to the first network element (or the core network element or core network function can be the NWDAF).

[0211] For example, the terminal device can be a vertical industry terminal (vertical UE, VAL UE), and the client inside the terminal can be a perception management client (SM client) inside the terminal; for example, the UE or the perception target equipped with the UE (such as a drone, a person, etc.) can obtain perception data through interaction with the base station and provide it to the first network element.

[0212] For example, a third-party device or network function can be a radar system, a radio signal monitoring device or network function, a visible light identification and tracking device or network function, or other third-party devices or network functions; for example, for a third-party device or network element function that supports sensing or obtaining sensing data, the third-party device or network element function can obtain sensing data and provide it to the first network element.

[0213] In some embodiments, the sensed data includes, but is not limited to, at least one of the following:

[0214] Sensing target information; for example, sensing target information can be used to indicate the type, shape, etc. of the sensing target. In some embodiments, the sensing target information includes at least one of the following: identification information of the sensing target (such as the model of the sensing target, the unique identifier of the sensing target, or the specific identifier of the sensing target in the target area); material information of the sensing target; size information of the sensing target (such as the size of the sensing target, the overall size of the sensing target, the local size that can reflect the characteristics of the sensing target); image information of the sensing target (such as photos, videos, etc. of the sensing target obtained by the second network element, or photos, videos, etc. of the sensing target collected or provided by a third party); service latency of the sensing target, etc., and the embodiments of this disclosure are not limited thereto.

[0215] The mobility analysis information of the perceived target; for example, the mobility analysis information of the perceived target includes the movement trajectory of the perceived target, such as the position, speed, direction, and height of the perceived target at one or more times, etc., but this disclosure is not limited to this.

[0216] The moving trajectory prediction and analysis information of the perceived target; for example, the moving trajectory prediction and analysis information of the perceived target includes: the predicted moving trajectory of the perceived target, such as the predicted position, speed, direction, height, etc. of the perceived target at one or more times, and the embodiments disclosed herein are not limited thereto.

[0217] The perception accuracy analysis information of the perceived target; for example, the perception accuracy analysis information of the perceived target includes at least one of the following: position accuracy analysis of the perceived target, perception reliability analysis of the perceived target, etc., and the embodiments disclosed herein are not limited thereto.

[0218] Information on the perceived credibility of the target.

[0219] In some embodiments, the perception detection result includes at least one of the following:

[0220] Perception detection result A1: A sensing target exists within the target area or no sensing target exists within the target area;

[0221] For example, the perceived target may include at least one of the following: electronic devices (such as UE, drones, etc.), people, animals, and non-living things (such as obstacles). In this embodiment of the present disclosure, the first network element can determine whether a perceived target exists in the target area based on the perception data provided by the second network element. That is, the perception detection result may include whether a perceived target exists in the target area or whether a perceived target does not exist in the target area.

[0222] For example, if the first network element determines that a sensing target exists within the target area, the sensing detection result includes A1. That is, when the sensing detection result includes A1, it indicates that a sensing target exists within the target area; when the sensing detection result does not include A1, it indicates that a sensing target does not exist within the target area. Alternatively, regardless of whether a sensing target exists within the target area, the sensing detection result always includes A1. For example, if A1 takes the first value, it indicates that a sensing target exists within the target area; if A1 takes the second value, it indicates that a sensing target does not exist within the target area. Here, the first value and the second value are not equal.

[0223] Perception detection result A2: The perceived target in the target area meets the safety conditions or the perceived target in the target area does not meet the safety conditions;

[0224] For example, meeting security conditions can be a network configuration or a condition that a sensing target conforming to the requirements of the target area must meet, based on protocol agreements, or it can be a sensing target considered legitimate within the target area. Conversely, not meeting security conditions means that a sensing target that does not meet the requirements of the target area must meet, or it can be a sensing target considered illegitimate within the target area. In this embodiment, the first network element can determine whether a sensing target existing in the target area meets security conditions based on the sensing data provided by the second network element. That is, the sensing detection result can include whether a sensing target in the target area meets security conditions or whether a sensing target in the target area does not meet security conditions.

[0225] For example, if the first network element determines that there is a sensing target within the target area that does not meet the security conditions, the sensing detection result includes A2. That is, when the sensing detection result includes A2, it means that there is a sensing target within the target area that does not meet the security conditions; when the sensing detection result does not include A2, it means that there is no sensing target within the target area that does not meet the security conditions (or all sensing targets within the target area meet the security conditions). Alternatively, regardless of whether there is a sensing target within the target area that does not meet the security conditions, the sensing detection result always includes A2. For example, when A2 is the third value, it means that there is a sensing target within the target area that does not meet the security conditions; when A2 is the fourth value, it means that there is no sensing target within the target area that does not meet the security conditions (in some embodiments, A2 is the third and fourth values, or when A2 is the fifth value, it means that there are both sensing targets within the target area that meet and do not meet the security conditions), where the third, fourth, and fifth values ​​are all different.

[0226] Perception detection result A3: First type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0227] For example, this first type of sensing target information can be used to indicate which or more sensing targets within the target area are sensing targets that do not meet the security conditions.

[0228] In some embodiments, the first type of perceived target information includes at least one of the following:

[0229] The identification information of the first type of sensing target; for example, the identification information may be the model of the sensing target, the unique identifier of the sensing target, or the specific identifier of the sensing target in the target area, etc., and the embodiments disclosed herein are not limited thereto.

[0230] The type of the first type of perceived target; for example, the type can be electronic devices (such as UE, drones, etc.), people, animals, non-biological objects (such as obstacles), etc., but this disclosure is not limited to this.

[0231] The size information of the first type of sensing target; for example, the size can be the size of the sensing target, the overall size of the sensing target, the local size that can reflect the characteristics of the sensing target, etc., and the embodiments disclosed herein are not limited thereto.

[0232] Material information of the first type of perceived target;

[0233] The location of the first type of sensing target; for example, for sensing targets with poor mobility or that have not moved for a period of time, the location can also be used to indicate which or more sensing targets do not meet the safety conditions.

[0234] The service latency of the first type of sensing target.

[0235] In this embodiment of the present disclosure, the first network element can determine whether there are any sensing targets in the target area that do not meet the security conditions based on the sensing data provided by the second network element. For example, when it is determined that there are sensing targets in the target area that do not meet the security conditions, it can also determine which or more sensing targets are the first type of sensing targets that do not meet the security conditions.

[0236] Perception detection result A4: There is a conflict between different perception targets within the target area, or there is no conflict between different perception targets within the target area;

[0237] For example, the conflict between different sensing targets within the target area can refer to a conflict between different first-type sensing targets within the target area, or a conflict between first-type sensing targets and second-type sensing targets, or a conflict between different second-type sensing targets; correspondingly, the absence of conflict between different sensing targets within the target area can refer to the absence of conflict between different first-type sensing targets within the target area, or a conflict between first-type sensing targets and second-type sensing targets, or a conflict between different second-type sensing targets, etc., and this disclosure is not limited to these embodiments; wherein, the second-type sensing targets are sensing targets that meet the security conditions.

[0238] In some embodiments, a conflict between different sensing targets may include at least one of the following: a conflict in the positions of different sensing targets (for example, when the first sensing target is currently located at a certain position, and the second sensing target is about to move to that position (or within a preset range corresponding to that position), it is determined that there is a conflict in the positions of the different sensing targets); a conflict in the movement trajectories of different sensing targets (for example, the movement trajectory of the first sensing target and the movement trajectory of the second sensing target overlap at a certain moment, it is determined that there is a conflict in the movement trajectories of the different sensing targets), or other conflict detection methods, etc., which are not limited to the embodiments disclosed herein.

[0239] In this embodiment of the present disclosure, the first network element can determine whether there is a sensing target in the target area based on the sensing data provided by the second network element. For example, when it is determined that there is a sensing target in the target area, it can also determine whether there is a conflict between different sensing targets based on the sensing data, that is, whether there is a conflict or not between different sensing targets.

[0240] For example, if the first network element determines that there is a conflict between different sensing targets within the target area, the sensing detection result includes A4. That is, when the sensing detection result includes A4, it indicates that there is a conflict between different sensing targets within the target area; when the sensing detection result does not include A4, it indicates that there is no conflict between different sensing targets within the target area. Alternatively, regardless of whether there is a conflict between different sensing targets within the target area, the sensing detection result always includes A4. For example, if A4 is the sixth value, it indicates that there is a conflict between different sensing targets within the target area; if A4 is the seventh value, it indicates that there is no conflict between different sensing targets within the target area. Here, the sixth and seventh values ​​are not equal.

[0241] Perception detection result A5: Time information on conflicts occurring between different perceived targets within the target area;

[0242] For example, the time information can be absolute time, relative time, or world time, etc., and the embodiments disclosed herein are not limited thereto.

[0243] In this embodiment of the present disclosure, the first network element can determine whether there is a conflict between different sensing targets in the target area based on the sensing data provided by the second network element. For example, if the first network element determines that there is a conflict between different sensing targets in the target area, it can also determine the time information of the conflict between different sensing targets based on the sensing data.

[0244] Perception detection result A5: Location information of conflicts between different perceived targets within the target area;

[0245] For example, the location information can be an absolute location or a relative location, etc., and the embodiments disclosed herein are not limited thereto.

[0246] In this embodiment of the present disclosure, the first network element can determine whether there is a conflict between different sensing targets in the target area based on the sensing data provided by the second network element. For example, if the first network element determines that there is a conflict between different sensing targets in the target area, it can also determine the location information of the conflict between different sensing targets based on the sensing data.

[0247] Perception detection result A7: There are conflicting perceived target information within the target area;

[0248] For example, conflicting perception target information can be used to indicate which perception targets within a target area are in conflict.

[0249] In some embodiments, conflicting perceived target information includes at least one of the following:

[0250] Identification information of conflicting sensing targets; for example, the identification information may be the model of the sensing target, the unique identifier of the sensing target, or the specific identifier of the sensing target in the target area, etc., and the embodiments disclosed herein are not limited thereto.

[0251] The types of conflicting perceived targets; for example: conflicting perceived targets are different first-type perceived targets, or there is a conflict between first-type and second-type perceived targets, or conflicting perceived targets are different second-type perceived targets, etc. Specifically, this type can be electronic devices (such as UE, drones, etc.), people, animals, non-living things (such as obstacles), etc.

[0252] The size information of the sensing target that conflict; for example, the size can be the size of the sensing target, the overall size of the sensing target, or the local size that can reflect the characteristics of the sensing target, etc., and the embodiments disclosed herein are not limited thereto.

[0253] Material information of conflicting perceived targets;

[0254] The location of conflicting sensing targets; for example, for sensing targets with poor mobility or that have not moved for a period of time, the location can also be used to indicate conflicting sensing target information.

[0255] In this embodiment of the present disclosure, the first network element can determine whether there is a conflict between different sensing targets in the target area based on the sensing data provided by the second network element. For example, if the first network element determines that there is a conflict between different sensing targets in the target area, it can also determine which sensing targets are in conflict.

[0256] In some embodiments, determining the perception detection result based on the perception data includes at least one of the following methods:

[0257] Method B1: Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, determine whether the sensing target meets the safety conditions or does not meet the safety conditions.

[0258] For example, the first network element can acquire the identification information of sensing targets (or legitimate sensing targets) that meet security conditions within the target area. By comparing the identification information of the sensing targets contained in the sensing data with the identification information of sensing targets that meet security conditions (or legitimate sensing targets), it can be determined whether the corresponding sensing target meets the security conditions, that is, whether the corresponding sensing target meets or does not meet the security conditions. For example, if the identification information is consistent, it is determined that the sensing target meets the security conditions (i.e., the sensing target is legitimate); otherwise, it is determined that the sensing target does not meet the security conditions (i.e., the sensing target is illegitimate).

[0259] For example, the first network element can acquire at least one of the following: material information, size information, and image information of the sensing target (or legal sensing target) that meets the security conditions within the target area. For example, based on the material information, size information, etc., it can determine whether the sensing target is a target object (such as a person, animal, etc.) or a terminal device (such as a UE, drone, etc.), thereby helping to determine whether the sensing target meets the security conditions, that is, to determine whether the corresponding sensing target meets the security conditions or does not meet the security conditions.

[0260] For example, the first network element can acquire mobility analysis information and / or trajectory prediction analysis information of sensing targets (or legitimate sensing targets) that meet security conditions within the target area. By comparing the mobility analysis information of sensing targets contained in the sensing data with the mobility analysis information of sensing targets (or legitimate sensing targets) that meet security conditions, and / or comparing the trajectory prediction analysis information of sensing targets contained in the sensing data with the trajectory prediction analysis information of sensing targets (or legitimate sensing targets) that meet security conditions, it can be determined whether the corresponding sensing target meets the security conditions, that is, whether the corresponding sensing target meets or does not meet the security conditions. For example, if the mobility analysis information and / or the trajectory prediction analysis information are consistent, it is determined that the sensing target meets the security conditions (i.e., the sensing target is a legitimate sensing target); otherwise, it is determined that the sensing target does not meet the security conditions (i.e., the sensing target is an illegitimate sensing target).

[0261] For example, the first network element can also determine whether the perceived target meets the security conditions or does not meet the security conditions based on at least one of the following included in the sensing data: the identification information of the perceived target, the material information of the perceived target, the size information of the perceived target, and the image information of the perceived target, as well as at least one of the mobility analysis information and the trajectory prediction analysis information of the perceived target. Specifically, see the combination of the above examples. For example, if the identification information is consistent and the mobility analysis information is consistent, it is determined that the corresponding perceived target meets the security conditions (i.e., the perceived target is a legitimate perceived target); otherwise, it is determined that the corresponding perceived target does not meet the security conditions (i.e., the perceived target is an illegitimate perceived target). This will not be elaborated further here.

[0262] Method B2: Determine the type of the sensing target based on at least one of the following: material information of the sensing target, size information of the sensing target, identification information of the sensing target, and image information of the sensing target contained in the sensing data;

[0263] For example, the identification information of a perceived target can be unique or include its model number. Based on this identification information, the type of the perceived target can be determined, such as a drone or a user interface (UE). Another example: considering the different materials of animals (such as birds) and drones, the type of the perceived target can be determined based on its material information. Yet another example: considering the different sizes of airplanes and animals (such as birds), the type of the perceived target can be determined based on its size information. Finally, based on the image information of the perceived target obtained through sensing, the type of the perceived target can be determined intuitively and accurately.

[0264] Method B3: Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine whether there is a conflict between different perceived targets in the target area or whether there is no conflict between different perceived targets in the target area.

[0265] For example, the first network element can acquire at least one of the following: mobility analysis information and trajectory prediction analysis information of the sensing targets that meet security conditions (or are legal sensing targets) within the target area. By comparing the mobility analysis information of the sensing targets contained in the sensing data with the mobility analysis information of the sensing targets that meet security conditions (or are legal sensing targets), and / or comparing the trajectory prediction analysis information of the sensing targets contained in the sensing data with the trajectory prediction analysis information of the sensing targets that meet security conditions (or are legal sensing targets), it can be determined whether there is a conflict between the corresponding sensing targets; or the first network element can also determine whether there is a conflict between the corresponding sensing targets based on the mobility analysis information and / or trajectory prediction analysis information of different sensing targets contained in the sensing data.

[0266] For example, the mobility analysis information of the perceived target includes at least one of the following: the movement trajectory of the perceived target, such as the position, speed, direction, and altitude of the perceived target at one or more moments. For example, if the first perceived target is currently at a certain position, and the second perceived target is about to move to that position (or within a preset range corresponding to that position), then it is determined that there is a conflict between the first and second perceived targets; or if the movement trajectories of the first and second perceived targets overlap at a certain moment (e.g., their directions and altitudes overlap), then it is determined that there is a conflict between the first and second perceived targets. Similarly, the trajectory prediction and analysis information of the perceived target may include at least one of the following: the predicted trajectory of the perceived target, such as the predicted position, speed, direction, and height of the perceived target at one or more times. For example, if it is predicted that when the first perceived target is at a certain position at a certain time, the second perceived target will also move to that position (or within a preset range corresponding to that position) at the same time, then it is determined that there is a conflict between the first and second perceived targets; or if it is predicted that the trajectory of the first perceived target and the trajectory of the second perceived target overlap at a certain time (e.g., their directions and heights overlap), then it is determined that there is a conflict between the first and second perceived targets. Of course, the embodiments of this disclosure may also include other conflict detection methods, and are not limited thereto.

[0267] Method B4: Determine the time information of conflict between different sensing targets within the target area based on at least one of the mobility analysis information of the sensing target and the trajectory prediction analysis information of the sensing target contained in the sensing data;

[0268] For example, the mobility analysis information of a sensed target includes at least one of the following: the movement trajectory of the sensed target, such as the target's position, speed, direction, and altitude. For instance, based on the movement trajectories of different sensed targets, the time information of a conflict between them can be determined. Similarly, the movement trajectory prediction analysis information of a sensed target may include at least one of the following: the predicted movement trajectory of the sensed target, such as based on the predicted movement trajectories of different sensed targets, the time information of a conflict between them can be determined. In some embodiments, this time information may be absolute time, relative time, or world time, etc.

[0269] Method B5: Determine the location information of the conflict between different sensing targets within the target area based on at least one of the mobility analysis information of the sensing target and the trajectory prediction analysis information of the sensing target contained in the sensing data.

[0270] For example, the mobility analysis information of the sensed target includes at least one of the following: the movement trajectory of the sensed target, such as the position, speed, direction, and altitude of the sensed target at one or more moments. Based on the movement trajectories of different sensed targets, the location information of the conflict between different sensed targets can be determined. Similarly, the movement trajectory prediction analysis information of the sensed target may include at least one of the following: the predicted movement trajectory of the sensed target, such as the location information of the conflict between different sensed targets can be determined based on the predicted movement trajectories of different sensed targets. In some embodiments, this location information may be an absolute position or a relative position, etc.

[0271] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity. That is, in this embodiment of the disclosure, the sensing target that does not meet the security conditions may also be referred to as an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity, etc.

[0272] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity. That is, in this embodiment of the disclosure, the sensing target that meets the security conditions can also be referred to as an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity, etc.

[0273] In some embodiments, before receiving the sensing data of the target area sent by the second network element, the method further includes:

[0274] Send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

[0275] For example, a first network element can send a first request message to a second network element to request the second network element to provide corresponding sensing data. This first request message may be a sensing request message or other names; this embodiment does not specifically limit the message name. After receiving the first request message from the first network element, the second network element can perform sensing to obtain sensing data and send a response message to the first network element; wherein the response message carries sensing data of the target area provided by the second network element. For example, when the second network element includes a core network element or a core network function, the first network element can send the first request message to the core network element or core network function through a Network Exposure Function (NEF) to request the core network element or core network function to initiate a RAN-based sensing process.

[0276] In some embodiments, the perception detection method further includes:

[0277] The system receives a second request message sent by a third network element; wherein the second request message is used to request the detection of sensing target-related information within the target area.

[0278] For example, a third network element can send a second request message to a first network element to request the detection of sensing target information within the target area, such as requesting the detection of a first type of sensing target within the target area, and / or requesting the detection of conflicting sensing targets within the target area. Upon receiving the second request message from the second network element, the first network element can determine the sensing detection result based on the sensing data of the target area sent by the second network element (e.g., the first network element can subscribe to sensing data from the second network element, or the second network element can periodically report sensing data). This result could include: the presence or absence of sensing targets within the target area; the sensing targets in the target area meeting or not meeting security conditions; information about the first type of sensing targets within the target area; conflicts between different sensing targets within the target area or no conflicts between different sensing targets within the target area; time information of conflicts between different sensing targets within the target area; and location information of conflicts between different sensing targets within the target area.

[0279] For example, a third network element can send a second request message to a first network element to request the detection of sensing target-related information within the target area, such as requesting the detection of a first type of sensing target within the target area, and / or requesting the detection of conflicting sensing targets within the target area. Upon receiving the second request message from the second network element, the first network element can send a first request message to the second network element to request corresponding sensing data. After receiving the first request message from the first network element, the second network element can perform sensing to obtain sensing data and send a response message to the first network element; wherein the response message carries the sensing data of the target area provided by the second network element. In this way, when the first network element receives the sensing data sent by the second network element, the sensing detection result can be determined based on the sensing data, such as: the presence or absence of a sensing target in the target area; the sensing target in the target area meeting or not meeting the security conditions; information on a first type of sensing target in the target area; conflicts between different sensing targets in the target area or no conflicts between different sensing targets in the target area; time information of conflicts between different sensing targets in the target area; and location information of conflicts between different sensing targets in the target area.

[0280] In some embodiments, the second request message carries at least one of the following:

[0281] Second type of sensing target information; wherein, the second type of sensing target is a sensing target that meets the security conditions; for example, the second type of sensing target information includes at least one of the following: identification information of the second type of sensing target (such as the model, unique identifier, or specific identifier in the target area of ​​the second type of sensing target), material information of the second type of sensing target, size information of the second type of sensing target, mobility information of the second type of sensing target (such as movement trajectory, including position, speed, direction, height, etc.), service latency of the second type of sensing target, etc., and the embodiments disclosed herein are not limited thereto.

[0282] The perception service type includes, for example, at least one of the following: perception target detection (such as detecting perception targets within a target area, or detecting the first type of perception target within a target area, etc.), perception target conflict detection (i.e., detecting perception targets that are in conflict), etc., and the embodiments disclosed herein are not limited thereto.

[0283] Sensing service requirements; for example, sensing service requirements include at least one of the following: target area information, the location accuracy of the sensing target, the speed of the sensing target, the sensing resolution, service latency, etc., but this disclosure is not limited to these.

[0284] Triggering conditions for sensing services; for example, the triggering conditions for sensing services include at least one of the following: the sensing target enters the target area, the reporting time interval of sensing data (such as real-time reporting, etc.), but this disclosure is not limited to these.

[0285] In some embodiments, the perception detection method further includes:

[0286] Send a third request message to the third network element;

[0287] A response message is received from the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

[0288] For example, when the first network element determines the perception detection result based on the perception data sent by the second network element, if the third network element has not previously notified the first network element of the second type of perception target information for the target area, the first network element can send a request message to the third network element to request the third network element to provide the second type of perception target information for the target area. Upon receiving the third request message from the first network element, the third network element can send a response message to the first network element, which carries the second type of perception target information. In this way, the first network element can determine the perception detection result based on the second type of perception target information provided by the third network element and the perception data provided by the second network element. For details, please refer to the above embodiments, which will not be repeated here.

[0289] In some embodiments, the perception detection method further includes:

[0290] Authorization verification is performed on the third network element;

[0291] If the authorization verification of the third network element is successful, a first request message is sent to the second network element.

[0292] For example, when a first network element receives a second request message from a third network element, or when the first network element sends a third request message to the third network element, the first network element can perform authorization verification on the third network element to determine whether the third network element can send a corresponding request to detect sensing targets within the target area (such as a sensing target detection request and / or a sensing target conflict detection request within the target area), or whether the third network element can provide second-type sensing target information within the target area. The first network element will only determine the sensing detection result based on the third network element's request or the second-type sensing target information provided by the third network element if the authorization verification of the third network element is successful. For example, if the authorization verification of the third network element is successful, the first network element determines the sensing detection result based on the sensing data of the target area. Alternatively, if the authorization verification of the third network element is successful, the first network element sends a first request message to the second network element, receives the sensing data of the target area sent by the second network element according to the first request message, and determines the sensing detection result based on the sensing data.

[0293] In some embodiments, the perception detection method further includes:

[0294] The sensing and detection results are sent to the third network element.

[0295] For example, when a first network element receives a second request message from a third network element requesting the detection of sensing target-related information within the target area (such as requesting the detection of sensing targets within the target area and / or requesting the detection of conflicts between sensing targets within the target area), the first network element can provide the sensing detection result to the third network element based on the sensing data provided by the second network element.

[0296] In some embodiments, the third network element includes at least one of the following: an application server, a terminal device, and a terminal internal perception management client.

[0297] For example, the third network element can be an application server, such as a vertical industry server (VAL server). This VAL server can initiate a detection request to the first network element, such as requesting the detection of information related to sensing targets within the target area (e.g., requesting the detection of sensing targets within the target area and / or requesting the detection of conflicts between sensing targets within the target area). The first network element can obtain the sensing detection results based on the sensing data provided by the second network element and provide the sensing detection results to the third network element. For example, the results may include: the presence or absence of sensing targets within the target area; the sensing targets within the target area meeting or not meeting security conditions; information about first-type sensing targets within the target area; conflicts between different sensing targets within the target area or no conflicts between different sensing targets within the target area; time information of conflicts between different sensing targets within the target area; and location information of conflicts between different sensing targets within the target area.

[0298] For another example, the third network element can be a UE (such as a terminal device or a terminal internal perception management client). The UE can initiate a detection request to the first network element, such as requesting to detect whether there is a conflict between the UE and the perception target in the target area. The first network element can obtain the perception detection result based on the perception data provided by the second network element and provide the perception detection result to the third network element. For example, the perception target exists in the target area or does not exist in the target area; the perception target in the target area meets the security conditions or does not meet the security conditions; the first type of perception target information in the target area; there is a conflict between different perception targets in the target area or there is no conflict between different perception targets in the target area; the time information of the conflict between different perception targets in the target area; the location information of the conflict between different perception targets in the target area, etc.

[0299] The terminal devices involved in the embodiments of this disclosure can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. The names of the terminal devices may differ in different systems; for example, in a 5G system, a terminal device can be called User Equipment (UE). Wireless terminal devices can communicate with one or more core networks (CNs) via a Radio Access Network (RAN). Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices, for example, portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with the RAN. Examples include Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, and Personal Digital Assistants (PDAs). Wireless terminal equipment can also be referred to as a system, subscriber unit, subscriber station, mobile station, mobile station, remote station, access point, remote terminal, access terminal, user terminal, user agent, or user device, but is not limited to these terms in the embodiments disclosed herein.

[0300] As shown in Figure 2, an embodiment of this disclosure provides a sensing and detection method applied to a second network element, comprising the following steps:

[0301] Step 21: Send the sensing data of the target area to the first network element; wherein, the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

[0302] In some embodiments, the perception detection result includes at least one of the following:

[0303] The target area may contain a sensing target or the target area may not contain a sensing target.

[0304] The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions;

[0305] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0306] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0307] The time information of conflicts occurring between different sensing targets within the target area;

[0308] The location information of conflicts between different sensing targets within the target area.

[0309] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0310] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0311] In some embodiments, the perceived data includes at least one of the following:

[0312] Perceive target information;

[0313] Analyze the mobility of the target;

[0314] Analyze and predict the movement trajectory of the perceived target;

[0315] Analyzing the perception accuracy of the target;

[0316] Information on the perceived credibility of the target.

[0317] In some embodiments, the perceived target information includes at least one of the following:

[0318] Perceive the identification information of the target;

[0319] Perceive the material information of the target;

[0320] Perceive the size information of the target;

[0321] Perceive the image information of the target.

[0322] In some embodiments, sending the sensing data of the target area to the first network element includes:

[0323] Receive the first request message sent by the first network element;

[0324] Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

[0325] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0326] It should be noted that the perception detection method on the second network element side of this disclosure is based on the same inventive concept as the perception detection method on the first network element side described above. The two embodiments can refer to each other and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0327] The perception detection method of this disclosure will be described below with reference to specific embodiments:

[0328] Example 1: Detection of unauthorized / illegal drones (i.e., drones that do not meet safety requirements, or drones that are unauthorized, unregistered, or without legal status);

[0329] In this embodiment, taking the VAL server (i.e., the third network element) requesting the application enablement layer (i.e., the first network element) to detect unauthorized / illegal drones within a specific area (i.e., detecting sensing targets within the target area that do not meet security conditions) as an example, core network elements, third-party devices, or network functions (i.e., the second network element) are allowed to open the corresponding sensing data to the application enablement layer, such as the SM server (i.e., the first network element). As shown in Figure 3, the specific process includes:

[0330] Step 31: The VAL server sends a request message (i.e., the second request message) to the SM server to detect whether there is any unauthorized drone intrusion in the target area.

[0331] In some embodiments, the request information (i.e., the second request message) includes at least one of the following: service type (e.g., UAV detection), sensing target information (e.g., normal / legal UAV model, size, material, flight trajectory, etc.), sensing service requirements (e.g., target area information, sensing position accuracy, speed, sensing resolution, service latency, etc.), request triggering conditions (e.g., entering the target area), reporting time interval (e.g., real-time), etc. For details, please refer to the above embodiments, which will not be repeated here.

[0332] Step 32: The SM server performs an authorization check on the VAL server's black flight / illegal drone detection requests to determine whether the VAL server can initiate the corresponding request.

[0333] Step 33: After authorization to the VAL server is granted, the SM server can initiate a drone perception request to the second network element targeting the target area to obtain drone perception data entering the target area. For example, the second network element may include core network elements, ADAES, AIMLE, third parties, etc.

[0334] The SM server sends a perception request (i.e., the first request message) to the core network element via NEF. The core network element initiates a RAN-based perception process. When the perception triggering conditions are met, the RAN obtains information about the UAV entering the target area (including the UAV's size, dimensions, material, location, speed, latency, etc.) and confidence level information, and reports the measured perception data to the SM server. At the same time, the SM server can also send a perception request to NWDAF to obtain UAV perception mobility analysis (such as the UAV's movement trajectory, including speed, direction, altitude, etc.) and flight trajectory prediction analysis.

[0335] The SM server interacts with enablers such as ADAES or AIMLE, sending them a perception accuracy analysis request (i.e., the first request message) to obtain perception information accuracy analysis of UAVs within the target area (such as UAV position accuracy analysis, perception reliability analysis, etc.);

[0336] The SM server sends a perception request (i.e., the first request message) to a third party to obtain drone perception data (such as drone model information obtained through radio signals or photoelectric identification) in the target area through non-3GPP methods.

[0337] Step 34: The SM server performs fusion perception calculation on the UAV perception measurement data obtained in Step 33, determines all drones entering the target area (e.g., determines that they are drones rather than birds based on information such as material and model), and compares the flight trajectories of the drones (including speed, direction, altitude, etc.) with the flight trajectories of normal / legal drones (i.e., drones that meet safety conditions, also known as authorized drones, registered drones, or drones with legal status) to determine which drones entering the target area do not meet safety conditions.

[0338] And / or,

[0339] The SM server identifies all drones entering the target area from the acquired UAV perception measurement data, filters out the model information of all drones entering the target area, and compares it with the legal drone models to determine which drones entering the target area do not meet the safety conditions.

[0340] It should be noted that the information of a normal / legal drone can be carried in the above request information (i.e., the target information). If the above request information does not carry the information of the normal / legal drone, the information of the normal / legal drone (such as the normal / legal UAV model, size, material, flight trajectory, etc.) can be obtained by executing steps 35 to 36.

[0341] Step 35: The SM server sends a request message to the VAL server to request information about normal / legal drones in the target area, such as flight trajectory (including speed, direction, altitude, etc.), drone model, material, size, etc.

[0342] Step 36: The VAL server sends a response message to the SM server to return the information of the corresponding normal / legitimate drone.

[0343] Step 37: The SM server sends the detected illegal / unauthorized drone detection results to the VAL server. In some embodiments, the VAL server may take corresponding control measures based on the detection results; this disclosure does not impose specific limitations.

[0344] Example 2: Security Intrusion Detection;

[0345] This embodiment uses the example of a VAL server (i.e., the third network element) requesting the application enablement layer (i.e., the first network element) to enter a target area (such as a home, or the vicinity of a railway / highway) for target object (such as a person or animal) detection (i.e., detecting perceived targets within the target area that do not meet security conditions) to ensure security. As shown in Figure 4, the specific process includes:

[0346] Step 41: The VAL server sends an intrusion detection request to the SM server, requesting the detection of whether there are any illegal / unauthorized targets (such as people or animals) intruding into the target area (such as a home, the area around a railway / highway, and along the line).

[0347] In some embodiments, the request information (i.e., the second request message) includes at least one of the following: service type (e.g., intrusion detection), sensing target information (e.g., the size or dimensions of a person or animal), sensing service requirements (target area information, sensing location accuracy, speed, sensing resolution, service latency, etc.), the conditions for triggering the request, the reporting time interval (e.g., real-time), etc. For details, please refer to the above embodiments, which will not be repeated here.

[0348] Step 42. The SM server performs an authorization check on the intrusion detection request from the VAL server to determine whether the VAL server can initiate the corresponding request.

[0349] Step 43: Same as step 33 in Implementation 1. After authorization of the VAL server is approved, the SM server can initiate perception requests for target objects (such as people or animals) within the target area from core network elements, ADAES, AIMLE, third parties, etc., and obtain perception data of target objects entering the target area (such as the size, dimensions, material, location, speed, mobility analysis, location accuracy analysis, perception reliability analysis, etc. of people or animals). For details, please refer to the above embodiments, which will not be repeated here.

[0350] Step 44. The SM server performs fusion perception calculation on the perception data obtained in step 43 to calculate all target objects entering the target area and their feature information, such as movement trajectory (including speed, direction, height, etc.).

[0351] Step 45: (Optional) If the SM server obtains the basis for judging the legitimacy (or security conditions) of the perceived target object through the vertical application (such as normal movement trajectory, image information, etc.), it can further judge the legitimacy of the target object entering the target area by combining the perception calculation results, that is, determine whether the target object meets the security conditions.

[0352] Step 46: The SM server sends the determined intrusion detection result to the VAL server. In some embodiments, the VAL server can take corresponding control measures through the application layer (such as notifying train management personnel to slow down the train to avoid the intruder / animal).

[0353] Example 3: Collision Detection;

[0354] The application scope of conflict detection includes, but is not limited to, conflict detection in areas such as AGVs within smart factories, intelligent transportation, and drone monitoring. This embodiment takes drone conflict detection as an example, and differs from Embodiment 1 in that: in this embodiment, the drone carries a communicable UE (User Equipment). The VAL server (i.e., the third network element) can perceive the surrounding environment of the drone through the UE carried on the drone, ensuring that the drone will not collide with other perceived targets, thus avoiding conflicts. Furthermore, it can adjust the drone's flight trajectory to prevent conflicts in subsequent flight paths. As shown in Figure 5, the specific process includes:

[0355] Step 51: The VAL server sends a drone conflict detection request to the SM server (i.e., the first network element), requesting to check whether there will be a collision / conflict with other perceived targets (such as birds) on the drone's flight path.

[0356] In some embodiments, the request information (i.e., the second request message) includes at least one of the following: service type (e.g., UAV collision detection), sensing target information (e.g., UAV ID, bird size, material, etc.), sensing service requirements (target area information, sensing location accuracy, speed, sensing resolution, service latency, etc.), terminal information carried by the UAV (e.g., UE identifier), conditions for request triggering, and reporting time interval (real-time).

[0357] Step 52: The SM server performs an authorization check on the drone conflict detection request from the VAL server to determine whether the VAL server can initiate the corresponding request.

[0358] Step 53: After authorization to the VAL server is granted, the SM server can initiate a target UAV perception and monitoring request to the second network element to obtain perception data of the target UAV and surrounding perceived targets. In some embodiments, the second network element may include a terminal, a core network element, a third party, and an enabler in the application enablement layer (such as ADAES, AIMLE, etc.).

[0359] The SM server sends a perception request (i.e., the first request message) to the core network element via NEF. The core network element initiates a perception process based on UE and / or RAN to obtain information about the UAV and surrounding perceived targets (such as the size, material, position, altitude, speed, direction, etc. of birds). At the same time, the SM server can also send perception requests (i.e., the first request message) to NWDAF or other network elements / functions with AI capabilities (such as ADAES / AIMLE) to obtain UAV mobility analysis (such as UAV movement trajectory, including speed, direction, altitude, etc.), flight trajectory prediction analysis, perception accuracy analysis, etc.

[0360] The SM server sends a perception request (i.e., the first request message) to a third party to obtain perception data of the target drone and surrounding objects (such as information on the target drone and birds obtained through radar) through non-3GPP methods.

[0361] Step 54: The SM server performs fusion perception calculation on the perception measurement data of the UAV and surrounding perceived targets obtained in Step 53, calculates the flight trajectory of the UAV (including speed, direction, altitude, etc.) and the flight trajectory of the surrounding perceived targets (such as birds), compares the two flight trajectories, and combines the obtained flight trajectory prediction analysis to determine whether the two will conflict in the future and the time and / or location information of the conflict.

[0362] Step 55: The SM server sends the detected drone conflict results to the VAL server. If the SM server predicts a conflict, it includes the corresponding conflict prediction time and / or location information. Upon receiving the results, the VAL server may, through the application layer, instruct the drone to adjust its flight path at the predicted time and / or location to avoid subsequent conflicts.

[0363] Step 56. The SM server may send a collision detection notification to the VAL UE / SM client, informing it that there are obstacles (such as birds) approaching the target drone, as well as the predicted collision time and / or location information.

[0364] The above embodiments describe the sensing and detection method of this disclosure. The following embodiments will further describe the corresponding devices in conjunction with the accompanying drawings.

[0365] As shown in Figure 6, this embodiment provides a sensing and detection device that operates on a first network element, including a memory 61, a transceiver 62, and a processor 63. The memory 61 stores a computer program; the transceiver 62 transmits and receives data under the control of the processor 63; for example, the transceiver 62 receives and sends data under the control of the processor 63; the processor 63 reads the computer program from the memory 61 and performs the following operations:

[0366] Receive sensing data of the target area sent by the second network element;

[0367] Based on the perception data, a perception detection result is determined; wherein the perception detection result is used to indicate relevant information about the perception target within the target area.

[0368] In some embodiments, the perception detection result includes at least one of the following:

[0369] The target area may contain a sensing target or the target area may not contain a sensing target.

[0370] The sensing targets in the target area meet the safety conditions, or the sensing targets in the target area do not meet the safety conditions;

[0371] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0372] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0373] The time information of conflicts occurring between different sensing targets within the target area;

[0374] The location information of conflicts between different sensing targets within the target area.

[0375] In some embodiments, the first type of perceived target information includes at least one of the following:

[0376] The identification information of the first type of perceived target;

[0377] The type of the first type of perceived target;

[0378] Size information of the first type of perceived target;

[0379] Material information of the first type of perceived target.

[0380] In some embodiments, the perceived data includes at least one of the following:

[0381] Perceive target information;

[0382] Analyze the mobility of the target;

[0383] Analyze and predict the movement trajectory of the perceived target;

[0384] Analyzing the perception accuracy of the target;

[0385] Information on the perceived credibility of the target.

[0386] In some embodiments, the perceived target information includes at least one of the following:

[0387] Perceive the identification information of the target;

[0388] Perceive the material information of the target;

[0389] Perceive the size information of the target;

[0390] Perceive the image information of the target.

[0391] In some embodiments, the processor is configured to read a computer program from the memory and perform at least one of the following operations:

[0392] Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, it is determined whether the sensing target meets the safety conditions or whether the sensing target does not meet the safety conditions.

[0393] The type of the perceived target is determined based on at least one of the following: material information of the perceived target, size information of the perceived target, identification information of the perceived target, and image information of the perceived target contained in the perceived data;

[0394] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, it is determined that there is a conflict between different perceived targets in the target area or that there is no conflict between different perceived targets in the target area.

[0395] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine the time information of the conflict between different perceived targets in the target area;

[0396] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, the location information of the conflict between different perceived targets in the target area is determined.

[0397] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0398] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0399] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0400] Send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

[0401] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0402] The system receives a second request message sent by a third network element; wherein the second request message is used to request the detection of sensing target-related information within the target area.

[0403] In some embodiments, the second request message carries at least one of the following:

[0404] The second type of perceived target information; wherein, the second type of perceived target is a perceived target that meets the security conditions;

[0405] Perceive the business type;

[0406] Perceive business requirements;

[0407] The triggering conditions for sensing business processes.

[0408] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0409] Send a third request message to the third network element;

[0410] A response message is received from the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

[0411] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0412] Authorization verification is performed on the third network element;

[0413] If the authorization verification of the third network element is successful, a first request message is sent to the second network element.

[0414] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0415] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0416] The sensing and detection results are sent to the third network element.

[0417] In some embodiments, the third network element includes at least one of the following: an application server, a terminal device, and a terminal internal perception management client.

[0418] In Figure 6, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 63 and memory represented by memory 61. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. Transceiver 62 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium, including wireless channels, wired channels, optical fibers, etc. For different user equipment, user interface 64 can also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.

[0419] The processor 63 is responsible for managing the bus architecture and general processing, and the memory 61 can store the data used by the processor 63 when performing operations.

[0420] Optionally, the processor 63 can be a CPU (Central Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or CPLD (Complex Programmable Logic Device), and the processor can also adopt a multi-core architecture.

[0421] The processor executes any of the methods described in the embodiments of this disclosure by invoking a computer program stored in memory, according to the obtained executable instructions. The processor and memory may also be physically separated.

[0422] It should be noted that the apparatus provided in this embodiment can implement all the method steps implemented in the above-mentioned first network element side sensing and detection method embodiment, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0423] As shown in Figure 7, this embodiment of the present disclosure provides a sensing and detection device 700, including:

[0424] The first receiving unit 710 is used to receive sensing data of the target area sent by the second network element;

[0425] The processing unit 720 is configured to determine a perception detection result based on the perception data; wherein the perception detection result is used to indicate information related to the perception target within the target area.

[0426] In some embodiments, the perception detection result includes at least one of the following:

[0427] The target area may contain a sensing target or the target area may not contain a sensing target.

[0428] The sensing targets in the target area meet the safety conditions, or the sensing targets in the target area do not meet the safety conditions;

[0429] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0430] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0431] The time information of conflicts occurring between different sensing targets within the target area;

[0432] The location information of conflicts between different sensing targets within the target area.

[0433] In some embodiments, the first type of perceived target information includes at least one of the following:

[0434] The identification information of the first type of perceived target;

[0435] The type of the first type of perceived target;

[0436] Size information of the first type of perceived target;

[0437] Material information of the first type of perceived target.

[0438] In some embodiments, the perceived data includes at least one of the following:

[0439] Perceive target information;

[0440] Analyze the mobility of the target;

[0441] Analyze and predict the movement trajectory of the perceived target;

[0442] Analyzing the perception accuracy of the target;

[0443] Information on the perceived credibility of the target.

[0444] In some embodiments, the perceived target information includes at least one of the following:

[0445] Perceive the identification information of the target;

[0446] Perceive the material information of the target;

[0447] Perceive the size information of the target;

[0448] Perceive the image information of the target.

[0449] In some embodiments, the processing unit 720 is further configured to perform at least one of the following:

[0450] Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, it is determined whether the sensing target meets the safety conditions or whether the sensing target does not meet the safety conditions.

[0451] The type of the perceived target is determined based on at least one of the following: material information of the perceived target, size information of the perceived target, identification information of the perceived target, and image information of the perceived target contained in the perceived data;

[0452] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, it is determined that there is a conflict between different perceived targets in the target area or that there is no conflict between different perceived targets in the target area.

[0453] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine the time information of the conflict between different perceived targets in the target area;

[0454] Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, the location information of the conflict between different perceived targets in the target area is determined.

[0455] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0456] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0457] In some embodiments, the device 700 further includes:

[0458] The first sending unit is used to send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

[0459] In some embodiments, the device 700 further includes:

[0460] The second receiving unit is used to receive a second request message sent by the third network element; wherein the second request message is used to request the detection of sensing target-related information in the target area.

[0461] In some embodiments, the second request message carries at least one of the following:

[0462] The second type of perceived target information; wherein, the second type of perceived target is a perceived target that meets the security conditions;

[0463] Perceive the business type;

[0464] Perceive business requirements;

[0465] The triggering conditions for sensing business processes.

[0466] In some embodiments, the device 700 further includes:

[0467] The second sending unit is used to send a third request message to the third network element;

[0468] The third receiving unit is used to receive a response message to the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

[0469] In some embodiments, the device 700 further includes:

[0470] The verification unit is used to perform authorization verification on the third network element;

[0471] The third sending unit is used to send a first request message to the second network element when the authorization verification of the third network element is successful.

[0472] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0473] In some embodiments, the device 700 further includes:

[0474] The fourth transmitting unit is used to transmit the sensing and detection results to the third network element.

[0475] In some embodiments, the third network element includes at least one of the following: an application server, a terminal device, and a terminal internal perception management client.

[0476] It should be noted that the apparatus provided in this embodiment can implement all the method steps implemented in the above-mentioned first network element side sensing and detection method embodiment, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0477] As shown in Figure 8, this embodiment of the present disclosure provides a sensing and detection device that operates on a second network element, including a memory 81, a transceiver 82, and a processor 83; wherein, the memory 81 is used to store a computer program; the transceiver 82 is used to send and receive data under the control of the processor 83; for example, the transceiver 82 is used to receive and send data under the control of the processor 83; the processor 83 is used to read the computer program in the memory 81 and perform the following operations:

[0478] The first network element sends sensing data of the target area to the first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

[0479] In some embodiments, the perception detection result includes at least one of the following:

[0480] The target area may contain a sensing target or the target area may not contain a sensing target.

[0481] The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions;

[0482] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0483] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0484] The time information of conflicts occurring between different sensing targets within the target area;

[0485] The location information of conflicts between different sensing targets within the target area.

[0486] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0487] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0488] In some embodiments, the perceived data includes at least one of the following:

[0489] Perceive target information;

[0490] Analyze the mobility of the target;

[0491] Analyze and predict the movement trajectory of the perceived target;

[0492] Analyzing the perception accuracy of the target;

[0493] Information on the perceived credibility of the target.

[0494] In some embodiments, the perceived target information includes at least one of the following:

[0495] Perceive the identification information of the target;

[0496] Perceive the material information of the target;

[0497] Perceive the size information of the target;

[0498] Perceive the image information of the target.

[0499] In some embodiments, the processor is configured to read a computer program from the memory and perform the following operations:

[0500] Receive the first request message sent by the first network element;

[0501] Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

[0502] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, ADAES network element, AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0503] In Figure 8, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 83 and memory represented by memory 81. The bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 82 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. Processor 83 is responsible for managing the bus architecture and general processing, and memory 81 may store data used by processor 83 during operation.

[0504] The processor 83 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0505] It should be noted that the apparatus provided in this embodiment can implement all the method steps implemented in the above-mentioned second network element side sensing and detection method embodiment, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0506] As shown in Figure 9, this embodiment of the present disclosure also provides a sensing and detection device 900, including:

[0507] The transmitting unit 910 is used to transmit sensing data of a target area to a first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

[0508] In some embodiments, the perception detection result includes at least one of the following:

[0509] The target area may contain a sensing target or the target area may not contain a sensing target.

[0510] The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions;

[0511] The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions;

[0512] There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area.

[0513] The time information of conflicts occurring between different sensing targets within the target area;

[0514] The location information of conflicts between different sensing targets within the target area.

[0515] In some embodiments, the sensing target that does not meet the security conditions includes at least one of the following: an unauthorized sensing target, an unregistered sensing target, or a sensing target that has not obtained a legitimate identity;

[0516] The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

[0517] In some embodiments, the perceived data includes at least one of the following:

[0518] Perceive target information;

[0519] Analyze the mobility of the target;

[0520] Analyze and predict the movement trajectory of the perceived target;

[0521] Analyzing the perception accuracy of the target;

[0522] Information on the perceived credibility of the target.

[0523] In some embodiments, the perceived target information includes at least one of the following:

[0524] Perceive the identification information of the target;

[0525] Perceive the material information of the target;

[0526] Perceive the size information of the target;

[0527] Perceive the image information of the target.

[0528] In some embodiments, the sending unit 910 is further configured to:

[0529] Receive the first request message sent by the first network element;

[0530] Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

[0531] In some embodiments, the second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, application data analysis enabler service ADAES network element, artificial intelligence / machine learning enabler service AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

[0532] It should be noted that the apparatus provided in this embodiment can implement all the method steps implemented in the above-mentioned second network element side sensing and detection method embodiment, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0533] It should be noted that the division of units in the embodiments of this disclosure is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0534] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0535] This disclosure also provides a processor-readable storage medium storing a computer program. The computer program is used to cause the processor to execute the steps of the above-described sensing and detection method embodiments on the first or second network element side, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0536] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., compact disc (CD), digital video disc (DVD), Blu-ray disc (BD), high-definition versatile disc (HVD)), and semiconductor memory (e.g., ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), non-volatile memory (NAND (Non-volatile Memory Device) FLASH), solid state hard disk (SSD)).

[0537] This disclosure also provides a computer program product, including computer instructions. When executed by a processor, these computer instructions implement the various processes of the above-described sensing and detection method embodiments on the first or second network element side, and achieve the same technical effects. To avoid repetition, these will not be described again here.

[0538] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0539] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0540] These processor-executable instructions may also be stored in a processor-readable memory that can instruct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0541] These processor-executable instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0542] Furthermore, it should be noted that in the apparatus and method of this disclosure, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of this disclosure. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of this disclosure can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof, which can be achieved by those skilled in the art using their basic programming skills after reading the description of this disclosure.

[0543] Furthermore, it should be noted that in the apparatus and method of this disclosure, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of this disclosure. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of this disclosure can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof, which can be achieved by those skilled in the art using their basic programming skills after reading the description of this disclosure.

[0544] It should be noted that the above division of modules is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. For example, a module can be a separate processing element, or it can be integrated into a chip in the aforementioned device. Alternatively, it can be stored as program code in the memory of the aforementioned device, and its function can be called and executed by a processing element of the device. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0545] For example, each module, unit, subunit, or submodule can be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs). As another example, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together to implement a system-on-a-chip (SOC).

[0546] The terms “first,” “second,” etc., used in this disclosure and in the claims are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this disclosure described herein may be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. Additionally, the use of “and / or” in the specification and claims indicates at least one of the connected objects, such as A and / or B and / or C, indicating seven possibilities: A alone, B alone, C alone, and both A and B, both B and C, both A and C, and A, B, and C. Similarly, the use of “at least one of A and B” in this specification and claims should be understood as “A alone, B alone, or both A and B.”

[0547] Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. A sensing and detection method applied to a first network element, the method comprising: Receive sensing data of the target area sent by the second network element; Based on the perception data, a perception detection result is determined; wherein the perception detection result is used to indicate relevant information about the perception target within the target area.

2. The sensing and detection method according to claim 1, wherein, The perception detection result includes at least one of the following: The target area may contain a sensing target or the target area may not contain a sensing target. The sensing targets in the target area meet the safety conditions, or the sensing targets in the target area do not meet the safety conditions; The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions; There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area. The time information of conflicts occurring between different sensing targets within the target area; The location information of conflicts between different sensing targets within the target area.

3. The sensing and detection method according to claim 2, wherein, The first type of perceived target information includes at least one of the following: The identification information of the first type of perceived target; The type of the first type of perceived target; Size information of the first type of perceived target; Material information of the first type of perceived target.

4. The sensing and detection method according to claim 1, wherein, The perceived data includes at least one of the following: Perceive target information; Analyze the mobility of the target; Analyze and predict the movement trajectory of the perceived target; Analyzing the perception accuracy of the target; Information on the perceived credibility of the target.

5. The sensing and detection method according to claim 4, wherein, The perceived target information includes at least one of the following: Perceive the identification information of the target; Perceive the material information of the target; Perceive the size information of the target; Perceive the image information of the target.

6. The sensing and detection method according to any one of claims 1 to 5, wherein, Determining the perception detection result based on the perceived data includes at least one of the following: Based on at least one of the following included in the sensing data: the identification information of the sensing target, the material information of the sensing target, the size information of the sensing target, the image information of the sensing target, the mobility analysis information of the sensing target, and the trajectory prediction analysis information of the sensing target, it is determined whether the sensing target meets the safety conditions or whether the sensing target does not meet the safety conditions. The type of the perceived target is determined based on at least one of the following: material information of the perceived target, size information of the perceived target, identification information of the perceived target, and image information of the perceived target contained in the perceived data; Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, it is determined that there is a conflict between different perceived targets in the target area or that there is no conflict between different perceived targets in the target area. Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, determine the time information of the conflict between different perceived targets in the target area; Based on at least one of the mobility analysis information of the perceived target and the trajectory prediction analysis information of the perceived target contained in the perception data, the location information of the conflict between different perceived targets in the target area is determined.

7. The sensing and detection method according to claim 2 or 6, wherein, The sensed target that does not meet the security conditions includes at least one of the following: an unauthorized sensed target, an unregistered sensed target, or a sensed target that has not obtained a legitimate identity; The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

8. The sensing and detection method according to claim 1, wherein, Before receiving the sensing data of the target area sent by the second network element, the method further includes: Send a first request message to the second network element; wherein the first request message is used to request the second network element to provide sensing data of the target area.

9. The sensing and detection method according to claim 1 or 8, further comprising: The system receives a second request message sent by a third network element; wherein the second request message is used to request the detection of sensing target-related information within the target area.

10. The sensing and detection method according to claim 9, wherein, The second request message carries at least one of the following information: The second type of perceived target information; wherein, the second type of perceived target is a perceived target that meets the security conditions; Perceive the business type; Perceive business requirements; The triggering conditions for sensing business processes.

11. The sensing and detection method according to claim 1 or 8, further comprising: Send a third request message to the third network element; A response message is received from the third request message sent by the third network element; wherein the response message carries second type of sensing target information, and the second type of sensing target is a sensing target that meets the security conditions.

12. The sensing and detection method according to claim 9 or 11, further comprising: Authorization verification is performed on the third network element; If the authorization verification of the third network element is successful, a first request message is sent to the second network element.

13. The sensing and detection method according to claim 1, 8, or 12, wherein, The second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, application data analysis enabler service ADAES network element, artificial intelligence / machine learning enabler service AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

14. The sensing and detection method according to claim 1, further comprising: The sensing and detection results are sent to the third network element.

15. The sensing and detection method according to claim 9, 11, 12, or 14, wherein, The third network element includes at least one of the following: application server, terminal device, and terminal internal perception management client.

16. A sensing and detection method applied to a second network element, the method comprising: The first network element sends sensing data of the target area to the first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

17. The sensing and detection method according to claim 16, wherein, The perception detection result includes at least one of the following: The target area may contain a sensing target or the target area may not contain a sensing target. The sensing targets in the target area either meet the safety conditions or the sensing targets in the target area do not meet the safety conditions; The first type of perceived target information within the target area; wherein, the first type of perceived target is a perceived target that does not meet the security conditions; There may be a conflict between different sensing targets within the target area, or there may be no conflict between different sensing targets within the target area. The time information of conflicts occurring between different sensing targets within the target area; The location information of conflicts between different sensing targets within the target area.

18. The sensing and detection method according to claim 17, wherein, The sensed target that does not meet the security conditions includes at least one of the following: an unauthorized sensed target, an unregistered sensed target, or a sensed target that has not obtained a legitimate identity; The sensing target that meets the security conditions includes at least one of the following: an authorized sensing target, a registered sensing target, or a sensing target that has obtained a legitimate identity.

19. The sensing and detection method according to claim 16, wherein, The perceived data includes at least one of the following: Perceive target information; Analyze the mobility of the target; Analyze and predict the movement trajectory of the perceived target; Analyzing the perception accuracy of the target; Information on the perceived credibility of the target.

20. The sensing and detection method according to claim 19, wherein, The perceived target information includes at least one of the following: Perceive the identification information of the target; Perceive the material information of the target; Perceive the size information of the target; Perceive the image information of the target.

21. The sensing and detection method according to claim 16, wherein, The step of sending the sensing data of the target area to the first network element includes: Receive the first request message sent by the first network element; Based on the first request message, the sensing data of the target area and / or the target object are sent to the first network element.

22. The sensing and detection method according to claim 16 or 21, wherein, The second network element includes at least one of the following: core network element, core network function, application enabler, application enabler network element, application data analysis enabler service ADAES network element, artificial intelligence / machine learning enabler service AIMLE network element, terminal device, terminal internal client, third-party device, and third-party network function.

23. A sensing and detection device, comprising a memory, a transceiver, and a processor; in, The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs from the memory and perform the following operations: Receive sensing data of the target area sent by the second network element; Based on the perception data, a perception detection result is determined; wherein the perception detection result is used to indicate relevant information about the perception target within the target area.

24. A sensing and detection device, comprising: The first receiving unit is used to receive sensing data of the target area sent by the second network element; The processing unit is configured to determine a perception detection result based on the perception data; wherein the perception detection result is used to indicate information related to the perception target within the target area.

25. A sensing and detection device, acting on a second network element, the device comprising a memory, a transceiver, and a processor; in, The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs from the memory and perform the following operations: The first network element sends sensing data of the target area to the first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target related information in the target area.

26. A sensing and detection device, comprising: A transmitting unit is used to transmit sensing data of a target area to a first network element; wherein the sensing data is used by the first network element to determine the sensing detection result, and the sensing detection result is used to indicate the sensing target-related information within the target area.

27. A processor-readable storage medium, wherein, The processor-readable storage medium stores a computer program for causing the processor to perform the steps of the perception detection method according to any one of claims 1 to 22.

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