Patent Publication Number: US-2023156433-A1

Title: Monitoring objects capable of wireless communications

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 16/310,872 filed on Dec. 18, 2018, which itself is a 35 U.S.C. § 371 national stage application of PCT International Application No. PCT/IN2016/050190 filed on Jun. 20, 2016, the disclosures and contents of which are incorporated by reference herein in their entireties. 
    
    
     TECHNICAL FIELD 
     The invention relates to a method of monitoring objects capable of wireless communications, a device for monitoring objects capable of wireless communications, a corresponding computer program, and a corresponding computer program product. 
     BACKGROUND 
     In the art, there are methods available to detect proximity of devices based on technologies like Near-Field Communication (NFC), e.g., Radio-Frequency Identification (RFID), Bluetooth, 6LOWPAN (“IPv6 over Low Power Wireless Personal Area Networks”), and the like. 
     These technologies may be used for resolving issues relating to anti-theft, child security, providing reminders, and the like. Typically, the user has to configure a tracker application/device and the device(s) to be tracked, after which the tracker issues alarms if the tracked device(s) is/are not in proximity of the tracker, i.e., is/are outside a predetermined range from the tracker. For instance, a child may be provided with a tracked device in the form of a small radio transmitter, and the tracker device will sound an alarm if the child moves outside of a pre-defined area. 
     However, these prior art methods are inadequate when the set of devices in the proximity of the individual changes dynamically depending upon the environment and activities performed by the individual. The problem is being further aggravated due to the rapid increase of Internet-of-Things (IoT) devices like sensors, wearables, mobile phones, etc. 
     SUMMARY 
     An object of the present invention is to solve, or at least mitigate, this problem in the art and to provide an improved method of monitoring objects capable of wireless communications. 
     This object is attained in a first aspect of the invention by a method of monitoring objects capable of wireless communications. The method comprises detecting an activity performed by a user of a wireless communications device, acquiring information identifying an expected set of objects which are associated with the detected activity, determining whether at least one of the objects in the expected set is not in proximity of the wireless communications device, and if so notifying the user that at least one of the objects in the expected set is not in proximity of the wireless communications device. 
     This object is attained in a second aspect of the invention by a device for monitoring objects capable of wireless communications, the device comprising a processing unit and a memory. The memory contains instructions executable by the processing unit, whereby the device is operative to detect an activity performed by a user of a wireless communications device, acquire information identifying an expected set of objects which are associated with the detected activity, determine whether at least one of the objects in the expected set is not in proximity of the wireless communications device, and if so to notify the user that at least one of the objects in the expected set is not in proximity of the wireless communications device. 
     Hence, a device referred to as a tracker device, being for instance a mobile phone, a mobile terminal, a User Equipment (UE), or a smartphone of a user, detects that a certain activity is performed by the user. For instance, it may be detected that the user performs an activity such as “Go To Work” upon leaving her home premises during a time window specified for the activity (“Any Weekday, 07:00-08:00”). 
     To this end, a change in location of the user may, e.g., be detected using a Global Positioning System (GPS) of the tracker device (from a first location “on home premises” to a second location “off home premises”, or “leaving home premises”). 
     Thereafter, information is acquired identifying an expected set of objects which are associated with the detected activity, such as a wallet, a home key and a work pass. 
     It is noted that the objects are required to be equipped with wireless communications capability such as Near Field Communication (NFC) technology in the form of, e.g., a Radio-Frequency Identification (RFID) tag, a Bluetooth transmitter, or any other short-range radio transmitter, for communicating with the tracker device. 
     If it is determined that any one or more of the objects included in the expected set, e.g., the wallet, is not in proximity to the tracker device when the tracker device leaves the home premises of the user during the time window specified for the activity, as detected by means of, e.g., NFC-based communications between the tracker device and the objects, the user is notified accordingly. 
     Hence, if it is concluded that one or more of the objects in the expected set is not in proximity of the tracker device upon the user performing the activity (i.e., one or more of the objects are outside a proximity range of the tracker device), in this case leaving the home premises on a weekday between 7 and 8 AM, the user is advantageously notified accordingly. The user is thus made aware that she forgot one or more of the objects of the expected set associated with this particular activity and can go back into her house to pick up any forgotten object of the expected set before leaving for work. 
     In an embodiment, the user is notified by the tracker device emitting an audible sound, displaying a message, generating a haptic notification such as a vibration, etc. In an alternative embodiment, the tracker device may signal another wireless communications device that the user should be notified, for instance by requesting the user&#39;s smartwatch to vibrate, or requesting the user&#39;s car to not start the engine and/or display a message on the dashboard. 
     The method of monitoring the objects may be performed by the tracker device, a node of a communications network which is accessible by the wireless communications device, e.g., an application server, or one or more nodes of a cloud environment which is accessible by the wireless communications device. It is envisaged that a distributed solution may be provided, wherein the tracker device performs one or more steps of the method, while one or more cloud devices performs any further steps. 
     In a further embodiment, an actual set of objects which are in proximity of the wireless communications device is determined, and it is further determined whether at least one of the objects in the expected set is not in the actual set. If so, the user is notified accordingly. 
     In still a further embodiment, after or prior to notifying the user that one or more of the objects included in the expected set has not been detected as being in proximity to the tracker device, the user is queried as to whether any objects of the determined actual set are to be added to the expected set associated with the detected activity. If so, an updated expected set may be stored in a database comprising activities and corresponding expected sets of objects. 
     In yet another embodiment, after the user has been notified that one or more of the objects included in the expected set have not been detected as being in proximity to the tracker device, the user is queried as to whether one or more objects of the expected set associated with the detected activity are to be removed from the expected set to create an updated expected set for the detected activity. If so, an updated expected set may be stored in a database comprising activities and corresponding expected sets of objects. 
     In another embodiment, the activity which is performed by the user of the wireless communications device is detected based on at least one of, a combination, or a pattern, of: a location of the wireless communications device or a change thereof, a motion pattern of the wireless communications device or a change thereof, a date, a time of day, a calendar event, a communication event, sensor readings, and current weather conditions. 
     In still a further embodiment, a behaviour of the user is registered, and if it is concluded that the registered behaviour is a frequently occurring behaviour of the user, the registered behaviour is specified as an activity. In still another embodiment, a group of objects are registered as being carried by the user when the frequently occurring behaviour of the user is registered, the group of objects being specified as the expected set of objects associated with the specified activity. 
     Further provided is a computer program comprising computer-executable instructions for causing the device to perform steps according to an embodiment of the first aspect of the invention, when the computer-executable instructions are executed on a processing unit included in the device. 
     Further provided is a computer program product comprising a computer readable medium, the computer readable medium having an embodiment of the computer program embodied thereon. 
     Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to “a/an/the element, apparatus, component, means, step, etc.” are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention is now described, by way of example, with reference to the accompanying drawings, in which: 
         FIG.  1    illustrates a scenario where a user of a wireless communications device is monitored leaving the home premises for work, in accordance with embodiments of the invention. 
         FIG.  2    shows a flowchart illustrating an embodiment of a method of monitoring objects capable of wireless communications. 
         FIG.  3    shows a sequence diagram illustrating the embodiment of the method of monitoring objects capable of wireless communications according to  FIG.  2   , performed by the wireless communications device of the user. 
         FIG.  4    shows a sequence diagram illustrating an embodiment of the method of monitoring objects capable of wireless communications, performed by a remotely located network node. 
         FIG.  5    shows a sequence diagram illustrating another embodiment of the method of monitoring objects capable of wireless communications. 
         FIG.  6    shows a sequence diagram illustrating yet another embodiment of the method of monitoring objects capable of wireless communications. 
         FIG.  7    shows a sequence diagram illustrating still another embodiment of the method of monitoring objects capable of wireless communications. 
         FIG.  8    shows a sequence diagram illustrating still a further embodiment of the method of monitoring objects capable of wireless communications. 
         FIG.  9    shows a sequence diagram illustrating yet a further embodiment of the method of monitoring objects capable of wireless communications. 
         FIG.  10    shows a device for monitoring objects capable of wireless communications, in accordance with an embodiment of the invention. 
         FIG.  11    shows a device configured to monitor objects capable of wireless communications, in accordance with another embodiment of the invention. 
     
    
    
     DETAILED DESCRIPTION 
     The invention will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout the description. 
       FIG.  1    illustrates an exemplifying embodiment of the invention. Commonly, when an individual or user  10  leaves home  11  for work every morning, she will want to bring with her a set of objects that she will need during her work day, which set in this particular example is exemplified as comprising her wallet  12 , home key  13 , and work pass  14  to be used for entering work premises. 
     This set  15  of objects is referred to as the expected set of objects. That is, when the individual  10  with which the objects  12 ,  13 ,  14  are associated leaves home for work, she  10  is expected to carry the objects in the expected set  15  with her. 
     Individual  10  further carries a wireless communications device  16 , in  FIG.  1    exemplified as a smartphone  16 . This wireless communications device  16  is referred to as a tracker device. 
     It is noted that the objects  12 ,  13 ,  14  are required to be equipped with wireless communications capability. Such capability is typically already present at the work pass  14  which oftentimes utilizes Near Field Communication (NFC) technology in the form of, e.g., Radio-Frequency Identification (RFID) for communicating with a corresponding reader at the work premises. 
     Any objects not normally being equipped with wireless communications means, such as the wallet  12  and the key  13 , may be provided with wireless communications means such as an RFID tag, a Bluetooth or 6LoWPAN (“IPv6 over Low Power Wireless Personal Area Networks”) transmitter, or the like. 
     To this end, the objects  12 ,  13 ,  14  included in the expected set  15  are capable of communicating wirelessly with the tracker device  16 , in the form of a mobile phone, a smartphone, a mobile terminal, a UE, a tablet, a smartwatch, or any other appropriate wireless communications device, being equipped with a processing unit and a wireless communications interface. As discussed, the tracker device  16  may communicate with objects capable of wireless communications via any appropriate wireless technology, such as RFID, Bluetooth, 6LoWPAN, any cellular telecommunications technology (3G, 4G, 5G, etc), Wireless Local Area Network (WLAN)/WiFi, etc. It may further be envisaged that the tracker device  16  communicates with one or more remotely located network nodes, such as for instance an application server  17  or one or more nodes of a cloud environment which is/are accessible by the tracker device  16 , for fetching stored data, for storing data, or for having the network node perform any computing functions on behalf of the tracker device  16 . 
     Now, the expected set  15  of objects is associated with a particular activity in which the user  10  of the tracker device  16  is to partake, in this exemplifying embodiment an activity defined as “going to work”. Hence, the following associations are made at the tracker device  16  and/or the server  17 : 
     Expected_Set_of_Devices=“Wallet, Key, Work Pass”; 
     Expected_Set_of_Devices→Activity=“Go to Work” 
     The activity can be specified in many different ways, e.g., as a time window set to “Any Weekday, 07:00-08:00”. In this exemplifying embodiment, the activity may further specify a location criterion which is associated with the tracker device  16  used by the user  10 . 
     Similar to the above specified activity, the location criterion comprised in the activity can be specified in numerous ways depending on the particular implementation, in this exemplifying embodiment for instance as “Leave Home”. The tracker device  16  will accordingly detect indirectly whether at least one of the objects  12 ,  13 ,  14  in the expected set  15  complies with this predetermined location criterion by determining whether it complies with this predetermined location criterion itself. 
     Hence, the expected set  15  of objects may be associated with the specified activity as: 
     Expected_Set_of_Devices→Activity=“Go to Work”=[Location= 
     “Leave Home” AND Day=“Any Weekday” AND Time=“07:00-08:00”] 
     It is envisaged that there are numerous options for specifying an activity in which the user  10  is to partake. Further examples will be given hereinbelow. 
     Reference is further be made to the flowchart of  FIG.  2    for describing an embodiment of a method of monitoring objects capable of wireless communications. 
     In a first step S 101 , it is detected that a specified activity is performed by the user  10 . In this embodiment, the user  10  is considered to perform the activity upon leaving the home premises  11 , which is detected by means of the tracker device  16  leaving the home premises  11  during the time window specified for the activity (“Any Weekday, 07:00-08:00”). Hence, a change in location is detected, by detection a change in location of the tracker device  16  from a first location (“on home premises”) to a second location (“off home premises”). 
     Thereafter, in step S 102 , information is acquired identifying an expected set  15  of objects which are associated with the detected activity, in this case the wallet  12 , the home key  13 , and the work pass  14 . It can be envisaged that each object is given a unique numerical identifier. 
     If it is determined in step S 103  that any one or more of the objects included in the expected set  15 , e.g., the wallet  12 , is not in proximity to the tracker device  16  when the tracker device leaves the home premises  11  of the user  10  during the time window specified for the activity, the user  10  is notified thereof in step S 104 . The respective locations of the objects  12 ,  13 ,  14  and the tracker device  16  may be tracked using, e.g., Global Positioning System (GPS). Alternatively, it is envisaged that the location or position of tracker device  16  is determined using GPS, while the proximity of the objects  12 ,  13 ,  14  to the tracker device is detected using, e.g., NFC or any other short-range radio technology between the tracker device  16  and the objects  12 ,  13 ,  14 . 
     Hence, if it is concluded that one or more of the objects  12 ,  13 ,  14  in the expected set  15  are not in proximity of the tracker device  16  upon the user  10  performing the activity (i.e., one or more of the objects are outside a proximity range defined for the tracker device  16 ), in this case leaving the home premises  11  on a weekday between 7 and 8 AM, the user  10  is advantageously notified accordingly. The user  10  is thus made aware that she forgot one or more of the objects of the expected set  15  associated with this particular activity and can go back into her house  11  to pick up any forgotten object of the expected set  15  before leaving for work. 
     Typically, in case all the objects  12 ,  13 ,  14  in the expected set  15  are in proximity of the tracker device  16 , the user  10  is not notified, even though it could be envisaged that the user  10  is notified that all objects of the expected set  15  have been successfully detected. 
     In an embodiment, the user  10  is notified by tracker device  16  emitting an audible sound, displaying a message, generating a haptic notification such as a vibration, etc. In an alternative embodiment, the tracker device  16  may signal another wireless communications device that the user  10  should be notified, for instance by requesting the user&#39;s smartwatch to vibrate, or requesting the user&#39;s car to not start the engine and/or display a message on the dashboard. 
     Now, in the above-described embodiment, it may be envisaged that the tracker device  16  itself performs all steps S 101 -S 104  for monitoring the objects. Hence, the tracker device  16  detects in step S 101  that it is located outside of the home premises  11  (i.e., by detecting a change in its location from a first location to a second location as previously described) on a weekday at 07:00-08:00. 
     Thereafter, the tracker device  16  requests from a local data storage in step S 102  information identifying the expected set  15  of objects which are associated with the detected activity, and determines whether it is capable of communicating, e.g., by NFC, with all the objects  12 ,  13 ,  14  in the expected set  15  in step S 103 . Alternatively, the tracker device  16  may measure the strength of a signal submitted by the respective object, and if the signal strength is sufficient, i.e., exceeds a threshold value, the object is considered to be in proximity of the tracker device  16 . 
     If so, all the objects  12 ,  13 ,  14  of the expected set  15  are in proximity to the tracker device  16 . If not, the tracker device  16  notifies the user, and the user  10  is thus advantageously made aware that she forgot one or more of the objects of the expected set  15  associated with this particular activity and can go back into her house  11  to pick up any forgotten object of the expected set  15  before leaving for work. 
       FIG.  3    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to an embodiment of the invention. 
     The tracker device  16  has access to one or more specified activities of the user  10 , for instance fetched from a calendar app executing on the user&#39;s smartphone (exemplified here as being the tracker device  16 ). An alternative approach is to have the tracker device  16  learn activities of the user, and even to associate a learned expected set of objects with each learned activity. 
     For instance, after the tracker device  16  has (1) left the home premises on (2) a weekday at (3) 07:00-08:00 at a number of occasions, it will define the activity “Go To Work” based on these three criteria. Further, by repeatedly detecting a set of objects in its proximity at these occasions, the tracker device  16  will form the expected set of objects and associate the expected set with this activity. 
     Hence, a database may be maintained at the tracker device  16  specifying a number of activities and an expected set of objects associated with each of the activities: 
     
       
         
           
               
             
               
                 TABLE 1a 
               
             
            
               
                   
               
               
                 Database comprising activities and associated objects. 
               
            
           
           
               
               
               
            
               
                   
                 Activity 
                 Expected set of objects 
               
               
                   
                   
               
               
                   
                 Activity1 
                 Object1, Object2, Object3 
               
               
                   
                 Activity2 
                 Object1, Object4 
               
               
                   
                 Activity3 
                 Object5 
               
               
                   
                   
               
            
           
         
       
     
     As can be seen in Table 1a, at least one object is associated with each activity, thereby creating the expected set of objects. One and the same object may be associated with different activities. In the example Table, Object1 is comprised in the expected set both for Activity1 and Activity2. 
     In this particular exemplifying embodiment, the tracker device  16  detects in step S 101  its location, e.g., using GPS, or by detecting that it leaves a coverage area of the user&#39;s WLAN. If the location of the tracker device  16  changes from a first location (“on home premises”) to a second location (“off home premises”) on any weekday at 07:00-08:00, the user is considered to partake in this particular activity (“Go To Work”). It is assumed that this corresponds to Activity1 in Table 1a. 
     Thereafter, in step S 102 , the tracker device  16  acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device  16  maps the detected activity (“Activity1”) to the entries in Table 1a and concludes that the expected set  15  comprises Object1, Object2, and Object3, in this example corresponding to the wallet  12 , the home key  13 , and the work pass  14 , respectively. 
     Further, the tracker device  16  determines in step S 103  whether at least one of the objects  12 ,  13 ,  14  in the expected set is not in its proximity, upon the user performing the activity of going to work (“Activity1”). It is in this example assumed that the tracker device  16  communicates with the objects utilizing NFC. 
     As is illustrated in  FIG.  3   , the tracker device  16  determines whether the objects  12 ,  13 ,  14  are in its proximity, for instance by making an attempt to communicate with the objects, or by measuring the strength of a respective signal received from the objects. If the communication attempt is successful, or if the signal strength exceeds a threshold value, the object is considered to be in proximity of the tracker device  16 . Optionally, and indicator indicating “proximity” for each object can be stored in the database, e.g., in the form of a signal strength threshold defining “proximity” for that specific object. 
     In this particular example, the home key  13  and the work pass  14  are in proximity to the tracker device  16 , while the wallet  12  is not. 
     The tracker device  16  determines in step S 103  that the home key  13  (“Object2”) and the work pass  14  (“Object3”) are in proximity to the tracker device  16 , but that the wallet  12  (“Object1”) is not, thereby concluding from Table 1a that not all the objects in the expected set for Activity1 are in proximity to the tracker device  16 . 
     As a consequence, the tracker device  16  notifies the user  10  in step S 104  by emitting an audio alert to the user  10 , informing her about the lacking wallet  12 . As an alternative, or in addition, to emitting an audio alert, the tracker device  16  may optionally display a message notifying the user that an expected object is not in the user&#39;s  10  proximity, preferably also identifying the missing object by name (e.g., “You forgot your wallet.”). 
       FIG.  4    illustrates a sequence diagram where the method of monitoring is performed partly or fully at one or more remotely located network nodes, thereby facilitating a cloud solution. In  FIG.  4   , the network node(s) is/are embodied by the server  17 . 
     In this embodiment, the server  17  has access to one or more specified activities of the user  10 , for instance fetched from a calendar app executing on the user&#39;s smartphone (exemplified as being the tracker device  16 ) or from a cloud storage. In addition, sensor readings such as position or location data may be transmitted from the tracker device  16  to the server  17 . 
     To this end, a database may be maintained at the server  17  specifying a number of activities and an expected set of objects associated with each of the activities, as previously described with reference to Table 1a. 
     In this particular exemplifying embodiment, the server  17  detects in step S 101  the location of the tracker device  16  using GPS. If the tracker device  16  is leaving the user&#39;s  10  home premises  11  on any weekday at 07:00-08:00, the activity (“Go To Work”) is detected. Again, it is assumed that this corresponds to Activity1 in Table 1a. 
     Thereafter, in step S 102 , the server  17  acquires information identifying an expected set of objects which are associated with the detected activity, from the stored database. To this end, the server  17  maps the detected activity (“Activity1”) to the entries in Table 1a and concludes that the expected set  15  comprises Object1, Object2 and Object3, in this example corresponding to the wallet  12 , the home key  13 , and the work pass  14 , respectively. 
     Even though it may be envisaged that the server  17  communicates directly with the objects capable of wireless communication, i.e., the wallet  12 , the home key  13  and the work pass  14 , for determining their proximity to the tracker device  16  based on, e.g., GPS readings, it is in this example assumed that the tracker device  16  communicates with the respective object utilizing, e.g., NFC, and provides resulting information to the server  17 . In case the server  17  would communicate directly with the objects  12 ,  13 ,  14 , the method may be undertaken in its entirety “in the cloud”, either by the server  17  solely or in cooperation with other remote nodes. 
     Hence, the server  17  acquires in step S 103   a  information as to which objects actually are in proximity to the tracker device  16  upon the user performing the activity of going to work (“Activity1”). 
     As is illustrated in  FIG.  4   , the tracker device  16  concludes that the home key  13  and the work pass  14  are in proximity to the tracker device  16 , but that the wallet  12  is not, which the tracker device  16  reports accordingly to the server  17 . 
     The server  17  determines in step S 103  that the home key  13  (“Object2”) and the work pass  14  (“Object3”) are in proximity to the tracker device  16 , but that the wallet  12  (“Object1”) is not, thereby concluding from Table 1a that not all the objects in the expected set for Activity1 are in proximity to the tracker device  16 . 
     As a consequence, the server  17  sends a notification to the user  10  via the tracker device  16  in step S 104 , whereby the tracker device  16  emits an audio alert to the user  10  advantageously informing her about her lacking wallet  12 . 
     Again, as previously discussed, in case the server  17  would communicate directly with the objects  12 ,  13 ,  14 , and notify the user  10  via, e.g., her smartwatch (not shown), the tracker device  16  need not take any active part in the monitoring, not even causing an audio alert. 
       FIG.  5    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to another embodiment. However, it is noted that this embodiment may also be implemented by a remotely located network node, such as the server  17 . 
     In this embodiment, all objects which are in proximity to the tracker device  16  are determined upon detecting that the user  10  partakes in a specified activity. In the previously described embodiments of  FIGS.  2 - 4   , only the objects comprised in the expected set are detected as being in proximity to the tracker device  16 . Accordingly, as soon as all objects  12 ,  13 ,  14  of the expected set have been detected, there is no need to continue and detect any further proximate objects. 
     The objects determined to be in proximity to the tracker device  16  are referred to as an actual set of objects. 
     As in the previous embodiment, the tracker device  16  detects in step S 101  its location, e.g., using GPS. If the tracker device  16  is leaving the user&#39;s  10  home premises  11  on any weekday at 07:00-08:00, the user is considered to partake in the activity (“Go To Work”). It is assumed that this corresponds to Activity1 in Table 1 a. 
     Thereafter, in step S 102 , the tracker device  16  acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device  16  maps the detected activity (“Activity1”) to the entries in Table 1a and concludes that the expected set  15  comprises Object1, Object2 and Object3, in this example corresponding to the wallet  12 , the home key  13 , and the work pass  14 , respectively. 
     Further, the tracker device  16  determines in step S 103   b  the actual set of objects being in proximity of the tracker device  16 . As is illustrated in  FIG.  5   , the tracker device  16  determines that the home key  13  and the work pass  14  are in proximity to the tracker device  16 , but that the wallet  12  is not. 
     In this embodiment, the tracker device  16  further determines that a smartwatch  18  (“Object4”) is in proximity of the tracker device  16 , for instance by signalling based on Bluetooth or even via a Wireless Local Area Network (WLAN), commonly referred to as “WiFi”. 
     The objects determined to be in the actual set in step S 103   b  are thus the home key  13 , the work pass  14 , and the smartwatch  18 , i.e., Object2, Object3, and Object4. 
     Next, in step S 103 , the tracker device  16  determines whether any object in the expected set is not in the actual set. With reference to Table 1 a, the wallet  12  (“Object1”) is not in the actual set and thus not in proximity to the tracker device  16 , upon the user performing the activity of going to work (“Activity1”). 
     As a consequence, the tracker device  16  notifies the user  10  in step S 104  by emitting an audio alert and/or displaying a notification to the user  10 , advantageously informing her about the lacking wallet  12 . 
       FIG.  6    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to still another embodiment. However, it is noted that this embodiment may also be implemented at a remotely located network node, such as the server  17 . 
     As in the embodiment of  FIG.  5   , all objects being in proximity to the tracker device  16  upon detection of the user  10  performing a specified activity are determined, thereby forming an actual set. 
     However, in addition to the steps of the embodiment described with reference to  FIG.  5   , after (or before) having notified the user  10  in step S 104  that the wallet  12  included in the expected set has not been detected as being in proximity to the tracker device  16 , the user is queried in step S 105  as to whether any objects of the determined actual set are to be added to the expected set which is associated with the detected activity. 
     The user responds in step S 106 , in this particular example with the response that the smartwatch  18  is to be added to the expected set for Activity1. 
     The tracker device  16  will thus update its database of Table 1a in step S 107 , resulting in updated Table 1b: 
     
       
         
           
               
             
               
                 TABLE 1b 
               
             
            
               
                   
               
               
                 Updated database comprising activities and associated objects. 
               
            
           
           
               
               
               
            
               
                   
                 Activity 
                 Expected set of objects 
               
               
                   
                   
               
               
                   
                 Activity1 
                 Object1, Object2, Object3, Object 4 
               
               
                   
                 Activity2 
                 Object 1, Object4 
               
               
                   
                 Activity3 
                 Object3 
               
               
                   
                   
               
            
           
         
       
     
       FIG.  7    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to still a further embodiment. However, it is noted that this embodiment may also be implemented at a remotely located network node, such as the server  17 . 
     As in the embodiment of  FIG.  5   , all objects being in proximity to the tracker device  16  upon detection of the user  10  performing a specified activity are determined, thereby forming an actual set. It is noted that in this embodiment, it is not necessary to determine an actual set. Rather, steps S 108  and S 109  as will be described in the following may follow on step s 104  in either of the embodiments in  FIGS.  3  and  4   . 
     Now, in addition to the steps of the embodiment of  FIG.  5   , after having notified the user  10  in step S 104  that the wallet  12  included in the expected set has not been detected as being in proximity to the tracker device  16 , the user  10  is given the opportunity in step S 108  to indicate as to whether one or more objects of the expected set associated with the detected activity are to be removed from the expected set to create an updated expected set for the detected activity. 
     In this example, the user  10  indicates that the wallet  12  (“Object1”) is to be removed from the expected set illustrated in Table 1a, wherein the tracker device  16  updates its database of Table 1a in step S 109 , resulting in updated Table 1c: 
     
       
         
           
               
             
               
                 TABLE 1c 
               
             
            
               
                   
               
               
                 Updated database comprising activities and associated objects. 
               
            
           
           
               
               
               
            
               
                   
                 Activity 
                 Expected set of objects 
               
               
                   
                   
               
               
                   
                 Activity1 
                 Object2, Object3 
               
               
                   
                 Activity2 
                 Object1, Object4 
               
               
                   
                 Activity3 
                 Object5 
               
               
                   
                   
               
            
           
         
       
     
     It is noted that the embodiments described in  FIGS.  6  and  7    may be combined. That is, the user may add objects of the determined actual set, as well as remove objects from the expected set, wherein the tracker device  16  will update its database accordingly, as has been described. 
       FIG.  8    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to yet another embodiment. However, it is noted that this embodiment may also be implemented at a remotely located network node, such as the server  17 . 
     As in the embodiments of  FIGS.  5 - 7   , all objects being in proximity to the tracker device  16  upon detection of the user  10  performing a specified activity is determined, thereby forming an actual set. 
     This embodiment is advantageous since it facilitates machine learning, as will be described in detail in the following. 
     
       
         
           
               
             
               
                 TABLE 2a 
               
             
            
               
                   
               
               
                 Database comprising activities and associated objects. 
               
               
                 Assuming for instance the scenario of Table 2a in the below: 
               
            
           
           
               
               
               
            
               
                   
                 Activity 
                 Expected set of objects 
               
               
                   
                   
               
               
                   
                 Activity1 
                 — 
               
               
                   
                 Activity2 
                 Object1, Object4 
               
               
                   
                 Activity3 
                 Object5 
               
               
                   
                   
               
            
           
         
       
     
     In this exemplifying embodiment, the tracker device  16  again has access to one or more specified activities of the user  10 , for instance fetched from a calendar app executing on the user&#39;s smartphone (exemplified here as being the tracker device  16 ), or learned by means of machine learning as previously discussed. 
     However, in this embodiment, no expected set of objects has yet been recorded and associated with newly learned Activity1 (“Go To Work”), which may be learned by the tracker device  16  detecting that it leaves the home premises between 7 and 8 AM on a weekday at a number of occasions. 
     Again, the tracker device  16  detects in step S 101  its location using, e.g., GPS. If the tracker device  16  is leaving the user&#39;s  10  home premises  11  on any weekday at 07:00-08:00, the user is considered to partake in new Activity1, which is learned by the tracker device  16  and added to Table 2a. 
     Thereafter, in step S 102 , the tracker device  16  acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device  16  maps the detected activity (“Activity1”) to the entries in Table 2a and concludes that expected set associated with Activity1 not yet comprises any objects. 
     Further, the tracker device  16  determines in step S 103   b  the actual set of objects being in proximity of the tracker device  16 . As is illustrated in  FIG.  8   , the tracker device  16  concludes that the wallet  12 , the home key  13 , and the work pass  14 , are in proximity to the tracker device  16 . 
     Now, in step S 103   c , the tracker device  16  advantageously associates the actual set of objects  12 ,  13 ,  14  with the detected activity as a new expected set of objects, and thus updates Table 2a, resulting in Table 2b: 
     
       
         
           
               
             
               
                 TABLE 2b 
               
             
            
               
                   
               
               
                 Updated database comprising activities and associated objects. 
               
            
           
           
               
               
               
            
               
                   
                 Activity 
                 Expected set of objects 
               
               
                   
                   
               
               
                   
                 Activity1 
                 Object1, Object2, Object3 
               
               
                   
                 Activity2 
                 Object1, Object4 
               
               
                   
                 Activity3 
                 Object5 
               
               
                   
                   
               
            
           
         
       
     
     Advantageously, with this embodiment, machine learning can be applied to record activities and objects in the database as illustrated in Tables 2 and b, and to create appropriate associations between expected sets and corresponding activities. 
     In an embodiment, machine learning such as association rule mining and/or frequent itemsets (discussed, e.g., in Chapter 6 of “Mining of Massive Datasets” by J. Leskovec, A. Rajaraman, and J. D. Ullman), is used to deduce an expected set of devices to be associated with a particular activity. 
     For instance, a tracker device  16  such as a mobile phone or smartphone of a user, possibly in combination with further sensing devices, is used for building a database of activities and corresponding expected sets of devices to be associated with the activities. 
     In the present example, the tracker device  16  registers that when the user leaves at home during a weekday at 07:00-08:00, she usually brings her wallet  12 , home key  13 , and work pass  14 . Upon having registered that
         (1) The user leaves at home during a weekday at 07:00-08:00, and that   (2) The user usually brings her wallet, home key and work pass at these occasions,
 
at repeated occasions—such as at five different occasion—the tracker device  16  (or some other node such as the server  17  and/or a cloud service), may conclude that
   (1) The user leaving home during a weekday at 07:00-08:00 is a commonly or routinely performed activity, which is registered as an activity “Go To Work” (possibly giving the user a chance the name/define the activity), and that   (2) The user usually brings her wallet, home key, and work pass, upon performing this activity. Thus, the wallet, home key, and work pass, are registered as an expected set of devices to be associated with the activity “Go To Work”.       

     When deducing the expected set, the tracker device  16  may for instance stipulate that any object to be included in the expected set must fulfill a certain probability threshold, such as having been carried by the user at 80% of the occasions when the user performed the activity. 
     Hence, a behaviour (“leave home on a weekday at 07:00-08:00”) of the user is registered, and if it is concluded that the registered behaviour is a frequently occurring behaviour of the user (e.g., having occurred more than 5 times), the registered behaviour is registered as an activity (“Go To Work”). 
     Further, a group of objects (“wallet, home key, work pass”) is registered as being carried by the user when the frequently occurring behaviour (“leave home on a weekday at 07:00-08:00”) of the user is registered, the group of objects being specified as the expected set of objects associated with the specified activity (“Go To Work”). 
     It is understood that a great number of different activities and a correspondingly great number of expected sets to be associated with the different activities may be identified by the tracker device  16  and registered in the database. 
       FIG.  9    illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device  16  according to still another embodiment. However, it is noted that this embodiment may also be implemented at a remotely located network node, such as the server  17 . 
     As in the embodiments of  FIGS.  5 - 8   , all objects being in proximity to the tracker device  16  are detected upon detection of the user  10  performing a specified activity, thereby forming an actual set. 
     However, in addition to the steps of the embodiment of  FIG.  6   , after having determined the actual set of objects  12 ,  13 ,  14  in step S 103   b , the tracker device  16  queries the user  10  in step S 103   d  whether the objects  12 ,  13 ,  14  of the determined actual of objects are to be stored as a new expected set for the detected activity. 
     The user  10  responds to the query in step S 103   e , for instance by indicating on a screen of the tracker device  16  (being, e.g., a smartphone) whether all determined objects of the actual set are to be associated with the detected activity as the new expected set, or whether a subset of the objects of the actual set is to be associated with the detected activity as the new expected set, in response to which the tracker device  16  advantageously associates the objects  12 ,  13 ,  14  indicated by the user  10  with the detected activity as the new expected set of objects, and thus updates Table 2a, resulting in Table 2b. 
     The invention has mainly been described above with reference to a few embodiments. However, a number of scenarios may be envisaged, where a common feature is that a user is automatically notified of the device(s) she needs at different activities in different times and situations. 
     1. A doctor is called upon to deal with an activity in the form of an emergency situation where a patient experiences high blood sugar (hyperglycaemia). The expected set associated with this activity may thus comprise (a) a dose of insulin and (b) an injection device (e.g., being RFID-tagged). If the doctor has forgotten to pack the insulin and injection upon leaving his clinic, his mobile phone detects the absence and raises an alarm, so that the doctor realizes this before he leaves his clinic. 
     2. When going to court, a lawyer is expected to bring an important case file. The case file may be RFID-tagged to ensure that his smartwatch will sound an alarm if he leaves his office for the court proceedings without the case file. 
     3. A mother wants to go out with her family for a picnic. She wants to ensure that she carries the high resolution handy-cam to capture the beautiful moments during their time out. In case of bad weather, she will also want to bring a garden umbrella. The activity may thus specify a date and time of the picnic, and further weather conditions acquired for instance from a weather forecast. Hence, if she leaves home at the specified date and time, and the forecast predicts bad weather, her smartphone will notify her if she does not bring the handy-cam and/or the umbrella. 
     4. It is detected that the user arrives at home, and the actual set of objects is detected. Typically, this is the same set of objects as the set of objects which the user carried when leaving home. If an object is missing, the user may be notified that she has forgotten an object, or that an object has been stolen. 
     Even further, the activity which is performed by the user of the wireless communications device may be detected based on at least one, a combination, or a pattern, of: a location of the wireless communications device or a change thereof, a motion pattern of the wireless communications device or a change thereof, a date, a time of day, a calendar event, a communication event, or even current weather conditions. To this end, the behaviour and movements of the user, for instance the user leaving her home or her office, or whether the user is out running and suddenly stops (or starts) running, time windows, such as a particular time of the day, or a particular weekday derived for instance from a meeting event or itinerary information in a digital calendar, or even sensor information, where for instance the user&#39;s smartwatch alerts the user in case skin temperature measured by an IoT-type temperatures arranged in a garment of the user exceeds a threshold value, the activity being defined e.g. as “User Catching Fever”. 
     With reference to  FIG.  10   , the steps of the method performed by the tracker device  16 , or the server  17 , or a distributed cloud solution, according to embodiments are in practice performed by a processing unit  20  embodied in the form of one or more microprocessors arranged to execute a computer program  21  downloaded to a suitable storage medium  22  associated with the microprocessor, such as a Random Access Memory (RAM), a Flash memory or a hard disk drive. The processing unit  20  is arranged to cause the device  16  to carry out the method according to embodiments when the appropriate computer program  31  comprising computer-executable instructions is downloaded to the storage medium  32  and executed by the processing unit  30 . The storage medium  32  may also be a computer program product comprising the computer program  31 . Alternatively, the computer program  31  may be transferred to the storage medium  32  by means of a suitable computer program product, such as a Digital Versatile Disc (DVD) or a memory stick. As a further alternative, the computer program  31  may be downloaded to the storage medium  32  over a network. The processing unit  30  may alternatively be embodied in the form of a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc. 
       FIG.  11    illustrates a device  16  configured to monitor objects capable of wireless communication. The device  16  comprises detecting means  30  adapted to detect an activity performed by a user of a wireless communications device, acquiring means  31  adapted to acquire information identifying an expected set of objects which are associated with the detected activity, and determining means  32  adapted to determine whether at least one of the objects in the expected set is not in proximity of the wireless communications device. Further, the device  16  comprises notifying means  33  adapted to notify the user that at least one of the objects in the expected set is not in proximity of the wireless communications device 
     The device  16  may further comprise a communications interface for receiving and providing information, and further a local storage for storing data, and may (in analogy with that previously discussed) be implemented by a processor embodied in the form of one or more microprocessors arranged to execute a computer program downloaded to a suitable storage medium associated with the microprocessor, such as a RAM, a Flash memory or a hard disk drive. 
     As is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the invention, as defined by the appended patent claims.