WO2022069047A1

WO2022069047A1 - User equipment trajectory monitoring

Info

Publication number: WO2022069047A1
Application number: PCT/EP2020/077507
Authority: WO
Inventors: Péter SZILÁGYI; Anja Jerichow; Anatoly ANDRIANOV
Original assignee: Nokia Technologies Oy
Priority date: 2020-10-01
Filing date: 2020-10-01
Publication date: 2022-04-07

Abstract

Systems, methods, apparatuses, and computer program products for UE trajectory monitoring and/or analysis are provided. One method may include receiving or collecting trajectory information for at least one user equipment, UE, coupled with state information associated with the at least one user equipment, UE. The method may also include receiving or collecting, from a network node, location information for the at least one user equipment, UE, and location information for one or more other user equipment, UEs. The method may then include obtaining a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment, UEs, and providing a status indication associated to at least one location, where the at least one location is determined to have a predefined attribute based on the correlation.

Description

TITLE:

USER EQUIPMENT TRAJECTORY MONITORING

FIELD:

[0001] Some example embodiments may generally relate to mobile or wireless telecommunication systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technology or new radio (NR) access technology, or other communications systems. For example, certain embodiments may relate to systems and/or methods for user equipment (UE) trajectory monitoring.

BACKGROUND:

[0002] Examples of mobile or wireless telecommunication systems may include the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), LTE- Advanced (LTE- A), MulteFire, LTE-A Pro, and/or fifth generation (5G) radio access technology or new radio (NR) access technology. 5G wireless systems refer to the next generation (NG) of radio systems and network architecture. A 5G system is mostly built on a 5G new radio (NR), but a 5G (or NG) network can also build on the E-UTRA radio. It is estimated that NR provides bitrates on the order of 10-20 Gbit/s or higher, and can support at least service categories such as enhanced mobile broadband (eMBB) and ultra-reliable low-latency-communication (URLLC) as well as massive machine type communication (mMTC). NR is expected to deliver extreme broadband and ultra-robust, low latency connectivity and massive networking to support the Internet of Things (IoT). With loT and machine-to-machine (M2M) communication becoming more widespread, there will be a growing need for networks that meet the needs of lower power, low data rate, and long battery life. The next generation radio access network (NG-RAN) represents the RAN for 5G, which can provide both NR and LTE (and LTE-Advanced) radio accesses. It is noted that, in 5G, the nodes that can provide radio access functionality to a user equipment (i.e., similar to the Node B, NB, in UTRAN or the evolved NB, eNB, in LTE) may be named next-generation NB (gNB) when built on NR radio and may be named nextgeneration eNB (NG-eNB) when built on E-UTRA radio.

SUMMARY:

[0003] One embodiment may be directed to a method, which may include receiving or collecting trajectory information for at least one user equipment (UE) coupled with state information associated with the at least one user equipment (UE). The method may also include receiving or collecting, from a network node, location information for the at least one user equipment (UE) and location information for one or more other user equipment (UEs). The method may further include obtaining a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment (UEs), and providing a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation.

[0004] Another embodiment may be directed to an apparatus, which may include at least one processor and at least one memory comprising computer program code. The at least one memory and computer program code configured, with the at least one processor, to cause the apparatus at least to receive or collect trajectory information for at least one user equipment (UE) coupled with state information associated with the at least one user equipment (UE), to receive or collect, from a network node, location information for the at least one user equipment (UE) and location information for one or more other user equipment (UEs), to obtain a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment (UEs), and to provide a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation. [0005] Another embodiment may be directed to an apparatus that may include means for receiving or collecting trajectory information for at least one user equipment (UE) coupled with state information associated with the at least one user equipment (UE), means for receiving or collecting, from a network node, location information for the at least one user equipment (UE) and location information for one or more other user equipment (UEs), means for obtaining a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment (UEs), and means for providing a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation. [0006] Another embodiment may be directed to a method, which may include collecting, at a user equipment (UE), trajectory information of the user equipment (UE), receiving, from a trusted source, input of state information for the user equipment (UE) or for an object or user associated with the user equipment (UE), coupling the state information with the trajectory information of the user equipment (UE), and transmitting the coupled state information and trajectory information to a network side analytics server.

[0007] Another embodiment may be directed to an apparatus, which may include at least one processor and at least one memory comprising computer program code. The at least one memory and computer program code configured, with the at least one processor, to cause the apparatus at least to collect trajectory information of the apparatus, receive, from a trusted source, input of state information for the apparatus or for an object or user associated with the apparatus, to couple the state information with the trajectory information of the apparatus, and to transmit the coupled state information and trajectory information to a network side analytics server.

[0008] Another embodiment may be directed to an apparatus that may include means for collecting trajectory information of the apparatus, means for receiving, from a trusted source, input of state information for the apparatus or for an object or user associated with the apparatus, means for coupling the state information with the trajectory information of the apparatus, and means for transmitting the coupled state information and trajectory information to a network side analytics server.

BRIEF DESCRIPTION OF THE DRAWINGS:

[0010] For proper understanding of example embodiments, reference should be made to the accompanying drawings, wherein:

[0011] Fig. 1 illustrates a diagram of a method, according to one example embodiment;

[0012] Fig. 2 illustrates an example flow diagram of a method, according to an embodiment;

[0013] Fig. 3 illustrates an example flow diagram of a method, according to an embodiment;

[0014] Fig. 4 illustrates an example of the integration of a NWDAF with a public warning system (PWS);

[0015] Fig. 5 illustrates an example flow diagram of a method, according to an embodiment;

[0016] Fig. 6a illustrates an example block diagram of an apparatus, according to an embodiment; and

[0017] Fig. 6b illustrates an example block diagram of an apparatus, according to an embodiment.

DETAILED DESCRIPTION: [0018] It will be readily understood that the components of certain example embodiments, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of some example embodiments of systems, methods, apparatuses, and computer program products for UE trajectory monitoring and/or analysis, is not intended to limit the scope of certain embodiments but is representative of selected example embodiments.

[0019] The features, structures, or characteristics of example embodiments described throughout this specification may be combined in any suitable maimer in one or more example embodiments. For example, the usage of the phrases “certain embodiments,” “some embodiments,” or other similar language, throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment. Thus, appearances of the phrases “in certain embodiments,” “in some embodiments,” “in other embodiments,” or other similar language, throughout this specification do not necessarily all refer to the same group of embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments.

[0020] Additionally, if desired, the different functions or procedures discussed below may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the described functions or procedures may be optional or may be combined. As such, the following description should be considered as illustrative of the principles and teachings of certain example embodiments, and not in limitation thereof.

[0021] As will be discussed in more detail in the following, some example embodiments may be directed to network-side UE trajectory analytics, for instance, for risk detection and/or notification. For instance, certain example embodiments may relate to UE trajectory monitoring while maintaining data privacy and/or providing automated notifications.

[0022] Personal identity and location are understood as private data that should be protected. In addition, the sensitivity of such private data may be further increased if it is coupled with medical or health information (e.g., COVID-19 testing or other infection testing outcome and/or any other medical state). Meanwhile, tracking and searching the historical trajectories or movements of persons (e.g., including time and duration of presence at specific locations) may be desirable in certain situations. For example, it may be desirable to track the historical trajectories of devices or movements of people who are potential transmitters of disease or illness (or any other human-to-human transmittable condition). In fact, such tracking may be required, for example, in pandemic situations (for contact discovery or selfassessment of risk) or under other situations or pursuant to local requirements. However, knowing the trajectories of a specific device or UE may not be enough in certain situations (e.g., in order to analyze the potential spread of diseases or illnesses), since knowing the mobility of other devices or UEs may also be needed. Therefore, a method that balances between the level of information collected from people and the efficiency of providing insight to potentially important public information, such as the spread of infection or medical risks or traffic security, may be desired.

[0023] For the sake of simplicity, in the following disclosure, examples relating to health information and disease spread control will be described. It should, however, be clear that the principles described in the present disclosure can be applied to any scenario, where status information of an object, device or person associated with location information can be provided by an authorized authority. Further, UEs referred to in the following may be mobile devices, e.g. carried by a user, telecommunication units embedded in a vehicle or other object, or the like. [0024] A technical problem that certain embodiments can solve may include, among others, how to anonymously collect information from UEs in order to determine which UEs have been in the same area or location of interest. As one example, an embodiment may be able to collect anonymous data from UEs in order to detect if a location was a probable center of infection or risk (e.g., due to being visited with many people at the same time and some people may have been infected) without compromising privacy. An additional technical problem that certain embodiments can solve may include, but is not limited to, how to generate meaningful notifications or alerts to appropriate devices or UEs. As one non-limiting example, in infectious situations, some embodiments may be configured to generate notifications or alerts for those that could have been infected and/or to prevent the infection of further people. [0025] It should be noted that, while certain embodiments are described herein with respect to analyzing or determining the risk for infection or spread of disease, example embodiments are not just limited to these use cases. As such, some example embodiments may be applied to any situation that may benefit from UE trajectory monitoring and/or movement tracking. For instance, certain embodiments can be applied to traffic control scenarios, to risk exposure situations, public safety situations, or any other scenario that may benefit from monitoring and providing notifications or alerts.

[0026] Certain example embodiments may provide method(s) and apparatus(es) for a UE device and/or network side analytics server (e.g., network data analytics function (NWDAF)) to collect anonymous UE trajectories and/or state information. For example, the state information may describe a state of the UE or a user of the UE. According to certain embodiments, the state information may include one or more of medical state information describing a medical state of a user, risk state information describing a risk associated with a UE or a location that the UE has visited or is visiting, a traffic state information describing traffic associated with a location, or other information that may be of interest to other UEs or the network.

[0027] In an example embodiment, the collected UE trajectories and/or state information may be used, for instance, to determine and/or analyze a center or area of interest. For instance, in one non-limiting example, the collected UE trajectories and/or state information may be used to analyze the risk of locations becoming centers of infection.

[0028] According to certain embodiments, the method may collect information from at least two sources, which may include: (1) an application stored and/or run on the UE that is able to provide trajectory information coupled with state information for the user or UE, and/or (2) network side UE location information to provide location and/or trajectory information without the state information.

[0029] In an embodiment, the application on the UE may record the trajectory of the device, until a trigger occurs, until the UE visits a certain location, or for a pre-defined time period. As one example, the application on the UE may record the trajectory of the UE until a user of the UE visits, e.g., a medical facility that provides status information, such as a medical status, medical state information, risk state information, traffic state information, or other information of interest, for the user. In one example, the status information may be entered into the UE application and be attached to the trajectory of the UE. The UE application may also upload the trajectory of the device together with the status information of the device to a network side analytics server.

[0030] In certain embodiments, the network side analytics server may also collect UE location information (e.g., cell information) using sources available in the network, such as the access and mobility management function (AMF). Such information may be available about the UEs without having to install a dedicated application on the UEs. According to an embodiment, the network side analytics server may correlate the anonymous trajectory information collected from UE(s), which has been tagged or coupled with the status information (e.g., medical status information or risk status information), with the anonymous mobility-only information collected from the network side sources. If the correlation reveals that the number of UEs around a certain location was or is becoming high and the location was or is visited by UEs whose presence may require notification to other UEs or the authorities (e.g., where an owner of a UE has been or may have been infected or the occurrence of any other risk situation requiring an alert), the network side analytics server may provide a notification or alert to authorities or directly to the UEs that are or have been around the location, e.g., using a public warning system (PWS).

[0031] Therefore, according to certain embodiments, an implementation of an application configured to run on the UE may contain several features. For instance, in one embodiment, the application may be configured to support the collection of trajectory using the location services of the device. The trajectory collection may be implemented by saving the location of the device periodically (e.g., every 20 seconds as one example) or when the device has moved. In some embodiments, the location may be collected according to different granularities, e.g., on a global positioning system (GPS) coordinate level or on cell ID level (if GPS is not enabled). In an embodiment, the application may support the input of state information by a trusted source. For instance, as one non-limiting example, the application may be configured to receive medical state information from a trusted source of diagnosis (e.g., a doctor, medical professional, hospital, or an approved test mechanism, or the like).

[0032] Furthermore, according to an embodiment, the application may support the synthesis of anonymous state information suitable to be coupled to the trajectory information of the device or UE. In one embodiment, the application may support communication with a NWDAF. As one example, the application may be configured to communicate with the NWDAF via a pre-configured uniform resource locator (URL) where the trajectory and state information may be uploaded.

[0033] It is noted that, in examples where some embodiments are applicable to infectious disease situations, isolating a possibly infected person as soon as a positive (infectious) diagnosis is made does not conclude the applicability of certain embodiments, as the diagnosis may just reveal that the person has been infected for some time already before the diagnosis and therefore the past trajectory of the person (correlated with mass mobility data) may be an important input to the analysis even if the positively diagnosed person does not produce any future trajectory due to hospitalization or home quarantine. For example, in some embodiments, the analysis can immediately or proximately reveal that a location may have been a center of infection at a past time and thus a rise in the number of infected cases can be expected. Further, in certain embodiments, the analysis can also provide information on who may have been at risk (i.e., those who visited such a location) and those persons can be alerted automatically, speeding up the usually manual contact discovery and tracing process. Again, it should be noted that example embodiments are not merely limited to such medical situations, as certain embodiments may be applied at least to any situation that may benefit from the analysis of trajectory information.

[0034] Fig. 1 illustrates a diagram of an example method, according to one embodiment. In an embodiment, a network side analytics server (NWDAF) may continuously or periodically collect the location of one, more or every UE that is registered to the network. This information may be kept private by the NWDAF. In certain embodiments, the information may be used later to identify current or past mobility hotspots and, therefore, a certain length of history (e.g., two weeks) of UE location may be maintained. [0035] According to an embodiment, one or more UE(s) (e.g., UE-X), which may have installed or can execute a dedicated application, may be configured to perform certain procedures. As illustrated in the example of Fig. 1, at 1, the UE application may collect the trajectory of the UE or device. The trajectory may be stored on the device or stored elsewhere. In this example embodiment, at 2, a user of the UE may visit or be at or in proximity of a location controlled by an authority. This location could be a pole of a traffic infrastructure including or connected to an loT device, e.g., for smart road applications, or a medical professional or doctor to collect medical state information (e.g., a medical diagnosis). In an embodiment, at 3, the identification of the person or object carrying the UE is guaranteed or confirmed by the authority, such as the medical professional or doctor (i.e., the doctor checks the identity of the person that is inspected). At 4, the authority may provide the status indication associated to the person or object. For example, the medical professional or doctor may provide the diagnosis for the person, i.e., creating a medical state.

[0036] According to certain embodiments, at 5, the status indication, e.g. the diagnosis or medical state, which is originally attached to the person’s identity, may be coupled to the trajectory of the phone. In one embodiment, the procedure at 5 may involve proximity based communication, such as Bluetooth, QR code, NFC, and the like. Thus, in this embodiment, the person’s device or UE and the authority, e.g., doctor’s (or medical professional’s) device may need to be in physical proximity for the voluntary data exchange to take place. As such, the authority’s presence is the source of trust and user consent. This embodiment may apply, for example, in the following cases: where the medical test and diagnosis are done in one step, i.e., the tested person is naturally at the doctor, or where the diagnosis is made after the test but the tested person is re-visiting the doctor to be informed about the outcome of the test. In another embodiment, the transfer of medical state from the doctor to the device may be via a trusted server, from where the tested person’s device periodically fetches (or receive via push notification) its own medical state. According to an embodiment, if the diagnosis comes from an automated test (e.g., user providing a sample and a machine providing the test output), the medical state may come from such machine as well.

[0037] In an embodiment, when the status information of the person or object may trigger a risk condition, for instance when the diagnosis is positive (i.e., the person poses a risk to others), at 6, the trajectory and relevant parts of the status (e.g., medical) information (i.e., those that do not identify the person specifically but capture the level of risk the person poses to others) may be uploaded to the network side analytics server (e.g., NWDAF).

[0038] As further illustrated in the example of Fig. 1, at 7, the network side analytics server may correlate the anonym trajectory and (medical) state information with the mass location information. The analysis may conclude that a given location has been at risk, for instance of becoming a center of mass infection or other risky event. At 8, the network side analytics server may alert the authorities on detecting a center of risk event, such as mass infection, so that appropriate measures can be taken (e.g., broadcasting of information to citizens, or publishing the information on a government website or otherwise informing the public). In an embodiment, at 9, the network side analytics server may interface with the PWS to broadcast an alert to UEs residing in a given area to draw their attention to the risks. For example, this alert may be particularly useful if there is a near real time detection of a forming center of infection or the infection is spreading through a contaminated environment at the location (not only through human to human contact).

[0039] It should be noted that, while the example of Fig. 1 is described in relation to the collection of medical state information that can be used to analyze or determine the risk for infection or spread of disease, example embodiments are not just limited to this use case or application. As such, some example embodiments may be applied to any situation that may benefit from UE trajectory monitoring and/or movement tracking. Therefore, Fig. 1 illustrates just one example and other examples are contemplated according to certain embodiments.

[0040] According to certain embodiments, the network side analytics server provided by some embodiments may include a NWDAF as specified by 3 GPP architecture. For example, an NWDAF may refer to an entity configured to provide a data consumer or consumer network function (NF) with analytics that assist in control decisions. The NWDAF can collect input data by subscribing to event-based or timer-based notifications from source NFs and/or the operations, administration and maintenance (0AM). The NWDAF may be configured to produce analytics outputs based on the collected inputs, and to deliver these analytics outputs to a data consumer or NF.

[0041] In an embodiment, the NWDAF may continuously collect mass data on UE locations by subscribing to a service offerred by an AMF that enables an NF to subscribe to event notifications, such as a Namf EventExposure service. Such UE location information can be used to build per location statistics (e.g., series of data points capturing location, time and number of UEs at the time at the given location) without additional medical information. According to an embodiment, location may be represented by a cell identifier (ID), which can then be converted to geography areas.

[0042] According to some embodiments, the NWDAF may collect UE location information coupled with state information through an application running on the UE. In an embodiment, the state information may include at least one or more of the following: a time interval within which the state information is valid, a reason for the state, and/or a geographical radius of applicability for the state. For instance, in certain embodiments where the state information relates to a medical state, the medical state may include at least one or more of the following elements: time interval within which the medical state is valid (or starting time since when the state is valid, if it is still ongoing), infection radius (e.g., in meters or other distance measurement, which may mean that owners of other UEs being in the proximity of the trajectory have a risk of catching the infection), and/or transmission of the infection (i.e., human to human via proximity or contact, or by visiting a location after somebody else was there, etc.). In certain example embodiments, the UE trajectories coupled with such state information may enable the NWDAF to correlate them with mass UE data, e.g., the NWDAF may count per area or per cell how many UEs have been in a certain geographical radius of at least one UE of interest.

[0043] In some example embodiments, the analytics may be triggered when a new trajectory with state information is uploaded to the NWDAF. The NWDAF may check whether the uploaded trajectory within the time interval of valid state information (e.g., an active infection) matches any other UE’s location collected from the AMF. Even if a UE uploading the trajectory information is no longer moving or active, it may be desirable to collect past trajectory and maintain a history of the UE’s location. In general, the historical duration for which past location(s) is maintained may be set according to the situation. For example, in example embodiments where the state information relates to a medical state, the duration for which location(s) are saved may be based on the lifecycle and spreading capability of infection, e.g., 2 weeks or any other appropriate duration. If the analytics is able to match an uploaded trajectory with locations (e.g., cell areas or geographic areas) where many other UEs have been (e.g., more than a given threshold), the NWDAF may provide an indication to authorities (e.g., by interfacing with a dashboard, a public website or a logging system that can send email or other notifications) or provide an indication to one or more UE(s). In one example, the indication to the authorities or the UE(s) may be an alert sent through PWS, if appropriate.

[0044] Fig. 2 illustrates an example flow chart of a method of collecting and analyzing trajectory information and/or state information, according to an embodiment. In certain example embodiments, the flow diagram of Fig. 2 may be performed by a network entity or network node in a communications system, such as LTE or 5G NR. In some example embodiments, the network entity performing the method of Fig. 2 may include or be included in a base station, access node, node B, eNB, gNB, NG RAN node, or the like. For instance, in one example embodiment, the method of Fig. 2 may be performed by a network analytics server, AF, or central entity, such as the NWDAF depicted in the example diagram of Fig. 1.

[0045] As illustrated in the example of Fig. 2, the method may include, at 200, receiving or collecting trajectory information for at least one UE coupled with state information associated with the at least one UE and/or associated with a user of the at least one UE. The receiving 200 may include receiving the trajectory information coupled with the state information from the at least one UE and/or from an application running on the at least one UE. In some embodiments, the state information may include or may indicate one or more of: (1) a time interval within which the state information is valid, (2) a reason for the state, or (3) a radius of applicability for the state. According to some example embodiments, the state information may include one or more of: medical state information, risk state information, traffic state information, or other information of interest to the other UEs.

[0046] In an embodiment, the method of Fig. 2 may also include, at 210, receiving or collecting, from a network node or network function, location information for the at least one UE and/or location information for one or more other UEs. According to certain embodiments, the collecting 210 may include continuously collecting a location of UEs that are registered to a network associated with the network node or network function.

[0047] According to certain embodiments, the method may also include, at 220, obtaining a correlation of the trajectory information that is coupled with the state information of the at least one UE with the location information for the other UEs. In some embodiments, the state information may indicate a certain property of a user of the at least one UE about which the other UEs having been in proximity of the at least one UE should be informed. For instance, in one example embodiment, the certain property may indicate that the user of the at least one UE may pose a risk to users of the other UEs.

[0048] In one embodiment, the method may include, at 230, providing a status indication associated to at least one location, where the at least one location may be determined to have a predefined attribute based on the correlation obtained at 220. According to one embodiment, it may be concluded that the at least one location has the predefined attribute when it is determined that the at least one location is an area of interest in which the correlation indicates that the other UEs were in proximity of the at least one UE within the area of interest. In one example embodiment, the providing 230 of the status indication may include providing an alert to authorities or directly to the other UEs that have been in proximity of the at least one location, for example, by using a public warning system (PWS).

[0049] According to some embodiments, the obtaining 220 of the correlation and/or the providing 230 may be triggered when new trajectory information for the at least one UE is received or collected. In certain embodiments, the collected location of the UEs may be kept private or anonymous. In an embodiment, the method may include storing the collected location of the UEs for a certain period of time.

[0050] According to an embodiment, the method may include using the collected location of the UEs to build location statistics that may include one or more of a series of data points capturing past and present locations of the UEs, or a time and number of UEs that are located at a given location or within a certain radius of the given location. In an embodiment, the collected location may be represented by a cell identifier (ID) that can then be converted to a geographical area.

[0051] In some embodiments, the providing 230 of the status indication may include creating one or more cell broadcast service (CBS) messages that may include one or more of: a type of status indication to be communicated, a time associated with the state information, an impact related to the state information, and/or an action to be taken by those receiving the status indication. The one or more cell broadcast service (CBS) messages may then be provided to a cell broadcast center.

[0052] In some example embodiments, the method may include receiving, at a network side analytics server, from at least one other network side analytics server, data comprising trajectory information for one or more UEs coupled with state information of the one or more UEs. The receiving network side analytics server may then merge the received data from the other network side analytics server with data collected at the network side analytics server or central entity, and may then decide, based on the merged data, whether a status indication should be provided. When it is decided that the status indication should be provided, the method may include notifying the other network side analytics server that the status indication should be sent.

[0053] Fig. 3 illustrates an example flow diagram of a method applying an example use case, according to an example embodiment. In one embodiment, the example method of Fig. 3 may be performed at a network entity, network node or network function, such as a NWDAF.

[0054] As illustrated in the example of Fig. 3, the method may include, at 305, receiving trajectory and medical state information from one or more UEs and, at 310, receiving UE location information from a network node or function. The method may also include, at 315, correlating and analyzing the UE trajectories having medical state information with the UE location information received from the network node or function. As further illustrated in the example of Fig. 3, at 320, the method may include determining if a predetermined number of UEs were or are co-located with a trajectory point of at least one UE whose medical state indicates that it carries a risk for others and, if so, marking such trajectory points as centers of infection or risk. The predetermined number of UEs may be defined based on at least one of specific application configuration, operator configuration and regional regulations. In one embodiment, the predetermined number may be more than one UE that is or was co-located with a trajectory point of a UE being a potential source of risk, e.g., a UE having a risky medical state associated therewith, then this may be considered as a significant number of UEs.

[0055] As also illustrated in the example of Fig. 3, the method may include, at 325, transmitting an alert to authorities that may include an indication of the center of infection or risky location(s) and/or the number of UEs that have visited the risky location(s). Additionally or alternatively, in an embodiment, the method may include, at 330, transmitting an alert to the UE(s) that are or have been in proximity of the center of infection or risky location(s), e.g., via a PWS.

[0056] In certain embodiments, PWS integration may be implemented according to 3GPP cell broadcast service (CBS). In this context, the NWDAF may act as a cell broadcast entity (CBE) and connects to cell broadcast center function (CBCF). The CBE may create the CBS messages, and the CBCF may initiate the broadcast of the CBS messages in the proper area (list of cells). Fig. 4 illustrates an example of the integration of NWDAF with the PWS.

[0057] In some embodiments, the communication from the NWDAF to the CBCF may contain certain information. As an example, the information may include, but is not limited to, one or more of the following information elements: the type of warning to be communicated, the time of the risk, the impact, and/or the action to be taken by those receiving the alert.

[0058] According to an example embodiment, the type of warning to be communicated may include risk of health by visiting a location (in case an infection is airborne at a given location, or there is another location-bound condition such as chemical threat or environmental contamination). It should be clear that visiting the location itself should be avoided. Risk of health by meeting people around a location (in case an infection is transmitted human to human). It should be clear that being in the proximity of people is a risk at the area (e.g., in a closed dense space such as a supermarket) and special attention is needed to avoid getting too close to one another.

[0059] In certain embodiments, the time of the risk may be a past time interval (e.g., risk existed within a given time frame where, for example, infected persons may have been visited a location and many others were there). Additionally or alternatively, the time of risk may indicate that the risk is currently ongoing and whoever is at the location currently should take actions immediately.

[0060] According to an example embodiment, the impact information may include the number of persons who may be or may have been impacted, and/or the number of persons who may pose or may have posed the risk to others (e.g., whether there was 1 infected person for every 100 others or 10 for every 100 people) as this information may lead to different expectations on the level of infection transmission).

[0061] In an example embodiment, the action to be taken by those receiving the alert may include that people may stay at the location but should take personal safety measure(s) (e.g., wearing masks, keep a certain social distancing), that people should be leaving the location as soon as possible, and/or whether the action is recommended or mandatory. If it is mandatory, the source of authority (e.g., police, medical staff, facility manager, etc.) may also be included.

[0062] In one example embodiment, a NWDAF may collect information from and about UEs in one operator’s network, but in a given area (e.g., a country or state) where multiple operators may provide service, whose subscribers may meet in real life. Therefore, there may be a need to exchange data between NWDAFs so that they can build a complete picture of all user’s mobility and trajectory crossings. According to certain embodiments, this data exchange may be implemented in multiple ways. For example, the data exchange may be implemented via NWDAF-to-NWDAF interaction and/or via the introduction of a central entity.

[0063] According to certain embodiments, a NWDAF-to-NWDAF interaction may include different options. For instance, in one option, a first NWDAF may share its data (trajectories coupled with medical state information) with a second NWDAF. The second NWDAF may merge this data with its own and perform analytics. The first NWDAF does not necessarily perform analytics in this case. The second NWDAF, if it decides that an alert should be sent, may notify the first NWDAF about the alert so that the first NWDAF may trigger the alert in its own network. The notification from the second NWDAF to the first NWDAF may contain the same information as discussed above for the interface between the NWDAF and the CBCF.

[0064] According to another option for a NWDAF-to-NWDAF interaction, a first NWDAF may share the outcome of its own analysis with a second NWDAF. The outcome of the analysis may include determined risky locations and corresponding statistics on UEs (e.g., number of impacted UEs, number of UEs posing risk to others, etc.). The second NWDAF may combine this information with the outcome of its own analytics and trigger alerts similarly to the option discussed above (i.e., second NWDAF alerts the subscribers of its network and notifies the first NWDAF so that it can alert within its own network).

[0065] As mentioned above, in a further embodiment, a central entity (e.g., application function - AF) may be provided. This central entity may be configured to communicate with multiple operators’ NWDAF (through a network exposure function (NEF), or through a SBA in case of a trusted AF). The role of the central entity may correspond to that of the second NWDAF in the options discussed above, and the NWDAF(s) may act as a first NWDAF according to the options discussed above.

[0066] Fig. 5 illustrates an example flow diagram of a method relating to collecting and/or analyzing trajectory information and/or state information, according to an embodiment. In some example embodiments, the method of Fig. 5 may be performed by a network node or element, such as a UE, mobile station, mobile device, mobile unit, mobile equipment, user device, subscriber station, wireless terminal, tablet, smart phone, stationary device, loT device, NB-IoT device, sensor, and/or other device.

[0067] As illustrated in the example of Fig. 5, at 500, the method may include collecting, at a UE, trajectory information of the UE. In one embodiment, the collecting 500 may include collecting the trajectory information using location services of the user equipment. In an embodiment, the method may include storing the trajectory information. For example, the storing of the trajectory information may include storing a location of the UE periodically or when the UE has moved. In some embodiments, the collecting 500 may include collecting the trajectory information on different granularities.

[0068] In an embodiment, the method of Fig. 5 may include, at 510, receiving, from a trusted source, an input of state information for the UE and/or state information for an object or user associated with the UE. According to an embodiment, the method may also include, at 520, coupling the state information for the UE, or for the object or user associated with the UE, with the trajectory information of the UE. In one embodiment, the method may include, at 530, transmitting the coupled state information and trajectory information to a network node, such as a network side analytics server, an NWDAF, or the like. According to some example embodiments, the state information may include one or more of: medical state information, risk state information, traffic state information, or other information of interest to other UEs that are or may have been in proximity of the UE. In certain embodiments, the collecting 500, receiving 510 and/or coupling 520 may be performed by an application running on the UE.

[0069] Fig. 6a illustrates an example of an apparatus 10 according to an embodiment. In an embodiment, apparatus 10 may be a node, host, or server in a communications network or serving such a network. For example, apparatus 10 may be a satellite, base station, a Node B, an evolved Node B (eNB), 5G Node B or access point, next generation Node B (NG-NB or gNB), transmission receive point (TRP), high altitude platform station (HAPS), integrated access and backhaul (IAB) node, and/or WLAN access point, associated with a radio access network, such as a LTE network, 5G or NR. In one example embodiment, apparatus 10 may be a network function, network side analytics server, and/or NWDAF.

[0070] It should be understood that, in some example embodiments, apparatus 10 may be comprised of an edge cloud server as a distributed computing system where the server and the radio node may be stand-alone apparatuses communicating with each other via a radio path or via a wired connection, or where they may be located in a same entity communicating via a wired connection. For instance, in certain example embodiments where apparatus 10 represents a gNB, it may be configured in a central unit (CU) and distributed unit (DU) architecture that divides the gNB functionality. In such an architecture, the CU may be a logical node that includes gNB functions such as transfer of user data, mobility control, radio access network sharing, positioning, and/or session management, etc. The CU may control the operation of DU(s) over a front-haul interface. The DU may be a logical node that includes a subset of the gNB functions, depending on the functional split option. It should be noted that one of ordinary skill in the art would understand that apparatus 10 may include components or features not shown in Fig. 6a.

[0071] As illustrated in the example of Fig. 6a, apparatus 10 may include a processor 12 for processing information and executing instructions or operations. Processor 12 may be any type of general or specific purpose processor. In fact, processor 12 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), applicationspecific integrated circuits (ASICs), and processors based on a multi-core processor architecture, or any other processing means, as examples.

[0072] While a single processor 12 is shown in Fig. 6a, multiple processors may be utilized according to other example embodiments. For example, it should be understood that, in certain embodiments, apparatus 10 may include two or more processors that may form a multiprocessor system (e.g., in this case processor 12 may represent a multiprocessor) that may support multiprocessing. In some embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0073] Processor 12 may perform functions associated with the operation of apparatus 10, which may include, for example, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 10, including processes related to management of communication resources. [0074] Apparatus 10 may further include or be coupled to a memory 14 (internal or external), which may be coupled to processor 12, for storing information and instructions that may be executed by processor 12. Memory 14 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory. For example, memory 14 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, hard disk drive (HDD), or any other type of non-transitory machine or computer readable media, or other appropriate storing means. The instructions stored in memory 14 may include program instructions or computer program code that, when executed by processor 12, enable the apparatus 10 to perform tasks as described herein.

[0075] In an embodiment, apparatus 10 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium. For example, the external computer readable storage medium may store a computer program or software for execution by processor 12 and/or apparatus 10.

[0076] In some embodiments, apparatus 10 may also include or be coupled to one or more antennas 15 for transmitting and receiving signals and/or data to and from apparatus 10. Apparatus 10 may further include or be coupled to a transceiver 18 configured to transmit and/or receive information. The transceiver 18 may include, for example, a plurality of radio interfaces that may be coupled to the anteima(s) 15, or may include any other appropriate transceiving means. In certain embodiments, the radio interfaces may correspond to a plurality of radio access technologies including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, radio frequency identifier (RFID), ultrawideband (UWB), MulteFire, and/or the like. According to an example embodiment, the radio interface may include components, such as filters, converters (e.g., digital-to-analog converters and the like), mappers, a Fast Fourier Transform (FFT) module, and/or the like, e.g., to generate symbols or signals for transmission via one or more downlinks and to receive symbols (e.g., via an uplink).

[0077] As such, transceiver 18 may be configured to modulate information on to a carrier waveform for transmission by the anteima(s) 15 and to demodulate information received via the anteima(s) 15 for further processing by other elements of apparatus 10. In other example embodiments, transceiver 18 may be capable of transmitting and receiving signals or data directly. Additionally or alternatively, in some embodiments, apparatus 10 may include an input device and/or output device (I/O device), or an input/output means.

[0078] In an embodiment, memory 14 may store software modules that provide functionality when executed by processor 12. The modules may include, for example, an operating system that provides operating system functionality for apparatus 10. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 10. The components of apparatus 10 may be implemented in hardware, or as any suitable combination of hardware and software.

[0079] According to some embodiments, processor 12 and memory 14 may be included in or may form a part of processing circuitry or control circuitry. In addition, in some embodiments, transceiver 18 may be included in or may form a part of transceiver circuitry.

[0080] As used herein, the term “circuitry” may refer to hardware-only circuitry implementations (e.g., analog and/or digital circuitry), combinations of hardware circuits and software, combinations of analog and/or digital hardware circuits with software/firmware, any portions of hardware processor(s) with software (including digital signal processors) that work together to cause an apparatus (e.g., apparatus 10) to perform various functions, and/or hardware circuit(s) and/or processor(s), or portions thereof, that use software for operation but where the software may not be present when it is not needed for operation. As a further example, as used herein, the term “circuitry” may also cover an implementation of merely a hardware circuit or processor (or multiple processors), or portion of a hardware circuit or processor, and its accompanying software and/or firmware. The term circuitry may also cover, for example, a baseband integrated circuit in a server, cellular network node or device, or other computing or network device. [0081] As introduced above, in certain embodiments, apparatus 10 may be a network node or RAN node, such as a base station, access point, Node B, eNB, gNB, TRP, HAPS, IAB node, WLAN access point, or the like. In one example embodiment, apparatus 10 may be a network function, network side analytics server, and/or NWDAF. For example, in some embodiments, apparatus 10 may be configured to perform one or more of the processes depicted in any of the flow charts or signaling diagrams described herein, such as those illustrated in Fig. 2 or Fig. 3. In some embodiments, as discussed herein, apparatus 10 may be configured to perform a procedure relating to collecting, analyzing and/or applying UE trajectory information, for example. [0082] In some embodiments, apparatus 10 may be controlled by memory 14 and processor 12 to receive or collect trajectory information for at least one UE coupled with state information associated with the at least one UE and/or associated with a user of the at least one UE. For example, apparatus 10 may be controlled by memory 14 and processor 12 to receive the trajectory information coupled with the state information from the at least one UE and/or from an application running on the at least one UE. In some embodiments, the state information may include or may indicate one or more of a time interval within which the state information is valid, a reason for the state, or a radius of applicability for the state. According to some example embodiments, the state information may include one or more of: medical state information, risk state information, traffic state information, or other information of interest to the other UEs.

[0083] In an embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to receive or collect, from a network node or network function, location information for the at least one UE and/or location information for one or more other UEs. According to certain embodiments, apparatus 10 may be controlled by memory 14 and processor 12 to continuously collect a location of UEs that are registered to a network associated with the network node or network function.

[0084] According to certain embodiments, apparatus 10 may be controlled by memory 14 and processor 12 to obtain a correlation of the trajectory information that is coupled with the state information of the at least one UE with the location information for the other UEs. In some embodiments, the state information may indicate a certain property of a user of the at least one UE about which the other UEs having been in proximity of the at least one UE should be informed. For instance, in one example embodiment, the certain property may indicate that the user of the at least one UE may pose a risk to users of the other UEs.

[0085] Fig. 6b illustrates an example of an apparatus 20 according to another embodiment. In an embodiment, apparatus 20 may be a node or element in a communications network or associated with such a network, such as a UE, mobile equipment (ME), mobile station, mobile device, stationary device, loT device, or other device. As described herein, UE may alternatively be referred to as, for example, a mobile station, mobile equipment, mobile unit, mobile device, user device, subscriber station, wireless terminal, tablet, smart phone, loT device, sensor or NB-IoT device, or the like. As one example, apparatus 20 may be implemented in, for instance, a wireless handheld device, a wireless plug-in accessory, or the like.

[0086] In some example embodiments, apparatus 20 may include one or more processors, one or more computer-readable storage medium (for example, memory, storage, or the like), one or more radio access components (for example, a modem, a transceiver, or the like), and/or a user interface. In some embodiments, apparatus 20 may be configured to operate using one or more radio access technologies, such as GSM, LTE, LTE-A, NR, 5G, WLAN, WiFi, NB-IoT, Bluetooth, NFC, MulteFire, and/or any other radio access technologies. It should be noted that one of ordinary skill in the art would understand that apparatus 20 may include components or features not shown in Fig. 6b.

[0087] As illustrated in the example of Fig. 6b, apparatus 20 may include or be coupled to a processor 22 (or processing means) for processing information and executing instructions or operations. Processor 22 may be any type of general or specific purpose processor. In fact, processor 22 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field- programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples. While a single processor 22 is shown in Fig. 6b, multiple processors may be utilized according to other embodiments. For example, it should be understood that, in certain embodiments, apparatus 20 may include two or more processors that may form a multiprocessor system (e.g., in this case processor 22 may represent a multiprocessor) that may support multiprocessing. In certain embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster). [0088] Processor 22 may perform functions associated with the operation of apparatus 20 including, as some examples, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 20, including processes related to management of communication resources.

[0089] Apparatus 20 may further include or be coupled to a memory 24 (internal or external), which may be coupled to processor 22, for storing information and instructions that may be executed by processor 22. Memory 24 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory. For example, memory 24 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, hard disk drive (HDD), or any other type of non-transitory machine or computer readable media, or other storage means. The instructions stored in memory 24 may include program instructions or computer program code that, when executed by processor 22, enable the apparatus 20 to perform tasks as described herein.

[0090] In an embodiment, apparatus 20 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium. For example, the external computer readable storage medium may store a computer program or software for execution by processor 22 and/or apparatus 20.

[0091] In some embodiments, apparatus 20 may also include or be coupled to one or more antennas 25 for receiving a downlink signal and for transmitting via an uplink from apparatus 20. Apparatus 20 may further include a transceiver 28 (or transceiving means) configured to transmit and receive information. The transceiver 28 may also include a radio interface (e.g., a modem) coupled to the antenna 25. The radio interface may correspond to a plurality of radio access technologies including one or more of GSM, LTE, LTE-A, 5G, NR, WLAN, NB-IoT, Bluetooth, BT-LE, NFC, RFID, UWB, and the like. The radio interface may include other components, such as filters, converters (for example, digital-to-analog converters and the like), symbol demappers, signal shaping components, an Inverse Fast Fourier Transform (IFFT) module, and the like, to process symbols, such as OFDMA symbols, carried by a downlink or an uplink.

[0092] For instance, transceiver 28 may be configured to modulate information on to a carrier waveform for transmission by the anteima(s) 25 and demodulate information received via the anteima(s) 25 for further processing by other elements of apparatus 20. In other embodiments, transceiver 28 may be capable of transmitting and receiving signals or data directly. Additionally or alternatively, in some embodiments, apparatus 20 may include an input and/or output device (I/O device) or input/output means. In certain embodiments, apparatus 20 may further include a user interface, such as a graphical user interface or touchscreen.

[0093] In an embodiment, memory 24 stores software modules that provide functionality when executed by processor 22. The modules may include, for example, an operating system that provides operating system functionality for apparatus 20. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 20. The components of apparatus 20 may be implemented in hardware, or as any suitable combination of hardware and software. According to an example embodiment, apparatus 20 may optionally be configured to communicate with apparatus 10 via a wireless or wired communications link 70 according to any radio access technology, such as NR.

[0094] According to some embodiments, processor 22 and memory 24 may be included in or may form a part of processing circuitry or control circuitry. In addition, in some embodiments, transceiver 28 may be included in or may form a part of transceiving circuitry.

[0095] As discussed above, according to some embodiments, apparatus 20 may be a UE, mobile device, mobile station, ME, loT device and/or NB-IoT device, for example. According to certain embodiments, apparatus 20 may be controlled by memory 24 and processor 22 to perform the functions associated with example embodiments described herein. For example, in some embodiments, apparatus 20 may be configured to perform one or more of the processes or procedures depicted in any of the flow charts or signaling diagrams described herein, such as that illustrated in Fig. 5. In certain embodiments, apparatus 20 may be configured to perform or execute procedure(s) relating to collecting, analyzing and/or applying UE trajectory information, for instance.

[0096] For example, in some embodiments, apparatus 20 may be controlled by memory 24 and processor 22 to collect trajectory information of the apparatus 20. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to collect the trajectory information using location services of the apparatus 20. In an embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to store the trajectory information. For example, apparatus 20 may be controlled by memory 24 and processor 22 to store a location of the apparatus 20 periodically or when the apparatus 20 has moved. In some embodiments, apparatus 20 may be controlled by memory 24 and processor 22 to collect the trajectory information on different granularities. [0097] In an embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to receive, from a trusted source, an input of state information for the apparatus 20 and/or for a user of the apparatus 20. According to an embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to couple the state information for the apparatus 20 or the user of the apparatus 20 with the trajectory information of the apparatus 20. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to transmit the coupled state information and trajectory information to a network side analytics server or network function, such as an NWDAF. According to some example embodiments, the state information may include one or more of: medical state information, risk state information, traffic state information, or other information of interest to other UEs that are or may have been in proximity of the apparatus 20.

[0098] Therefore, certain example embodiments provide several technological improvements, enhancements, and/or advantages over existing technological processes and constitute an improvement at least to the technological field of wireless network control and management. For example, certain embodiments can collect anonymous information from UEs in order to detect if a certain location is a probable center of interest (e.g., to the public) without compromising privacy. As such, some example embodiments may be utilized in public warning systems to allow privacy compliant alerts to impacted UEs or to groups of UEs in a center or location of interest. Accordingly, the use of certain example embodiments results in improved functioning of communications networks and their nodes, such as base stations, eNBs, gNBs, and/or UEs or mobile stations.

[0099] In some example embodiments, the functionality of any of the methods, processes, signaling diagrams, algorithms or flow charts described herein may be implemented by software and/or computer program code or portions of code stored in memory or other computer readable or tangible media, and executed by a processor.

[00100] In some example embodiments, an apparatus may be included or be associated with at least one software application, module, unit or entity configured as arithmetic operation(s), or as a program or portions of it (including an added or updated software routine), executed by at least one operation processor. Programs, also called program products or computer programs, including software routines, applets and macros, may be stored in any apparatus-readable data storage medium and may include program instructions to perform particular tasks.

[00101] A computer program product may include one or more computerexecutable components which, when the program is run, are configured to carry out some example embodiments. The one or more computer-executable components may be at least one software code or portions of code. Modifications and configurations used for implementing functionality of an example embodiment may be performed as routine(s), which may be implemented as added or updated software routine(s). In one example, software routine(s) may be downloaded into the apparatus.

[00102] As an example, software or computer program code or portions of code may be in source code form, object code form, or in some intermediate form, and it may be stored in some sort of carrier, distribution medium, or computer readable medium, which may be any entity or device capable of carrying the program. Such carriers may include a record medium, computer memory, read-only memory, photoelectrical and/or electrical carrier signal, telecommunications signal, and/or software distribution package, for example. Depending on the processing power needed, the computer program may be executed in a single electronic digital computer or it may be distributed amongst a number of computers. The computer readable medium or computer readable storage medium may be a non-transitory medium. [00103] In other example embodiments, the functionality may be performed by hardware or circuitry included in an apparatus, for example through the use of an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software. In yet another example embodiment, the functionality may be implemented as a signal, such as a nontangible means, that can be carried by an electromagnetic signal downloaded from the Internet or other network.

[00104] According to an example embodiment, an apparatus, such as a node, device, or a corresponding component, may be configured as circuitry, a computer or a microprocessor, such as single-chip computer element, or as a chipset, which may include at least a memory for providing storage capacity used for arithmetic operation(s) and/or an operation processor for executing the arithmetic operation(s).

[00105] One having ordinary skill in the art will readily understand that the example embodiments as discussed above may be practiced with procedures in a different order, and/or with hardware elements in configurations which are different than those which are disclosed. Therefore, although some embodiments have been described based upon these example embodiments, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of example embodiments.

Claims

35 We Claim:

1. A method, comprising: receiving or collecting trajectory information for at least one user equipment, UE, coupled with state information associated with the at least one user equipment, UE; receiving or collecting, from a network node, location information for the at least one user equipment, UE, and location information for one or more other user equipment, UEs; obtaining a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment, UEs; and providing a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation.

2. The method according to claim 1, wherein it is determined that the at least one location has the predefined attribute when it is determined that the at least one location is an area of interest in which the correlation indicates that a predetermined number of the other user equipment, UEs, were in proximity of the at least one user equipment, UE, within the area of interest.

3. The method according to claims 1 or 2, wherein the state information indicates a certain property of an object or user associated with the at least one user equipment, UE, about which the other user equipment, UEs, having been in proximity of the at least one user equipment, UE, should be informed.

4. The method according to claim 3, wherein the certain property indicates that the object or user associated with the at least one user equipment, UE, 36 poses a risk to objects or users associated with the other user equipment, UEs.

5. The method according to any of claims 1-4, wherein the providing of the status indication comprises providing an alert to authorities or directly to the other user equipment, UEs, that have been in proximity of the at least one location using a public warning system, PWS.

6. The method according to any of claims 1-5, wherein at least one of the obtaining of the correlation or the providing of the status indication is triggered when new trajectory information for the at least one user equipment is received or collected.

7. The method according to any of claims 1-6, wherein the receiving comprises receiving the trajectory information coupled with the state information of the at least one user equipment, UE, from an application running on the user equipment, UE.

8. The method according to any of claims 1-7, wherein the state information comprises at least one of a time interval within which the state information is valid, a reason for the state, or a radius of applicability for the state.

9. The method according to any of claims 1-8, wherein the collecting from the network node comprises continuously collecting a location of user equipment, UEs, that are registered to a network associated with the network node.

10. The method according to claim 9, wherein the collected location of the user equipment, UEs, is kept private or anonymous.

11. The method according to claims 9 or 10, further comprising storing the collected location of the user equipment, UEs, for a certain period of time.

12. The method according to any of claims 9-11, further comprising using the collected location of the user equipment, UEs, to build location statistics comprising at least one of a series of data points capturing past and present locations of the user equipment, UEs, or a time and number of user equipment, UEs, at a given location.

13. The method according to any of claims 9-12, wherein the collected location is represented by a cell identifier, ID, that is then converted to a geographical area.

14. The method according to any of claims 1-13, wherein the providing of the status indication comprises: creating one or more cell broadcast service, CBS, messages comprising at least one of a type of status indication to be communicated, a time associated with the state information, an impact related to the state information, and an action to be taken by those receiving the status indication; and providing the one or more cell broadcast service, CBS, messages to a cell broadcast center.

15. The method according to any of claims 1-14, wherein the method is performed by at least one of a network side analytics server, network data analytics function, NWDAF, application function, AF, or central entity.

16. The method according to any of claims 1-15, further comprising: receiving at a network side analytics server or central entity, from at least one other network side analytics server, data comprising trajectory information for at least one user equipment, UE, coupled with state information of the user equipment, UE; merging the received data from said at least one other network side analytics server with data collected at the network side analytics server or central entity; deciding, based on the merged data, whether a status indication should be provided; and when it is decided that the status indication should be provided, notifying said at least one other network side analytics server that the status indication should be sent.

17. The method according to any of claims 1-16, wherein the state information comprises at least one of: medical state information, risk state information, traffic state information, or other information of interest to the other user equipment, UEs.

18. An apparatus, comprising: at least one processor; and at least one memory comprising computer program code, the at least one memory and computer program code configured, with the at least one processor, to cause the apparatus at least to receive or collect trajectory information for at least one user equipment, UE, coupled with state information associated with the at least one user equipment, UE; receive or collect, from a network node, location information for the at least one user equipment, UE, and location information for one or more other user equipment, UEs; obtain a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location 39 information for the other user equipment, UEs; and provide a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation.

19. The apparatus according to claim 18, wherein it is determined that the at least one location has the predefined attribute when it is determined that the at least one location is an area of interest in which the correlation indicates that a predetermined number of the other user equipment, UEs, were in proximity of the at least one user equipment, UE, within the area of interest.

20. The apparatus according to claims 18 or 19, wherein the state information indicates a certain property of an object or user associated with the at least one user equipment, UE, about which the other user equipment, UEs, having been in proximity of the at least one user equipment, UE, should be informed.

21. The apparatus according to claim 20, wherein the certain property indicates that the object or user of the at least one user equipment, UE, poses a risk to objects or users associated with the other user equipment, UEs.

22. The apparatus according to any of claims 18-21, wherein the status indication comprises an alert provided to authorities or directly to the other user equipment, UEs, that have been in proximity of the at least one location using a public warning system, PWS.

23. The apparatus according to any of claims 18-22, wherein at least one of the obtaining of the correlation or the providing of the status indication is triggered when new trajectory information for the at least one user equipment is received or collected. 40

24. The apparatus according to any of claims 18-23, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to receive the trajectory information coupled with the state information of the at least one user equipment, UE, from an application running on the user equipment, UE.

25. The apparatus according to any of claims 18-24, wherein the state information comprises at least one of a time interval within which the state information is valid, a reason for the state, or a radius of applicability for the state.

26. The apparatus according to any of claims 18-25, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to continuously collect a location of user equipment, UEs, that are registered to a network associated with the network node.

27. The apparatus according to claim 26, wherein the collected location of the user equipment, UEs, is kept private or anonymous.

28. The apparatus according to claims 26 or 27, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to store the collected location of the user equipment, UEs, for a certain period of time.

29. The apparatus according to any of claims 26-28, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to use the collected location of the 41 user equipment, UEs, to build location statistics comprising at least one of a series of data points capturing past and present locations of the user equipment, UEs, or a time and number of user equipment, UEs, at a given location.

30. The apparatus according to any of claims 26-29, wherein the collected location is represented by a cell identifier, ID, that is then converted to a geographical area.

31. The apparatus according to any of claims 18-30, wherein, when providing the status indication, the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to: create one or more cell broadcast service, CBS, messages comprising at least one of a type of status indication to be communicated, a time associated with the state information, an impact related to the state information, and an action to be taken by those receiving the status indication; and provide the one or more cell broadcast service, CBS, messages to a cell broadcast center.

32. The apparatus according to any of claims 18-31, wherein the apparatus comprises at least one of a network side analytics server, network data analytics function, NWDAF, application function, AF, or central entity.

33. The apparatus according to any of claims 18-32, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to: receive, at a network side analytics server or central entity, from at least one other network side analytics server, data comprising trajectory 42 information for at least one user equipment, UE, coupled with state information of the user equipment, UE; merge the received data from said at least one other network side analytics server with data collected at the network side analytics server or central entity; decide, based on the merged data, whether a status indication should be provided; and when it is decided that the status indication should be provided, notify said at least one other network side analytics server that the status indication should be sent.

34. The apparatus according to any of claims 18-33, wherein the state information comprises at least one of: medical state information, risk state information, traffic state information, or other information of interest to the other user equipment, UEs.

35. An apparatus, comprising: means for receiving or collecting trajectory information for at least one user equipment, UE, coupled with state information associated with the at least one user equipment, UE; means for receiving or collecting, from a network node, location information for the at least one user equipment, UE, and location information for one or more other user equipment, UEs; means for obtaining a correlation of the trajectory information that is coupled with the state information of the at least one user equipment with the location information for the other user equipment, UEs; and means for providing a status indication associated to at least one location, wherein the at least one location is determined to have a predefined attribute based on the correlation. 43

36. A method, comprising: collecting, at a user equipment, UE, trajectory information of the user equipment, UE; receiving, from a trusted source, input of state information for the user equipment, UE, or for an object or user associated with the user equipment, UE; coupling the state information with the trajectory information of the user equipment, UE; and transmitting the coupled state information and trajectory information to a network side analytics server.

37. The method according to claim 36, wherein the collecting comprises collecting the trajectory information using location services of the user equipment.

38. The method according to claims 36 or 37, further comprising storing the trajectory information.

39. The method according to claim 38, wherein the storing of the trajectory information comprises storing a location of the user equipment, UE, periodically or when the user equipment has moved.

40. The method according to any of claims 36-39, wherein the collecting comprises collecting the trajectory information on different granularities.

41. The method according to any of claims 36-40, wherein the state information comprises at least one of: medical state information, risk state information, traffic state information, or other information of interest to other 44 user equipment, UEs, that are or have been in proximity of the user equipment, UE.

42. The method according to any of claims 36-41, wherein the collecting, receiving and coupling are performed by an application running on the user equipment, UE.

43. An apparatus, comprising: at least one processor; and at least one memory comprising computer program code, the at least one memory and computer program code configured, with the at least one processor, to cause the apparatus at least to collect trajectory information of the apparatus; receive, from a trusted source, input of state information for the apparatus or for an object or user associated with the apparatus; couple the state information with the trajectory information of the apparatus; and transmit the coupled state information and trajectory information to a network side analytics server.

44. The apparatus according to claim 43, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to collect the trajectory information using location services of the apparatus.

45. The apparatus according to claims 43 or 44, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to store the trajectory information. 45

46. The apparatus according to claim 45, wherein to store the trajectory information, the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to store a location of the apparatus periodically or when the apparatus has moved.

47. The apparatus according to any of claims 43-46, wherein the at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to collect the trajectory information on different granularities.

48. The apparatus according to any of claims 43-47, wherein the state information comprises at least one of: medical state information, risk state information, traffic state information, or other information of interest to other user equipment, UEs, that are or may have been in proximity of the user equipment, UE.

49. The apparatus according to any of claims 43-48, wherein the apparatus comprises an application configured to collect the trajectory information, to receive the input and to couple the state information with the trajectory information.

50. An apparatus, comprising: means for collecting trajectory information of the apparatus; means for receiving, from a trusted source, input of state information for the apparatus or for an object or user associated with the apparatus; means for coupling the state information with the trajectory information of the apparatus; and means for transmitting the coupled state information and trajectory information to a network side analytics server. 46

51. A computer readable medium comprising program instructions stored thereon for performing at least the method according to any of claims 1-17 or 36-42.