Identifying node devices in an environment

Abstract

A mechanism for identifying which node devices are within a field of view of a control device. A location of each node device is predicted during a scanning procedure performed by the control device. This information is used, together with orientation information of the field of view and location information of the control device, to predict which node devices fall within the field of view.

Description

[0001] Identifying node devices in an environment

[0002] FIELD OF THE INVENTION

[0003] The present invention relates to the field of device communications, and in particular to the identification of node devices by a control device.

[0004] BACKGROUND OF THE INVENTION

[0005] There is an increasing interest in networks, systems or arrangements of devices, such as lighting devices. One example is a lighting systems that is used to provide artificial light in a wide variety of environments, such as in domestic, industrial and / or public settings.

[0006] Systems of devices commonly comprise a plurality of (node) devices. There is a desire to facilitate configuration and / or commissioning of the plurality of (node) devices, and it is typical for a control device to be configured or designed for this task. An existing technique for configuring the plurality of devices is to configure each (node) device in turn. A (node) device will indicates when it its turn for configuration, e.g., by flashing, blinking or dimming a light emitting element (e.g., for a lighting device, the lighting element of the lighting device). The control device, of an operator thereof, will identify the flashing / blinking / dimming to identify which device is to be configured - before performing one or more configuration tasks with the identified device.

[0007] Examples of configuration tasks to be performed for a device include: defining a location of the device in space; defining to which group(s) and / or sub-group(s) of devices the device belongs; defining which device(s) is / are to operate or be controlled simultaneously; and so on. Typically, configuration tasks are adapted to configure a device for distributed control during use of the device.

[0008] US2024078805A1 discloses an augmented reality (AR) node location and activation technique for use in an AR system in a process plant or other field environment quickly and easily detects an AR node in a real-world environment and is then able to activate an AR scene within the AR system.

[0009] US2015310664A1 discloses a capability for managing a representation of a smart environment, which is configured to support augmented reality (AR)-based management of a representation of a smart environment, which may include AR-based generation of a representation of the smart environment, AR-based alignment of the representation of the smart environment with the physical reality of the smart environment, and the like.

[0010] There is an ongoing desire to increase the ease and speed of configuring devices.

[0011] SUMMARY OF THE INVENTION

[0012] The invention is defined by the claims.

[0013] According to examples in accordance with an aspect of the invention, there is provided a computer-implemented method for identifying one or more node devices. The computer-implemented method comprises: scanning an environment, using a control device, for one or more node devices in the environment to generate a node device list, the node device list identifying each node device and a relative location of the node device within the environment; identifying an orientation of a field of view of the control device; identifying a location of the control device within the environment; and processing the identified orientation; the identified location of the control device and the node device list to identify which, if any, node devices are within the field of view of the control device.

[0014] Thus, at least initial predicted locations for each node device are established during a scanning procedure performed by the control device. These initial predicted locations are used to establish or predict which node devices fall within the field of view of the control device. In this way, a list of node devices can be filtered to identify only the node devices within a field of view of the control device (e.g., in front of the control device).

[0015] The proposed approach facilitates the identification of node devices in front of the control device, which can be exploited, for example, to trigger only node devices in the field of view to output a user-perceptible output (e.g., a flashing light) during a configuration or commissioning procedure. This avoids or reduces a likelihood that the control device (or operator thereof) will need to rotate in order to identify a triggered node device during the configuration or commissioning procedure, thereby increasing a speed of configuring and commissioning devices.

[0016] In the context of the present disclosure, a node device is any device whose location or device groupings (e.g., for group operations) can be defined by a control device. Examples of node devices include luminaires or lighting elements within an environment to be illuminated. In some examples, the scanning the environment, using the control device, comprises: obtaining, for each of a plurality of different locations of the control device within the environment, a respective distance-responsive measure for each node device, each distance-responsive measure being a measure of distance between the node device and the control device; and processing the distance-responsive measures of each node device to predict a relative location of the node device within the environment.

[0017] In this way, a distance-responsive measure may be iteratively sampled as the control device is moved or moves around the environment. This facilitates, for each node device, identification of locations at which the control device is nearer (or further) from the node device. This approach increases an accuracy of estimating the location of each node device, e.g., as a trilateration approach could be used, and / or provides a simple and resourceefficient approach for associating a location with the node device.

[0018] In at least one example, the processing the distance-responsive measures comprises, for each node device: constructing a heat map of the obtained distance-responsive measures for the node device; and predicting a relative location of the node device by processing the heat map.

[0019] By way of example, predicting the relative location of the node device by processing the heat map may comprise identifying a heat center of the heat map as the location of the node device. This approach provides a mechanism for effectively performing a multilateration approach for identifying or predicting the location of the node device within a co-ordinate system in which the location of the control device is established. This provides an easy approach.

[0020] The step of processing the distance-responsive measures of each node device may comprise defining the location of control device, for which the obtained distance responsive measure indicates a shortest distance, as the relative location of the node device. This approach provides a resource-efficient mechanism for establishing or approximating the relative location of the node device.

[0021] In some examples, each distance-responsive value is a measure of signal strength between the control device and the respective node device. This approach facilitates the exploitation of existing communication(s) between the control device and the node devices in order to identify or predict the location of each node device. Thus, a more resource-efficient approach for determining a location of each node device is achieved. The measure of signal strength may comprise a received signal strength indicator. This approach provides a reliable mechanism for defining a distance-responsive measure for each node device.

[0022] In some examples, the obtaining, for each of a plurality of different locations of the control device within the environment, a respective distance-responsive measure for each node device comprises iteratively sampling a distance-responsive parameter, for each node device, at predefined time or distance intervals during a movement of the control device within the environment.

[0023] In other words, there may be a regular sampling of the distance-responsive parameter for each node device as the control device is moved within the environment. This provides a more uniform distribution or dispersion of the distance-responsive measures across the environment, for more accurate identification or prediction of the location of each node device.

[0024] In at least one example, the processing the identified orientation; the identified location of the control device and the node device list comprises filtering the node device list using the identified orientation, the identified location of the control device and the node device list.

[0025] In some examples, the control device comprises an augmented reality display; and the field of view is a field of view of the environment visually represented in the augmented reality display.

[0026] In some examples, the control device comprises a 3D scanning system configured to perform a scanning procedure, for building a model of the environment, as the control device is moved about the environment; and the scanning for node devices is performed during the scanning procedure performed by the 3D scanning system.

[0027] This provides a more time efficient mechanism for predicting the location of each node device for the purposes of performing the proposed method, as it is performed alongside another, pre-existing technique that requires movement of the control device about the environment.

[0028] The computer-implemented method may further comprise triggering, using the control device, a node device, predicted to be within the field of view of the control device, to emit a user-perceptible signal; receiving a user input, responsive to the user-perceptible signal, that indicates a location of the triggered node device; and updating the location of the triggered node device using the user input. In this way, the proposed method can be integrated into a configuration and / or commissioning procedure for updating the relative location of the node device(s). In some examples, the user input may alternatively and / or additionally provide other forms of information about the triggered node device (e.g., an identity of a group to which the node device belongs, an identity of the type of device or control information for the node device), which can be used to update and / or define stored information about the triggered node device.

[0029] There is also provided a computer program product comprising computer program code means which, when executed on a computing device having a processing system, cause the processing system to perform all of the steps of any herein disclosed (computer-implemented) method.

[0030] There is also provided a control device for identifying one or more node devices. The control device comprises a processing system configured to: scan an environment, using a communications module, for one or more node devices in the environment to generate a node device list, the node device list identifying each node device and a relative location of the node device within the environment; identify an orientation of a field of view of the control device; identify a location of the control device within the environment; and process the identified orientation; the identified location of the control device and the node device list to identify which, if any, node devices are within the field of view of the control device.

[0031] In some examples, the control device further comprises an augmented reality display, wherein the field of view is a field of view of the environment visually represented in the augmented reality display.

[0032] The skilled person appropriately skilled in the art would be readily capable of modifying the control device to perform the functions of any herein disclosed (computer- implemented) method, and vice versa.

[0033] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter.

[0034] BRIEF DESCRIPTION OF THE DRAWINGS

[0035] For a better understanding of the invention, and to show more clearly how it may be carried into effect, reference will now be made, by way of example only, to the accompanying drawings, in which:

[0036] Fig. 1 illustrates an environment in which embodiments may be employed; Fig. 2 is a flowchart illustrating a proposed method;

[0037] Fig. 3 is a flowchart illustrating an example step for the proposed method;

[0038] Fig. 4 is a flowchart illustrating an alternative step for the proposed method;

[0039] Fig. 5 is a heat map for a device node; and

[0040] Fig. 6 is a flowchart illustrating a further proposed method.

[0041] DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The invention will be described with reference to the Figures.

[0043] It should be understood that the detailed description and specific examples, while indicating exemplary embodiments of the apparatus, systems and methods, are intended for purposes of illustration only and are not intended to limit the scope of the invention. These and other features, aspects, and advantages of the apparatus, systems and methods of the present invention will become better understood from the following description, appended claims, and accompanying drawings. It should be understood that the Figures are merely schematic and are not drawn to scale. It should also be understood that the same reference numerals are used throughout the Figures to indicate the same or similar parts.

[0044] The invention provides a mechanism for identifying which node devices are within a field of view of a control device. A location of each node device is predicted during a scanning procedure performed by the control device. This information is used, together with orientation information of the field of view and location information of the control device, to predict which node devices fall within the field of view.

[0045] In the context of the present disclosure, a location may be a location defined with respect to a predefined co-ordinate system. The precise data structure and format of the location will, of course, depend upon the localization system or technique(s) employed, which may vary in different embodiments. A model of an environment may be built and / or defined in this predefined co-ordinate system.

[0046] Similarly, orientations may be defined as a (relative) orientation within the pre-defined co-ordinate system.

[0047] Figure 1 illustrates a plan view of an environment 10 in which embodiments may be employed for improved contextual understanding of the proposed disclosure.

[0048] The environment 10 comprises a plurality of node devices 111, 112, e.g., luminaires or lighting devices, which are here represented as circles. The environment also includes a control device 120 for defining an operation of each node device, e.g., for configuring or commissioning each node device, which is here represented as a square.

[0049] The node devices 111, 112 and the control device 120 are configured to communicate with one another, e.g., wirelessly. Thus, the node device and the control device may each comprise a communications module, such as a wireless transceiver.

[0050] Suitable wireless communication protocols that may be used to perform such communications include: an infrared link, Zigbee, Bluetooth, a wireless local area network protocol such as in accordance with the IEEE 802.11 standards family, a 2G, 3G, 4G or 5G telecommunication protocol, and so on. Other formats, including proprietary formats, will be readily apparent to the person skilled in the art.

[0051] As previously explained, to perform a commissioning or configuring procedure, a control device will typically send a request to a node device 111, 112 to identify itself, e.g., by a user-perceptible output such as a flashing / blinking / dimming of a light. The control device (or operator thereof) will identify this user-perceptible output to locate the relative position of the node device with respect to: the control device; a model of the environment and / or a predefined co-ordinate system. In this way, it is possible to define a relative location of the node device, e.g., within a predefined co-ordinate system.

[0052] It has been recognized that if the node device (providing the visual indication) is located outside of a field of view 125 of the control device 120 (or operator thereof), then identification of the visual indication is significantly slowed, e.g., as the device and / or operator must turn around to identify the node device. Cumulatively, this can significantly impact a length of time taken to commission all node devices in the plurality of node devices.

[0053] As a working example, the control device may comprise an augmented reality system for an operator of the control device. The augmented reality system may provide a field of view of the environment (e.g., at an augmented reality display). It is possible for an operator to identify, via the augmented reality system, a location within the environment visually represented in the augmented reality display. This can be exploited to facilitate accurate identification of the location of a node device that is outputting a user-perceptible output. If the operator needs to rotate themselves (e.g., and / or the control device) to adjust the field of view in order to identify the node device providing a visual indication, then this results in a significant delay in identifying the relative location of the node device(s).

[0054] The location of control device with respect to a / the predefined co-ordinate system may be known (i.e., a location within the environment). By determining the relative location of a node device with respect to the control device, then the location of said node device with respect to the model of the environment, or predefined co-ordinate system, can be trivially determined.

[0055] The present disclosure provides a technique for identifying a provisional location of each node device within the environment. This is exploited to perform a prediction of those node devices falling within the field of view of the control device, whose position within the environment is also known. In turn, this can be used to restrict the device triggered to emit a user-perceptible signal to only those devices predicted to fall within the field of view of the control device. This can significantly reduce a time taken for the control device and / or operator to identify the triggered node device.

[0056] Figure 2 is a flowchart illustrating a proposed computer-implemented method 200 for identifying one or more node devices. The method is performed by the control device 200.

[0057] The method 200 comprises a step 210 of scanning the environment, using the control device, for one or more node devices in the environment to generate a node device list. The node device list identifying each node device and a relative location of the node device within the environment. In this way, a provisional (i.e., initial or preliminary) location for each node device is established by the control device during a scanning procedure.

[0058] Step 210 may comprise, for instance, receiving a communication from each node device (within range) providing its identity, e.g., its MAC address or similar.

[0059] Thus, the control device may comprise a scanning system for performing step 210. The scanning system may, for instance, comprise a communications module - e.g., a wireless transceiver for making and receiving wireless communications.

[0060] The method 200 also comprises a step 220 of identifying an orientation of a field of view of the control device. This can be readily achieved using an accelerometer, inclinometer or magnetometer (e.g., integrated into a MEMS system or a Hall effect sensor). It is possible to compare a value obtained by such an element to one or more reference or calibration values that define a baseline orientation for the field of view, e.g., with reference to an environment.

[0061] Thus, the control device may comprise an orientation determining system for identifying an orientation of the field of view of the control device. Orientation determining systems are well known, for instance, in the field of AR or MR systems.

[0062] The method 200 also comprises a step 230 of identifying a location of the control device within the environment. This can be achieved using any one of a variety of positioning systems, such as a Wi-Fi ® positioning system, a Lighthouse tracking system, a simultaneous localization and mapping system or even a satellite navigation system. Other approaches are known in the art, for instance, some device tracking systems employ a time- of-flight sensor and IMU sensor (e.g., accelerometer) to detect the coordinates of a device in the physical environment and track movement. Thus, the control device may comprise a positioning system for identifying a location of the control device within the environment.

[0063] The method 200 also comprises a step 240 of processing the identified orientation; the identified location of the control device and the node device list to predict which, if any, node devices are within the field of view of the control device. It will be appreciated that, once the relative locations of the node devices, the control device and the orientation of the field of view is known, then it is trivial to predict which node devices fall within the field of view using geometrical techniques. Such approaches would be readily apparent to the skilled person.

[0064] The shape and / or size of the field of view may be predetermined or predefined (e.g., within the control device itself), such that identification of the relative volume occupied by the field of view (and therefore which node devices fall within this volume) can be trivially determined. In some examples, the shape and / or size of the field of view may be adjusted or modified (e.g., expanded by an operator of the control device) - which adjustment may also be taken into account in step 240 where appropriate.

[0065] As a working example, the field of view may represent a region in front of the control device, e.g., having a range of 180° about a central axis extending from the control device.

[0066] As another working example, the field of view may represent a volume of the environment that is visually represented in an augmented reality display of the control device.

[0067] As another working example, the field of view may represent a volume of the environment that is captured by a camera carried or of the control device.

[0068] Step 240 may, for instance, comprise filtering the node device list using the identified orientation, the identified location of the control device and the node device list.

[0069] In particular, step 240 may comprise iteratively checking each node device in the node device list to identify whether or not the node device is predicted to fall within the field of view of the control device by processing the identified orientation (of the FOV); the identified location of the control device and the relative location of the node device in the environment.

[0070] Figure 3 illustrates a proposed process 300 for performing step 210 of scanning the environment, which may be employed in some embodiments. The process 300 comprises a step 310 of obtaining, for each of a plurality of different locations of the control device within the environment, a respective distance- responsive measure for each node device, each distance-responsive measure being a measure of distance between the node device and the control device.

[0071] Thus, during the course of step 310, the control device is moved about the environment. The location of the control device as it is moved about the environment is tracked, such that the relative location (in the environment) of each of the different locations is known. Approaches for tracking a device location have been previously described, e.g., using a positioning system for identifying a location of the control device within the environment.

[0072] For each of a plurality of locations (as the device is moved about the environment), a distance-responsive measure is obtained for each node device. This is a measure that changes responsive to a distance between the node device and the control device. A wide variety of examples of distance-responsive measures could be used, such as a measure of signal strength (of a communication between the node device and the control device), a time of flight measure, a measure of latency (of a communication between the node device and the control device) and so on. One suitable example of a measure of signal strength is an RS SI.

[0073] As a more specific example, a distance-responsive measure for a node device may be obtained by the control device receiving (from the node device) a beacon signal (such as a Bluetooth Low Energy (BLE) beacon). The signal strength (e.g., RS SI) of the beacon signal may be measured as the distance-responsive measure for the node device.

[0074] Thus, the control device may comprise a scanning system having a communications module for at least receiving communications from any node device in the environment. The communications module may, for instance, comprise a wireless transceiver for making and receiving wireless communications.

[0075] Suitable wireless communication protocols that may be used (by the node device(s) and / or the control device) to perform communications include: an infrared link, Zigbee, Bluetooth, a wireless local area network protocol such as in accordance with the IEEE 802.11 standards family, a 2G, 3G, 4G or 5G telecommunication protocol, and so on. Other formats, including proprietary formats, will be readily apparent to the person skilled in the art. The process 300 also comprises a step 320 of processing the distance- responsive measures of each node device to predict a relative location of the node device within the environment.

[0076] In a simple example, step 320 may comprise defining the (tracked) location of the control device, for which the obtained distance responsive measure indicates a shortest distance, as the relative location of the node device. In particular, due to step 310, each location of the control device is associated with a different distance-responsive measure. The distance-responsive measure associated with the shortest distance may be identified, wherein the corresponding location (of the control device) defines the relative location of the node device.

[0077] In a more complex example, step 320 may comprise using a multilateration (e.g., trilateration) technique to establish or predict the location of the node device. Multilateration approaches effectively facilitate identification of a location of an object based on distance-responsive measurements between the object and known locations. As the locations of the control device are known (for each distance-responsive measurement), then the location of the object can be accurately identified. An example that makes use of this technique is later described.

[0078] In step 310, if the distance-responsive measure is obtained from communications from each node device, then each communication may also provide an identifier of the node device. This facilitates building of the node device list, e.g., a list of identifiers of node devices, for which a location is subsequently obtained (in step 320). In this way, the node device list can be trivially constructed.

[0079] Figure 4 illustrates a variation for a process 400 for performing step 210 of scanning the environment, which may be employed in some embodiments. This variation effectively comprises a multilateration technique to identify or predict the location of each node device.

[0080] In particular, process 400 again comprises steps 310 and 320, previously disclosed. Step 320 is here embodied as a process comprising: a sub-step 321 of constructing a heat map of the obtained distance-responsive measures for the node device; and a sub-step 322 of predicting a relative location of the node device by processing the heat map. The heat map is effectively a dataset that maps locations (of the control device) to a corresponding distance-responsive measure.

[0081] For the sake of illustrative clarity, Figure 5 provides an example of a plan view of a heat map 50. The true location 500 of a node device is identified. For each of a plurality of locations 510, 520, 530 of the control device, a distance-responsive measure is obtained. In Figure 5, this is illustrated with shading, with darker shades including increasing proximity between the control device and the node device. It is intuitively understandable how, using the heat map, it is possible to identify the (approximate) location of the node device within the environment.

[0082] For instance, turning back to Figure 4, sub-step 322 may comprise identifying a heat center of the heat map as the relative location of the node device. The heat center (of the heat map) will represent the predicted location of the node device within the environment, i.e., with respect to a co-ordinate system in which the control device is positioned.

[0083] With reference now to both Figures 3 and 4, step 310 may comprise iteratively sampling a distance-responsive parameter, for each node device, at predefined time or distance intervals during a movement of the control device within the environment. This facilitates a mechanism for regular sampling of the distance-responsive measure.

[0084] As a working example, step 310 may comprise sampling a distance-responsive parameter for every 2 m moved by the control device as the control device is moved within the environment. A distance moved by the control device can be readily monitored using the location tracking system and / or a movement sensor (such as an accelerometer).

[0085] In preferred examples, step 310 is performed during a scanning procedure executed or carried out by the control device. The scanning procedure may be a 3D scanning procedure for building a model of the environment as the control device is moved about the environment. This approach exploits actions taken during an activity that may be performed using the control device (i.e., building a model of the environment) to also be used in the generation of distance-responsive values for each node device.

[0086] Thus, the control device may comprise a 3D scanning system configured to perform a scanning procedure, for building a model of the environment, as the control device is moved about the environment.

[0087] Approaches and systems for building a 3D model of an environment as device is moved about the environment are well known to the skilled person. For instance, the device may be configured to perform simultaneous localization and mapping (SLAM), photogrammetry and / or LIDAR mapping techniques to generate the 3D model. Appropriate apparatus for performing such techniques are well known in the art.

[0088] Figure 6 illustrates another proposed computer-implemented method 600 that makes use of the previously disclosed method 200. The method 600 may be performed by the control device. The method 600 comprises performing any previously described example of method 200.

[0089] The method 600 further comprises a step 610 of triggering, using the control device, a node device, predicted to be within the field of view of the control device, to emit a user-perceptible signal. Thus, step 610 requests or asks a node device, which is predicted to he in the field of view, to emit a user-perceptible signal - such as a particular pattern of light or sound.

[0090] Step 610 may be performed, for instance, by providing an instruction signal from the control device to the node device.

[0091] The method 600 further comprises a step 620 of receiving a user input, responsive to the user-perceptible signal, that indicates a location of the triggered node device. Thus, a user or operator may provide (as an input interface) a user input that identifies the location of the triggered node device.

[0092] By way of example, consider a scenario in which the control device comprises an augmented reality system comprising an augmented reality display; and the field of view is a field of view of the environment visually represented in the augmented reality display. In this scenario, the triggered node device may generate a user-perceptible output in the form of a blinking or flashing light. The user interface may comprise an input to the augmented reality system (e.g., an input that influences an existence or property, such as a location, of a (virtual) object or element in the augmented reality display). The operator may control the user interface to control a location of a virtual object (e.g., a ray of light) in the augmented reality display to intersect or overlay the representation of the blinking or flashing light. The augmented reality system may then map the location of the virtual object in the augmented reality display to a relative location in the environment. This is possible because the augmented reality system is able to map a virtual location to a physical location, and vice versa, as is well known in the art.

[0093] The method 600 then performs a step 630 of updating the location of the triggered node device using the user input. In particular, the relative location of the node device is updated to reflect the user-defined (and more accurate) relative location of the node device. This location can be used in subsequent commissioning or configuring of the node device.

[0094] Step 630 may be replaced or supplemented with a step of performing any other configuration task for the triggered node device, such as defining to which group(s) and / or sub-group(s) of devices the device belongs; defining which device(s) is / are to operate or be controlled simultaneously; and so on.

[0095] The method may then perform a step 641 of determining whether or not all node devices, predicted to he within the field of view of the control device, have been triggered and had their location updated responsive to a user input. Responsive to a positive determination in step 641, the method 600 ends in step 642. Responsive to a negative determination, the method moves to a step 643 of selecting a next node device (for triggering in step 610).

[0096] The node device(s) may be triggered in a particular or predetermined order, e.g., in order of predicted proximity to the control device - which can be defined by the location of each node device in the node device list.

[0097] Method 600 can be repeated as the control device changes orientation and / or angle, e.g., each time the control device changes orientation and / or angle. Of course, in subsequent repetitions of method 600, it may not be necessary to repeat the performance of step 210 (i.e., the step 210 of scanning the environment can be omitted). Alternatively and / or additionally, method 600 may be repeated or performed responsive to a user input or indication to perform the method 600.

[0098] The skilled person would be readily capable of developing a control device, e.g., comprising a processing system, for carrying out any herein described method. Thus, each step of the flow chart may represent a different action performed by a processing system of a control device, e.g., using one or more further elements (such as a communication module or the like) where necessary and may be performed by a respective module of the processing system.

[0099] Embodiments may therefore make use of a processing system. The processing system can be implemented in numerous ways, with software and / or hardware, to perform the various functions required. A processor is one example of a processing system which employs one or more microprocessors that may be programmed using software (e.g., microcode) to perform the required functions. A processing system may however be implemented with or without employing a processor, and also may be implemented as a combination of dedicated hardware to perform some functions and a processor (e.g., one or more programmed microprocessors and associated circuitry) to perform other functions.

[0100] Examples of processing system components that may be employed in various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, application specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs).

[0101] In various implementations, a processor or processing system may be associated with one or more storage media such as volatile and non-volatile computer memory such as RAM, PROM, EPROM, and EEPROM. The storage media may be encoded with one or more programs that, when executed on one or more processors and / or processing systems, perform the required functions. Various storage media may be fixed within a processor or processing system or may be transportable, such that the one or more programs stored thereon can be loaded into a processor or processing system.

[0102] It will be understood that disclosed methods are preferably computer- implemented methods. As such, there is also proposed the concept of a computer program comprising code means for implementing any described method when said program is run on a processing system, such as a computer. Thus, different portions, lines or blocks of code of a computer program according to an embodiment may be executed by a processing system or computer to perform any herein described method.

[0103] There is also proposed a non-transitory storage medium that stores or carries a computer program or computer code that, when executed by a processing system, causes the processing system to carry out any herein described method.

[0104] In some alternative implementations, the functions noted in the block diagram(s) or flow chart(s) may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.

[0105] Variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure and the appended claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0106] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. If the term "adapted to" is used in the claims or description, it is noted the term "adapted to" is intended to be equivalent to the term "configured to". If the term "arrangement" is used in the claims or description, it is noted the term "arrangement" is intended to be equivalent to the term "system", and vice versa. A single processor or other unit may fulfill the functions of several items recited in the claims. If a computer program is discussed above, it may be stored / distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0107] Any reference signs in the claims should not be construed as limiting the scope.

Claims

CLAIMS:

1. A computer-implemented method (200, 600) for identifying one or more node devices (111, 112), the computer-implemented method comprising: scanning (210) an environment, using a control device (120), for one or more node devices in the environment to generate a node device list, the node device list identifying each node device and a relative location of the node device within the environment; identifying (220) an orientation of a field of view (125) of the control device; identifying (230) a location of the control device within the environment; and processing (240) the identified orientation; the identified location of the control device and the node device list to predict which, if any, node devices are within the field of view of the control device; wherein the scanning the environment, using the control device, comprises: obtaining (310), for each of a plurality of different locations of the control device within the environment, a respective distance-responsive measure for each node device, each distance-responsive measure being a measure of distance between the node device and the control device; and processing (320) the distance-responsive measures of each node device to predict a relative location of the node device within the environment; wherein each distance-responsive value is a measure of signal strength between the control device and the respective node device.

2. The computer-implemented method of claim 1, wherein the processing the distance-responsive measures comprises, for each node device: constructing (321) a heat map of the obtained distance-responsive measures for the node device; and predicting (322) a relative location of the node device by processing the heat map.

3. The computer-implemented method of claim 2, wherein predicting the relative location of the node device by processing the heat map comprises identifying a heat center of the heat map as the relative location of the node device.

4. The computer-implemented method of claim 1, wherein the step of processing the distance-responsive measures of each node device comprises defining the location of the control device, for which the obtained distance responsive measure indicates a shortest distance, as the relative location of the node device.

5. The computer-implemented method of any of claims 1 to 4, wherein the measure of signal strength is a received signal strength indicator.

6. The computer-implemented method of any of claims 1 to 5, wherein the obtaining, for each of a plurality of different locations of the control device within the environment, a respective distance-responsive measure for each node device comprises iteratively sampling a distance-responsive parameter, for each node device, at predefined time or distance intervals during a movement of the control device within the environment.

7. The computer-implemented method of any of claims 1 to 6, wherein the processing the identified orientation; the identified location of the control device and the node device list comprises filtering the node device list using the identified orientation, the identified location of the control device and the node device list.

8. The computer-implemented method of any of claims 1 to 7, wherein: the control device comprises an augmented reality display; and the field of view is a field of view of the environment visually represented in the augmented reality display.

9. The computer-implemented method of any of claims 1 to 8, wherein: the control device comprises a 3D scanning system configured to perform a scanning procedure, for building a model of the environment, as the control device is moved about the environment; and the scanning for node devices is performed during the scanning procedure performed by the 3D scanning system.

10. The computer-implemented method (600) of any of claims 1 to 9, further comprising: triggering (610), using the control device, anode device, predicted to be within the field of view of the control device, to emit a user-perceptible signal; receiving (620) a user input, responsive to the user-perceptible signal, that indicates a location of the triggered node device; and updating (630) the location of the triggered node device using the user input.

11. A computer program product comprising computer program code means which, when executed on a computing device having a processing system, cause the processing system to perform all of the steps of the method according to any of claims 1 to 10.

12. A control device (120) for identifying one or more node devices, the control device comprising a processing system configured to: scan (210) an environment, using a communications module, for one or more node devices in the environment to generate a node device list, the node device list identifying each node device and a relative location of the node device within the environment; identify (220) an orientation of a field of view of the control device; identify (230) a location of the control device within the environment; and process (240) the identified orientation; the identified location of the control device and the node device list to predict which, if any, node devices are within the field of view of the control device; wherein the scanning the environment, using the control device, comprises: obtaining (310), for each of a plurality of different locations of the control device within the environment, a respective distance-responsive measure for each node device, each distance-responsive measure being a measure of distance between the node device and the control device; and processing (320) the distance-responsive measures of each node device to predict a relative location of the node device within the environment; wherein each distance-responsive value is a measure of signal strength between the control device and the respective node device.

13. The control device of claim 12, further comprising an augmented reality display, wherein the field of view is a field of view of the environment visually represented in the augmented reality display.

Images