Visualization of physical characteristics in augmented reality

A system and method for visualization of physical characteristics are described. A sensor coupled to an object generates live data. Physical characteristics of the object are computed using the live data. A visualization of the physical characteristics of the object is generated and communicated to a viewing device configured to capture an image of the object. The viewing device augments the image of the object with the visualization of the physical characteristics of the object.

TECHNICAL FIELD

The subject matter disclosed herein generally relates to the processing of data. Specifically, the present disclosure addresses systems and methods for visualization of physical characteristics in augmented reality.

BACKGROUND

A device can be used to generate and display data in addition to an image captured with the device. For example, augmented reality (AR) is a live, direct or indirect view of a physical, real-world environment whose elements are augmented by computer-generated sensory input such as sound, video, graphics or GPS data. With the help of advanced AR technology (e.g., adding computer vision and object recognition) the information about the surrounding real world of the user becomes interactive. Device-generated (e.g., artificial) information about the environment and its objects can be overlaid on the real world.

DETAILED DESCRIPTION

Augmented reality applications allow a user to experience information, such as in the form of a three-dimensional virtual object overlaid on an image of a physical object captured by a camera of a viewing device. The physical object may include a visual reference that the augmented reality application can identify. A visualization of the additional information, such as the three-dimensional virtual object overlaid or engaged with an image of the physical object, is generated in a display of the device. The three-dimensional virtual object may be selected based on the recognized visual reference or captured image of the physical object. A rendering of the visualization of the three-dimensional virtual object may be based on a position of the display relative to the visual reference. Other augmented reality applications allow a user to experience visualization of the additional information overlaid on top of a view or an image of any object in the real physical world. The virtual object may include a three-dimensional virtual object, a two-dimensional virtual object. For example, the three-dimensional virtual object may include a three-dimensional view of a chair or an animated dinosaur. The two-dimensional virtual object may include a two-dimensional view of a dialog box, menu, or written information such as statistics information for a baseball player. An image of the virtual object may be rendered at the viewing device.

A system and method for visualization of physical characteristics are described. A sensor coupled to an object generates live data. Physical characteristics of the object are computed using the live data at a server. A visualization of the physical characteristics of the object is generated and communicated to a viewing device configured to capture an image of the object. The viewing device augments the image of the object with the visualization of the physical characteristics of the object.

In one example embodiment, the server receives an identification of the object from the viewing device and accesses live data corresponding to the identification of the object. The live data may be communicated to the viewing device that computes physical characteristics of the object using the live data and generates the visualization of the physical characteristics of the object.

In another example embodiment, the viewing device displays the visualization of the physical characteristics of the object in relation to the image of the object in a display of the viewing device. The visualization can include an animation with movements based on the live data or visual indicators having shapes and colors that change according to the live data. The physical characteristics of the object may include a weight, a force, a pressure, a heart rate, a pressure rate, or EEG data.

In another example embodiment, the server accesses historical physical characteristics of the object and generates a visualization that compares the physical characteristics of the object to the historical physical characteristics of the object.

In another example embodiment, the server receives a parameter related to the object from the viewing device, computes modified physical characteristics of the object based on the live data affected by the parameter, generates a visualization of the modified physical characteristics of the object, and communicates the visualization of the modified physical characteristics of the object to the viewing device.

In another example embodiment, the server renders a virtual object using the computed physical features, and communicates the rendered virtual object to the viewing device. The viewing device displays the rendered virtual object in relation to a position of the viewing device relative to the object.

In another example embodiment, the viewing device includes an optical device configured to capture the image of the object and a display configured to display the visualization of the physical characteristics of the object in a transparent display. A position and size of the visualization of the physical characteristics of the object in the transparent display may be based on a position and orientation of the viewing device relative to the object.

In another example embodiment, a non-transitory machine-readable storage device may store a set of instructions that, when executed by at least one processor, causes the at least one processor to perform the method operations discussed within the present disclosure.

FIG. 1is a network diagram illustrating a network environment100suitable for operating an augmented reality application of a device, according to some example embodiments. The network environment100includes a viewing device101and a server110, communicatively coupled to each other via a network108. The viewing device101and the server110may each be implemented in a computer system, in whole or in part, as described below with respect toFIGS. 2 and 5.

The server110may be part of a network-based system. For example, the network-based system may be or include a cloud-based server system that provides additional information, such as three-dimensional models, to the viewing device101.

A user102may utilize the viewing device101to capture a view of a physical object (e.g., a bridge) or a subject (e.g., a human being) in a local real world environment. The user102may be a human user (e.g., a human being), a machine user (e.g., a computer configured by a software program to interact with the viewing device101), or any suitable combination thereof (e.g., a human assisted by a machine or a machine supervised by a human). The user102is not part of the network environment100, but is associated with the viewing device101and may be a user102of the viewing device101. For example, the viewing device101may be a computing device with a display such as a smartphone, a tablet computer, or a wearable computing device (e.g., watch or glasses). The computing device may be hand held or may be removably mounted to the head of the user102. In one example, the display may be a screen that displays what is captured with a camera of the viewing device101. In another example, the display of the viewing device101may be transparent or semi-transparent such as in lenses of wearable computing glasses.

The user102may be a user of an augmented reality application in the viewing device101and at the server110. The augmented reality application may provide the user102with an experience triggered by a subject or a physical object, such as a two-dimensional physical object (e.g., a picture), a three-dimensional physical object (e.g., a factory machine), a location (e.g., at the bottom floor of a factory), or any references (e.g., perceived corners of walls or furniture) in the real world physical environment. For example, the user102may point a camera of the viewing device101to capture an image of a subject/object114.

In one embodiment, the image is tracked and recognized locally in the viewing device101using a local context recognition dataset or any other previously stored dataset of the augmented reality application of the viewing device101. The local context recognition dataset module may include a library of virtual objects associated with real-world physical objects or references. In one example, the viewing device101identifies feature points in an image of the subject/object114to determine different planes (e.g., edges, corners, surface of the machine). The viewing device101also identifies tracking data related to the subject/object114(e.g., GPS location of a bridge, facing west, e.g., viewing device101standing x meters away from the bridge, etc.). If the captured image is not recognized locally at the viewing device101, the viewing device101downloads additional information (e.g., the three-dimensional model) corresponding to the captured image, from a database of the server110over the network108.

In another embodiment, the image is tracked and recognized remotely at the server110using a remote context recognition dataset or any other previously stored dataset of an augmented reality application in the server110. The remote context recognition dataset module may include a library of virtual objects associated with real-world physical objects or references.

Sensors112coupled to the subject/object114may measure physical properties on the subject/object114. For example, sensors112may be disposed throughout a span of a bridge to measure movement, pressure, orientation, temperature, etc. The server110can compute physical characteristics of the subject/object114using the live data generated by the sensors112. For example, the server110can compute the amount of stress at specific locations throughout the bridge as cars drive over the bridge. The server110can generate virtual indicators such as vectors or colors based on the computed physical characteristics of the subject/object114. The virtual indicators are then overlaid on top of a live image of the subject/object114to show the amount of real-time stress on the bridge. For example, the virtual indicators may include arrows with shapes and colors that change based on real-time data. The visualization may be provided to the viewing device101so that the viewing device101can render the virtual indicators in a display of the viewing device101. In another embodiment, the virtual indicators are rendered at the server110and streamed to the viewing device101. The viewing device101displays the virtual indicators or visualization corresponding to a display of the subject/object114. For example, the virtual arrows are positioned at locations corresponding to the amount of stress measured on the bridge.

In another example, the sensors112may include a blood pressure and heart rate monitor coupled to a subject. For example, the server110can generate a picture of a heart with a beating animation with a pace corresponding to the measured hear rate from the sensors112. The server110may change a color of the heart based on the measured blood pressure. The live animation is provided to the viewing device101such that the picture of the heart is displayed on top of a chest area of the subject114in the display of the viewing device101. The position of the picture of the heart may be determined based on the orientation and position of the viewing device101relative to the subject using sensors (e.g., gyroscope) internal to the viewing device101.

The sensors112may include other sensors used to track the location and orientation of the viewing device101externally without having to rely on the sensors internal to the viewing device101. The tracking sensors112may include optical sensors (e.g., depth-enabled 3D camera), wireless sensors (Bluetooth, Wi-Fi), GPS sensor, and audio sensor to determine the location of the user102having the viewing device101, distance of the user102to the tracking sensors112in the physical environment (e.g., sensors placed in corners of a venue or a room), the orientation of the viewing device101to track what the user102is looking at (e.g., direction at which the viewing device101is pointed, viewing device101pointed towards a player on a tennis court, viewing device101pointed at a person in a room).

In another embodiment, data from the tracking sensors112and internal sensors in the viewing device101may be used for analytics data processing at the server110(or another server) for analysis on usage and how the user102is interacting with the physical environment. Live data from other servers from other servers may also be used in the analytics data processing. For example, the analytics data may track at what locations (e.g., points or features) on the physical or virtual object the user102has looked, how long the user102has looked at each location on the physical or virtual object, how the user102held the viewing device101when looking at the physical or virtual object, which features of the virtual object the user102interacted with (e.g., such as whether a user102tapped on a link in the virtual object), and any suitable combination thereof. The viewing device101receives a visualization content dataset related to the analytics data. The viewing device101then generates a virtual object with additional or visualization features, or a new experience, based on the visualization content dataset.

The network108may be any network that enables communication between or among machines (e.g., server110), databases, and devices (e.g., device101). Accordingly, the network108may be a wired network, a wireless network (e.g., a mobile or cellular network), or any suitable combination thereof. The network108may include one or more portions that constitute a private network, a public network (e.g., the Internet), or any suitable combination thereof.

FIG. 2is a block diagram illustrating modules (e.g., components) of the viewing device101, according to some example embodiments. The viewing device101may include sensors202, a display204, a processor206, and a storage device208. For example, the viewing device101may be a wearing computing device, desktop computer, a vehicle computer, a tablet computer, a navigational device, a portable media device, or a smart phone of a user. The user may be a human user (e.g., a human being), a machine user (e.g., a computer configured by a software program to interact with the viewing device101), or any suitable combination thereof (e.g., a human assisted by a machine or a machine supervised by a human).

The sensors202may include, for example, a proximity or location sensor (e.g., Near Field Communication, GPS, Bluetooth, Wi-Fi), an optical sensor (e.g., camera), an orientation sensor (e.g., gyroscope), an audio sensor (e.g., a microphone), or any suitable combination thereof. For example, the sensors202may include a rear facing camera and a front facing camera in the viewing device101. It is noted that the sensors202described herein are for illustration purposes; the sensors202are thus not limited to the ones described. The sensors202may be used to generate internal tracking data of the viewing device101to determine what the viewing device101is capturing or looking at in the real physical world.

The display204may include, for example, a touchscreen display configured to receive a user input via a contact on the touchscreen display. In one example, the display204may include a screen or monitor configured to display images generated by the processor206. In another example, the display204may be transparent or semi-opaque so that the user102can see through the display204(e.g., Head-Up Display).

The processor206may include an augmented reality application216for creating a virtual display of real-time or live physical characteristics related to an object when the viewing device101captures an image of an object or a subject. In one example embodiment, the augmented reality application216may include a recognition module214and a physical characteristics module218.

The recognition module214identifies the object that the viewing device101is pointed to. The recognition module214may detect, generate, and identify identifiers such as feature points of the physical object being viewed or pointed at the viewing device101using an optical device of the viewing device101to capture the image of the physical object. As such, the recognition module214may be configured to identify a physical object. In one example embodiment, the recognition module214may include a feature points module302and a contextual local image module304as illustrated inFIG. 3. The identification of the object may be performed in many different ways. For example, the feature points module302may determine feature points of the object based on several image frames of object. The feature points module302also determines the identity of the object using any visual recognition algorithm. In another example, a unique identifier may be associated with the object. The unique identifier may be a unique wireless signal or a unique visual pattern such that the recognition module214can look up the identity of the object based on the unique identifier from a local or remote content database. In another example embodiment, the recognition module214includes a facial recognition algorithm to determine an identity of a subject. The contextual local image module304may be configured to determine whether the captured image matches an image locally stored in a local database of images and corresponding additional information (e.g., three-dimensional model and interactive features) on the viewing device101. In one embodiment, the contextual local image module304retrieves a primary content dataset from the server110, and generates and updates a contextual content dataset based an image captured with the viewing device101.

The physical characteristics module218determines information or status including physical characteristics related to the object. In one example embodiment, the physical characteristics module218may include a visualization module402and a live data module404as illustrated inFIG. 4. The visualization module402may generate a visualization of the live physical characteristics related to the object. The visualization may include rendering a three-dimensional object (e.g., model of a beating heart) or a two-dimensional object (e.g., arrow or symbols). In one example embodiment, the visualization module402receives data from the server110to render the visualization. In another example embodiment, the visualization module402receives the rendered object. The visualization module402further determines the position and size of the rendered object to be displayed in relation to an image of the object. For example, the visualization module402places the animated heart with the size and position based on the image of the subject such that the animated heart is displayed on the chest of the subject with the appropriate size. The visualization module402may track the image of the subject and render the virtual object based on the position of the image of the subject in a display of the viewing device101.

The live data module404communicates with the server110to receive live data related to physical characteristics of the object or subject. In another embodiment, the object may broadcast live data from sensors internal to the object. For example, the object may have sensors embedded in it. The sensors can broadcast real time data to the live data module404of the viewing device101and the server110. The live data module404may receive the live data after authentication with the object. In another example, the live data module404can receive computed physical characteristics from the server110, or live raw data from sensors112.

In one example embodiment, the viewing device101accesses from a local memory a visualization model (e.g., vector shapes) corresponding to the image of the object (e.g., bridge). In another example, the viewing device101receives a visualization model corresponding to the image of the object from the server110. The viewing device101then renders the visualization model to be displayed in relation to an image of the object being displayed in the viewing device101or in relation to a position and orientation of the viewing device101relative to the object. The augmented reality application216may adjust a position of the rendered visualization model in the display204to correspond with the last tracked position of the object (as last detected either from the sensors202of the viewing device101or from the tracking sensors112of the server110).

The visualization module402may include a local rendering engine that generates a visualization of a three-dimensional virtual object overlaid (e.g., superimposed upon, or otherwise displayed in tandem with) on an image of a physical object captured by a camera of the viewing device101in the display204of the viewing device101. A visualization of the three-dimensional virtual object may be manipulated by adjusting a position of the physical object (e.g., its physical location, orientation, or both) relative to the camera of the viewing device101. Similarly, the visualization of the three-dimensional virtual object may be manipulated by adjusting a position of the camera of the viewing device101relative to the physical object.

In one example embodiment, the visualization module402may retrieve three-dimensional models of virtual objects associated with a captured real world object. For example, the captured image may include a visual reference (also referred to as a marker) that consists of an identifiable image, symbol, letter, number, machine-readable code. For example, the visual reference may include a bar code, a quick response (QR) code, or an image that has been previously associated with a three-dimensional virtual object (e.g., an image that has been previously determined to correspond to the three-dimensional virtual object).

In one example embodiment, the visualization module402may include a manipulation module that identifies the physical object (e.g., a physical telephone), access virtual functions (e.g., increase or lower the volume of a nearby television) associated with physical manipulations (e.g., lifting a physical telephone handset) of the physical object, and generate a virtual function corresponding to a physical manipulation of the physical object.

The storage device208may be configured to store a database of identifiers of physical object, tracking data, and corresponding virtual user interfaces. In another embodiment, the database may also include visual references (e.g., images) and corresponding experiences (e.g., three-dimensional virtual objects, interactive features of the three-dimensional virtual objects). For example, the visual reference may include a machine-readable code or a previously identified image (e.g., a picture of a shoe). The previously identified image of the shoe may correspond to a three-dimensional virtual model of the shoe that can be viewed from different angles by manipulating the position of the viewing device101relative to the picture of the shoe. Features of the three-dimensional virtual shoe may include selectable icons on the three-dimensional virtual model of the shoe. An icon may be selected or activated by tapping or moving on the viewing device101.

In one embodiment, the storage device208includes a primary content dataset, a contextual content dataset, and a visualization content dataset. The primary content dataset includes, for example, a first set of images and corresponding experiences (e.g., interaction with three-dimensional virtual object models). For example, an image may be associated with one or more virtual object models. The primary content dataset may include a core set of images or the most popular images determined by the server110. The core set of images may include a limited number of images identified by the server110. For example, the core set of images may include the images depicting covers of the ten most popular magazines and their corresponding experiences (e.g., virtual objects that represent the ten most popular magazines). In another example, the server110may generate the first set of images based on the most popular or often scanned images received at the server110. Thus, the primary content dataset does not depend on objects or images scanned by the recognition module214of the viewing device101.

The contextual content dataset includes, for example, a second set of images and corresponding experiences (e.g., three-dimensional virtual object models) retrieved from the server110. For example, images captured with the viewing device101that are not recognized (e.g., by the server110) in the primary content dataset are submitted to the server110for recognition. If the captured image is recognized by the server110, a corresponding experience may be downloaded at the viewing device101and stored in the contextual content dataset. Thus, the contextual content dataset relies on the context in which the viewing device101has been used. As such, the contextual content dataset depends on objects or images scanned by the recognition module214of the viewing device101.

In one embodiment, the viewing device101may communicate over the network108with the server110to retrieve a portion of a database of visual references, corresponding three-dimensional virtual objects, and corresponding interactive features of the three-dimensional virtual objects. The network108may be any network that enables communication between or among machines, databases, and devices (e.g., the viewing device101). Accordingly, the network108may be a wired network, a wireless network (e.g., a mobile or cellular network), or any suitable combination thereof. The network108may include one or more portions that constitute a private network, a public network (e.g., the Internet), or any suitable combination thereof.

Any one or more of the modules described herein may be implemented using hardware (e.g., a processor of a machine) or a combination of hardware and software. For example, any module described herein may configure a processor to perform the operations described herein for that module. Moreover, any two or more of these modules may be combined into a single module, and the functions described herein for a single module may be subdivided among multiple modules. Furthermore, according to various example embodiments, modules described herein as being implemented within a single machine, database, or device may be distributed across multiple machines, databases, or devices.

FIG. 5is a block diagram illustrating modules (e.g., components) of the server110. The server110includes a sensor interface501, a processor502, and a database510. The sensor interface501may communicate with the sensors112(FIG. 1) to receive real time data.

The processor502may include a subject/object identifier504, a physical characteristics identifier506, and a physical characteristics visualization module508. The subject/object identifier504may operate similarly to the recognition module214of the viewing device101. For example, the subject/object identifier504may identify an subject/object114based on a picture being received from the viewing device101. In another example, the viewing device101already has identified the subject/object114and has provided the identification information to the subject/object identifier504.

The physical characteristics identifier506may determine the physical characteristics associated with the subject/object114identified. For example, if the subject/object114is bridge “abc” at location x, the physical characteristics may include the number of cars driven on the bridge during rush hours, the amount of stress on a particular span of the bridge, the temperature of the pavement in the middle of the bridge, etc.

The physical characteristics visualization module508generates a graphical visualization based on the real time data of the physical characteristics of subject/object114. For example, the physical characteristics visualization module508may generate arrows or vectors corresponding to sections of the bridge. In another embodiment, the physical characteristics visualization module508may generate a visual model based on the real time data of the physical characteristics. For example, the visual model may include a three dimensional model of the bridge.

The database510may store a content dataset512, a virtual content dataset514, and physical characteristics dataset516. The content dataset512may store a primary content dataset and a contextual content dataset. The primary content dataset comprises a first set of images and corresponding virtual object models. The subject/object identifier504determines that a captured image received from the viewing device101is not recognized in the content dataset, and generates the contextual content dataset for the viewing device101. The contextual content dataset may include a second set of images and corresponding virtual object models. The virtual content dataset514includes models of virtual objects to be generated upon receiving a notification associated with an image of a corresponding physical object. The physical characteristics dataset516includes a table of identified subjects/objects with corresponding physical characteristics.

FIG. 6is a ladder diagram illustrating an example embodiment of a system for visualizing physical characteristics in an augmented reality application of a viewing device and a server. At operation602, the viewing device101identifies a subject or object (e.g., subject/object114) and tracks data related to the subject/object being captured by the viewing device101. At operation604, the viewing device101communicates the identity of the subject/object being tracked to the server110. At operation606, the server110retrieves live data related to the subject/object and computes physical characteristics of the subject/object. At operation608, the server110sends the live physical characteristics of the subject/object to the viewing device101. At operation610, the viewing device101generates a visualization based on the live physical characteristics of the subject/object. For example, a virtual heart may be displayed on an image of a chest of the identified subject. In another example, the visualization may be projected onto another object. For example, the viewing device101points to a physical plastic heart model in the physician's office. The viewing device101then starts to animate a virtual heart over the image of the plastic heart model based on the live heartbeat of a patient/subject. As such, the viewing device101may recognize the object as a plastic heart model and request live data from any sensor connected to any patient. Furthermore, the viewing device101may be moved around the physical plastic heart. The visualization is accordingly modified based on the position of the viewing device101relative to the plastic heart so as to show from a different angle. Thus, the visualization of live data from one object may be projected on an image of another object.

At operation612, the viewing device101modifies (e.g., animates) the visualization based on the live physical characteristics of the subject/object in relation to a display of the subject/object.

FIG. 7is a ladder diagram illustrating an example embodiment of training an augmented reality application at a viewing device. At operation702, the server110identifies a physical object. At operation704, the server110accesses live data from sensors related to the subject/object. At operation706, the server110computes physical characteristics of the subject/object from the live data. At operation708, the server110generates a visualization from the computed physical characteristics. At operation710, the viewing device101identifies a subject/object. At operation712, the viewing device101communicates an identification of the identified subject/object to the server110. At operation714, the server110retrieves a visualization related to the identified subject/object. At operation716, the server110sends the visualization from the live data to the viewing device101. At operation718, the viewing device101displays a visualization in relation to the subject/object.

FIG. 8is a flowchart illustrating an example operation of comparing visualization physical characteristics of real world objects in an augmented reality application. At operation802, the viewing device identifies a subject or/and an object. At operation804, the viewing device retrieves live physical characteristics data related to the identified subject/object from a server. At operation806, the viewing device accesses live physical characteristics data from a related subject/object (e.g., brother of the subject, bridge with similar structure). In another example, the viewing device may access historical data of the same subject/object being viewed. For example, the historical data may be heart beat data from the same subject from a previous day. At808, the viewing device generates a visualization that compares the live physical characteristics data with the live physical characteristics data from a related subject/object or with historical data of the same subject/object being viewed. Different colors may be used to indicate the differences. At operation810, the viewing device modifies the visualization based on changes in the live physical characteristics data.

FIG. 9is a flowchart illustrating an example operation of a visualization of physical characteristics in augmented reality at a viewing device. At operation902, the viewing device identifies a subject/object. At operation904, the viewing device retrieves live physical characteristics data related to the identified subject/object from a server. At operation906, the viewing device generates a visualization associated with the identified subject/object. At operation908, the viewing device modifies the visualization based on the live physical characteristics data.

FIG. 10is a flowchart illustrating an example operation of visualization of physical characteristics in augmented reality at a server. At operation1002, the server identifies the subject/object. At operation1004, the server identifies sensors related to the identified subject/object. At operation1006, the server accesses live data from the identified sensors. At operation1008, the server generates a visualization from the live data. At operation1010, the server streams the visualization to a viewing device.

FIG. 11is a diagram illustrating an example operation of a visualization of physical characteristics in augmented reality applications. The viewing device101may include a handheld mobile device having a rear view camera1102and a touch sensitive display1104. The viewing device101may be pointed at an object1110. The rear view camera1102captures an image of the object1110and displays a picture1106of the object1110in the display1104. Identifiers and tracking data related to the object1110may be determined by the viewing device101based on the picture1106of the object1110so as to identify the object1110. The viewing device101communicates an identification of the identified object1110to the server110. The server110accesses live data from physical characteristics sensors112coupled to the object1110. The server110computes physical characteristics based on the live data and generates a visualization of the computed physical characteristics. The server110sends the visualization of the computed physical characteristics to the viewing device101. The viewing device101displays the visualization1108on top of the picture1106of the object1110.

Modules, Components and Logic

Electronic Apparatus and System

Example Machine Architecture and Machine-Readable Medium

The example computer system1200includes a processor1202(e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory1204and a static memory1206, which communicate with each other via a bus1208. The computer system1200may further include a video display unit1210(e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system1200also includes an alphanumeric input device1212(e.g., a keyboard), a user interface (UI) navigation (or cursor control) device1214(e.g., a mouse), a disk drive unit1216, a signal generation device1218(e.g., a speaker) and a network interface device1220.

The disk drive unit1216includes a machine-readable medium1222on which is stored one or more sets of data structures and instructions1224(e.g., software) embodying or utilized by any one or more of the methodologies or functions described herein. The instructions1224may also reside, completely or at least partially, within the main memory1204and/or within the processor1202during execution thereof by the computer system1200, the main memory1204and the processor1202also constituting machine-readable media. The instructions1224may also reside, completely or at least partially, within the static memory1206.

Transmission Medium

Example Mobile Device

FIG. 13is a block diagram illustrating a mobile device1300, according to an example embodiment. The mobile device1300may include a processor1302. The processor1302may be any of a variety of different types of commercially available processors1302suitable for mobile devices1300(for example, an XScale architecture microprocessor, a microprocessor without interlocked pipeline stages (MIPS) architecture processor, or another type of processor1302). A memory1304, such as a random access memory (RAM), a flash memory, or other type of memory, is typically accessible to the processor1302. The memory1304may be adapted to store an operating system (OS)1306, as well as application programs1308, such as a mobile location enabled application that may provide LBSs to a user. The processor1302may be coupled, either directly or via appropriate intermediary hardware, to a display1310and to one or more input/output (I/O) devices1312, such as a keypad, a touch panel sensor, a microphone, and the like. Similarly, in some embodiments, the processor1302may be coupled to a transceiver1314that interfaces with an antenna1316. The transceiver1314may be configured to both transmit and receive cellular network signals, wireless data signals, or other types of signals via the antenna1316, depending on the nature of the mobile device1300. Further, in some configurations, a GPS receiver1318may also make use of the antenna1316to receive GPS signals.