Virtual assistant circuitry and method for virtual assistant circuitry

Abstract

The present disclosure generally pertains to virtual assistant circuitry configured to: obtain a user-related motion profile; obtain environmental data from at least one sensor that is located in an environment of the user; adapt a digital representation of the environment based on the obtained environmental data; and generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

Description

[0001] VIRTUAL ASSISTANT CIRCUITRY AND METHOD FOR VIRTUAL

[0002] ASSISTANT CIRCUITRY

[0003] TECHNICAL FIELD

[0004] The present disclosure generally pertains to virtual assistant circuitry and a method for virtual assistant circuitry.

[0005] TECHNICAL BACKGROUND

[0006] Generally, virtual assistants are known. A virtual assistant may be configured to interact with a user in various situations, such as speech assistance, knowledge database, or the like.

[0007] Furthermore, digital twins are known. A digital twin may represent a three-dimensional model an environment (e.g., a city).

[0008] Although there exist techniques that include digital twins, it is generally desirable to provide virtual assistant circuitry and a method for virtual assistant circuitry.

[0009] SUMMARY

[0010] According to a first aspect, the disclosure provides virtual assistant circuitry configured to: obtain a user-related motion profile; obtain environmental data from at least one sensor that is located in an environment of the user; adapt a digital representation of the environment based on the obtained environmental data; and generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

[0011] According to a second aspect, the disclosure provides a method for virtual assistant circuitry, the method comprising: obtaining a user-related motion profile; obtaining environmental data from at least one sensor that is located in an environment of the user; adapting a digital representation of the environment based on the obtained environmental data; and generating, based on the adapted digital representation and for the user, a command to adapt the motion profile. Further aspects are set forth in the dependent claims, the drawings and the following description.

[0012] BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Embodiments are explained by way of example with respect to the accompanying drawings, in which:

[0014] Fig. 1 depicts a system including virtual assistant circuitry according to the present disclosure in which the virtual assistant circuitry is provided separate from a user device and a server;

[0015] Fig. 2 depicts a system including virtual assistant circuitry according to the present disclosure in which the virtual assistant circuitry is provided as a part of a server;

[0016] Fig. 3 depicts a system including virtual assistant circuitry according to the present disclosure in which the virtual assistant circuitry is provided as a part of a user device;

[0017] Fig. 4 depicts an embodiment of a method for virtual assistant circuitry according to the present disclosure in a block diagram;

[0018] Fig. 5 depicts an embodiment of a method for virtual assistant circuitry according to the present disclosure in a block diagram, in which additionally, an adapted digital representation is provided for other users; and

[0019] Fig. 6 depicts a method carried out in a server according to the present disclosure in a block diagram.

[0020] DETAILED DESCRIPTION OF EMBODIMENTS

[0021] Before a detailed description of the embodiments starting with Fig. 1 is given, general explanations are made.

[0022] Therefore, some embodiments pertain to virtual assistant circuitry configured to: obtain a user- related motion profile; obtain environmental data from at least one sensor that is located in an environment of the user; adapt a digital representation of the environment based on the obtained environmental data; and generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

[0023] The circuitry may include any entity or multitude of entities that are configurable to access and to adapt a digital representation of an environment, such as a processor, e.g., a central processing unit (CPU), and graphics processing unit (GPU), a chip that includes both a CPU and a GPU, or the like. The circuitry may be implemented in a user device, such as a wearable device (e.g., at least one of a head-mounted device, a smartwatch, a smartphone, smart ring, or the like) or distributed among more than one wearable devices. Likewise, the circuitry may be implemented in at least one server configured to communicate with a user device. Also, the circuitry may be distributed among at least one user device and at least one server, in some embodiments.

[0024] The circuitry may provide for a virtual (personal) assistant that can generate a command for a user such that a user’s behavior may be influenced.

[0025] The circuitry may be configured to obtain a user-related motion profile. Such a motion profile may be based on any motion-related data of the user, such as a type of motion / movement, a velocity, a speed, a physical level of the user, a physique of the user, means of transportation, or the like, as will be discussed further below.

[0026] The circuitry may further be configured to obtain environmental data including any data that may refer to the motion of the user. For example, if the user rides a car, the environmental data may include a traffic light, such that a speed of the car may be adapted. Also, traffic information may be used for navigating the user. On the other hand, if the user walks by foot, data pertaining to a traffic light may also be used to adapt the walking speed. Moreover, if the user is running or persecuting a specific training, environmental data may be used to adapt the training, e.g., obstacles may be included for the user, or the user may be led to a place that is less frequented by other people such that the user can do pushups, for example, or the user may be instructed / motivated (commanded) to run faster in order to not having to stop at a red traffic light and not having to interrupt his training.

[0027] If the virtual assistant circuitry is used as a virtual sports coach (if the user performs a training), without limiting the present disclosure in that regard, data from the athlete (the user) and his surroundings may be obtained to improve the athlete’s performance under his unique environment in any sport. Factors like weather, elevation, temperature, humidity, and the like may influence the athlete’s performance and impact his training, making it difficult to follow routines that do not consider these factors, particularly for athletes without a personal coach.

[0028] Landmarks and semantic segmentation may be used to make the virtual coach more immersive and utilize the information of the objects located in the real -world to enhance the training (wherein such data may also be used in the more general context of the present disclosure).

[0029] Interactive tasks may be matched with a training plan of the user, but instead of just telling to sprint or stop, the real-world environment and real-time actions may be taken into account. The virtual coach may understand all relevant real-world environment factors and may relate them to the athlete’s personal information to provide an optimal workout for the athlete. Additionally, the virtual coach may use the digital representation to create engaging storylines.

[0030] For example, the virtual coach may create a persecution storyline across a city in real-time when the athlete workout requires an intense, high-paced training session. In another example, the virtual coach may tell the user to cross the road on the zebra crossing and sprint up that small hill in front to reach a statue as fast as possible. Another example may include for a cyclist to keep up with a bus (as a sprinting interval) driving between the two stops since the real-time position of the bus may be known to the circuitry.

[0031] As discussed herein, a “Multiplayer”-mode may be enabled according to the present disclosure, i.e., a same training may be provided for at least two persons who want to complete a similar training achievement (e.g., a similar distance). It may be carried out in real-time when users compete against each other, e.g., by doing sports together or in two separate locations. In such embodiments where the users are at two different locations, the circuitry may be configured to determine a training with a similar degree of difficulty for the users (e.g., similar slope, similar obstacles, or the like). In such embodiments, feedback may be provided to the respective users on how the other person did at a similar stage, and if the user is ahead or behind.

[0032] The environmental data may be obtained from at least one sensor that is located in an environment of the user. The environment may also include that the sensor is placed at the user, such as being included in a wearable device. Moreover, the at least one sensor may include fixed sensors (e.g., cameras on a building, traffic light sensors), or the like. Moreover, the at least one sensor may be moving sensors, such as sensors of other users, of cars, busses, or the like that are in vicinity of the user.

[0033] It should be noted that the sensors do not necessarily need to detect the user and that “environment” should be understood broadly. For example, if the user is running or driving, or the like, a sensor that is still some distance (e.g., one or two kilometers) away may be regarded as an environmental sensor according to the present disclosure since based on such a sensor, a prediction may be carried out regarding of state of the environment when the user arrives at the place of the sensor. Also, a sensor that is farther away may be used to obtain a current state of the environment in order to lead the user there based on the current state (e.g., in order to modify his training, in order to avoid traffic, or the like).

[0034] Based on the obtained environmental data, a digital representation of the environment may be adapted. For example, the digital representation may be a static representation on which many users have access to (e.g., metaverse, a digital twin, or the like). A static representation may be used in order to save processing power and storage. Such a digital representation may be adapted “on-the-fly”.

[0035] For example, traffic light data may be included in the digital representation. However, for the user, it may not be necessary to include traffic light data for a whole city since it may only be necessary to include it for the route that the user is travelling.

[0036] On the other hand, in some embodiments, the environment data may be used for a large area (e.g., a whole city). Such a scenario may be applied, if multiple users have interest in the environmental data, for example.

[0037] The adaptation of the digital representation may include to adapt the environment based on people or movable objects in the environment that are not represented in the static representation.

[0038] By adapting the digital representation in such a way, a static representation may be made at least partially dynamic.

[0039] In some embodiments, the circuitry is further configured to generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

[0040] For example, as already discussed above, the user may be instructed to run faster, take another way, carry out a specific exercise, or the like.

[0041] Thereby, the motion of the user may be influenced according to a specific goal or objective that the user may have. For example, if the user’s goal or objective is to improve his athleticism, tailored exercises may be generated on-the-fly according to the environment. If the user’s goal is to arrive at a place in the most-efficient manner, taken into account his physique, means of transportation and / or a particular route may be suggested.

[0042] It should be noted that according to the present disclosure, it may be possible to generate a command to the user without the need for the user to use a device with high processing power since the adaptation of the digital representation may happen within the digital representation, in some embodiments, such that the user device may only need to receive the command. On the other hand, in case of bad reception, the digital representation may be pre-adapted (based on at least one of a current state or a predicted state of the environment).

[0043] In some embodiments, the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user, as discussed herein. In some embodiments, the environmental data includes real-time data, as discussed herein.

[0044] In some embodiments, the real-time data includes infrastructure-related data, as discussed herein (such as at least one of traffic data, traffic light data, public transportation data, data indicating how much an area is frequented, data indicating moving / movable objects, data indicating other users, or the like).

[0045] In some embodiments, the digital representation includes a digital twin of the environment, as discussed herein.

[0046] A Digital Twin may refer to a virtual representation that mirrors a city or a natural ecosystem (e.g., in real-time). It may integrate data from various sources, such as sensors, satellite imagery, and other loT devices, to simulate the dynamics and behavior of urban or natural elements. Generally, such a digital counterpart may enable city planners, environmentalists, and policymakers to monitor, analyze, and optimize different aspects of the city or environment. It may facilitate simulations of urban development scenarios, environmental changes, and resource management strategies, providing insights for sustainable planning, disaster preparedness / prevention, and informed decision-making to create more resilient and efficient cities and nature environments.

[0047] For modelling the digital twin, for example, semantic segmentation may be used according to which buildings, signs, roads and other infrastructure and natural objects may be modelled.

[0048] In some embodiments, the adaptation of the digital representation is carried out within the digital twin, as discussed herein.

[0049] In some embodiments, the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, physical level of the user, a physique of the user, and means of transportation.

[0050] A motion type may indicate whether the user is running or walking (or swimming, in some embodiments). The motion type may, for example, be acquired based on at least one of an acceleration sensor or a camera that detects the user.

[0051] A velocity may include movement directions of the user, whereas the speed may indicate how fast the user moves, as generally known.

[0052] A physical level of the user may correspond to a fitness level, if the user carries out a training. If the user intends to get to a specific place, the physical level may be used to determine whether it is sensible to suggest that the user rides the bike to that place or rather to drive by car. The physique of the user may include body parameters, such a height, weight, resting heart rate, body fat percentage, or the like.

[0053] The means of transportation may be similar to motion type, but may further include whether the user drives by bike, by car, by public transportation, or the like. Also a mixture of different means of transportation or motion types may be envisaged, such as first driving by bike, then swimming, then running. Moreover, for example, if the user drives with a battery-powered vehicle (e.g., e-bike, e-scooter, or the like), a remaining battery level may be taken into account.

[0054] In some embodiments, the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter, as discussed herein. For example, the changing of the at least one motion parameter may include increasing or decreasing a speed, carrying out a specific exercise, take a detour, or the like.

[0055] In some embodiments, the circuitry is further configured to: provide access to the adapted digital representation to a further user.

[0056] Thereby, the data may be re-used and processing power may be saved. Also a “multiplayer”- mode may be enabled thereby.

[0057] In some embodiments, the at least one sensor is an Internet of Things sensor.

[0058] Some embodiments pertain to a method for virtual assistant circuitry, the method including: obtaining a user-related motion profile; obtaining environmental data from at least one sensor that is located in an environment of the user; adapting a digital representation of the environment based on the obtained environmental data; and generating, based on the adapted digital representation and for the user, a command to adapt the motion profile, as discussed herein.

[0059] The method may be carried out in virtual assistant circuitry according to the present disclosure.

[0060] In some embodiments, the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user, as discussed herein. In some embodiments, the environmental data includes real-time data, as discussed herein. In some embodiments, the real-time data includes infrastructure-related data, as discussed herein. In some embodiments, the digital representation includes a digital twin of the environment, as discussed herein. In some embodiments, the adaptation of the digital representation is carried out within the digital twin, as discussed herein. In some embodiments, the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, physical level of the user, a physique of the user, and means of transportation, as discussed herein. In some embodiments, the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter, as discussed herein. In some embodiments, the method further includes: providing access to the adapted digital representation to a further user, as discussed herein. In some embodiments, the at least one sensor is an Internet of Things sensor, as discussed herein.

[0061] Some embodiments pertain to a server including circuitry configured to: provide a digital representation of an environment of a user; adapt the digital representation of the environment based on environmental data acquired from at least one sensor that is located in an environment of the user.

[0062] In some embodiments, the digital representation is adapted based on a control signal from virtual assistant circuitry according to the present disclosure.

[0063] In some embodiments, the virtual assistant circuitry is included in the server, whereas in other embodiments, the virtual assistant circuitry is provided distinct from the server. It should be noted that the expression “adapting the digital representation” may be carried out by the virtual assistant circuitry by providing the environmental data to the server without the need for the virtual assistant circuitry to be part of the server. In the context of the server adapting the digital representation, it should be noted that receiving the environmental data and updating the digital representation may serve the purpose of “adapting the digital representation”. The server may, in such embodiments, provide the digital representation to the virtual assistant circuitry and / or directly to the user device (depending on the user device, e.g., if it is capable to deal with such type and magnitude of data).

[0064] On the other hand, the virtual assistant circuitry may obtain the digital representation, in some embodiments, and adapt it locally (e.g., in the case of bad reception).

[0065] In some embodiments, the server is an Internet of Things server.

[0066] Some embodiments pertain to a system including a server (as discussed herein), virtual assistant circuitry (as discussed herein), and a user device (as discussed herein).

[0067] Some embodiments pertain to a method carried out in a server, the method including: : providing a digital representation of an environment of a user; and adapting the digital representation of the environment based on environmental data acquired from at least one sensor that is located in an environment of the user.

[0068] For providing guidance and challenges to the user, certain data, including metadata may be used to determine the command for the user. According to the present disclosure, downloading and observing (visualization of) the (whole) digital representation may not be needed. For example, positions of certain traffic signs, intersections, or landmarks, such as buildings, trees, lakes, etc may be used. Only the information about objects of interest may be transferred to the user device and / or the virtual assistant circuitry to manage data rates and processing power required for the virtual coach. The full digital twin would be located on a cloud infrastructure (e.g., loT server, as discussed herein), but not on the user device.

[0069] Such information could also be pre-loaded on the user device to reduce the data usage and ensure that the methods discussed herein work in bad reception areas. In such embodiments, the planned route may be observed and deviations may be determined, such that the command is generated to adapt a route when a deviation is determined.

[0070] As discussed herein, motion parameters may be used, such as height, weight, heart rate, location, orientation, and the like.

[0071] The virtual assistant circuitry may interact with the user in various ways, such as using audio through headphones or earphones. A wearable or a smartphone may include the virtual assistant circuitry or may communicate with the virtual assistant circuitry and provide an audio signal to headphones.

[0072] In some embodiments, in which the user might has a screen in front of him, for example a phone, a cycling computer attached on the handlebars, a head-mounted device, or the like, additional visual information may be shown on the screen.

[0073] Furthermore, in some embodiments, an interface with haptic feedback may be used for outputting the command.

[0074] The present disclosure may further be applied in the context of rehabilitation where a user is motivated to move more and perform certain movements during a recovery process.

[0075] The methods as described herein are also implemented in some embodiments as a computer program causing a computer and / or a processor to perform the method, when being carried out on the computer and / or processor. In some embodiments, also a non-transitory computer- readable recording medium is provided that stores therein a computer program product, which, when executed by a processor, such as the processor described above, causes the methods described herein to be performed.

[0076] Returning to Fig. 1, there is depicted a system 1 including virtual assistant (VA) circuitry 2 according to the present disclosure, an Internet of Things (loT) server 3, and a user device 4 (a smartwatch, in this embodiment). In this embodiment, the three entities are separate from each other and are communicating with each other. As depicted in Fig. 1, the VA circuitry 2 communicates with the server in that it provides the server with environmental data and thereby adapts a digital representation of an environment stored in the server, as discussed herein.

[0077] Furthermore, the VA circuitry 2 obtains a user-related motion profile, as discussed herein.

[0078] After obtaining the adapted digital representation, the VA circuitry generates a command to adapt the motion profile, as discussed herein.

[0079] Fig. 2 depicts a system 10 including VA circuitry 11, an loT server 12, and a user device 13. In contrast to the embodiment of Fig. 1, the server 12 includes the VA circuitry 11, such that the VA circuitry adapts the environmental data directly as a part of the server 12.

[0080] Fig. 3 depicts a system 20 including VA circuitry 21, a user device 22, and an loT server 23. The embodiment of Fig. 3 is different from the previous ones in that the VA circuitry 21 is provided as a part of the user device 22.

[0081] However, it should be noted that the VA circuitry may be distributed among the user device and the server (and possibly, at least one further device), depending on the task that is to be carried out by the VA circuitry. For example, (at least a part of) the VA circuitry may be implemented in a dedicated server, such that other tasks typically carried out by a virtual assistant (e.g., speech assistance) may be carried out in the same device, whereas the generation of the command may directly happen in the loT server according to the present disclosure.

[0082] Fig. 4 depicts a method 30 for VA circuitry according to the present disclosure.

[0083] At 31, a motion profile is obtained, as discussed herein. In this embodiment, the user carries out a running program, such that the motion profile includes at least a motion type (running), a speed, a physical level, and a physique of the user.

[0084] At 32, environmental data are obtained with the user’s wearable device (smartwatch) indicating a position of the user. Furthermore, traffic light information is acquired.

[0085] At 33, a digital representation of the user’s environment is adapted based on the environmental data. In this embodiment, the traffic light information is sent to an loT server and traffic lights in vicinity of the user are updated, such that an ideal running route can be determined by the VA circuitry based on the adapted digital representation and the position of the user. It should be noted that the position of the user is not sent in this embodiment, but generally, it may be taken into account to adapt the digital representation of the environment, as well, for example to show the position of the user to other users. At 34, a command for the user to adapt the motion profile is generated based on the adapted digital representation. In this embodiment, it is recognized that the user would have to wait at the next traffic light, such that the command includes to increase a pace (speed), such that the user does not have an unwanted break at the traffic light.

[0086] Fig. 5 depicts a further embodiment of a method for VA circuitry according to the present disclosure. Method numbers 41 to 44 correspond to 31 to 34 of Fig. 5. However, the method further includes, to provide access to the adapted digital representation to at least one further user, such that it is not necessary to obtain the sensor data twice for the at least one further user.

[0087] Fig. 6 depicts a method 50 carried out in a server according to the present disclosure.

[0088] At 51, the server provides a digital representation of an environment of a user, as discussed herein.

[0089] At 52, the server adapts the digital representation based on environmental data provided by VA circuitry according to the present disclosure.

[0090] It should be recognized that the embodiments describe methods with an exemplary ordering of method steps. The specific ordering of method steps is however given for illustrative purposes only and should not be construed as binding. For example the ordering of 31 and 32 in the embodiment of Fig. 4 may be exchanged. Also, the ordering of 41 and 42 in the embodiment of Fig. 5 may be exchanged. Further, also the ordering of 44 and 45 in the embodiment of Fig. 5 may be exchanged. Other changes of the ordering of method steps may be apparent to the skilled person.

[0091] Please note that the division of the system 1, 10, or 20 into units 2, 3, and 4, or 11, 12, and 13, or 21, 22, and 23 is only made for illustration purposes and that the present disclosure is not limited to any specific division of functions in specific units. For instance, the system 1, 10, or 20 could be implemented by a respective programmed processor, field programmable gate array (FPGA) and the like.

[0092] The methods discussed herein can also be implemented as a computer program causing a computer and / or a processor to perform the method, when being carried out on the computer and / or processor. In some embodiments, also a non-transitory computer-readable recording medium is provided that stores therein a computer program product, which, when executed by a processor, such as the processor described above, causes the method described to be performed.

[0093] All units and entities described in this specification and claimed in the appended claims can, if not stated otherwise, be implemented as integrated circuit logic, for example on a chip, and functionality provided by such units and entities can, if not stated otherwise, be implemented by software.

[0094] In so far as the embodiments of the disclosure described above are implemented, at least in part, using software-controlled data processing apparatus, it will be appreciated that a computer program providing such software control and a transmission, storage or other medium by which such a computer program is provided are envisaged as aspects of the present disclosure.

[0095] Note that the present technology can also be configured as described below.

[0096] (1) Virtual assistant circuitry configured to: obtain a user-related motion profile; obtain environmental data from at least one sensor that is located in an environment of the user; adapt a digital representation of the environment based on the obtained environmental data; and generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

[0097] (2) The circuitry of (1), wherein the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user.

[0098] (3) The circuitry of (1) or (2), wherein the environmental data includes real-time data.

[0099] (4) The circuitry of (3), wherein the real-time data includes infrastructure-related data.

[0100] (5) The circuitry of anyone of (1) to (4), wherein the digital representation includes a digital twin of the environment.

[0101] (6) The circuitry of (5), wherein the adaptation of the digital representation is carried out within the digital twin.

[0102] (7) The circuitry of anyone of (1) to (6), wherein the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, a physical level of the user, a physique of the user, and means of transportation.

[0103] (8) The circuitry of (7), wherein the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter.

[0104] (9) The circuitry of anyone of (1) to (8), further configured to: provide access to the adapted digital representation to a further user. (10) The circuitry of anyone of (1) to (9), wherein the at least one sensor is an Internet of Things sensor.

[0105] (11) A method for virtual assistant circuitry, the method comprising: obtaining a user-related motion profile; obtaining environmental data from at least one sensor that is located in an environment of the user; adapting a digital representation of the environment based on the obtained environmental data; and generating, based on the adapted digital representation and for the user, a command to adapt the motion profile.

[0106] (12) The method of (11), wherein the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user.

[0107] (13) The method of (11), wherein the environmental data includes real-time data.

[0108] (14) The method of (13), wherein the real-time data includes infrastructure-related data.

[0109] (15) The method of anyone of (11) to (14), wherein the digital representation includes a digital twin of the environment.

[0110] (16) The method of (15), wherein the adaptation of the digital representation is carried out within the digital twin.

[0111] (17) The method of anyone of (11) to (16), wherein the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, physical level of the user, a physique of the user, and means of transportation.

[0112] (18) The method of (17), wherein the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter.

[0113] (19) The method of anyone of (11) to (18), further comprising: providing access to the adapted digital representation to a further user.

[0114] (20) The method of anyone of (11) to (19), wherein the at least one sensor is an Internet of Things sensor.

[0115] (21) A computer program comprising program code causing a computer to perform the method according to anyone of (11) to (20), when being carried out on a computer. (22) A non-transitory computer-readable recording medium that stores therein a computer program product, which, when executed by a processor, causes the method according to anyone of (11) to (20) to be performed.

Claims

CLAIMS1. Virtual assistant circuitry configured to: obtain a user-related motion profile; obtain environmental data from at least one sensor that is located in an environment of the user; adapt a digital representation of the environment based on the obtained environmental data; and generate, based on the adapted digital representation and for the user, a command to adapt the motion profile.

2. The circuitry of claim 1, wherein the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user.

3. The circuitry of claim 1, wherein the environmental data includes real-time data.

4. The circuitry of claim 3, wherein the real-time data includes infrastructure-related data.

5. The circuitry of claim 1, wherein the digital representation includes a digital twin of the environment.

6. The circuitry of claim 5, wherein the adaptation of the digital representation is carried out within the digital twin.

7. The circuitry of claim 1, wherein the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, a physical level of the user, a physique of the user, and means of transportation.

8. The circuitry of claim 7, wherein the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter.

9. The circuitry of claim 1, further configured to: provide access to the adapted digital representation to a further user.

10. The circuitry of claim 1, wherein the at least one sensor is an Internet of Things sensor.

11. A method for virtual assistant circuitry, the method comprising: obtaining a user-related motion profile; obtaining environmental data from at least one sensor that is located in an environment of the user; adapting a digital representation of the environment based on the obtained environmental data; andgenerating, based on the adapted digital representation and for the user, a command to adapt the motion profile.

12. The method of claim 11, wherein the sensor being located in the environment includes at least one of the user wearing the sensor and the sensor being located in a surrounding of the user.

13. The method of claim 11, wherein the environmental data includes real-time data.

14. The method of claim 13, wherein the real-time data includes infrastructure-related data.

15. The method of claim 11, wherein the digital representation includes a digital twin of the environment.

16. The method of claim 15, wherein the adaptation of the digital representation is carried out within the digital twin.

17. The method of claim 11, wherein the user-related motion profile includes at least one motion parameter including a motion type, a velocity, a speed, physical level of the user, a physique of the user, and means of transportation.

18. The method of claim 17, wherein the command to adapt the motion profile includes changing a motion intensity based on changing at least one motion parameter.

19. The method of claim 11, further comprising: providing access to the adapted digital representation to a further user.

20. The method of claim 11, wherein the at least one sensor is an Internet of Things sensor.

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