System and method for connecting a user to a receiver

Abstract

The present invention relates to a system for connecting a user with a receiver, the system comprising: a sensory data component configured to provide a plurality of sensory datasets to the user, and a selection component configured to assist the user in making a selection between the plurality of sensory datasets, wherein the system is configured to connect the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user. The present invention also relates to a corresponding method and computer program product.

Description

[0001] System and method for connecting a user to a receiver

[0002] Field

[0003] The present invention relates generally to the field of data processing. More particularly, it relates to a system and a method for connecting a user with a receiver based on a selection of data by the user.

[0004] Background

[0005] The rise of the Internet has opened a world of new possibilities to people around the world. For example, there are now more options than ever before for new / first job-seekers looking to pivot / start their professional lives. At the other end of the spectrum, there are also more options than ever before for employers to choose from. The explosion of options on both sides has thrown up some unique challenges. A particularly relevant challenge may be that of connecting options on one side, that may be called users, with suitable options on the other side, that may be called potential receivers. Further exemplarily, users may comprise students and potential receivers may comprise universities, or university departments.

[0006] While it may be possible for a user, for example, to research the different options, this may be time-consuming, complex, inefficient, and unreliable. The amount of time and complexity involved may also serve to demotivate users from determining the most appropriate receiver(s). Similarly, it may not be efficient or possible for a potential receiver to consider all the users, at least equivalently, leading to potentially missed suitable connections.

[0007] In recent years, a diminishing interest among school students in pursuing vocational and practical professions has been observed. A predominant inclination towards university education may overshadow the significance of hands-on, skills-based training. This trend may not only affect the availability of skilled tradespeople in various industries but may also place undue pressure on university systems. It may be of advantage for educational stakeholders and policymakers to address this imbalance, recognizing the intrinsic value of both academic and vocational pathways, to ensure a holistic, diversified, and skilled future workforce.

[0008] If individuals engage in professions misaligned with their innate strengths, interests, or values, it may result in a multitude of adverse implications. Such misalignments may lead to reduced job satisfaction, diminished productivity, and increased workplace stress. Over time, this may manifest in higher turnover rates, frequent job transitions, and potentially even burnout. From an organizational perspective, the misallocation of talent may hinder optimal operational efficiency and growth. It is thus of advantage for both individuals and organizations to prioritize appropriate career fit, ensuring not only individual well-being but also the sustained efficacy and success of the organization. Individuals and employers may only realize this after considerable time which may result in considerable psychological as well as financial problems.

[0009] The present invention can assist to improve one or more or all of the deficiencies mentioned above. In particular, it may enable deciding on an objective level, or at least more a more objective level.

[0010] Generally, embodiments of the present technology may be of particular advantage for scenarios where a connection has to be established between a user and a receiver. In particular, embodiments of the present technology may be of relevance where connections are established based, at least in part, on sensory data.

[0011] Summary

[0012] The present invention seeks to overcome or at least alleviate the shortcomings and disadvantages of the prior art. More particularly, it is an object of the present invention to provide a system and a method for connecting users with receivers that may be more efficient, simple, and reliable.

[0013] According to a first aspect, the present invention relates to a system for connecting a user with a receiver, the system comprising : a sensory data component configured to provide a plurality of sensory datasets to the user, and a selection component configured to assist the user in making a selection between the plurality of sensory datasets. A sensory dataset may be generally understood to comprise a dataset that may provide information to the user via a sensory stimulus to the user.

[0014] The system may be configured to connect the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user. In other words, the user may select some of the plurality of sensory datasets based, for example, on their personal sensory and / or content preferences and based, at least in part, on this selection, the user may be connected to the receiver.

[0015] Each of the plurality of sensory datasets may comprise a sensory control parameter. The sensory control parameter may be associated with a value, corresponding to the value of the sensory control parameter. The sensory control parameter may be of advantage in determining the user's preference as described further below. Further, the sensory control parameter may be used to control an aspect of the sensory dataset.

[0016] At least one of the plurality of sensory datasets may be representative of an image. A dataset representative of an image may be understood, generally, to comprise data that may, at least in part, be represented as an image. For example, the data may comprise RGB values at various pixel locations. Each of the plurality of sensory datasets may be representative of an image.

[0017] The sensory data component may comprise a display. The display may be of advantage in displaying sensory datasets representative of an image.

[0018] The sensory control parameter may comprise any of a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0019] At least one of the plurality of sensory datasets may be representative of an audio track.

[0020] Each of the plurality of sensory datasets may be representative of an audio track.

[0021] The sensory data component may comprise a speaker and / or a headphone. The speaker and / or headphone may be of advantage in playing sensory datasets representative of an audio track.

[0022] The sensory control parameter may comprise any of a frequency range, an amplitude, a timbre, harmonics and overtones, an attack, a decay, a sustain, a release, a reverberation, an echo, a phase, a filtering, a compression, a noise reduction, a stereo panning and / or modulation, and / or a total length.

[0023] At least one of the plurality of sensory datasets may be representative of an animation. The animation may be displayed on the display as described above. The animation may additionally, or alternatively, comprise an audio track, that may be played using the speaker and / or headphone as described above.

[0024] Each of the plurality of sensory datasets may be representative of an animation.

[0025] The sensory control parameter may comprise any of a frame rate, a total length, a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0026] At least one of the plurality of sensory datasets may be representative of a tactile stimulus.

[0027] Each of the plurality of sensory datasets may be representative of a tactile stimulus. Tactile stimuli may be provided to the user by means of one or more actuators, for example, that may be arranged on to the user's body. Alternatively, or additionally, the stimuli may be provided by means of components whose temperature may be individually controlled. Generally, any suitable device may be used, depending on the kind of tactile stimulus to be provided. The sensory control parameter may comprise any of a pressure / force, a frequency of the stimulus, an amplitude of the stimulus, a texture, a temperature, a size, a shape, a location, a duration, a direction of stimulation, a pattern, a pressure distribution, a pain sensation to the stimulus, an adaptation to the stimulus.

[0028] The selection component may be configured to allow the user to either select or deselect a sensory dataset. In particular, the selection component may comprise a touchscreen to allow the user to select or deselect a sensory dataset. For example, when the sensory dataset is representative of an image, it may be displayed on the touchscreen, and the user may swipe on the touchscreen. The direction of the swiping may be used to determine whether the sensory dataset has been selected or deselected.

[0029] The receiver may correspond to one of a plurality of potential receivers.

[0030] Each of the plurality of potential receivers may be associated with a set of sensory datasets. The set of sensory datasets may comprise at least one sensory dataset. In some embodiments, the set of sensory datasets may comprise a plurality of sensory datasets.

[0031] Each of the plurality of potential receivers may be associated with a unique set of sensory datasets. In other words, it may be possible to uniquely determine the receiver based on a set of sensory datasets.

[0032] Connecting the user to the receiver may be based, at least in part, on a set of sensory datasets selected by the user. For example, the set of sensory datasets selected by the user, that may comprise, for example, each of the sensory datasets selected and none of the sensory datasets deselected by the user, as described above, may be compared with the set of sensory datasets associated with each of the plurality of potential receivers. A result of the comparison may be one of success or failure. The user may then be connected to the receiver(s) for which the result of the comparison is success. Note that appropriate measures may be used for determining the result of the comparison as are described further below. Further, appropriate methods may be used to optimize the efficiency of the comparison process.

[0033] The system may comprise a sensory control optimizer component.

[0034] The sensory control optimizer component may be configured to determine an optimal value for the sensory control parameter.

[0035] The optimal value for the sensory control parameter may be determined based, at least in part, on the selection between the plurality of sensory datasets made by the user. For example, the sensory control parameter may determine as the optimal value, a statistical measure, such as a mean, of the values of the sensory control parameter based on the sensory datasets selected by the user.

[0036] The sensory data component may be further configured to provide a sensory dataset with the optimal value of the sensory control parameter.

[0037] The system may comprise a plurality of sensory dataset layers, wherein each of the plurality of sensory dataset layers may comprise at least one sensory dataset.

[0038] The plurality of sensory dataset layers may comprise a first sensory dataset layer, that may be called a control parameter optimization layer, comprising a plurality of sensory datasets.

[0039] The optimal value of the sensory control parameter may be based, at least in part, on the selection made by the user between the plurality of sensory datasets in the control parameter optimization layer.

[0040] The plurality of sensory dataset layers may comprise a second sensory dataset layer.

[0041] The sensory data component may be configured to provide any of the datasets in the second sensory dataset layer with the optimal value of the sensory control parameter.

[0042] The set of sensory datasets associated with each of the plurality of potential receivers may comprise at least one sensory dataset from the second sensory dataset layer.

[0043] The system may further comprise a timing component configured to determine a time taken by the user in making the selection between the plurality of sensory datasets.

[0044] The timing component may be configured to determine a time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0045] Connecting the user to the receiver may be based, at least in part, on the time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0046] The system may comprise an artificial intelligence component.

[0047] The artificial intelligence component may be configured to modify and / or generate any of the plurality of sensory datasets.

[0048] The system may be configured to send the selection between the plurality of sensory datasets made by the user to the artificial intelligence component. The artificial intelligence component may be configured to determine a most appropriate receiver from the plurality of potential receivers based, at least in part, on the selection made by the user.

[0049] The artificial intelligence component may be configured to assign a label to each of the plurality of potential receivers, wherein the label may be representative of an appropriateness of the potential receiver, based, at least in part, on the selection made by the user.

[0050] The system may be configured to connect the user to the receiver based, at least in part, on the most appropriate receiver and / or on the labels assigned to each of the plurality of potential receivers.

[0051] The system may comprise a feedback component configured, in response to connecting the user to the receiver, to prompt the user for feedback.

[0052] The feedback component may be configured to receive the feedback from the user.

[0053] The system may be configured to connect the user to the receiver based, at least in part, on the feedback from a previous user.

[0054] The feedback component may be configured to send the feedback received from the user to the artificial intelligence component.

[0055] The artificial intelligence component may be configured to determine the most appropriate receiver and / or to assign the labels to each of the plurality of potential receivers based, at least in part, on the feedback from a previous user.

[0056] The system may comprise a virtual reality device configured for use by the user.

[0057] The virtual reality device may comprise an eye-tracking component configured to track eye motion of the user.

[0058] The virtual reality device may be configured to track physical motion of the user.

[0059] The sensory data component may comprise the virtual reality device, or at least a part thereof.

[0060] The selection component may comprise the virtual reality device, or at least a part thereof.

[0061] Any of the plurality of sensory datasets may be representative of (pseudo) 3-dimensional (3D) sensory data. The selection component may be configured to assist the user in making the selection based, at least in part, on the motion of their eye(s).

[0062] The selection component may be configured to assist the user in making the selection based, at least in part, on their physical motion.

[0063] The system may be configured to connect the user to a plurality of receivers. Each of the plurality of receivers may correspond to one of the plurality of potential receivers described above.

[0064] The system may comprise a data processing component.

[0065] The sensory control parameter may comprise a plurality of sensory control parameters.

[0066] The artificial intelligence component may comprise, at least in part, a supervised learningbased model.

[0067] The artificial intelligence component may comprise, at least in part, an unsupervised learningbased model.

[0068] The artificial intelligence component may comprise, at least in part, a transfer learning-based model.

[0069] The artificial intelligence component may comprise, at least in part, a reinforcement learningbased model.

[0070] The artificial intelligence component may comprise, at least in part, a deep learning-based model.

[0071] The artificial intelligence component may comprise, at least in part, a hybrid model.

[0072] The artificial intelligence component may comprise, at least in part, a knowledge graph-based model.

[0073] The artificial intelligence component may comprise, at least in part, a probabilistic graphbased model.

[0074] The artificial intelligence component may comprise, at least in part, an ensemble-based model.

[0075] The artificial intelligence component may comprise, at least in part, a natural language processing-based model. The artificial intelligence component may comprise, at least in part, an explainable artificial intelligence-based model. Preferably, the artificial intelligence component may comprise the explainable artificial intelligence-based model.

[0076] The system may be configured to allow changes to the explainable artificial intelligence-based model. The changes may be made in response to the prediction of the explainable artificial intelligence-based model, particularly, to correct an explanation provided by the artificial intelligence-based model.

[0077] The system may be configured to authenticate an identity before allowing the changes.

[0078] Authenticating the identity may comprise determining if a user requesting changes belongs to a pre-defined group of users.

[0079] The system may comprise a memory component configured to store the selection made by the user.

[0080] The system may be configured to associate a unique identifier with the user. The system may be further configured to store an association between the unique identifier and the selection made by the user. Thus, advantageously, the system may allow access to the selection made by any user.

[0081] The system may be configured to allow access to a supervising user of the selection made by the user. A supervising user may, generally, be an entity trusted by the user. For example, the user may be a child and the supervising user may be a parent or a teacher or a mentor of the child. Generally, the supervising user may be anyone who can provide a reliable estimate of the user's abilities.

[0082] Users may associate supervising users with a user account provided to them by the system voluntarily. Alternatively, the system may only allow users access (to the system) provided at least one supervising user has been associated with the user account.

[0083] The system may be configured to verify an identity of the supervising user before allowing access to the selection made by the user. The user may also be required to verify their identity by any suitable, known means.

[0084] The system may be configured to allow the supervising user to edit the selection made by the user. Thus, for example, a parent may review and / or edit the selection made by their child. This may be of advantage in accounting for the parent's assessment of the child's interests in connecting the child to the receiver. The system may be configured to connect the user to the receiver based, at least in part, on the updated selection.

[0085] The system may be configured to obtain a location of the user.

[0086] The system, particularly the sensory data component thereof, may be configured to adjust at least one of the plurality of sensory datasets based, at least in part, on the location of the user. Thus, the system may provide sensory datasets with which the user can associate themselves. For example, the sensory dataset may comprise an animation based on a popular cartoon character. The system may then adjust the sensory dataset based on a cartoon character popular at the user's location. The system may be appropriately configured to obtain information related to popular cartoon characters at any location, for example, by a connection to the Internet and a web-analytics service.

[0087] The system may be configured to obtain data related, at least in part, to an interest and / or a background of the user.

[0088] The system, particularly the sensory data component thereof, may be configured to adjust at least one of the plurality of sensory datasets based, at least in part, on the data related, at least in part, to an interest and / or a background of the user. The data related, at least in part, to an interest of the user may be of particular advantage in curating the sensory dataset according to interests of the user. For example, instead of adjusting the animation based on a cartoon character popular at the user's location, the system may, instead, adjust the animation based on the user's preferred cartoon character.

[0089] Further exemplarily, the system may be configured to connect the user to the receiver based, at least in part, on the data related, at least in part, to an interest of the user. For example, the system may obtain information about the kind of content the user consumes. The user's interests may indicate an interest, for example, in medical content. The system may then be configured to generate and / or provide sensory datasets, as described above, that may all relate to medical content but with varying degree of detail such as related to drug manufacture, surgery, radiological or pathological diagnosis, or other similar details.

[0090] The data related to a background of the user may, in particular, comprise data related to a residence status of the user at their location. For example, the residence status may be used to determine if the user is an immigrant. Further, the data related to a background of the user may comprise data related to a language best understood by the user. The system, particularly the sensory data component thereof, may be configured to adjust the sensory dataset accordingly. Alternatively, or additionally, the system may be configured to connect the user to the receiver in accordance with the language best understood by the user or their residence status. The system, particularly the artificial intelligence component thereof, may be further configured to generate data related, at least in part, to facilitating the connection between the user and the receiver. For example, the data may comprise a letter or a CV of the user. In particular, a large language model (LLM) may be trained and / or adapted and / or used to generate such data.

[0091] The system may be configured to generate the data related, at least in part, to facilitating the connection based, at least in part, on the selection made by the user.

[0092] According to a second aspect, the present invention relates to a method for connecting a user with a receiver, the method comprising : providing a plurality of sensory datasets to the user, and assisting the user in making a selection between the plurality of sensory datasets.

[0093] The method may comprise connecting the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user.

[0094] Assisting the user may comprise allowing the user to either select or deselect a sensory dataset.

[0095] Connecting the user to the receiver may be based, at least in part, on a set of sensory datasets selected by the user.

[0096] The method may comprise determining an optimal value for the sensory control parameter.

[0097] The method may comprise providing a sensory dataset with the optimal value of the sensory control parameter.

[0098] The plurality of sensory datasets may be divided among a plurality of sensory dataset layers, each of the plurality of sensory dataset layers comprising at least one sensory dataset.

[0099] The plurality of sensory dataset layers may comprise a first sensory dataset layer, that may be called a control parameter optimization layer, comprising a plurality of sensory datasets.

[0100] The plurality of sensory dataset layers may comprise a second sensory dataset layer.

[0101] The method may comprise providing any of the datasets in the second sensory dataset layer with the optimal value of the sensory control parameter.

[0102] The method may comprise determining a time taken by the user in making the selection between the plurality of sensory datasets. The method may comprise determining a time interval between providing the plurality of sensory datasets and the user making the selection.

[0103] Connecting the user to the receiver may be based, at least in part, on the time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0104] The method may comprise using, at least in part, an artificial intelligence-based model.

[0105] The method may comprise generating and / or modifying any of the plurality of sensory datasets using the artificial intelligence-based model.

[0106] The method may comprise determining a most appropriate receiver from the plurality of potential receivers based, at least in part, on the selection made by the user using the artificial intelligence-based model.

[0107] The method may comprise assigning a label to each of the plurality of potential receivers, wherein the label is representative of an appropriateness of the potential receiver, based, at least in part, on the selection made by the user using the artificial intelligence-based model.

[0108] The method may comprise connecting the user to the receiver based, at least in part, on the most appropriate receiver and / or on the labels assigned to each of the plurality of potential receivers using the artificial intelligence-based model.

[0109] The method may comprise, in response to connecting the user to the receiver, to prompt the user for feedback.

[0110] The method may comprise receiving the feedback from the user.

[0111] The method may comprise connecting the user to the receiver based, at least in part, on the feedback from a previous user.

[0112] The method may comprise determining the most appropriate receiver and / or assigning the labels to each of the plurality of potential receivers based, at least in part, on the feedback from a previous user.

[0113] Assisting the user in making a selection may comprise providing a virtual reality device to the user.

[0114] The method may comprise tracking eye motion of the user.

[0115] The method may comprise tracking physical motion of the user. Any of the plurality of sensory datasets may be representative of (pseudo) 3-dimensional (3D) sensory data.

[0116] Assisting the user in making the selection may be based, at least in part, on the motion of their eye(s).

[0117] Assisting the user in making the selection may be based, at least in part, on their physical motion.

[0118] The method may comprise connecting the user to a plurality of receivers.

[0119] Each of the plurality of receivers may correspond to one of the plurality of potential receivers.

[0120] The system as described above may be configured to perform the method as described above.

[0121] According to a third aspect, the present invention relates to a computer program product comprising instructions, when run on a data processing component of a system as described above, to perform the method as described above.

[0122] The present invention is also described by the following numbered embodiments.

[0123] Below, system embodiments will be discussed. These are abbreviated by the letter "S" followed by a number. Whenever reference is, herein, made to system embodiments, the following embodiments are meant.

[0124] 51. A system for connecting a user with a receiver, the system comprising : a sensory data component configured to provide a plurality of sensory datasets to the user, and a selection component configured to assist the user in making a selection between the plurality of sensory datasets.

[0125] 52. The system according to the preceding embodiment, wherein the system is configured to connect the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user.

[0126] 53. The system according to any of the preceding system embodiments, wherein each of the plurality of sensory datasets comprises a sensory control parameter.

[0127] 54. The system according to any of the preceding system embodiments, wherein at least one of the plurality of sensory datasets is representative of an image. 55. The system according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an image.

[0128] 56. The system according to any of the 2 preceding embodiments, wherein the sensory data component comprises a display.

[0129] 57. The system according to any of the 3 preceding embodiments and with the features of embodiment S3, wherein the sensory control parameter comprises any of a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0130] 58. The system according to any of the preceding system embodiments, wherein at least one of the plurality of sensory datasets is representative of an audio track.

[0131] 59. The system according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an audio track.

[0132] 510. The system according to any of the 2 preceding embodiments, wherein the sensory data component comprises a speaker and / or a headphone.

[0133] 511. The system according to any of the 3 preceding embodiments and with the features of embodiment S3, wherein the sensory control parameter comprises any of a frequency range, an amplitude, a timbre, harmonics and overtones, an attack, a decay, a sustain, a release, a reverberation, an echo, a phase, a filtering, a compression, a noise reduction, a stereo panning and / or modulation, and / or a total length.

[0134] 512. The system according to any of the preceding system embodiments, wherein at least one of the plurality of sensory datasets is representative of an animation.

[0135] 513. The system according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an animation.

[0136] 514. The system according to any of the 2 preceding embodiments and with the features of embodiment S3, wherein the sensory control parameter comprises any of a frame rate, a total length, a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0137] S15. The system according to any of the preceding system embodiments, wherein at least one of the plurality of sensory datasets is representative of a tactile stimulus. 516. The system according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of a tactile stimulus.

[0138] 517. The system according to any of the 2 preceding embodiments and with the features of embodiment S3, wherein the sensory control parameter comprises any of a pressure / force, a frequency of the stimulus, an amplitude of the stimulus, a texture, a temperature, a size, a shape, a location, a duration, a direction of stimulation, a pattern, a pressure distribution, a pain sensation to the stimulus, an adaptation to the stimulus.

[0139] 518. The system according to any of the preceding system embodiments, wherein the selection component is configured to allow the user to either select or deselect a sensory dataset.

[0140] 519. The system according to any of the preceding system embodiments, wherein the receiver corresponds to one of a plurality of potential receivers.

[0141] 520. The system according to the preceding embodiment, wherein each of the plurality of potential receivers is associated with a set of sensory datasets.

[0142] 521. The system according to the preceding embodiment, wherein each of the plurality of potential receivers is associated with a unique set of sensory datasets.

[0143] 522. The system according to any of the 2 preceding embodiments and with the features of embodiment S18, wherein connecting the user to the receiver is based, at least in part, on a set of sensory datasets selected by the user.

[0144] 523. The system according to any of the preceding system embodiments, wherein the system comprises a sensory control optimizer component.

[0145] 524. The system according to the preceding embodiment and with the features of embodiment S3, wherein the sensory control optimizer component is configured to determine an optimal value for the sensory control parameter.

[0146] 525. The system according to the preceding embodiment, wherein the optimal value for the sensory control parameter is determined based, at least in part, on the selection between the plurality of sensory datasets made by the user.

[0147] S26. The system according to any of the 2 preceding embodiments, wherein the sensory data component is further configured to provide a sensory dataset with the optimal value of the sensory control parameter. 527. The system according to any of the preceding system embodiments, wherein the system comprises a plurality of sensory dataset layers, and wherein each of the plurality of sensory dataset layers comprises at least one sensory dataset.

[0148] 528. The system according to the preceding embodiment, wherein the plurality of sensory dataset layers comprises a first sensory dataset layer, that may be called a control parameter optimization layer, comprising a plurality of sensory datasets.

[0149] 529. The system according to the preceding embodiment and with the features of embodiment S24, wherein the optimal value of the sensory control parameter is based, at least in part, on the selection made by the user between the plurality of sensory datasets in the control parameter optimization layer.

[0150] 530. The system according to any of the 3 preceding embodiments, wherein the plurality of sensory dataset layers comprises a second sensory dataset layer.

[0151] 531. The system according to the preceding embodiment and with the features of embodiment S26, wherein the sensory data component is configured to provide any of the datasets in the second sensory dataset layer with the optimal value of the sensory control parameter.

[0152] 532. The system according to any of the 2 preceding embodiments and with the features of embodiment S20, wherein the set of sensory datasets associated with each of the plurality of potential receivers comprises at least one sensory dataset from the second sensory dataset layer.

[0153] 533. The system according to any of the preceding system embodiments, wherein the system further comprises a timing component configured to determine a time taken by the user in making the selection between the plurality of sensory datasets.

[0154] 534. The system according to the preceding embodiment, wherein the timing component is configured to determine a time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0155] 535. The system according to the preceding embodiment, wherein connecting the user to the receiver is based, at least in part, on the time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0156] S36. The system according to any of the preceding system embodiments, wherein the system comprises an artificial intelligence component. 537. The system according to the preceding embodiment, wherein the artificial intelligence component is configured to modify and / or generate any of the plurality of sensory datasets.

[0157] 538. The system according to any of the 2 preceding embodiments, wherein the system is configured to send the selection between the plurality of sensory datasets made by the user to the artificial intelligence component.

[0158] 539. The system according to the preceding embodiment and with the features of embodiment S19, wherein the artificial intelligence component is configured to determine a most appropriate receiver from the plurality of potential receivers based, at least in part, on the selection made by the user.

[0159] 540. The system according to any of the 2 preceding embodiments and with the features of embodiment S19, wherein the artificial intelligence component is configured to assign a label to each of the plurality of potential receivers, wherein the label is representative of an appropriateness of the potential receiver, based, at least in part, on the selection made by the user.

[0160] 541. The system according to any of the 2 preceding embodiments, wherein the system is configured to connect the user to the receiver based, at least in part, on the most appropriate receiver and / or on the labels assigned to each of the plurality of potential receivers.

[0161] 542. The system according to any of the preceding system embodiments, wherein the system comprises a feedback component configured, in response to connecting the user to the receiver, to prompt the user for feedback.

[0162] 543. The system according to the preceding embodiment, wherein the feedback component is configured to receive the feedback from the user.

[0163] 544. The system according to the preceding embodiment, wherein the system is configured to connect the user to the receiver based, at least in part, on the feedback from a previous user.

[0164] 545. The system according to any of the 2 preceding embodiments and with the features of embodiment S36, wherein the feedback component is configured to send the feedback received from the user to the artificial intelligence component.

[0165] 546. The system according to the preceding embodiment and with the features of any of embodiments S41, and S42, wherein the artificial intelligence component is configured to determine the most appropriate receiver and / or to assign the labels to each of the plurality of potential receivers based, at least in part, on the feedback from a previous user. 547. The system according to any of the preceding system embodiments, wherein the system comprises a virtual reality device configured for use by the user.

[0166] 548. The system according to the preceding embodiment, wherein the virtual reality device comprises an eye-tracking component configured to track eye motion of the user.

[0167] 549. The system according to any of the 2 preceding embodiments, wherein the virtual reality device is configured to track physical motion of the user.

[0168] 550. The system according to any of the 3 preceding embodiments, wherein the sensory data component comprises the virtual reality device, or at least a part thereof.

[0169] 551. The system according to any of the 4 preceding embodiments, wherein the selection component comprises the virtual reality device, or at least a part thereof.

[0170] 552. The system according to any of the preceding system embodiments, wherein any of the plurality of sensory datasets is representative of (pseudo) 3-dimensional (3D) sensory data.

[0171] 553. The system according to any of the preceding system embodiments and with the features of embodiment S48, and S51, wherein the selection component is configured to assist the user in making the selection based, at least in part, on the motion of their eye(s).

[0172] 554. The system according to any of the preceding system embodiments and with the features of embodiment S49, and S51, wherein the selection component is configured to assist the user in making the selection based, at least in part, on their physical motion.

[0173] 555. The system according to any of the preceding system embodiments, wherein the system is configured to connect the user to a plurality of receivers.

[0174] 556. The system according to the preceding embodiment and with the features of embodiment S19, wherein each of the plurality of receivers corresponds to one of the plurality of potential receivers.

[0175] 557. The system according to any of the preceding system embodiments, wherein the system comprises a data processing component.

[0176] S58. The system according to any of the preceding system embodiments and with the features of embodiment S3, wherein the sensory control parameter comprises a plurality of sensory control parameters. 559. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a supervised learning-based model.

[0177] 560. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, an unsupervised learning-based model.

[0178] 561. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a transfer learning-based model.

[0179] 562. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a reinforcement learning-based model.

[0180] 563. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a deep learning-based model.

[0181] 564. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a hybrid model.

[0182] 565. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a knowledge graph-based model.

[0183] 566. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a probabilistic graph-based model.

[0184] 567. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, an ensemble-based model.

[0185] S68. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, a natural language processing-based model. 569. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the artificial intelligence component comprises, at least in part, an explainable artificial intelligence-based model.

[0186] 570. The system according to the preceding embodiment, wherein the system is configured to allow changes to the explainable artificial intelligence-based model.

[0187] 571. The system according to the preceding embodiment, wherein the system is configured to authenticate an identity before allowing the changes.

[0188] 572. The system according to the preceding embodiment, wherein authenticating the identity comprises determining if a user requesting changes belongs to a pre-defined group of users.

[0189] 573. The system according to any of the preceding system embodiments, wherein the system comprises a memory component configured to store the selection made by the user.

[0190] 574. The system according to the preceding embodiment, wherein the system is configured to associate a unique identifier with the user.

[0191] 575. The system according to any of the 2 preceding embodiments, wherein the system is configured to allow access to a supervising user of the selection made by the user.

[0192] 576. The system according to the preceding embodiment, wherein the system is configured to verify an identity of the supervising user before allowing access to the selection made by the user.

[0193] 577. The system according to any of the 2 preceding embodiments, wherein the system is configured to allow the supervising user to edit the selection made by the user.

[0194] 578. The system according to the preceding embodiment and with the features of embodiment S2, wherein the system is configured to connect the user to the receiver based, at least in part, on the updated selection.

[0195] 579. The system according to any of the preceding system embodiments, wherein the system is configured to obtain a location of the user.

[0196] S80. The system according to the preceding embodiment, wherein the system, particularly the sensory data component thereof, is configured to adjust at least one of the plurality of sensory datasets based, at least in part, on the location of the user. 581. The system according to any of the preceding system embodiments, wherein the system is configured to obtain data related, at least in part, to an interest and / or a background of the user.

[0197] 582. The system according to the preceding embodiment, wherein the system, particularly the sensory data component thereof, is configured to adjust at least one of the plurality of sensory datasets based, at least in part, on the data related, at least in part, to an interest of the user.

[0198] 583. The system according to any of the preceding system embodiments and with the features of embodiment S36, wherein the system, particularly the artificial intelligence component thereof, is configured to generate data related, at least in part, to facilitating the connection between the user and the receiver.

[0199] 584. The system according to the preceding embodiment, wherein the system is configured to generate the data related, at least in part, to facilitating the connection based, at least in part, on the selection made by the user.

[0200] Below, method embodiments will be discussed. These are abbreviated by the letter "M" followed by a number. Whenever reference is, herein, made to method embodiments, the following embodiments are meant.

[0201] Ml. A method for connecting a user with a receiver, the method comprising: providing a plurality of sensory datasets to the user, and assisting the user in making a selection between the plurality of sensory datasets.

[0202] M2. The method according to the preceding embodiment, wherein the method comprises connecting the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user.

[0203] M3. The method according to any of the preceding method embodiments, wherein each of the plurality of sensory datasets comprises a sensory control parameter.

[0204] M4. The method according to any of the preceding method embodiments, wherein at least one of the plurality of sensory datasets is representative of an image.

[0205] M5. The method according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an image.

[0206] M6. The method according to any of the 2 preceding embodiments and with the features of embodiment M3, wherein the sensory control parameter comprises any of a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0207] M7. The method according to any of the preceding method embodiments, wherein at least one of the plurality of sensory datasets is representative of an audio track.

[0208] M8. The method according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an audio track.

[0209] M9. The method according to any of the 2 preceding embodiments and with the features of embodiment M3, wherein the sensory control parameter comprises any of a frequency range, an amplitude, a timbre, harmonics and overtones, an attack, a decay, a sustain, a release, a reverberation, an echo, a phase, a filtering, a compression, a noise reduction, a stereo panning and / or modulation, and / or a total length.

[0210] MIO. The method according to any of the preceding method embodiments, wherein at least one of the plurality of sensory datasets is representative of an animation.

[0211] Mil. The method according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of an animation.

[0212] M12. The method according to any of the 2 preceding embodiments and with the features of embodiment M3, wherein the sensory control parameter comprises any of a frame rate, a total length, a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

[0213] M13. The method according to any of the preceding method embodiments, wherein at least one of the plurality of sensory datasets is representative of a tactile stimulus.

[0214] M14. The method according to the preceding embodiment, wherein each of the plurality of sensory datasets is representative of a tactile stimulus.

[0215] M15. The method according to any of the 2 preceding embodiments and with the features of embodiment M3, wherein the sensory control parameter comprises any of a pressure / force, a frequency of the stimulus, an amplitude of the stimulus, a texture, a temperature, a size, a shape, a location, a duration, a direction of stimulation, a pattern, a pressure distribution, a pain sensation to the stimulus, an adaptation to the stimulus.

[0216] M16. The method according to any of the preceding method embodiments, wherein assisting the user comprises allowing the user to either select or deselect a sensory dataset. M17. The method according to any of the preceding method embodiments, wherein the receiver corresponds to one of a plurality of potential receivers.

[0217] M18. The method according to the preceding embodiment, wherein each of the plurality of potential receivers is associated with a set of sensory datasets.

[0218] M19. The method according to the preceding embodiment, wherein each of the plurality of potential receivers is associated with a unique set of sensory datasets.

[0219] M20. The method according to any of the 2 preceding embodiments and with the features of embodiment M16, wherein connecting the user to the receiver is based, at least in part, on a set of sensory datasets selected by the user.

[0220] M21. The method according to any of the preceding method embodiments and with the features of embodiment M3, wherein the method comprises determining an optimal value for the sensory control parameter.

[0221] M22. The method according to the preceding embodiment, wherein the optimal value for the sensory control parameter is determined based, at least in part, on the selection between the plurality of sensory datasets made by the user.

[0222] M23. The method according to any of the 2 preceding embodiments, wherein the method comprises providing a sensory dataset with the optimal value of the sensory control parameter.

[0223] M24. The method according to any of the preceding method embodiments, wherein the plurality of sensory datasets is divided among a plurality of sensory dataset layers, each of the plurality of sensory dataset layers comprising at least one sensory dataset.

[0224] M25. The method according to the preceding embodiment, wherein the plurality of sensory dataset layers comprises a first sensory dataset layer, that may be called a control parameter optimization layer, comprising a plurality of sensory datasets.

[0225] M26. The method according to the preceding embodiment and with the features of embodiment M21, wherein the optimal value of the sensory control parameter is based, at least in part, on the selection made by the user between the plurality of sensory datasets in the control parameter optimization layer.

[0226] M27. The method according to any of the 3 preceding embodiments, wherein the plurality of sensory dataset layers comprises a second sensory dataset layer. M28. The method according to the preceding embodiment and with the features of embodiment M23, wherein the method comprises providing any of the datasets in the second sensory dataset layer with the optimal value of the sensory control parameter.

[0227] M29. The method according to any of the 2 preceding embodiments and with the features of embodiment M18, wherein the set of sensory datasets associated with each of the plurality of potential receivers comprises at least one sensory dataset from the second sensory dataset layer.

[0228] M30. The method according to any of the preceding method embodiments, wherein the method comprises determining a time taken by the user in making the selection between the plurality of sensory datasets.

[0229] M31. The method according to the preceding embodiment, wherein the method comprises determining a time interval between providing the plurality of sensory datasets and the user making the selection.

[0230] M32. The method according to the preceding embodiment, wherein connecting the user to the receiver is based, at least in part, on the time interval between the sensory data component providing the plurality of sensory datasets and the user making the selection.

[0231] M33. The method according to any of the preceding method embodiments, wherein the method comprises using, at least in part, an artificial intelligence-based model.

[0232] M34. The method according to the preceding embodiment, wherein the method comprises generating and / or modifying any of the plurality of sensory datasets using the artificial intelligence-based model.

[0233] M35. The method according to any of the 2 preceding embodiments and with the features of embodiment M17, wherein the method comprises determining a most appropriate receiver from the plurality of potential receivers based, at least in part, on the selection made by the user using the artificial intelligence-based model.

[0234] M36. The method according to any of the 3 preceding embodiments and with the features of embodiment M17, wherein the method comprises assigning a label to each of the plurality of potential receivers, wherein the label is representative of an appropriateness of the potential receiver, based, at least in part, on the selection made by the user using the artificial intelligence-based model.

[0235] M37. The method according to any of the 2 preceding embodiments, wherein the method comprises connecting the user to the receiver based, at least in part, on the most appropriate receiver and / or on the labels assigned to each of the plurality of potential receivers using the artificial intelligence-based model.

[0236] M38. The method according to any of the preceding method embodiments, wherein the method comprises, in response to connecting the user to the receiver, to prompt the user for feedback.

[0237] M39. The method according to the preceding embodiment, wherein the method comprises receiving the feedback from the user.

[0238] M40. The method according to the preceding embodiment, wherein the method comprises connecting the user to the receiver based, at least in part, on the feedback from a previous user.

[0239] M41. The method according to any of the 2 preceding embodiments and with the features of any of embodiments M35, and M36, wherein the method comprises determining the most appropriate receiver and / or assigning the labels to each of the plurality of potential receivers based, at least in part, on the feedback from a previous user.

[0240] M42. The method according to any of the preceding method embodiments, wherein assisting the user in making a selection comprises providing a virtual reality device to the user.

[0241] M43. The method according to the preceding embodiment, wherein the method comprises tracking eye motion of the user.

[0242] M44. The method according to any of the 2 preceding embodiments, wherein the method comprises tracking physical motion of the user.

[0243] M45. The method according to any of the preceding method embodiments, wherein any of the plurality of sensory datasets is representative of (pseudo) 3-dimensional (3D) sensory data.

[0244] M46. The method according to any of the preceding method embodiments and with the features of embodiment M43, wherein assisting the user in making the selection is based, at least in part, on the motion of their eye(s).

[0245] M47. The method according to any of the preceding method embodiments and with the features of embodiment M44, wherein assisting the user in making the selection is based, at least in part, on their physical motion.

[0246] M48. The method according to any of the preceding method embodiments, wherein the method comprises connecting the user to a plurality of receivers. M49. The method according to the preceding embodiment and with the features of embodiment M17, wherein each of the plurality of receivers corresponds to one of the plurality of potential receivers.

[0247] M50. The method according to any of the preceding method embodiments, wherein the method comprises storing the selection made by the user.

[0248] M51. The method according to the preceding embodiment, wherein the method comprises associating a unique identifier with the user.

[0249] M52. The method according to any of the 2 preceding embodiments, wherein the method comprises allowing access to a supervising user of the selection made by the user.

[0250] M53. The method according to the preceding embodiment, wherein the comprises verifying an identity of the supervising user before allowing access to the selection made by the user.

[0251] M54. The method according to any of the 2 preceding embodiments, wherein the method comprises allowing the supervising user to edit the selection made by the user.

[0252] M55. The method according to the preceding embodiment and with the features of embodiment M2, wherein the method comprises connecting the user to the receiver based, at least in part, on the updated selection.

[0253] M56. The method according to any of the preceding method embodiments, wherein the method comprises obtaining a location of the user.

[0254] M57. The method according to the preceding embodiment, wherein the method comprises adjusting at least one of the plurality of sensory datasets based, at least in part, on the location of the user.

[0255] M58. The method according to any of the preceding method embodiments, wherein the method comprises obtaining data related, at least in part, to an interest and / or a background of the user.

[0256] M59. The method according to the preceding embodiment, wherein the method comprises adjusting at least one of the plurality of sensory datasets based, at least in part, on the data related, at least in part, to an interest of the user.

[0257] M60. The method according to any of the preceding method embodiments, wherein the method comprises generating data related, at least in part, to facilitating the connection between the user and the receiver. M61. The method according to the preceding embodiment, wherein the method comprises generating the data related, at least in part, to facilitating the connection based, at least in part, on the selection made by the user.

[0258] S85. The system according to any of the preceding system embodiments, wherein the system is configured to perform the method according to any of the preceding method embodiments.

[0259] Below, computer program product embodiments will be discussed. These are abbreviated by the letter "C" followed by a number. Whenever reference is, herein, made to computer program product embodiments, the following embodiments are meant.

[0260] Cl. A computer program product comprising instructions, when run on a data processing component of a system according to any of the preceding system embodiments, to perform the method according to any of the preceding method embodiments.

[0261] Brief Description of Figures

[0262] Figure 1 depicts an embodiment of a system for connecting a user with a receiver, and

[0263] Figure 2 depicts an embodiment of a method for connecting a user with a receiver.

[0264] Detailed Description of Figures

[0265] Figure 1 depicts one embodiment of a system 1 configured for connecting a user 2 to a receiver 3. The double arrows in Figure 1 depict possible directions of data flow between different components of the system 1. Note, however, that the depicted data flows may not be considered exhaustive, or limiting, and that other, different directions of data flow may also be possible in some embodiments of the system 1.

[0266] The system 1 may comprise a sensory data component 101 configured for providing a plurality of sensory datasets 102 to the user 2. The system 1 may further comprise a selection component 111 configured to allow the user 2 to make a selection between the plurality of sensory datasets 102.

[0267] Each of the plurality of sensory datasets 102 may comprise a sensory control parameter. The sensory control parameter may be of advantage in controlling a sensory response of the user 2 to the sensory dataset 102. Examples of sensory control parameters will be described further below.

[0268] The sensory dataset 102 may comprise data representative of an image. In other words, the sensory dataset 102, or at least a part thereof, may be represented as an image. Representation as an image may be understood to comprise the ability of the sensory data component 101 to render the sensory dataset 102, or at least the part thereof, as an image.

[0269] The image may comprise a sensory control parameter as described above. In some embodiments, the image may comprise a plurality of sensory control parameters. For example, the sensory control parameter(s) may comprise any of a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression. Thus, for example, when the sensory control parameter comprises the brightness of the image, the sensory response of the user 3 may be changed as the brightness of the image is changed.

[0270] The sensory dataset 102 may comprise data representative of an audio track. In other words, the sensory dataset 102, or at least a part thereof, may be represented as an audio track. Representation as an audio track may be understood to comprise the ability of the sensory data component 101 to render the sensory dataset 102, or at least the part thereof, as an audio track.

[0271] The audio track may comprise a sensory control parameter as described above. In some embodiments, the audio track may comprise a plurality of sensory control parameters. For example, the sensory control parameter(s) may comprise any of a frequency range, an amplitude, a timbre, harmonics and overtones, an attack, a decay, a sustain, a release, a reverberation, an echo, a phase, a filtering, a compression, a noise reduction, a stereo panning and / or modulation, and / or a total length. Thus, for example, when the sensory control parameter comprises the frequency range of the audio track, the sensory response of the user 3 may be changed as the frequency range of the audio track is changed.

[0272] The sensory dataset 102 may comprise data representative of an animation. In other words, the sensory dataset 102, or at least a part thereof, may be represented as an animation. Representation as an animation may be understood to comprise the ability of the sensory data component 101 to render the sensory dataset 102, or at least the part thereof, as an animation.

[0273] The animation may comprise a sensory control parameter as described above. In some embodiments, the animation may comprise a plurality of sensory control parameters. For example, the sensory control parameter(s) may comprise any of a frame rate, a total length, a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression. Thus, for example, when the sensory control parameter comprises the frame rate of the animation, the sensory response of the user 3 may be changed as the frame rate of the animation is changed. Note that in the above, the term "animation" may be understood to also comprise video, comprising not only a sequence of images but also an audio track interlaced with the sequence of images. Thus, generally, any of the plurality of sensory datasets 102 may also be each representative of a video. Moreover, the sensory control parameters may comprise not only the sensory control parameters described above for an animation, but also those described further above for an audio track.

[0274] The sensory dataset 102 may comprise data representative of a tactile stimulus. In other words, the sensory dataset 102, or at least a part thereof, may be represented as a tactile stimulus. Representation as a tactile stimulus may be understood to comprise the ability of the sensory data component 101 to render the sensory dataset 102, or at least the part thereof, as a tactile stimulus. In particular, the sensory data component 101 may comprise suitable means to provide the tactile stimulus, such as an actuator controlled by the sensory data component 101 and in communication (i.e., capable of exchanging energy) with the user 2.

[0275] The tactile stimulus may comprise a sensory control parameter as described above. In some embodiments, the tactile stimulus may comprise a plurality of sensory control parameters. For example, the sensory control parameter(s) may comprise any of a pressure / force, a frequency of the stimulus, an amplitude of the stimulus, a texture, a temperature, a size, a shape, a location, a duration, a direction of stimulation, a pattern, a pressure distribution, a pain sensation to the stimulus, an adaptation to the stimulus. Thus, for example, when the sensory control parameter comprises the pressure applied as part of the tactile stimulus, the sensory response of the user 3 may be changed as the pressure applied is changed.

[0276] The selection component 111 may be configured to allow the user 2 to either select or deselect a sensory dataset 102. In other words, the selection between the plurality of sensory datasets 102 may be made one-by-one, i.e., for each of the plurality of sensory datasets 102, the user 2 may be asked to either select or deselect the sensory dataset 102. Alternatively, or additionally, the selection may be made in one go, i.e., all of the plurality of sensory datasets 102 may be provided to the user 2 at once, and the user 2 may select some of the plurality of sensory datasets 102. Note that providing all of the sensory datasets 102 at once may not be possible, or sensible, for all kinds of sensory datasets 102 such as those representative of audio tracks or animations.

[0277] The system 1 may comprise a sensory control optimizer component 121. The sensory control optimizer component 121 may be configured to determine an optimal value for the sensory control parameter, or for any of the plurality of sensory control parameters.

[0278] The optimal value for the sensory control parameter, or for any of the plurality of sensory control parameters, may be determined based, at least in part, on the selection between the plurality of different datasets 102 made by the user. Based on the set of sensory datasets 102 which the user 2 selects, the optimal value of one, or of some of the plurality of, sensory control parameter(s) may be determined.

[0279] The optimal value of any of the sensory control parameters may be determined based on a statistical distribution of the sensory control parameter values of the sensory datasets 102 selected by the user 2, such as an average, a median, a maximum, a minimum, or a quartile.

[0280] Alternatively, or additionally, the optimal value may be determined based on an artificial intelligence-based model that may, for example, accept as input the sensory datasets 102, or the sensory control parameter(s) thereof, selected by the user 2 and output the optimal value for any of the sensory control parameters, as will be further described below.

[0281] Thus, the sensory control optimizer component 121 may be of advantage in calibrating the system 1 for the user 2. Once the system 1 has been calibrated for the user 2, as described above, the system 1, particularly the sensory data component 101 thereof, may be configured to provide the plurality of sensory datasets 102 with the optimal value(s) of the sensory control parameter(s).

[0282] The receiver 3 may correspond to one of a plurality of potential receivers. Each of the plurality of potential receivers may be associated with a set of sensory datasets 102. More particularly, in some embodiments, each of the plurality of potential receivers may be associated with a distinct set of sensory datasets 102.

[0283] For example, a first potential receiver may be associated with a first set of sensory datasets 102, the first set comprising at least one sensory dataset 102. Further, a second potential receiver may be associated with a second set of sensory datasets 102, the second set comprising at least one sensory dataset 102. Then, an intersection of the first set and the second set may be empty. However, in some embodiments, the first set and the second set need not have an empty intersection.

[0284] Each sensory dataset 102 in the set of sensory datasets 102 associated with a potential receiver may be representative of a characteristic of the potential receiver. For example, the potential receiver may comprise a hospital, and the set of sensory datasets 102 associated with the hospital may comprise images representative of a hospital.

[0285] The system 1 may be configured to connect the user 2 to the receiver 3 based, at least in part, on a set of sensory datasets 102 selected by the user 2. In particular, the set of sensory datasets 102 may be compared to the set associated with each of the potential receivers, and a connection may be established when the sets are equal.

[0286] In some embodiments, however, a measure of distance between the sets may be used to connect the user 2 to the receiver 3 such that the user 2 is connected to the receiver 3 when the set of sensory datasets 102 selected by the user 2 is close to the set associated with the receiver 3, where closeness may be determined based on the distance between the two sets. For example, the measure of distance may correspond to a cardinality of the intersection between the two sets, and a connection may be established when the cardinality is greater than, say 4.

[0287] Further, comparing the set of sensory datasets 102 selected by the user to any of the sets associated with each of the plurality of potential receivers may comprise disregarding the value(s) of the sensory control parameter(s).

[0288] Note, further, that the user 2 may be connected to a plurality of the potential receivers, so long as the condition for establishing a connection is fulfilled, as described above.

[0289] The system 1 may comprise a plurality of sensory dataset layers. Each of the plurality of sensory dataset layers may comprise at least one sensory dataset. The plurality of sensory dataset layers may be of advantage in connecting the user 2 with the receiver 3 as will be described further below.

[0290] The plurality of sensory dataset layers may comprise a first layer, that may be called a control parameter optimization layer. The control parameter optimization layer may comprise a plurality of sensory datasets 102. The plurality of sensory datasets 102 in the control parameter optimization layer may be of advantage in optimization of the sensory control parameter(s) by the sensory control optimizer component 121.

[0291] For example, the plurality of sensory datasets 102 in the control parameter optimization layer may comprise sensory datasets 102 such that the value of at least one sensory control parameter is different between any pair of the plurality of sensory datasets 102 in the control parameter optimization layer.

[0292] The sensory data component 101 may be configured to provide at least a plurality of sensory datasets 102 in the control parameter optimization layer to the user 2. The user 2 may select a subset of the plurality of sensory datasets 102 from the control parameter optimization layer, and the sensory control optimizer component 121 may optimize the value(s) of the sensory control parameter(s) based on the selection made by the user 2.

[0293] For example, as described above, the plurality of sensory datasets 102 in the control parameter optimization layer may comprise sensory datasets 102 differing in the value(s) of their sensory control parameter(s). The selection made by the user 2 may be indicative of the user's preference for the optimal value(s) of the sensory control parameter(s). Thus, based on this selection, the optimal value(s) may be determined. The plurality of sensory dataset layers may comprise a second sensory dataset layer. Any of the datasets in the second sensory dataset layer may allow the value(s) of their sensory control parameter(s) to be set. For example, the sensory data component 101 may be configured to set the value(s) of the sensory control parameter(s).

[0294] The sensory data component 101 may be configured to provide any of the datasets in the second sensory dataset layer with the optimal value(s) of the sensory control parameter(s).

[0295] The set of sensory datasets 102 associated with any of the potential receivers, as described above, may comprise at least one sensory dataset 102 from each of the plurality of sensory dataset layers.

[0296] Each of the sensory datasets 102 from each successive sensory dataset layer may be associated with a decreasing number of potential receivers. For example, a sensory dataset 102 from the first sensory dataset layer may be associated with a first number of potential receivers. A sensory dataset 102 from the second sensory dataset layer may be associated with a second number of potential receivers. Then, the first number may be at least as large as the second number. Thus, selecting between the plurality of sensory datasets 102 from each of the sensory dataset layers may allow the user 2 to be connected to the receiver 3 more efficiently.

[0297] In some embodiments, however, the association with a decreasing number of potential receivers may only hold for sensory datasets 102 from the second sensory dataset layer onwards, i.e., any of the sensory datasets 102 in the control parameter optimization layer may be associated with fewer number of potential receivers than any of the sensory datasets 102 in the second (or further) sensory dataset layer. In particular, any of the sensory datasets 102 in the control parameter optimization layer may not be associated with any of the plurality of potential receivers such that the sensory datasets 102 in the control parameter optimization layer may only be used for optimizing the value(s) of the sensory control parameter(s).

[0298] The system 1 may further comprise a timing component 131. The timing component 131 may be of further advantage in improving an efficiency of connecting the user 2 to the receiver 3 as will be described further below.

[0299] The timing component 131 may be configured to determine a time taken by the user 2 in making the selection between the plurality of sensory datasets 102. In particular, the timing component 131 may be configured to determine a time interval between the sensory data component 101 providing any of the plurality of sensory datasets 102, and the user 2 making the selection.

[0300] For example, when the sensory data component 101 is configured to provide the plurality of sensory datasets 102 one-by-one, and the user 2 selects or deselects the sensory dataset 102, as described above, the timing component 131 may be configured to determine the time interval between the provision of the sensory dataset 102 by the sensory data component 101, and the selection / deselection of the sensory dataset 102 by the user 2.

[0301] Further exemplarily, when the sensory data component 101 is configured to provide the plurality of sensory datasets 102 all at once, as described above, the timing component 131 may be configured to determine a time interval between when a sensory dataset 102 is provided to the user 2 (that may, for example, correspond to a time when the sensory dataset 102 is first visible to the user 2 when the sensory dataset 102 is representative of an image), and when the user 2 selects / deselects it.

[0302] Connecting the user 2 to the receiver 3 may be further based, at least in part, on the time taken by the user 2 to make the selection. In particular, a weight may be assigned to a sensory dataset 102 that is selected by the user 2, that may be inversely proportional to the time taken to select it.

[0303] The receiver 3 that is connected to the user 2 may then be determined based on a total of the weights assigned to each of the sensory datasets 102 associated with that receiver 3. Thus, generally, the faster the user 2 selects a sensory dataset 102, the more likely it is that the user 2 is connected to a receiver 3 with whom the sensory dataset 102 is associated.

[0304] The system 1 may comprise an artificial intelligence component 141. The artificial intelligence component 141 may be configured for various tasks as will be further described below.

[0305] The artificial intelligence component 141 may be configured to generate any of the plurality of sensory datasets 102. Generating any of the plurality of sensory datasets 102 may comprise sending a text prompt to the artificial intelligence component 141. Alternatively, or additionally, it may comprise sending an image, an audio, an animation, or a video prompt. The artificial intelligence component 141 may generate any of the plurality of sensory datasets 102 using supervised or unsupervised machine learning.

[0306] For example, the artificial intelligence component 141 can comprise a Generative Adversarial Network (GAN). The sensory dataset 102 to be generated may comprise, for example, an image, and the GAN may be trained using data comprising a text prompt and an expected image for the prompt. When the sensory dataset 102 to be generated may comprise, for example, a video, the GAN may be trained using a text prompt and an expected video, or at least a snippet thereof. Further exemplarily, when the GAN is used to generate a pseudo-3D dataset 102 as described further below, particularly for use with a virtual reality device 161, the GAN may be trained using training data comprising a video. Generally, it may be understood that any known techniques for generating data may be used. The system 1 may be configured to send to the artificial intelligence component 141 the selection of sensory datasets made by the user 2. For example, each of the plurality of sensory datasets 102 may comprise a unique identifier, and the system 1 may send the identifiers corresponding to each of the sensory datasets 102 selected by the user 2. Alternatively, or additionally, the system 1 may be configured to send each of the plurality of sensory datasets 102 selected by the user 2.

[0307] The artificial intelligence component 141 may be configured to determine the optimal value(s) of the sensory control parameter(s) based, at least in part, on the set of selected sensory datasets received. For example, the artificial intelligence component 141 may comprise a module (that may be understood to comprise one or more functions) that may be called when the optimal value(s) of the sensory control parameter(s) have to be determined.

[0308] Alternatively, or additionally, the artificial intelligence component 141 may be configured to determine the receiver 3, or a plurality thereof, to which the user 2 is connected, from among the plurality of potential receivers, based, at least in part, on the set of selected sensory datasets received.

[0309] For example, the artificial intelligence component 141 may be configured to determine a most appropriate receiver from among the plurality of potential receivers. Alternatively, or additionally, the artificial intelligence component 141 may be configured to assign a label to each of the plurality of potential receivers, wherein the label is representative of an appropriateness of the potential receiver. This may be of advantage in determining a ranking of potential receivers to which the user 2 may be connected.

[0310] The system 1 may comprise a feedback component 151 configured, in response to connecting the user 2 to the receiver 3, to prompt the user 2 for feedback. Additionally, or alternatively, the feedback component 151 may be configured, in response to connecting the user 2 to the receiver 3, to prompt the receiver 3 for feedback.

[0311] The system 1 may be configured to connect the user 2 to the receiver 3 based, at least in part, on the feedback received from a previous user 2, and / or a previous receiver 3.

[0312] In particular, the feedback component 151 may be configured to send the feedback received from a first user 2 and / or a first receiver 3 to the artificial intelligence component 141. The artificial intelligence component 141 may be configured to update an artificial intelligencebased model for connecting a user 2 to a receiver 3 based, at least in part, on the received feedback. Then, the updated model may be used to connect a second user 2 to a second receiver 3.

[0313] The system 1 may further comprise a virtual reality device 161 configured for use by the user 2. The virtual reality device 161 may comprise a set of virtual reality glasses that may be worn by the user 2. Alternatively, or additionally, the virtual reality device 161 may comprise means for providing tactile stimulus to the user 2. For example, the virtual reality device 161 may comprise one or more actuators, controlled by a microcontroller. Further exemplarily, the virtual reality device 161 may comprise a bodysuit comprising a plurality of actuators embedded in the bodysuit. Generally, any suitable configuration of actuators may be used.

[0314] The virtual reality device 161 may additionally, or alternatively, comprise means for tracking motion. Generally, it may be understood that the virtual reality device 161 may be used to track a physiological response of the user 2 to any of the plurality of sensory datasets 102.

[0315] For example, the virtual reality device 161 may comprise means for tracking motion of the eyes of the user 2. In particular, means for tracking eye motion may be comprised in the virtual reality glasses.

[0316] Further exemplarily, the virtual reality device 161 may comprise means for tracking motion of any of the body parts of the user 2. In particular, the virtual reality device 161 may comprise one or more inertial sensors that may be arranged to the body part of the user 2 to be tracked. For example, inertial sensors may be arranged to each of the fingers of one or both hands of the user 2.

[0317] Tracking the physiological response of the user 2 may be of advantage in determining the selection between the plurality of sensory datasets 102 made by the user 2. In particular, the sensory data component 101 may comprise the virtual reality device 161, or at least a part thereof. For example, the sensory data component 101 may comprise a display of the virtual reality glasses. Alternatively, or additionally, the sensory data component 101 may comprise any of the actuators for tactile stimulus.

[0318] Further, the selection component 111 may comprise the virtual reality device 161, or at least a part thereof. For example, the selection component 111 may comprise the eye-motion- tracking means of the virtual reality device 111. Alternatively, or additionally, the selection component 111 may comprise the any of the inertial sensors.

[0319] Any of the plurality of sensory datasets 102 may be representative of (pseudo) 3-dimensional (3D) sensory data. Pseudo-3D sensory data may be understood to comprise data that may be represented as a 3D scene in virtual reality glasses, for example. For example, the pseudo- 30 sensory data may comprise any of a hologram or a stereographic image. Generally, the pseudo-3D data may be understood to comprise any data that may be virtual and 3D.

[0320] The virtual reality device 161 may be of advantage in connecting the user 2 to the receiver 3.

[0321] For example, first, the plurality of sensory datasets 102 may be provided to the user 2, by displaying in the virtual reality glasses. Then, the user 2 may either select / deselect a sensory dataset 102 either by a motion of their eyes, as tracked through means in the virtual reality glasses, or by moving, for example, their hands or fingers or nodding their head, as tracked by the inertial sensor(s) arranged to these parts. The selection made by the user 2 may then be used to connect to the receiver 3 as described above.

[0322] Figure 2 depicts an embodiment of a method according to the present invention. The method may comprise a first step, Pl, providing a plurality of sensory datasets 102 to the user 2 for calibration. The next step, P2, may comprise optimizing the sensory control parameter(s) as described above. A further step, P3, may comprise providing at least one sensory dataset 102 to the user 2 with the optimal value(s) of the sensory parameter(s). The next step, P4, may comprise determining whether or not further sensory datasets 102 are to be provided to the user 2. If more sensory datasets 102 need to be provided, step P3 is repeated. If no further sensory datasets 102 need to be provided, the next step, P5, may comprise determining the receiver 3 from among the plurality of potential receivers. In the next step, P6, a connection may be established between the user 2 and the receiver 3. Finally, in a step, P7, a feedback may be sought from the user 2 and / or the receiver 3.

[0323] Overall, embodiments of the present technology thus allow connecting a user to a receiver more efficiently and with greater reliability.

[0324] Whenever a relative term, such as "about", "substantially" or "approximately" is used in this specification, such a term should also be construed to also include the exact term. That is, e.g., "substantially straight" should be construed to also include "(exactly) straight".

[0325] Whenever steps were recited in the above or also in the appended claims, it should be noted that the order in which the steps are recited in this text may be accidental. That is, unless otherwise specified or unless clear to the skilled person, the order in which steps are recited may be accidental. That is, when the present document states, e.g., that a method comprises steps (A) and (B), this does not necessarily mean that step (A) precedes step (B), but it is also possible that step (A) is performed (at least partly) simultaneously with step (B) or that step (B) precedes step (A). Furthermore, when a step (X) is said to precede another step (Z), this does not imply that there is no step between steps (X) and (Z). That is, step (X) preceding step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Yl), ..., followed by step (Z). Corresponding considerations apply when terms like "after" or "before" are used.

[0326] While in the above, preferred embodiments have been described with reference to the accompanying drawings, the skilled person will understand that these embodiments were provided for illustrative purpose only and should by no means be construed to limit the scope of the present invention, which is defined by the claims.

Claims

Claims1. A system for connecting a user with a receiver, the system comprising : a sensory data component configured to provide a plurality of sensory datasets to the user, and a selection component configured to assist the user in making a selection between the plurality of sensory datasets, wherein the system is configured to connect the user to the receiver based, at least in part, on the selection between the plurality of sensory datasets made by the user.

2. The system according to the preceding claim, wherein each of the plurality of sensory datasets comprises a sensory control parameter.

3. The system according to the preceding claim, wherein at least one of the plurality of sensory datasets is representative of an image, wherein the sensory control parameter comprises any of a brightness, a contrast, a saturation, a hue, a sharpness, a gamma, a white balance, an aspect ratio, a resolution, a noise reduction, a color grading, a spatial filtering and / or a signal compression.

4. The system according to any of the preceding claims, wherein the selection component is configured to allow the user to either select or deselect a sensory dataset.

5. The system according to the preceding claim, wherein the receiver corresponds to one of a plurality of potential receivers, wherein each of the plurality of potential receivers is associated with a set of sensory datasets, wherein connecting the user to the receiver is based, at least in part, on a set of sensory datasets selected by the user.

6. The system according to any of the preceding claims and with the features of claim 2, wherein the system comprises a sensory control optimizer component, wherein the sensory control optimizer component is configured to determine an optimal value for the sensory control parameter.

7. The system according to the preceding claim, wherein the optimal value for the sensory control parameter is determined based, at least in part, on the selection between the plurality of sensory datasets made by the user.

8. The system according to any of the preceding claims, wherein the system comprises a plurality of sensory dataset layers, and wherein each of the plurality of sensory dataset layers comprises at least one sensory dataset.

9. The system according to the preceding claim and with the features of claim 6, wherein the optimal value of the sensory control parameter is based, at least in part, on theselection made by the user between the plurality of sensory datasets in the control parameter optimization layer.

10. The system according to any of the preceding claims, wherein the system comprises a data processing component.

11. A method for connecting a user with a receiver, the method comprising: providing a plurality of sensory datasets to the user, and assisting the user in making a selection between the plurality of sensory datasets.

12. The method according to preceding claim, wherein the method comprises determining a time taken by the user in making the selection between the plurality of sensory datasets.

13. The method according to the preceding claim, wherein the method comprises determining a time interval between providing the plurality of sensory datasets and the user making the selection.

14. The method according to any of the 2 preceding claims, wherein the method comprises using, at least in part, an artificial intelligence-based model, and wherein the method comprises generating and / or modifying any of the plurality of sensory datasets.

15. A computer program product comprising instructions, when run on a data processing component of a system according to any of the claims 1 to 10, to perform the method according to any of the claims 11 to 14.

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