A portable user device may rely on a global navigation satellite system (GNSS) to determine its position. However, there are some venues, referred to as GNSS dead zones, in which the user device cannot receive communication signals from the GNSS satellites, such as in the interior of radio-opaque buildings. The GNSS functionality therefore provides no help in determining the position of the user device as it moves within such an environment. The industry has proposed alternative techniques to determine the location of the user device within GNSS dead zones. But there remains room for improvement regarding the manner in which these alternative techniques are invoked.
The functionality described herein allows a user device to determine an appropriate juncture at which to initiate processing within a GNSS dead zone in an energy-efficient manner. This helps conserve the battery resources of the user device and provide satisfactory user experience.
In one implementation, the functionality employs a sensor management module for determining when to activate a device movement sensor module provided by a user device. Once activated, the user device uses the device movement sensor module to perform any environment-specific processing, such as a dead-reckoning process for determining incremental positions within the venue. Further, in a crowd-sourcing operation, the user device may report the incremental positions together with beacon information to remote processing functionality, where the beacon information is generated in response to signals received from one or more wireless signal sources. The positions and beacon information constitute collected information according to the terminology used herein.
According to another illustrative feature, the sensor management module adopts a different probing technique for each region that the user device traverses when advancing to a particular GNSS dead zone venue. The probing techniques provide position information of increasing robustness as the user draws closer to the venue. But this increased robustness may come at the cost of increased energy expenditure. When the sensor management module determines that the user device has reached a boundary of a region associated with the venue itself, it can turn on the device movement sensor module.
According to another illustrative feature, the remote processing functionality may instruct each user device to supply collected information with respect to a set of venues. In some cases, the set of venues for a first device may differ from the set of venues for a second device, at least in part.
According to another illustrative feature, the remote processing functionality may provide a quota to each user device. The quota describes a maximum number of information collection sessions that are to be performed by a user device in a prescribed time period. A user device can cease the above-summarized probing and collecting operations if it has met its quota.
According to another illustrative feature, each user device may monitor its battery level. The user device can cease the above-summarized probing and collection operations if the battery level falls below a prescribed threshold. It may resume the probing and collection operations when the battery is recharged.
The above approach can be manifested in various types of systems, components, methods, computer readable storage media, data structures, articles of manufacture, and so on.
This Summary is provided to introduce a selection of concepts in a simplified form; these concepts are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
The same numbers are used throughout the disclosure and figures to reference like components and features. Series 100 numbers refer to features originally found in
This disclosure is organized as follows. Section A describes illustrative functionality for governing the invocation of processing that is performed in a venue associated with a GNSS dead zone. Section B describes illustrative methods which explain the operation of the functionality of Section A. Section C describes illustrative computing functionality that can be used to implement any aspect of the features described in Sections A and B.
As a preliminary matter, some of the figures describe concepts in the context of one or more structural components, variously referred to as functionality, modules, features, elements, etc. The various components shown in the figures can be implemented in any manner by any physical and tangible mechanisms, for instance, by software, hardware (e.g., chip-implemented logic functionality), firmware, etc., and/or any combination thereof. In one case, the illustrated separation of various components in the figures into distinct units may reflect the use of corresponding distinct physical and tangible components in an actual implementation. Alternatively, or in addition, any single component illustrated in the figures may be implemented by plural actual physical components. Alternatively, or in addition, the depiction of any two or more separate components in the figures may reflect different functions performed by a single actual physical component.
Other figures describe the concepts in flowchart form. In this form, certain operations are described as constituting distinct blocks performed in a certain order. Such implementations are illustrative and non-limiting. Certain blocks described herein can be grouped together and performed in a single operation, certain blocks can be broken apart into plural component blocks, and certain blocks can be performed in an order that differs from that which is illustrated herein (including a parallel manner of performing the blocks). The blocks shown in the flowcharts can be implemented in any manner by any physical and tangible mechanisms, for instance, by software, hardware (e.g., chip-implemented logic functionality), firmware, etc., and/or any combination thereof.
As to terminology, the phrase “configured to” encompasses any way that any kind of physical and tangible functionality can be constructed to perform an identified operation. The functionality can be configured to perform an operation using, for instance, software, hardware (e.g., chip-implemented logic functionality), firmware, etc., and/or any combination thereof.
The term “logic” encompasses any physical and tangible functionality for performing a task. For instance, each operation illustrated in the flowcharts corresponds to a logic component for performing that operation. An operation can be performed using, for instance, software, hardware (e.g., chip-implemented logic functionality), firmware, etc., and/or any combination thereof. When implemented by a computing system, a logic component represents an electrical component that is a physical part of the computing system, however implemented.
The phrase “means for” in the claims, if used, is intended to invoke the provisions of 35 U.S.C. §112, sixth paragraph. No other language, other than this specific phrase, is intended to invoke the provisions of that portion of the statute.
The following explanation may identify one or more features as “optional.” This type of statement is not to be interpreted as an exhaustive indication of features that may be considered optional; that is, other features can be considered as optional, although not expressly identified in the text. Finally, the terms “exemplary” or “illustrative” refer to one implementation among potentially many implementations.
A. Illustrative Functionality
For example, in some cases, the venue 102 may correspond to a building, such as a store, a mall, an airport, a manufacturing facility, an academic building, a governing building, etc. The walls and ceiling of the building may block or severely attenuate the receipt of wireless GNSS signals from the satellite(s) which provide these signals. Alternatively, or in addition, the venue 102 may correspond to an outdoor region in which wireless GNSS signals are not reliably available, e.g., due to the topography of the region and/or interference caused by other communication sources. In some cases, the venue 102 uniformly fails to provide reliable wireless GNSS signals over the entire spatial extent of the venue 102, and with respect to time. In other cases, the venue 102 may have sub-regions in which the wireless GNSS signals are available and/or time spans in which the wireless GNSS signals are available. In contrast, assume that a user device has reliable access to wireless GNSS signals in regions outside the venue 102. While the user device may not be able to reliably receive GNSS signals in the venue 102, in some cases, it can still receive wireless cellular signals, WiFi signals, etc. in the venue 102.
In the merely representative case of
In other environments, the regions may have any shape (that is, not necessarily a circular shape). For example, a venue that lies on a shoreline may have regions defined by semicircles, rather than full circles. Further, other environments can adopt additional regions or fewer regions compared to the number of regions shown in
A user may advance through the environment 100 together with a user device. For example, a first user may mount a user device 112 to the dash of a vehicle 114 while traveling through the environment 100. In another case, a second user may carry a user device 116 as he or she advances through the environment 100 on foot. Moreover, any user can use plural forms of transportation in the course of moving through the environment 100. For example, a user can use a vehicle to drive to a parking lot associated with a mall (where the mall is associated with the venue 102), and then advance into the mall on foot.
Without limitation,
More specifically, the user device 112 can commence the dead-reckoning technique at an anchor position 122 along path 118, which corresponds to a known position established by wireless GNSS signals or some other position-determination technique. After moving from this anchor position 122, the user device 112 determines its new current position based on its previous position (in this case the known anchor position 122) in combination with the output of one or more device movement sensor devices. Such device movement sensor devices can include one or more accelerometers, one or more gyroscopes, one or more magnetometers, one or more barometers, and so on. But to facilitate explanation, this description will refer to the suite of possible device movement sensor devices as a generic “device movement sensor module.”
That is, to compute a new current position, the user device 112 can convert the output of the device movement sensor module into incremental movement information, and then add this incremental movement information to the previous position to derive the new current position. The user device 112 can continue this process to generate a series of incremental positions. At certain points within the venue, the user device 112 may gain access to a known reference position provided by any position-determination mechanism(s). The user device 112 can use this known reference position to remove or reduce accumulated error in its current position.
Before reaching the boundary of region Rv, the user device 112 performs probing at different points along the path 118 to determine the juncture (at anchor position 122) at which it is appropriate to turn on the device movement sensor module and commence the dead-reckoning procedure. The user device 112 performs this probing by selecting different probing techniques for different respective regions. For example, the user device 112 may use a technique Touter when travelling through the outer region Router, a technique T2 when traveling through the region R2, a technique T1 when traveling through the region R1, and a technique T0 when traveling through the region R0. And, as said, when the user device 112 enters the region Rv, it may commence the dead-reckoning procedure.
In one approach, different probing techniques may provide positions at different respective levels of robustness. Here, “robustness” may describe the frequency and/or accuracy at which a probing technique provides the positions. But, at the same time, different probing techniques also may incur different expenditures of energy. More specifically, the more robust techniques may consume more energy than the less robust techniques.
In one implementation, each user device is configured to use probing techniques of increasing robustness and energy consumption as the user device draws closer to the venue 102. This means that the probing technique Touter performed in the region Router will consume the least amount of energy, while the probing technique T0 will consume the greatest amount of energy. But the probing technique T0 will be more robust than the probing technique Touter. This behavior is useful to help conserve the limited power resources of each user device.
To illustrative the energy-conserving features of the above-described strategy, consider the behavior of any user device in the region Router. In this region, there is a relatively high degree of uncertainty as to whether the user is planning on traversing a path which will lead to the venue 102. For path 118, the user device 112 will indeed advance to the venue 102; but for path 120, the user will not continue on to the venue 102. Further, because the user is far from the venue 102, there is ample time to resolve the true travel intentions of the user. Due to these factors, it is appropriate to use a low-energy/low-sampling-rate probing technique for region Router. By contrast, in region R0, there is a much lower degree of uncertainty as to whether the user will enter the venue 102, and much less time to determine the true travel intentions of the user. For this reason, it is appropriate to use a high-energy/high-sampling-rate probing technique for region R0, relatively speaking.
In particular, the user device 112 can apply a relatively high-sampling-rate probing technique in region R0 to accurately detect an anchor position (such as illustrative anchor position 122) at which it is to commence the dead-reckoning procedure. That is, the GNSS signals are still available at the anchor position 122, but may not be reliably available as the user advances closer to the venue 102. If the user device 112 advances into the region Rv without having first detected an anchor position, it may lose its opportunity to capture an initial seed position for use in performing the dead-reckoning process, and hence it may be forced to forgo the dead-reckoning process in this particular instance. This unfavorable consequence justifies the use of the high-sampling-rate probing technique in R0. Note that it is possible to use the high-energy/high-sampling-rate probing technique for all regions of the environment 100, but this would result in the rapid depletion of the power resources of the user device.
The user devices can perform the dead-reckoning procedure within the venue 102 to serve different objectives. In one case, a user device can use the dead-reckoning procedure in the venue 102 to simply determine its position within the venue, with no other collateral goal.
In addition, or alternatively, the user device can use to the dead-reckoning position to identify positions in the venue 102, together with beacon information associated with each of the positions. The beacon information constitutes a “fingerprint” which characterizes the different wireless signals that are received at a particular position. More specifically, the beacon information may include information which identifies the sources of the wireless signals. The beacon information may also include information regarding the respective strengths of the wireless signals that have been received from the identified sources. Together, each pair of a position and its associated beacon information constitutes collected information according to the terminology used herein. The user device may then forward the collected information to remote processing functionality (to be described below). That remote processing functionality may aggregate the collected information received from plural user devices that have traversed the venue 102. This aggregation operation constitutes a crowd-sourcing operation that yields detailed position information about the venue 102.
Different applications can make use of the position information provided by the above-described crowd-sourcing operation in different ways. For example, in one case, a user device can determine beacon information within any venue, but without knowing its position. The user device can consult a database produced by the crowd-sourcing operation to determine a beacon signature which matches the detected beacon information, and a position associated therewith. That position corresponds to the approximate current position of the user device.
The user devices 202 may communicate with remote processing functionality 204 (and with each other) via a communication conduit 206. The remote processing functionality 204 may correspond to one or more server computers and associated data stores. More specifically, in some cases, the remote processing functionality 204 can include cloud computing resources. The remote processing functionality 204 can be implemented at one site or may be distributed over plural sites. Further, the remote processing functionality 204 may be administered by a single entity or plural entities.
The communication conduit 206 can include a local area network, a wide area network (e.g., the Internet), or a combination thereof. As at least part thereof, the communication conduit 206 can include wireless communication infrastructure. The wireless communication infrastructure can include any combination of satellite communication equipment, cell towers, base stations, central switching stations, wireless access points (for WiFi communication), and so on.
The parenthetical footnote to
After assignment, a user device in a particular group is tasked with the responsibility of supplying collected information regarding only those venues in its assigned subset of venues. For example, a user device within the above-mentioned group A is assigned the task of supplying collected information regarding only venues 1-10. To repeat, the collected information may constitute positions and beacon information collected by a user device as it traverses a particular venue. The user device generates the positions, in turn, using a dead-reckoning technique. In some implementations, the user devices can also forward collected information to the remote processing functionality 204 in regions that lie outside of the venues, e.g., in any of the regions Router through R0; the positions provided by the collected information in these cases can be determined based on wireless GNSS signals and/or any other position-determination mechanism(s).
The assignment management module 208 can perform the above-described allocation function in different ways. In one case, the assignment management module 208 can determine the area in which each user device typically operates. The assignment management module 208 can then assign venues to user devices which are within or nearby the areas in which the user devices typically operate. For example, consider a user who most often uses his or her smartphone in a 30 mile radius around his or her place of residence. The assignment module 208 may assign a subset of venues that lie within this 30 mile radius to this particular user device. In a yet more direct approach, the assignment management module 208 can determine the venues that a user typically visits, and/or the venues that a user is likely to visit based on any indirect evidence (e.g., based on demographic information, purchase history information, browsing history information, traveling history information, etc.). The assignment management module 208 can then assign a subset of those venues to the user device. The assignment management module 208 can use any technique for assigning venues to user devices, such as by randomly assigning viable venues to user devices. This assignment technique will result in the assignment of each venue to plural user devices.
In addition, or alternatively, the assignment management module 208 takes into consideration need-based factors in assigning user devices to venues. For example, consider a newly built or redesigned shopping mall. The assignment management module 208 initially will not have a robust database regarding positions and beacon signatures within this venue. In response, the assignment management module 208 can assign that venue to a relatively large group of user devices. This will result in the rapid accumulation of collected information for that venue. Next consider a popular establishment that has been in existence for many years. The assignment management module 208 may already have a robust database of positions and beacon signatures regarding this site. In this circumstance, the assignment management module 208 may assign the venue to fewer user devices compared to the above-mentioned start-up case, but it can continue to assign the venue to enough user devices so as to properly detect changes that may be made to the venue. For example, the venue may change by including additional wireless communication sources (such as additional WiFi access points), by changing the locations of existing communication sources, by changing the strengths of signals transmitted by the communication sources, by changing the physical layout of the venue, and so on. Also, the assignment management module 108 may wish to continue sampling positions from a well-trafficked venue to fill in information regarding sub-regions within those venues that are nevertheless relatively unpopular (such as certain stores in a mall).
The assignment management module 208 can also maintain venue information regarding each venue in a data store 210. The venue information includes different components which characterize each venue. Generally stated, the venue information can convey any information that enables a user device to perform probing so as to discover a juncture at which to commence the dead-reckoning process in connection with each venue.
For example, the venue information for a particular venue may include: a) an identifier associated with the venue; b) an address (e.g., a URL) at which a map of the venue may be obtained; c) position data; d) a venue proximity model; and e) venue beacon observation status information. The position data may describe the placement of the venue within a larger geographic area. The position data may also define the perimeter of the venue. The venue proximity model may store any descriptive information regarding the shapes, sizes, and placements of different probing regions associated with the venue, and/or any settings and instructions which describe the probing behavior that a user device is expected to perform in each of these regions. For example, the venue proximity model may describe the probing regions by defining positions associated with the probing regions, together with beacon signatures associated with those positions. In addition, or alternatively, a user device can apply one or more default rules to define these regions, such as by defining a particular probing region as a range of radii, measured with respect to a center location associated with a venue, etc. The beacon observation status information may indicate the relative level of robustness of the database of collected information for the venue. For example, the beacon observation status information for the new mall in the above example would indicate that the database for this venue is deficient, and is thus a worthy recipient of additional collected information.
The assignment management module 208 can send a subset of the venue information to each device. That subset pertains to the subset of venues that have been assigned to each user device. The received venue information informs the user device of the venues to which it has been assigned. And as stated, the received venue information also equips the user device with the appropriate information to perform probing with respect to the assigned venues.
In addition, the assignment management module 208 can assign a quota to each user device, and then download quota information which describes that quota to the user device. That is, in one implementation, the quota defines a number of information collection sessions that a user device is allowed to perform with respect to its assigned set of venues over a defined period of time. For example, assume that a particular user device is assigned a quota of 5 and is requested to supply collected information (for crowd-sourcing purposes) regarding venues X, Y, and Z. This means that the user device is instructed to supply positions and beacon information upon entering any of venues X, Y, and Z, but no more than five times in total. In one environment, the user device is considered to have engaged in an information collection session when it has entered some region associated with one of its assigned venues. Without limitation, in one illustrative implementation, the user device is considered to have engaged in an information collection session when it has entered the region R1, upon which the GNSS-based active probing is commenced. But different implementations can move this “trigger point” closer to or farther away from a venue to suit different environment-specific objectives. However, the occurrence of such a triggering event does not necessarily mean that the user will subsequently enter the region Rv and commence the dead-reckoning process. For example, a user may enter the region R1 but decline to continue on farther into the venue. Alternatively, the user may enter the venue but, for any environment-specific reason, the dead-reckoning process is not successful in generating viable collected information for the interior of the venue, e.g., because of a failure to extract meaningful movement information and/or a failure to receive viable wireless signals within the venue and/or a failure to establish an anchor position prior to entering the venue, etc.
The assignment management module 208 can also assign different quotas to different types of devices. For example, the assignment management module 208 can assign a larger quota to a tablet-type computing device compared to a smartphone, because the tablet-type computing device presumably has a larger battery capacity than the smartphone. The assignment management module 208 can also assign different quotas to different user devices depending on the preferences of the users who are associated with those devices.
Further, the assignment management module 208 can specify a maximum power expenditure that each user device is permitted to use in performing the probing and collecting activities. The assignment management module 208 can specify the maximum power expenditure in various ways, such as by specifying a maximum amount of time that can be spent in performing probing and collecting activities, and/or by more directly specifying an amount of power that a user device is allowed to expend in performing probing and collecting activities (e.g., quantified based on battery level, processing load, etc.). The assignment management module 208 can formulate these power constraints as part of the quota information that it sends to the user device.
Further, the assignment management module 208 can provide information which specifies the period of applicability of each quota. For example, the assignment management module 208 can specify a quota of five venues per month, a month corresponding to the period of applicability in this example. At the end of each month, a user device will reset its work-performed count or measurement to zero or alternatively receive a new quota.
Further, the assignment management module 208 can periodically or continuously tune the manner in which it allocates venues and quotas to user devices based on feedback information regarding the quantity and quality of collected information received from the user devices.
In one illustrative implementation, the probing and collecting operations performed by the system 200 occur as background processes that need not engage the attention of the users. Alternatively, or in addition, the probing and collecting operations can be performed by an application or other function that is expressly invoked by the user.
In summary, the assignment management module 208 assigns venues to user devices to help efficiently distribute the data collection task among user devices in an entire population of user devices. The assignment management module 208 assigns one or more quotas to each user device to limit the amount of data-collecting work that each user device is asked to perform, and hence the power drain associated with that work.
In any case, however, a user can be given the opportunity to expressly “opt in” and/or “opt out” with respect to any aspect of the processing described herein. Further, in some alternative cases, the assignment management module 208 can allow any user device to provide collected information pertaining to any venue that it enters, e.g., without constraining the user device to a particular subset of venues and/or without specifying a quota for the user device. And as mentioned above, the remote processing functionality 204 can also receive collected information from user devices while in regions outside of the venues.
A data collection module 212 receives the collected information supplied by the user devices. The data collection module 212 can then store the collected information in a data store 214. The data collection module 212 can use any technique to receive the collected information, such as a push technique (whereby the user devices independently supply the collected information), a pull technique (whereby the data collection module 212 polls the user devices to collect the information), or combination thereof.
A region management module 216 refines any characteristic(s) of the venue information based on the crowd-sourced collected information provided by a plurality of user devices. For example, the region management module 216 can examine the collected information to identify regions in which the wireless GNSS signals are not being reliably received. This may allow the region management module 216 to identify new venues to be investigated using the dead-reckoning technique. That is, the region management module 216 can convey these new venues to the assignment management module 208, whereupon the assignment management module 208 can instruct certain devices to provide collected information for the new venues in the above-described manner.
In addition, or alternatively, the region management module 216 can examine the collected information to determine the efficiency and accuracy at which user devices are discovering known GNSS-deprived venues. For example, the collected information may reveal the probabilities that users will enter a particular venue for different positions in proximity to the venue. In addition, the collected information may reveal the prevalence at which user devices enter a venue without first establishing an anchor position. In addition, the collected information may directly and/or indirectly reveal the amounts of resources consumed by the user devices in attempting to locate an anchor position for a particular venue, and so on.
The region management module 216 can use the above-described collected information (and conclusions derived therefrom) to modify the venue proximity model for a particular venue in any manner, such as by modifying the shapes, placements, sizes, etc. of the different probing regions associated with a particular venue. The region management module 216 can also use the collected information to determine the number of probing regions that are to be used in association with a particular venue. The region management module 216 can also use the collected information to provide beacon signatures associated with different positions within different probing regions; henceforth, a user device can consult that signature information to determine its position within a particular probing region associated with a particular venue.
To name just a few representative examples, the region management module 216 may increase the radius of circle 106 associated with region R0 to improve the ability of user devices to reliability detect an anchor position associated with the venue 102.
An incentive management module 218 can provide any type of reward to a user for taking part in the above-described information collection tasks. For example, the incentive management module 218 can give the user a coupon, rebate, discount, etc. in response to entering an assigned venue or plural assigned venues. Generally, the reward can specify any benefit to the user, and may be conferred by any granting entity (e.g., any cooperating store, service, etc.).
In operation, the incentive management module 218 can optionally send a qualifying user device a message that alerts its user to the existence of a reward and its terms of compliance. This may encourage the user to visit a particular venue associated with the reward. The incentive management module 218 can then examine the collected information in the data store 214 to glean evidence that indicates that the user has entered a venue associated with the reward. The incentive management module 218 can then deliver the reward to the user in any environment-specific manner, such as by electronically transferring and/or physically mailing information regarding the reward (and/or the reward itself) to the user.
In other cases, the incentive management module 218 can structure an incentive program as a game, e.g., as implemented as a game-like application or a game that is specified by textual instructions. That game can encourage users to visit locations. For example, the game may be structured as a scavenger hunt, a puzzle, an adventure, a competition, etc. The reward conferred in this context may correspond to any of the assets described above (e.g., coupons, discounts, rebates, etc.). In addition, or alternatively, the reward may simply constitute recognition that the user has completed a game-related task, achieved a certain score, etc.
The user device 300 includes a sensor management module (SMM) 302 which governs the activation and deactivation of a device movement sensor module 304.
The user device 300 also may include a GNSS module 306. The GNSS module 306 determines the position of the user device 300 based on wireless GNSS signals received from one or more satellites. For example, the GNSS module 306 can be implemented using Global Positioning System (GPS) functionality or the like.
A dead-reckoning module 308 determines the position of the user device 300 using any type of dead-reckoning technique, such as the technique described above. To perform this function, the dead-reckoning technique receives movement information from the device movement sensor module 304. When available, the dead-reckoning module 308 module can also receive wireless GNSS signals and/or wireless cellular signals while in the venue (if available). This allows the user device 300 to correct any error that may have accumulated in the dead-reckoning process and/or to determine when the user device 300 has exited the venue in question. The user device 300 can also optionally supplement the dead-reckoning process with any other position-determining technique to determine positions within a venue. The user device 300 can then use any fusion algorithm to combine positions provided by two or more position-determination techniques.
The dead-reckoning module 308 can terminate the dead-reckoning process in various circumstances, such as when the error of the positions provided by this process exceed a threshold, and/or when position information derived from any position-determination technique indicates that the user device 300 has exited the GNSS-deprived venue. The dead-reckoning module 308 can also deactivate the device movement sensor module 304 at this time.
In addition, the SMM 302 can deactivate the dead-reckoning module 308 and the device movement sensor module 304 when it detects that the user device 112 has left the venue 102. The SMM 302 can draw this conclusion based on a determination that the user device 112 is receiving reliable wireless GNSS signals from the GNSS module 306. In addition, or alternatively, the SMM 302 can deactivate the dead-reckoning module 308 and the device movement sensor module 304 when it detects that the position of the user device 112 (determined by any position-determining mechanism(s)) is suitably outside the venue 102. The SMM 302 can make this determination, in turn, based on map information provided by the venue information.
A cellular communication module 310 enables the user device 300 to communicate with any remote entity (such as any other user device or the remote processing functionality 204) using wireless cellular communication. The cellular communication module 310 can use any cellular protocol to perform this task. The cellular communication module 310 can also be used to generate beacon information which characterizes the wireless cellular signals that are received from one more wireless communication sources (such as different cell towers or the like) with respect to a particular position of the user device 300. The beacon information describes the identity of each detected wireless communication source. The beacon information may also describe the strength of each wireless cellular signal.
The user device 300 may also include one or more other communication modules 312, referred to in the singular below for brevity. For example, the other communication module 312 may comprise WiFi functionality which communicates with one or more wireless WiFi access points in the vicinity of the user device 300. Like the cellular communication module 310, the other communication module 312 can be also used to generate beacon information which characterizes the wireless WiFi signals that are received from one or more WiFi access points with respect to a particular position of the user device 300.
In addition, or alternatively, the other communication module 312 can detect signals transmitted by one or more short-range beacons provided in the vicinity of the user device 300, such as Near Field Communication (NFC) tags, Bluetooth Low Energy (BLE) devices, etc. For instance, in some cases, these short-range beacons may have a range of transmission that extends only a few meters from the beacons. In the merely illustrative case of
A data collection module 314 can receive and store information in a data store 316, for use in a crowd-sourcing operation. The collected information includes positions identified by the dead-reckoning module 308 within the venue, together with beacon information associated with those positions (which may be provided, for instance, by the other communication module 312 based on the wireless WiFi signals emitted by access points within the venue). (As stated above, the data collection module 314 can also collect and store crowd-sourcing information when the user device 300 is outside the venue.) A data transfer module 318 transfers the collected information provided in the data store 316 to the remote processing functionality 204 using any technique, such as a push technique, a pull technique, or combination thereof, based on any triggering event(s).
A battery level monitoring module 320 receives information regarding a battery level of a rechargeable battery 322. The battery 322 supplies power to the user device 300.
The user device 300 may also include one or more applications 324 that perform any functions. In some cases, an application may interact with the GNSS module 306 (and/or some other position-determination module) to determine the position of the user device 300. For example, a map application may interact with the GNSS module 306 to determine the current location of the user device 300. This enables the map application to provide a map to the user which is pertinent to the user's present location. The applications 324 may run with the assistance of low-level resource management functions provided by an operating system 326. Various functions of the operating system 326 and/or other functionality may also optionally interact with the GNSS module 306 for any purpose. For example, camera functionality may interact with the GNSS module 306 so as to annotate a picture with position information, describing the position at which the picture was taken.
Advancing to
The different components of the SMM 302 play different respective roles in various probing techniques. As described above in connection with
As a first component, an opportunistic management module 402 determines whether the user has activated any function that involves determining the position of the user device 300, such as an application, operating system function, etc. But to simplify explanation, it will henceforth be assumed that the invoking function is an application. The application determines the position of the user device 300 for a purpose that is unrelated to the task of performing dead-reckoning or crowd-sourcing within the venue. For example, as stated above, a map application may interact with the GNSS module 306 to determine the position of the user device 300 for the purpose of displaying an appropriate map to the user. The opportunistic management module 402 opportunistically uses the position reading obtained by any such “unrelated” application for its own use, e.g., to determine the proximity of the user device 300 with respect each of the venues that the user device 300 has been asked to monitor.
In addition, or alternatively, the opportunistic management module 402 can receive position information when a user independently “checks in” at a particular site, such as a restaurant, store, etc. That is, the user may manually provide any type of input which indicates that he or she is present at a particular locale. The opportunistic management module 402 can then consult a local and/or remote lookup table to map that location into a position associated with the presumed position of the user device 300. The opportunistic management module 402 can again parasitically use this position to assess the location of the user device 300 with respect to a venue in question.
In one case, the SMM 302 can call on the opportunistic management module 402 to provide positions when the user is relatively far from a venue, such as in the region Router. This probing technique may not provide frequent position updates, and it does not provide the position updates in an on-demand manner. But it does provide these updates in an energy efficient manner. This is because the user device 300 does not expend any additional energy (or any significant additional energy) in obtaining the positions beyond what energy has already been expended by the “host” application (e.g., the map application in the example above). But the SMM 302 can also call on the opportunistic management module 402 to provide opportunistic position readings in any region (e.g., regions R2, R1, R0, and Rv), e.g., so as to supplement the position information provided by other position-determination mechanisms that are used in those other regions.
A beacon information management module 404 obtains the position of the user device 300 based on beacon information. As described above, the beacon information identifies the communication sources associated with wireless cellular signals and/or WiFi signals received by the user device 300 at a particular position. The beacon information also describes the strengths of those wireless signals. The beacon information management module 404 can compare the detected beacon information with beacon signatures associated with a venue in question, as specified by the venue information. Each beacon signature comprises reference beacon information that has been collected on a prior occasion by one or more user devices, together with a known position associated with the reference beacon information. If there is a match between the measured beacon information and a particular beacon signature, the beacon information management module 404 can treat the position of the matching beacon signature as the current approximate position of the user device 300. In one approach, the SMM 302 applies the beacon information management module 404 to provide approximate positions with the region R2 shown in
In addition, the beacon information management module 404 can detect short-range beacons. Each short-range beacon has a known source position. Further, each short-range beacon can transmit identity information which identifies the short-range beacon, distinguishing it from signals provided by other short-range beacons. In operation, the beacon information management module 404: (1) detects a wireless signal transmitted by one of these short-range beacons; (2) determines the identity of the short-range beacon and its preregistered position; and (3) treats the discovered position as the estimated current position of the user device 300. In one implementation, the SMM 302 can perform the above-described detection of short-range beacons in any region shown in
A GNSS management module 406 manages the use of the GNSS module 306 to collect positions. For example, the GNSS management module 406 specifies the regions for which the GNSS management module 406 is applied, together with the frequency at which it is applied in each region. For example, the GNSS management module 406 can instruct the user device 300 to use the GNSS module 306 to determine the position of the user device 300 in the region R1 at a frequency f1, and to determine the position of the user device 300 in the region R0 at a frequency f0, where f0>f1. The user device 300 expends more energy performing its probing technique in region R0 compared to region R1, since the GNSS module 306 performs more work in region R0.
Alternatively, or in addition, the GNSS management module 406 can collect positions using the GNSS module 306 at a variable rate which depends on the distance d between the user device 300 and the venue in question (as opposed to providing only two discrete sampling frequencies for regions R1 and R0).
The beacon information management module 404 can also sample positions in the manner described above with respect to the GNSS management module 406, e.g., by determining positions at a frequency that depends on the distance between the user device 300 and the venue.
A quota management module 408 monitors how many information collection sessions (ICSs) have been performed by the user device 300. If this number has met the quota assigned to the user device 300, then the quota management module 408 will suspend further probing and collecting operations performed by the user device 300 (referred to as “probing/collecting operations”) until the quota is replenished/reinitialized by the remote processing functionality 204. The quota management module 408 may reinitialize the ICS parameter after a prescribed reporting period has transpired (e.g., at the end of each month, in one representative case).
A battery management module 410 receives the battery level from the battery level monitoring module 320. The battery management module 410 compares this battery level with respect to a prescribed threshold. If the battery level falls below the threshold, then the battery management module 410 will suspend further probing/collecting operations until the battery has been recharged. In some cases, the threshold that is used for this function is the same for every user device. In other cases, the assignment management module 208 can assign different thresholds to different user devices and/or different types of user devices.
In addition, or alternatively, the battery management module 410 can directly or indirectly monitor the amount of power consumed by the user device 300 in performing probing and collecting activities in one or more information collection sessions. The battery management module 410 can then compare this power measurement with respect to a power expenditure quota (or quotas) received from the assignment management module 208, to provide a comparison result. On the basis of that comparison result, the battery management module 410 determines whether to continue or discontinue further probing and collecting activities. More specifically, this decision can cause the battery management module 410 to discontinue probing and collecting activities even though the battery level of the user device 300 has not fallen below the first-mentioned threshold. This type of rationing behavior can be performed in addition to the above-described behavior of the quota management module 408, or instead of it. In both cases, the assignment management module 208 assigns each user device a certain amount of work relating to the probing and collecting activities; as set forth above, this work can be quantified in different ways.
An activity inference management module 412 determines the state of the user device 300 based on any available evidence. For example, the activity inference management module 412 can examine the positions collected by the user device 300 over a span of time. If these positions indicate that the user device 300 is not moving, the activity inference management module 412 can suspend further probing/collecting operations.
The activity inference management module 412 can also determine the manner in which the user device 300 is moving. For example, the activity inference management module 412 can determine the speed at which the user device 300 is moving, the mode of travel that is likely being used to transport the user device 300, and so on. The activity inference management module 412 can send this travel information to the GNSS management module 406 and/or the beacon information management module 404. These modules (404, 406) can use the travel information to govern the rate at which they generate positions. For example, these modules (404, 406) can determine positions at a first rate if the user is traveling by automobile and a second rate if the user is traveling by foot, where the first rate is higher than the second rate. The modules (404, 406) can afford to update the position of the user device 300 at a slower rate when the user is walking because the user's position can be expected to change at a relatively slow rate.
The activity inference management module 412 can also use any destination prediction functionality to predict the venue to which the user may be heading. One such destination prediction functionality that can be used is the statistical method described in U.S. Pat. No. 8,024,112, issued Sep. 20, 2011, entitled “Methods for Predicting Destinations from Partial Trajectories Employing Open-and Closed-world Modeling Methods,” naming the inventors of John C. Krumm and Eric J. Horvitz. The activity inference management module 412 can use the prediction of the destination to govern any aspect of the manner in which it performs probing over the course of the path taken by the user device 300.
A main management module 414 can coordinate the activities performed by all of the individual management modules described above. For example, the main management module 414 can invoke and deactivate different individual management modules as the user advances through the regions shown in
B. Illustrative Processes
Starting with
If the current position does not lie within the region Rv, then, in block 506, the SMM 302 selects a probing technique associated with the identified region, e.g., by selecting a probing technique Touter if the region corresponds to Router, by selecting probing technique T2 if the region corresponds to R2, and so on. In block 508, the SMM 302 receives a new current position based on whatever probing technique has been chosen in block 506. The procedure 500 then advances back to block 502 to repeat the above-described process.
More specifically, as a default, the SMM 302 will initially perform block 502 in a passive manner using the opportunistic management module 402. If the position detected in this manner indicates that the user device 300 is in the Router region, the SMM 302 will continue to use the opportunistic probing technique. But once the SMM 302 determines that the user device 300 is in any one of regions R2, R1, or R0, it will then adopt an active probing technique associated with that region. At that juncture, the SMM 302 performs block 502 in an active manner until that time that it determines that the user device 100 has again moved into the Router region.
As another point of clarification, the user device 300 can perform the procedure 500 with respect to any one of a subset of venues for which it has been assigned (if, in fact, it is constrained in this manner). For example, the venue that is being referenced in
In block 606, the SMM 302 determines whether the user device 300 is currently in the region R2. If so, in block 608, the SMM 302 uses a signature probing technique to determine the position of the user device 300. This procedure involves receiving beacon information from one or more wireless communication sources (such as wireless cellular sources), comparing the beacon information to the venue information (e.g., to beacon signatures associated with the venue in question) to generate a comparison result, and generating a current approximate position based on the comparison result.
In block 610, the SMM 302 determines whether the user device 300 is currently in region R1. If so, in block 612, the SMM 302 uses the GNSS module 306 to generate a current position of the user device 300. So long as the user device 300 remains in region R1, the SMM 302 invokes the GNSS module 306 to provide updated positions at a frequency f1.
Similarly, in block 614, the SMM 302 determines whether the user device 300 is currently in region R0. If so, in block 616, the SMM 302 uses the GNSS module 306 to generate a current position of the user device 300. So long as the user device 300 remains in region R0, the SMM 302 invokes the GNSS module 306 to provide updated positions at a frequency f0, where f0>f1.
In block 618, the SMM 302 determines whether the user device 300 has reached the boundary of region Rv, and establishes an anchor position for dead-reckoning. If so, in block 620, the SMM 302 activates the device movement sensor module 304 and commences the dead-reckoning procedure.
When the SMM 302 determines that the user device 300 has entered a new region it activates a new probing technique in the manner described above; in addition, in some cases, the SMM 302 may discontinue a probing technique that it was using in the region that it has just left. For example, a user device may move from region R2 into region R1, and then back into region R2. Upon detecting that the user device 300 has moved back into the region R2, the SMM 302 can discontinue receiving signals in an active manner using the GNSS management module 406. In another example, the SMM 302 can deactivate the movement sensor module 304 and the dead-reckoning module 308 once it determines that the user device 300 has left the venue 102 (which can be determined in any of the ways explained in Section A).
More generally, each user device 300 can supply collected information as it traverses any of the regions associated with the environment 100 of
More generally stated, the SMM 302 can receive one or more quotas which describe an amount of work it is allowed to perform in connection with probing and collecting activities. The SMM 302 monitors the amount of work it has actually performed in connection with these activities and terminates these activities once it reaches the applicable threshold(s). In the above example, the amount of work is quantified based a number of ICS sessions that have been performed. In addition, or alternatively, the amount of work can be assessed based on the amount of power expended by the user device 100 in performing the probing and collecting activities, e.g., as assessed based on battery level, processing load, processing time, etc.
C. Representative Computing functionality
The computing functionality 1700 can include volatile and non-volatile memory, such as RAM 1702 and ROM 1704, as well as one or more processing devices 1706 (e.g., one or more CPUs, and/or one or more GPUs, etc.). The computing functionality 1700 also optionally includes various media devices 1708, such as a hard disk module, an optical disk module, and so forth. The computing functionality 1700 can perform various operations identified above when the processing device(s) 1706 executes instructions that are maintained by memory (e.g., RAM 1702, ROM 1704, or elsewhere).
More generally, instructions and other information can be stored on any computer readable medium 1710, including, but not limited to, static memory storage devices, magnetic storage devices, optical storage devices, and so on. The term computer readable medium also encompasses plural storage devices. In all cases, the computer readable medium 1710 represents some form of physical and tangible entity.
The computing functionality 1700 also includes an input/output module 1712 for receiving various inputs (via input modules 1714), and for providing various outputs (via output modules). One particular output mechanism may include a presentation module 1716 and an associated graphical user interface (GUI) 1718. The computing functionality 1700 can also include one or more network interfaces 1720 for exchanging data with other devices via one or more communication conduits 1722. One or more communication buses 1724 communicatively couple the above-described components together.
The communication conduit(s) 1722 can be implemented in any manner, e.g., by a local area network, a wide area network (e.g., the Internet), etc., or any combination thereof. As noted above in Section A, the communication conduit(s) 1722 can include any combination of hardwired links, wireless links, routers, gateway functionality, name servers, etc., governed by any protocol or combination of protocols.
Alternatively, or in addition, any of the functions described in Sections A and B can be performed, at least in part, by one or more hardware logic components. For example, without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (ASICs), Application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.
In closing, functionality described herein can employ various mechanisms to ensure the privacy of user data maintained by the functionality. For example, the functionality can allow a user to expressly opt in to (and then expressly opt out of) the provisions of the functionality. The functionality can also provide suitable security mechanisms to ensure the privacy of the user data (such as data-sanitizing mechanisms, encryption mechanisms, password-protection mechanisms, etc.).
Further, the description may have described various concepts in the context of illustrative challenges or problems. This manner of explanation does not constitute an admission that others have appreciated and/or articulated the challenges or problems in the manner specified herein.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Number | Name | Date | Kind |
---|---|---|---|
4357593 | Von Tomkewitsch | Nov 1982 | A |
4796171 | Honey et al. | Jan 1989 | A |
4796191 | Honey et al. | Jan 1989 | A |
4949268 | Nishikawa et al. | Aug 1990 | A |
5493692 | Theimer et al. | Feb 1996 | A |
5544321 | Theimer et al. | Aug 1996 | A |
5555376 | Theimer et al. | Sep 1996 | A |
5564079 | Olsson | Oct 1996 | A |
5592173 | Lau et al. | Jan 1997 | A |
5603054 | Theimer et al. | Feb 1997 | A |
5611050 | Theimer et al. | Mar 1997 | A |
5623194 | Boll et al. | Apr 1997 | A |
5781704 | Rossmo | Jul 1998 | A |
5812865 | Theimer et al. | Sep 1998 | A |
5842130 | Oprescu-Surcobe et al. | Nov 1998 | A |
5845227 | Peterson | Dec 1998 | A |
5883598 | Parl et al. | Mar 1999 | A |
5943621 | Ho et al. | Aug 1999 | A |
5948040 | DeLorme | Sep 1999 | A |
5978732 | Kakitani et al. | Nov 1999 | A |
6052598 | Rudrapatna et al. | Apr 2000 | A |
6078826 | Croft et al. | Jun 2000 | A |
6116363 | Frank | Sep 2000 | A |
6122572 | Yavnai | Sep 2000 | A |
6175805 | Abe | Jan 2001 | B1 |
6292687 | Lowell et al. | Sep 2001 | B1 |
6313786 | Sheynblat et al. | Nov 2001 | B1 |
6314347 | Kuroda et al. | Nov 2001 | B1 |
6353398 | Amin et al. | Mar 2002 | B1 |
6381522 | Watanabe et al. | Apr 2002 | B1 |
6405134 | Smith | Jun 2002 | B1 |
6418424 | Hoffberg et al. | Jul 2002 | B1 |
6466232 | Newell et al. | Oct 2002 | B1 |
6480783 | Myr | Nov 2002 | B1 |
6490519 | Lapidot et al. | Dec 2002 | B1 |
6513046 | Abbott, III et al. | Jan 2003 | B1 |
6549915 | Abbott, III et al. | Apr 2003 | B2 |
6564149 | Lai | May 2003 | B2 |
6574351 | Miyano | Jun 2003 | B1 |
6577946 | Myr | Jun 2003 | B2 |
6603405 | Smith | Aug 2003 | B2 |
6615130 | Myr | Sep 2003 | B2 |
6668227 | Hamada et al. | Dec 2003 | B2 |
6672506 | Swartz et al. | Jan 2004 | B2 |
6678525 | Baranger et al. | Jan 2004 | B1 |
6721572 | Smith et al. | Apr 2004 | B1 |
6741188 | Miller et al. | May 2004 | B1 |
6747675 | Abbott et al. | Jun 2004 | B1 |
D494584 | Schlieffers et al. | Aug 2004 | S |
6791580 | Abbott et al. | Sep 2004 | B1 |
6796505 | Pellaumail et al. | Sep 2004 | B2 |
6799047 | Bahl et al. | Sep 2004 | B1 |
6801223 | Abbott et al. | Oct 2004 | B1 |
6807483 | Chao et al. | Oct 2004 | B1 |
6812937 | Abbott et al. | Nov 2004 | B1 |
6837436 | Swartz et al. | Jan 2005 | B2 |
6842877 | Robarts et al. | Jan 2005 | B2 |
6845324 | Smith | Jan 2005 | B2 |
RE38724 | Peterson | Apr 2005 | E |
6889382 | Anderson | May 2005 | B1 |
6925378 | Tzamaloukas | Aug 2005 | B2 |
6992625 | Krumm et al. | Jan 2006 | B1 |
7010501 | Roslak et al. | Mar 2006 | B1 |
7040541 | Swartz et al. | May 2006 | B2 |
7054938 | Sundqvist et al. | May 2006 | B2 |
7058506 | Kawase et al. | Jun 2006 | B2 |
7063263 | Swartz et al. | Jun 2006 | B2 |
7084762 | Pedrazzini et al. | Aug 2006 | B2 |
7096030 | Huomo | Aug 2006 | B2 |
7116987 | Spain, Jr. et al. | Oct 2006 | B2 |
7116988 | Dietrich et al. | Oct 2006 | B2 |
7127213 | Haymes et al. | Oct 2006 | B2 |
7130743 | Kudo et al. | Oct 2006 | B2 |
7161914 | Shoaib et al. | Jan 2007 | B2 |
7162367 | Lin et al. | Jan 2007 | B2 |
7171378 | Petrovich et al. | Jan 2007 | B2 |
7195157 | Swartz et al. | Mar 2007 | B2 |
7200394 | Aoki et al. | Apr 2007 | B2 |
7215969 | Benco et al. | May 2007 | B2 |
7233861 | Van Buer et al. | Jun 2007 | B2 |
7250907 | Krumm et al. | Jul 2007 | B2 |
7321774 | Lau et al. | Jan 2008 | B1 |
7359713 | Tiwari | Apr 2008 | B1 |
7385501 | Miller et al. | Jun 2008 | B2 |
7433696 | Dietrich et al. | Oct 2008 | B2 |
7463890 | Herz et al. | Dec 2008 | B2 |
7512462 | Nichols et al. | Mar 2009 | B2 |
7565157 | Ortega et al. | Jul 2009 | B1 |
7590589 | Hoffberg | Sep 2009 | B2 |
7617042 | Horvitz et al. | Nov 2009 | B2 |
7630986 | Herz et al. | Dec 2009 | B1 |
7636707 | Chaudhuri et al. | Dec 2009 | B2 |
7698055 | Horvitz et al. | Apr 2010 | B2 |
7705728 | Mock et al. | Apr 2010 | B2 |
7706964 | Horvitz et al. | Apr 2010 | B2 |
7739040 | Horvitz | Jun 2010 | B2 |
7778440 | Malone | Aug 2010 | B2 |
7796944 | Eaton et al. | Sep 2010 | B2 |
7796966 | Bhattacharya et al. | Sep 2010 | B2 |
7813870 | Downs et al. | Oct 2010 | B2 |
7856234 | Alizadeh-Shabdiz et al. | Dec 2010 | B2 |
7864048 | Cope et al. | Jan 2011 | B1 |
7873368 | Goren | Jan 2011 | B2 |
7899611 | Downs et al. | Mar 2011 | B2 |
7912628 | Chapman et al. | Mar 2011 | B2 |
7925426 | Koebler et al. | Apr 2011 | B2 |
7961651 | Kim et al. | Jun 2011 | B2 |
7962156 | Robertson | Jun 2011 | B2 |
7991718 | Horvitz et al. | Aug 2011 | B2 |
8024112 | Krumm et al. | Sep 2011 | B2 |
8090530 | Horvitz | Jan 2012 | B2 |
8126641 | Horvitz | Feb 2012 | B2 |
8155872 | Kjeldsen et al. | Apr 2012 | B2 |
8165773 | Chavez et al. | Apr 2012 | B1 |
8174447 | Loidl et al. | May 2012 | B2 |
8180366 | Ernst et al. | May 2012 | B2 |
8190362 | Barker et al. | May 2012 | B2 |
8228234 | Paulson | Jul 2012 | B2 |
8244272 | Morgan et al. | Aug 2012 | B2 |
8255275 | Collopy et al. | Aug 2012 | B2 |
8260481 | Naik et al. | Sep 2012 | B2 |
8311730 | Neff | Nov 2012 | B2 |
8320939 | Vincent | Nov 2012 | B1 |
8433334 | Huang et al. | Apr 2013 | B2 |
8433512 | Lopatenko et al. | Apr 2013 | B1 |
8443662 | Lane et al. | May 2013 | B2 |
8463545 | Boore | Jun 2013 | B2 |
8484113 | Collopy et al. | Jul 2013 | B2 |
8519860 | Johnson et al. | Aug 2013 | B2 |
8532670 | Kim | Sep 2013 | B2 |
8538686 | Gruen et al. | Sep 2013 | B2 |
8560218 | Kahn et al. | Oct 2013 | B1 |
8565783 | Yang et al. | Oct 2013 | B2 |
8566029 | Lopatenko et al. | Oct 2013 | B1 |
8589065 | Scofield et al. | Nov 2013 | B2 |
8620692 | Collopy et al. | Dec 2013 | B2 |
8639803 | Moritz et al. | Jan 2014 | B2 |
8712931 | Wahlen | Apr 2014 | B1 |
8751146 | Shrivathsan et al. | Jun 2014 | B2 |
8762053 | Lehman | Jun 2014 | B1 |
8788606 | Johnson et al. | Jul 2014 | B2 |
8825381 | Tang | Sep 2014 | B2 |
8898002 | Barrett | Nov 2014 | B2 |
8981995 | Schlesinger et al. | Mar 2015 | B2 |
8990333 | Johnson et al. | Mar 2015 | B2 |
9134137 | Brush et al. | Sep 2015 | B2 |
20010029425 | Myr | Oct 2001 | A1 |
20010030664 | Shulman et al. | Oct 2001 | A1 |
20010040590 | Abbott et al. | Nov 2001 | A1 |
20010040591 | Abbott et al. | Nov 2001 | A1 |
20010043231 | Abbott et al. | Nov 2001 | A1 |
20010043232 | Abbott et al. | Nov 2001 | A1 |
20020032689 | Abbott, III et al. | Mar 2002 | A1 |
20020044152 | Abbott, III et al. | Apr 2002 | A1 |
20020050944 | Sheynblat et al. | May 2002 | A1 |
20020052930 | Abbott et al. | May 2002 | A1 |
20020052963 | Abbott et al. | May 2002 | A1 |
20020054130 | Abbott, III et al. | May 2002 | A1 |
20020054174 | Abbott et al. | May 2002 | A1 |
20020067289 | Smith | Jun 2002 | A1 |
20020078204 | Newell et al. | Jun 2002 | A1 |
20020080155 | Abbott et al. | Jun 2002 | A1 |
20020080156 | Abbott et al. | Jun 2002 | A1 |
20020083025 | Robarts et al. | Jun 2002 | A1 |
20020083158 | Abbott et al. | Jun 2002 | A1 |
20020087525 | Abbott et al. | Jul 2002 | A1 |
20020099817 | Abbott et al. | Jul 2002 | A1 |
20020107618 | Deguchi et al. | Aug 2002 | A1 |
20030036842 | Hancock | Feb 2003 | A1 |
20030042051 | Kriger | Mar 2003 | A1 |
20030046401 | Abbott et al. | Mar 2003 | A1 |
20030069683 | Lapidot et al. | Apr 2003 | A1 |
20030135304 | Sroub et al. | Jul 2003 | A1 |
20030139863 | Toda et al. | Jul 2003 | A1 |
20030140088 | Robinson et al. | Jul 2003 | A1 |
20030153338 | Herz et al. | Aug 2003 | A1 |
20030154009 | Basir et al. | Aug 2003 | A1 |
20030154476 | Abbott, III et al. | Aug 2003 | A1 |
20030195700 | Hamada et al. | Oct 2003 | A1 |
20030229471 | Guralnik et al. | Dec 2003 | A1 |
20030229895 | Jasinschi et al. | Dec 2003 | A1 |
20040019603 | Haigh et al. | Jan 2004 | A1 |
20040068364 | Zhao et al. | Apr 2004 | A1 |
20040090121 | Simonds et al. | May 2004 | A1 |
20040090346 | Simonds et al. | May 2004 | A1 |
20040092253 | Simonds et al. | May 2004 | A1 |
20040093154 | Simonds et al. | May 2004 | A1 |
20040093155 | Simonds et al. | May 2004 | A1 |
20040128066 | Kudo et al. | Jul 2004 | A1 |
20040153445 | Horvitz et al. | Aug 2004 | A1 |
20040166877 | Spain et al. | Aug 2004 | A1 |
20040176211 | Kitajima et al. | Sep 2004 | A1 |
20040180671 | Spain | Sep 2004 | A1 |
20040181340 | Smith | Sep 2004 | A1 |
20040189475 | Cooper et al. | Sep 2004 | A1 |
20040201500 | Miller et al. | Oct 2004 | A1 |
20040230374 | Tzamaloukas | Nov 2004 | A1 |
20040260457 | Kawase et al. | Dec 2004 | A1 |
20040268403 | Krieger et al. | Dec 2004 | A1 |
20050021417 | Kassan | Jan 2005 | A1 |
20050034078 | Abbott et al. | Feb 2005 | A1 |
20050037775 | Moeglein et al. | Feb 2005 | A1 |
20050046584 | Breed | Mar 2005 | A1 |
20050048946 | Holland et al. | Mar 2005 | A1 |
20050049900 | Hirose et al. | Mar 2005 | A1 |
20050062643 | Pande et al. | Mar 2005 | A1 |
20050086004 | Smith | Apr 2005 | A1 |
20050125148 | Van Buer et al. | Jun 2005 | A1 |
20050131607 | Breed | Jun 2005 | A1 |
20050144318 | Chang | Jun 2005 | A1 |
20050149253 | Nambata | Jul 2005 | A1 |
20050197775 | Smith | Sep 2005 | A1 |
20050219120 | Chang | Oct 2005 | A1 |
20050228553 | Tryon | Oct 2005 | A1 |
20050240378 | Smith | Oct 2005 | A1 |
20050261004 | Dietrich et al. | Nov 2005 | A1 |
20050266858 | Miller et al. | Dec 2005 | A1 |
20050272442 | Miller et al. | Dec 2005 | A1 |
20050283503 | Hancock et al. | Dec 2005 | A1 |
20060015254 | Smith | Jan 2006 | A1 |
20060019676 | Miller et al. | Jan 2006 | A1 |
20060022048 | Johnson | Feb 2006 | A1 |
20060167784 | Hoffberg | Jul 2006 | A1 |
20060241862 | Ichihara et al. | Oct 2006 | A1 |
20060256005 | Thandu et al. | Nov 2006 | A1 |
20060264211 | Kalhan et al. | Nov 2006 | A1 |
20060284765 | Bernhardt et al. | Dec 2006 | A1 |
20060286988 | Blume et al. | Dec 2006 | A1 |
20060287813 | Quigley | Dec 2006 | A1 |
20070008927 | Herz et al. | Jan 2007 | A1 |
20070042790 | Mohi et al. | Feb 2007 | A1 |
20070073477 | Krumm et al. | Mar 2007 | A1 |
20070073832 | Curtis et al. | Mar 2007 | A1 |
20070091037 | Lee | Apr 2007 | A1 |
20070106465 | Adam et al. | May 2007 | A1 |
20070115174 | Herrick | May 2007 | A1 |
20070179792 | Kramer | Aug 2007 | A1 |
20070208495 | Chapman | Sep 2007 | A1 |
20080005172 | Gutmann | Jan 2008 | A1 |
20080018529 | Yoshioka | Jan 2008 | A1 |
20080070593 | Altman et al. | Mar 2008 | A1 |
20080077326 | Funk et al. | Mar 2008 | A1 |
20080090591 | Miller et al. | Apr 2008 | A1 |
20080091537 | Miller et al. | Apr 2008 | A1 |
20080104225 | Zhang et al. | May 2008 | A1 |
20080129598 | Godefroy et al. | Jun 2008 | A1 |
20080161018 | Miller et al. | Jul 2008 | A1 |
20080180637 | Kjeldsen et al. | Jul 2008 | A1 |
20080191941 | Saban et al. | Aug 2008 | A1 |
20080234935 | Wolf et al. | Sep 2008 | A1 |
20080248815 | Busch | Oct 2008 | A1 |
20080249667 | Horvitz | Oct 2008 | A1 |
20080268870 | Houri | Oct 2008 | A1 |
20080305808 | Chan et al. | Dec 2008 | A1 |
20080311947 | Soerensen et al. | Dec 2008 | A1 |
20080319658 | Horvitz et al. | Dec 2008 | A1 |
20080319660 | Horvitz et al. | Dec 2008 | A1 |
20090005061 | Ward et al. | Jan 2009 | A1 |
20090009397 | Taylor et al. | Jan 2009 | A1 |
20090043504 | Bandyopadhyay et al. | Feb 2009 | A1 |
20090051566 | Olsen et al. | Feb 2009 | A1 |
20090063038 | Shrivathsan et al. | Mar 2009 | A1 |
20090143082 | Begaja et al. | Jun 2009 | A1 |
20090149155 | Grossman | Jun 2009 | A1 |
20090184849 | Nasiri | Jul 2009 | A1 |
20090191892 | Kelley | Jul 2009 | A1 |
20090192709 | Yonker et al. | Jul 2009 | A1 |
20090201896 | Davis et al. | Aug 2009 | A1 |
20090248301 | Judd et al. | Oct 2009 | A1 |
20090312032 | Bornstein et al. | Dec 2009 | A1 |
20100010733 | Krumm et al. | Jan 2010 | A1 |
20100039929 | Cho | Feb 2010 | A1 |
20100070334 | Monteverde | Mar 2010 | A1 |
20100079332 | Garin | Apr 2010 | A1 |
20100079334 | Roh et al. | Apr 2010 | A1 |
20100082247 | Klein et al. | Apr 2010 | A1 |
20100087230 | Peh et al. | Apr 2010 | A1 |
20100097269 | Loidl et al. | Apr 2010 | A1 |
20100127926 | Wang | May 2010 | A1 |
20100131308 | Collopy et al. | May 2010 | A1 |
20100153007 | Crowley | Jun 2010 | A1 |
20100156708 | Chen | Jun 2010 | A1 |
20100161179 | McClure et al. | Jun 2010 | A1 |
20100176992 | T'siobbel | Jul 2010 | A1 |
20100185388 | Horvitz | Jul 2010 | A1 |
20100231383 | Levine et al. | Sep 2010 | A1 |
20100250133 | Buros | Sep 2010 | A1 |
20100255856 | Kansal et al. | Oct 2010 | A1 |
20100255858 | Juhasz | Oct 2010 | A1 |
20100310071 | Malone et al. | Dec 2010 | A1 |
20100323715 | Winders et al. | Dec 2010 | A1 |
20100324813 | Sundararajan et al. | Dec 2010 | A1 |
20100332125 | Tan et al. | Dec 2010 | A1 |
20110035142 | Tang | Feb 2011 | A1 |
20110039573 | Hardie | Feb 2011 | A1 |
20110050493 | Torimoto et al. | Mar 2011 | A1 |
20110071759 | Pande et al. | Mar 2011 | A1 |
20110148623 | Bishop et al. | Jun 2011 | A1 |
20110151839 | Bolon et al. | Jun 2011 | A1 |
20110151898 | Chandra et al. | Jun 2011 | A1 |
20110163914 | Seymour | Jul 2011 | A1 |
20110169632 | Walker et al. | Jul 2011 | A1 |
20110171024 | Jensen | Jul 2011 | A1 |
20110178708 | Zhang et al. | Jul 2011 | A1 |
20110182238 | Marshall et al. | Jul 2011 | A1 |
20110184644 | McBurney et al. | Jul 2011 | A1 |
20110191024 | DeLuca | Aug 2011 | A1 |
20110191052 | Lin et al. | Aug 2011 | A1 |
20110197200 | Huang et al. | Aug 2011 | A1 |
20110207471 | Murray et al. | Aug 2011 | A1 |
20110208430 | Tun et al. | Aug 2011 | A1 |
20110212732 | Garrett et al. | Sep 2011 | A1 |
20110238289 | Lehmann et al. | Sep 2011 | A1 |
20110238308 | Miller et al. | Sep 2011 | A1 |
20110246059 | Tokashiki | Oct 2011 | A1 |
20110270940 | Johnson | Nov 2011 | A1 |
20110282571 | Krumm et al. | Nov 2011 | A1 |
20110291886 | Krieter | Dec 2011 | A1 |
20110306323 | Do et al. | Dec 2011 | A1 |
20110319094 | Usui et al. | Dec 2011 | A1 |
20120052873 | Wong | Mar 2012 | A1 |
20120089322 | Horvitz | Apr 2012 | A1 |
20120121161 | Eade et al. | May 2012 | A1 |
20120129546 | Yang et al. | May 2012 | A1 |
20120158289 | Brush et al. | Jun 2012 | A1 |
20120173139 | Judd et al. | Jul 2012 | A1 |
20120176491 | Garin et al. | Jul 2012 | A1 |
20120188124 | Reidevall et al. | Jul 2012 | A1 |
20120209507 | Serbanescu | Aug 2012 | A1 |
20120218142 | Leclercq | Aug 2012 | A1 |
20120221244 | Georgy et al. | Aug 2012 | A1 |
20120238293 | Pan et al. | Sep 2012 | A9 |
20120259541 | Downey et al. | Oct 2012 | A1 |
20120259666 | Collopy et al. | Oct 2012 | A1 |
20120290615 | Lamb et al. | Nov 2012 | A1 |
20120299724 | Kuper et al. | Nov 2012 | A1 |
20130002857 | Kulik | Jan 2013 | A1 |
20130018581 | Sidhu et al. | Jan 2013 | A1 |
20130018629 | Sidhu et al. | Jan 2013 | A1 |
20130030690 | Witmer | Jan 2013 | A1 |
20130035111 | Moeglein et al. | Feb 2013 | A1 |
20130095848 | Gold et al. | Apr 2013 | A1 |
20130114687 | Kim et al. | May 2013 | A1 |
20130115971 | Marti et al. | May 2013 | A1 |
20130116921 | Kasargod et al. | May 2013 | A1 |
20130138314 | Viittala et al. | May 2013 | A1 |
20130211711 | Kelly et al. | Aug 2013 | A1 |
20130285849 | Ben-Moshe | Oct 2013 | A1 |
20130297204 | Bartels | Nov 2013 | A1 |
20140024354 | Haik et al. | Jan 2014 | A1 |
20140070991 | Zhong et al. | Mar 2014 | A1 |
20140121960 | Park | May 2014 | A1 |
20140327547 | Johnson | Nov 2014 | A1 |
20150018008 | Schlesinger et al. | Jan 2015 | A1 |
20150073697 | Barrett et al. | Mar 2015 | A1 |
20150339397 | Brush et al. | Nov 2015 | A1 |
Number | Date | Country |
---|---|---|
1375999 | Oct 2002 | CN |
1488955 | Apr 2004 | CN |
101109808 | Jan 2008 | CN |
101251589 | Aug 2008 | CN |
102006550 | Apr 2011 | CN |
102204374 | Sep 2011 | CN |
101675597 | Feb 2014 | CN |
10042983 | Mar 2002 | DE |
2293016 | Mar 2011 | EP |
2431261 | Apr 2007 | GB |
04-364491 | Dec 1992 | JP |
2007-083678 | Mar 1995 | JP |
2008-271277 | Oct 1996 | JP |
10132593 | May 1998 | JP |
2011-153446 | Aug 1999 | JP |
2002-328035 | Nov 2002 | JP |
2004-317160 | Nov 2004 | JP |
19970071404 | Nov 1997 | KR |
20040033141 | Apr 2004 | KR |
20040050550 | Jun 2004 | KR |
8141 | Oct 1998 | RU |
WO 9800787 | Jan 1998 | WO |
2009016505 | Feb 2009 | WO |
2009039161 | Mar 2009 | WO |
2012085876 | Jun 2012 | WO |
Entry |
---|
Lachapelle, Gerard, “GNSS Indoor Location Technologies”, retrieved at <http://www.gmat.unsw.edu.au/wang/jgps/v3n12/v3n12p01.pdf>>, Journal of Global Positioning Systems, vol. 3, No. 1-2, Nov. 15, 2004, pp. 2-11. |
Toledo-Moreo, et al., “Performance Aspects of Navigation Systems for GNSS-Based Road User Charging,” retrieved at <<http://ants.inf.um.es/˜josesanta/doc/ION—GNSS10.pdf>>, Proceedings of the 23rd International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS), Sep. 21-24, 2010, pp. 1157-1165. |
Collin, et al., “Indoor positioning System Using Accelerometry and High Accuracy Heading Sensors,” retrieved at <<http://plan.geomatics.ucalgary.ca/papers/gps03jussic.pdf>>, Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation, ION GPS/GNSS Conference (Session C3), Sep. 2003, pp. 1-7. |
Wendlandt, et al., “Continuous location and direction estimation with multiple sensors using particle filtering,” retrieved at <<http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04042026>>, IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Sep. 2006, pp. 92-97. |
Toledo-Moreo, et al., “Lane-Level Integrity Provision for Navigation and Map Matching With GNSS, Dead Reckoning, and Enhanced Maps,” retrieved at <<http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5286855>>, IEEE Transactions on Intelligent Transportation Systems, vol. 11, No. 1, Mar. 2010, pp. 100-112. |
Chun, et al., “CloneCloud: Elastic Execution between Mobile Device and Cloud,” retrieved at <<http://eurosys2011.cs.uni-salzburg.at/pdf/eurosys2011-chun.pdf>>, Proceedings of the Sixth Conference on Computer Systems (EuroSys'11 ), Apr. 2011, pp. 301-314. |
Cabero, et al., “Indoor People Tracking Based on Dynamic Weighted MultiDimensional Scaling,” retrieved at <<http://www.ri.cmu.edu/pub—files/pub4/maria—cabero—jose—2007—1/maria—cabero—jose—2007—1.pdf>>, MSWIM '07, Proceedings of the 10th ACM Symposium on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, Oct. 2007, 8 pages. |
De Moraes, et al., “Calibration-Free WLAN Location System Based on Dynamic Mapping of Signal Strength,” retrieved at <<http//:www.ravel.ufrj.br/arquivosPublicacoes/WAC11-demoraes.pdf>>, MobiWac '06, Proceedings of the 4th ACM International Workshop on Mobility Management and Wireless Access, Oct. 2006, 8 pages. |
Goyal, Vishal, “MEMS Based Motion Sensing Design,” retrieved at <<http://www.eeherald.com/section/design-guide/mems—application.html>>, retrieved on Mar. 30, 2011, Electronics Engineering Herald, 2006, 2 pages. |
Jimenez, et al., “A Comparison of Pedestrian Dead-Reckoning Algorithms using a Low-Cost MEMS IMU,” retrieved at <<http://www.iai.csic.es/users/fseco/papers/WISP2009Jimenez.pdf>>, WISP 2009, 6th IEEE International Symposium on Intelligent Signal Processing, Aug. 2009, pp. 37-42. |
Jin, et al., “A Robust Dead-Reckoning Pedestrian Tracking System with Low Cost Sensors,” retried at <<http://www.ami-lab.org/uploads/Publications/Conference/WP2/Robust%20Dead-Reckoning%20Pedestrian%20Tracking%20System%20with%20Low%20Cost%20Sensors.pdf>>, 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom), Mar. 21-25, 2011, pp. 222-230. |
Koyuncu, et al., “A Survey of Indoor Positioning and Object Locating Systems,” retrieved at <<http://paper.ijcsns.org/07—book/201005/20100518.pdf>>, IJCSNS International Journal of Computer Science and Network Security, vol. 10, No. 5, May 2010, pp. 121-128. |
Paul, et al., “Wi-Fi Based Indoor Localization and Tracking Using Sigma-Point Kalman Filtering Methods,” retrieved at <<http//:www.cse.ogi.edu/˜anindya/Paul—Wan—Plans08.pdf>>, IEEE/ION Position, Location and Navigation Symposium, May 2008, 14 pages. |
Rogoleva, Luba, “Crowdsourcing Location Information to Improve Indoor Localization,” retrieved at <<http://ecollection.ethbib.ethz.ch/eserv/eth:1224/eth-1224-01.pdf>>, Master Thesis, Eidgenossiche Technische Hochschule Zurich, Apr. 30, 2010, 91 pages. |
Shin, et al., “Sit-Down and Stand-Up Awareness Algorithm for the Pedestrian Dead Reckoning,” retrieved at <<http://sspace.snu.ac.kr/bitstream/10371/27736/1/Sit-Down%20&%020Stand-Up%20Awareness%20Algorithm%20for%20the%20Pedestrian%20Dead%20Reckoning.pdf>>, GNSS '09, May 2009, 6 pages. |
Xuan, et al., “Crowd Sourcing Indoor Maps with Mobile Sensors,” retrieved at <<http://www.ocf.berkeley.edu/˜xuanyg/IndoorMap—Mobiquitous2010—ver2.pdf>>, 7th International ICST Conference on Mobile and Ubiquitous Systems (Mobiquitous 2010), Dec. 2010, 12 pages. |
Zhu, et al-, “Indoor/Outdoor Location of Cellular Handsets Based on Received Signal Strength,” retrieved at <<http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=01543256>>, Electronics Letters, vol. 41, No. 1, 2 pages. |
Gusenbauer, et al., “Self-Contained Indoor Positioning on Off-The-Shelf Mobile Devices,” retrieved at <<http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05646681>>, International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sep. 2010, 9 pages. |
Sidhu, et al., “Multi-Stage Dead Reckoning for Crowd Sourcing,” U.S. Appl. No. 13/284,128, filed Oct. 28, 2011, 42 pages. |
Sidhu, et al., “Activating and Deactivating Sensors for Dead Reckoning,” U.S. Appl. No. 13/183,050, filed Jul. 14, 2011, 48 pages. |
Sidhu, et al., “Crowd Sourcing Based on Dead Reckoning,” U.S. Appl. No. 13/183,124, filed Jul. 14, 2011, 48 pages. |
Yang, et al., “Path Progression Matching for Indoor Positioning Systems,” U.S. Appl. No. 12/954,545, filed Nov. 24, 2010, 43 pages. |
Goyal, Vishal, “MEMS based motion sensing design,” retrieved at <<http://www.eeherald.com/section/design-guide/mems—application.html>>, EE Herald, retrieved Jul. 9, 2012, 2 pages. |
Beard, K., et al., “Estimating positions and paths of moving objects”, Temporal Representation and Reasoning, 2000. TIME 2000. Proceedings. Seventh International Workshop on; Digital Object Identifier: 10.1109/TIME.2000.856597 Publication Year: 2000, pp. 155-162. |
Billinghurst, Mark, et al., “An Evaluation of Wearable Information Spaces”, Proceedings of the Virtual Reality Annual International Symposium, 1998, 8 pages. |
Billinghurst, Mark, et al., “Research Directions in Wearable Computing”, University of Washington, May, 1998, 48 pages. |
Billinghurst, Mark, et al., “Wearable Devices: New Ways to Manage Information”, IEEE Computer Society, Jan. 1999, pp. 57-64. |
Chen, Guanling, et al., “A Survey of Context-Aware Mobile Computing Research,” Dartmouth Computer Science Technical Report, 2000, 16 pages. |
Choi, Jae-Hyeong,et al., “Performance evaluation of traffic control based on geographical information”, Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on; vol. 3; Publication Year: 2009, pp. 85-89. |
Harter, Andy, et al., “A Distributed Location System for the Active Office,” IEEE Network, 1994, pp. 62-70. |
Horvitz, Eric, et al., “Attention-Sensitive Alerting in Computing Systems”, Microsoft Research, Aug. 1999. |
Horvitz, Eric, et al., “In Pursuit of Effective Handsfree Decision Support: Coupling Bayesian Inference”, Speech Understanding, and User Models,1995, 8 pages. |
Joachims, T., “Text categorization with support vector machines: learning with many relevant features”, Machine Learning, European Conference on Machine Learning, Apr. 21, 1998, pp. 137-142. |
Kostov, V., et al., “Travel destination prediction using frequent crossing pattern from driving history”, Intelligent transportation Systems, 2005. Proceedings. 2005 IEEE; Digital Object Identifier: 10.1109/ITSC.2005.1520182 Publication Year: 2005, pp. 343-350. |
Krumm, “Predestination: Where Do You Want to Go Today?”; Computer; vol. 40, Issue 4; Apr. 2007; pp. 105-107. |
Lee, Junghoon, et al., “Design and implementation of a movement history analysis frame-work for the Taxi telematics system”, Communications, 2008. APCC 2008. 14th Asia-Pacific Conference on; Publication Year: 2008, pp. 1-4. |
Liu, Feng, et al., “Remaining Delivery Time Estimation Based Routing for Intermittently Connected Mobile Networks”, Distributed Computing Systems Workshops, 2008. ICDCS '08. 28th International Conference, Publication Year: 2008, pp. 222-227. |
Losee, Robert M. Jr., “Minimizing information overload: the ranking of electronic messages”, Journal of Information Science 15, Elsevier Science Publishers B.V., 1989, pp. 179-189. |
Miyashita, K. et al., “A Map Matching Algorithm for Car Navigation Systems that Predict User Destination”, Advanced Information Networking and Applications—Workshops, 2008. AINAW 2008. 22nd International Conference, Publication Year: 2008, pp. 1551-1556. |
Rhodes, Bradley J., “The Wearable Remembrance Agent: A System for Augmented Memory”, Personal Technologies Journal Special Issue on Wearable Computing, 1997, 12 pages. |
Rhodes, Bradley J., “The Wearable Remembrance Agent: A System for Augmented Theory”, The Proceedings of the First International Symposium on Wearable Computers, Oct. 1997, pp. 123-128. |
Sananmongkhonchai, S. et al., “Cell-based traffic estimation from multiple GPS-equipped cars”, 2009 IEEE Region 10 Conference Publication Year: 2009, pp. 1-6. |
Schilit, Bill, et al., “Context-Aware Computing Applications”, In Proceedings of the Workshop on Mobile Computing Systems and Applications, Dec. 1994, pp. 85-90. |
Schilit, Bill, et al., “Customizing Mobile Applications”, Proceedings USENIX Symposium on Mobile and Location Independent Computing, Aug. 1993, 9 pages. |
Schilit, Bill, et al., “Disseminating Active Map Information to Mobile Hosts”, IEEE Network, 1994 pp. 22-32, vol. 8—No. 5. |
Schilit, Bill, et al., “The ParcTab Mobile Computing System”, IEEE WWOS-IV, 1993, 4 pages. |
Schilit, William Noah, “A System Architecture for Context-Aware Mobile Computing”, Columbia University, 1995, 153 pages. |
Simmons, R, et al, “Learning to Predict Driver Route and Destination Intent”, Intelligent Transportation Systems Conference, 2006. IEEE; Digital Object Identifier: 10.1109/ITSC.2006.1706730 Publication Year: 2006, pp. 127-132. |
Spreitzer, Mike, et al., “Providing Location Information in a Ubiquitous Computing Environment”, SIGOPS '93, 1993, pp. 270-283. |
Spreitzer, Mike, et al., “Architectural Considerations for Scalable, Secure, Mobile Computing with Location Information”, In the 14th International Conference on Distributed Computing Systems, Jun. 1994, pp. 29-38. |
Spreitzer, Mike, et al., “Scalable, Secure, Mobile Computing with Location Information”, Communications of the ACM, Jul. 1993, 1 page, vol. 36—No. 7. |
Starner, Thad Eugene, “Wearable Computing and Contextual Awareness”, Massachusetts Institue of Technology, Jun. 1999, 248 pages. |
Terada, T, et al., “Design of a Car Navigation System that Predicts User Destination”, Mobile Data Management, 2006. MDM 2006. 7th International Conference on; Publication Year: 2006, pp. 145-150. |
Theimer, Marvin, et al., “Operating System Issues for PDA's”, in Fourth Workshop on Workstation Operating Systems, 1993, 7 pages. |
Vaughan-Nichols, S.J., “Will Mobile Computing's Future Be Location, Location, Location?”, Computer; vol. 42, Issue: 2 Digital Object Identifier: 10.1109/MC.2009.65; Publication Year: 2009, pp. 14-17. |
Want, Roy, “Active Badges and Personal Interactive Computing Objects”, IEEE Transactions on Consumer Electronics, 1992, 11 pages, vol. 38—No. 1. |
Want, Roy, et al., “The Active Badge Location System”, ACM Transactions on Information Systems, Jan. 1992, pp. 91-102, vol. 10—No. 1. |
Wei, Chien-Hung, et al., “Development of Freeway Travel Time Forecasting Models by Integrating Different Sources of Traffic Data”, IEEE Transactions on Vehicular Technology; vol. 56, Issue: 6, Part: 2; Nov. 2007, pp. 3682-3694. |
Weiser, Mark, “Some Computer Science Issues in Ubiquitous Computing”, Communications of the ACM, Jul. 1993, pp. 75-84, vol. 36—No. 7. |
Weiser, Mark, “The Computer for the 21st Century”, Scientific American, Sep. 1991, 8 pages. |
Workshop on Wearable Computing Systems, Aug. 19-21, 1996. |
Wu, Yan-Jing, et al., “A dynamic navigation scheme for vehicular ad hoc networks”, Networked Computing and Advanced Information Management (NCM), 2010 Sixth International Conference on; Publication Year: 2010, pp. 231-235. |
Xie, M. et al., “Development of Navigation System for Autonomous Vehicle to Meet the DARPA Urban Grand Challenge”, Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE; Sep. 30-Oct. 3, 2007, Seattle, WA; pp. 767-772. |
Ye, Qian, et al, “Predict Personal Continuous Route”, 2008. 11th International IEEE Conference on Intelligent Transportation Systems; Oct. 12-15, 2008, Beijing, China; pp. 587-592. |
PCT Application Serial No. PCT/US2008/067808, International Search Report and Written Opinion dated Dec. 12, 2008; 8 pages. |
PCT Application Serial No. PCT/US2006/034608, International Search Report dated Jan. 15, 2007; 2 pages. |
PCT Application Serial No. PCT/US00/20685; International Search Report dated Sep. 29, 2003; 3 pages. |
Russian Patent Appln. 2008112196/11; Office Action dated Jun. 8, 2010. |
Rhodes, “Remembrance Agent: A Continuously Running Automated Information Retrieval System”, Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi Talent Technology, Apr. 22-24, 1996. |
Biegel et al., “A Framework for Developing Mobile, Context-Aware Applications”, Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications, pp. 361-365, Mar. 14-17, 2004. |
Bisdikian et al., “Intelligent Pervasive Middleware for Context-Based and Localized Telematics Services”, Proceedings of the Second International ACM Conference on Mobile Commerce, pp. 15-24, Sep. 2002. |
Kargl et al., “Smart Reminder—Personal Assistance in a Mobile Computing Environment”, Proceedings of the International Conference on Pervasive Computing, Aug. 26-28, 2002. |
“Non-Final Office Action”, Dated Aug. 15, 2014, From U.S. Appl. No. 13/284,128, filed Oct. 28, 2011. |
“Non-Final Office Action”, Dated Mar. 1, 2013, From U.S. Appl. No. 12/954,545, filed Nov. 24, 2010. |
“Non-Final Office Action”, Dated Jun. 15, 2012, From U.S. Appl. No. 12/954,545, filed Nov. 24, 2010. |
Response to the Jun. 15, 2012 Non-Final Office Action, From U.S. Appl. No. 12/954,545, filed Sep. 24, 2012. |
Response to the Mar. 1, 2013 Non-Final Office Action, From U.S. Appl. No. 12/954,545, filed Jun. 24, 2013. |
“Non-Final Office Action”, Dated May 28, 2014, From U.S. Appl. No. 13/183,124, filed Jul. 14, 2011. |
“Non-Final Office Action”, Dated Jun. 11, 2014, From U.S. Appl. No. 13/183,050, filed Jul. 14, 2011. |
“Non-Final Office Action”, Dated Mar. 26, 2009, From U.S. Appl. No. 11/733,701, filed Apr. 10, 2007. |
Response to the Mar. 26, 2009 Non-Final Office Action, From U.S. Appl. No. 11/733,701, filed Jun. 26, 2009. |
“Final Office Action”, Dated Oct. 21, 2009, From U.S. Appl. No. 11/733,701, filed Apr. 10, 2007. |
Response to the Oct. 21, 2009 Final Office Action, From U.S. Appl. No. 11/733,701, filed Dec. 2, 2009. |
“Non-Final Office Action”, Dated Dec. 23, 2011, From U.S. Appl. No. 11/733,701, filed Apr. 10, 2007. |
Response to the Dec. 23, 2011 Non-Final Office Action, From U.S. Appl. No. 11/733,701, filed Mar. 27, 2012. |
“Non-Final Office Action”, Dated Sep. 3, 2009, From U.S. Appl. No. 11/426,540, filed Jun. 26, 2006. |
Response to the Jun. 26, 2009 Non-Final Office Action, From U.S. Appl. No. 11/426,540, filed Nov. 24, 2009. |
“Non-Final Office Action”, Dated Oct. 14, 2010, From U.S. Appl. No. 11/426,540, filed Jun. 26, 2006. |
Response to the Oct. 14, 2010 Non-Final Office Action, From U.S. Appl. No. 11/426,540, filed Jan. 25, 2011. |
“Non-Final Office Action”, Dated Apr. 6, 2010, From U.S. Appl. No. 11/426,540, filed Jun. 26, 2006. |
Response to the Apr. 6, 2010 Non-Final Office Action, From U.S. Appl. No. 11/426,540, filed Jul. 6, 2010. |
“Amendment After Allowance Under 37 C.F.R. 1.312” From U.S. Appl. No. 11/426,540, filed Jun. 14, 2011. |
Office Communication in Response to Amendment After Allowance Under 37 C.F.R. 1.312 From U.S. Appl. No. 11/426,540, filed Jun. 29, 2011. |
Japanese Office Action from Application No. 2008-533377 Dated: May 31, 2011, Filed: Sep. 5, 2006. |
Chinese Office Action Dated: Jul. 23, 2009 from Application No. 200680036290.9, Filed: Sep. 5, 2006. |
Response to the Mar. 20, 2009 Chinese Office Action from Application No. 200680036290.9, Dated: Jul. 22, 2009. |
Chinese Office Action Dated: Mar. 20, 2009 from Application No. 200680036290.9, Filed: Sep. 5, 2006. |
Response to Jul. 31, 2012 Malaysian Office Action from Application No. PI 20080636, Filed Sep. 26, 2012. |
Response to the Oct. 12, 2009 New Zealand Examination Report from Application No. 566701, Filed Apr. 29, 2010. |
“Examination Report”, Dated: Oct. 12, 2009 from New Zealand Application No. 566701. Filed Sep. 5, 2006. |
Response to the May 18, 2010 New Zealand Examination Report from Application No. 566701, Filed May 24, 2010. |
“Examination Report”, Dated: May 18, 2010 from New Zealand Application No. 566701. Filed Sep. 5, 2006. |
Philippine Office Action Dated: Sep. 9, 2011 from Philippine Application No. 1-2008-500513 Filed: Sep. 5, 2006. |
Russian Office Action Dated: Mar. 30, 2010 from Russian Application No. 2008112196, Filed Sep. 5, 2006. |
“Response to the May 28, 2014 Non-Final Office Action” From U.S. Appl. No. 13/183,124, filed Sep. 29, 2014. |
“Response to the Jun. 11, 2014 Non-Final Office Action” From U.S. Appl. No. 13/183,050, filed Oct. 10, 2014. |
Ghasemzadeh, H. et al., “Action Coverage Formulation for Power Organization in Body Sensor Networks,” in Proceedings of the 2008 Asia and South Pacific Design Automation Conference, Jan. 2008, IEEE Computer Society Press, pp. 446-451. |
Final Office Action Mailed Nov. 26, 2014 from U.S. Appl. No. 13/183,050, 22 ages. |
Response to Non-Final Office Action Filed Nov. 17, 2014 from U.S. Appl. No. 13/284,128, 15 pages. |
Non-Final Office Action Mailed Feb. 3, 2015, From U.S. Appl. No. 13/183,124, 29 Pages. |
Response to Final Office Action Filed Feb. 25, 2015, From U.S. Appl. No. 13/183,050, 17 Pages. |
“MEMS based motion sensing design”, Retrieved at <<http://www.eeherald.com/selection/design-guide/mems—application.html>>, Retrieved Mar. 30, 2011, 2 Pages. |
Ashbrook et al., “Using GPS to Learn Significant Locations and Predict Movement Across Multiple Users”, Personal and Ubiquitous Computing, 7(5), 2003, pp. 275-286, 15 pages. |
Chen et al., “HarpiaGrid: A Reliable Grid-based Rounding Protocol for Vehicular Ad Hoc Networks”, Intelligent Transportation Systems, ITSC 2008, 11th International IEEE Conference, pp. 383-388, 6 pages. |
Coyne et al., “Comparison of Differentially Corrected GPS Sources for Support of Site-Specific Management in Agriculture”, Jul. 2003, Kansas State University Agricultural Experiment Station and Cooperative Extension Service, 35 pages. |
Hu et al., “Simulation-Assignment-Based Travel Time Prediction Model for Traffic Corridors,” Intelligent Transportation Systems, IEEE Transactions, vol. PP, Issue 99, 2012, pp. 1277-1286, 10 pages. |
Hu et al., “Summary of Travel Trends”, 2001 National Household Survey, Dec. 2004, U.S. Department of Transportation, U.S. Federal Highway Administration, 135 pages. |
Kanoh et al., “Evaluation of GA-based Dynamic Rout Guidance for Car Navigation using Cellular Automata,” Intelligent Vehicle Symposium, 2002, IEEE, vol. 1, pp. 178-183, 6 pages. |
Kanoh et al., “Route Guidance with Unspecific Staging Post using Genetic Algorithm for Car Navigation Systems,” Intelligent Transport Systems, 2000, IEEE, pp. 119-124, 6 pages. |
Kanoh et al., “Knowledge Based Genetic Algorithm for Dynamic Route Selection,” Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000, Proceedings Fourth International Conference on vol. 2, pp. 616-619, 4 pages. |
Krumm et al., “The Microsoft Multiperson Location Survey”, (MSR-TR-2005-103), Aug. 2005, Microsoft Research, 4 pages. |
Lai et al., “Hierarchical Incremental Pat Planning and Situation-Dependent Optimized Dynamic Motion Planning Considering Accelerations,” Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on vol. 37, Issue 6, 2007, pp. 1541-1554, 14 pages. |
Marmasse et al., “A User-Centered Location Model”, Personal and Ubiquitos Computing, 2002(6), pp. 318-321, 4 pages. |
Patterson et al., “Opportunity Knocks: A System to Provide Dobnitive Assistance with Transportation Services”, in UbiComp 2004: Ubiquitous Computing, 2004, Nottingham, UK; Springer, 18 pages. |
Rish, “An Empirical Study of the Naïve Bayes Classifier”, IJCAI-01 Workshop on Empirical Methods in AI, Nov. 2, 2001, 7 pages. |
Vanajakshi et al., “Support Vector Machine Technique for the Short Term Prediction of Travel Time,” Intelligent Vehicles Symposium, 2007 IEEE, pp. 600-605, 6 pages. |
Cheng, et al., “Location Prediction Algorithms for Mobile Wireless Systems,” Wireless Internet Handbook: Technologies, Standards, and Applications, 2003, CRC Press, Boca Raton, FL, pp. 245-263, 17 pages. |
Hariharan, et al., “Project Lachesis: Parsing and Modeling Location Histories,” Geographic Information Science: Third International Conference, GI Science 2004, Adelphi, MD, Springer-Verlag GmbH, 19 pages. |
Liao, et al., “Learning and Inferring Transportation Route ins,” Proceedings of the 19th National Conference on Artificial Intelligence (AAAI), 2004, San Jose, CA, 6 pages. |
Gogate, et al., “Modeling Transportation Routines using Hybrid Dynamic Mixed Networks,” Uncertainty in Artificial Intelligence (UAI), 2005, 8 pages. |
Angermann, et al., “Software Represenation for Heterogeneous Location Data Sources Using Probability Density Functions,” International Symposium on Location Based Services for Cellular Users (LOCELLUS), 2001, Munich, Germany, 10 pages. |
Elfes et al., “Using Occupancy Grids for Mobile Robot Perception and Navigation,” IEEE Computer, 1989, 22(6), pp. 46-57, 12 pages. |
Krumm, “Predestination: Predicting Driving Destinations from Map Data,” UbiComp 2006: Ubiquitous Computing 8th International Conference, 18 pages. |
Krumm, John, “Real Time Destination Prediction Based on Efficient Routes,” SAE Technical Paper, Paper No. 2006-01-0811, Apr. 3, 2006, 6 pages. |
Karbassi et al., “Vehicle Route Prediction and Time of Arrival Estimation Techniques for Improved Transportation System Management,” Proceedings of the Intelligent Vehicles Symposium, 2003, pp. 511-516, 6 pages. |
Notice of Allowance mailed Apr. 15, 2011 from U.S. Appl. No. 11/426,540, 10 pages. |
Second Office Action mailed Sep. 4, 2009 from Chinese Patent Application No. 200680036290.9, 7 pages. |
Supplemental Amendment filed Feb. 13, 2013 from U.S. Appl. No. 12/954,545, 11 pages. |
Notice of Allowance mailed Jul. 11, 2013 from U.S. Appl. No. 12/954,545, 10 pages. |
Applicant Initiated Interview Summary mailed Aug. 26, 2013 from U.S. Appl. No. 12/954,545, 3 pages. |
Response filed May 4, 2015 to the Non-Final Office Action dated Feb. 3, 2015 from U.S. Appl. No. 13/183,124, 16 pages. |
Non-Final Rejection mailed Jun. 18, 2015 from U.S. Appl. No. 13/184,050, 24 pages. |
Official Action mailed Mar. 25, 2014 Withdrawing/Vacating previous Office Action from U.S. Appl. No. 13/184,050, 2 pages. |
Applicant Initiated Interview Summary mailed Dec. 26, 2013 from U.S. Appl. No. 13/184,050, 3 pages. |
Non-Final Office Action mailed Sep. 24, 2013 from U.S. Appl. No. 13/184,050, 11 pages. |
Notice of Allowance and Examiner Initiated Interview Summary mailed Jul. 22, 2015 from U.S. Appl. No. 13/183,124, 17 pages. |
Supplemental Notice of Allowability mailed Aug. 4, 2015 from from U.S. Appl. No. 13/183,124, 2 pages. |
Response to Second Office Action filed Nov. 4, 2009 from Chinese Patent Application No. 200680036290.9, 12 pages. |
Notice of Allowance mailed Jan. 22, 2010 from Chinese Patent Application No. 200680036290.9, 4 pages. |
Extended European Search Report mailed Jun. 14, 2012 from European Patent Application No. 06802991.7, 6 pages. |
Notice of Rejection and translation mailed May 31, 2011 from Japanese Patent Application No. 2008-533377, 6 pages. |
Response filed Aug. 25, 2011 from Japanese Patent Application No. 2008-533377, 2 pages. |
Notice of Allowance mailed Dec. 16, 2011 from Japanese Patent Application No. 2008-533377, 6 pages. |
Request for Examination and Amendment filed Aug. 26, 2011 from Korean Patent Application No. 10-2008-7007693, 22 pages. |
Notice of Allowance mailed Aug. 30, 2013 from Malaysian Patent Application No. PI 20080636, 3 pages. |
Notice of Acceptance mailed Jun. 11, 2010 from New Zealand Patent Application No. 566701, 1 page. |
Response filed May 13, 2010 from Russian Patent Application No. 20081121996, 8 pages. |
Amendment filed Apr. 9, 2009 from South African Patent Application No. 2008102681, 3 pages. |
Notice of Panel Decision from Pre-Appeal Brief Review mailed May 19, 2015 from U.S. Appl. No. 13/190,121, 2 pages. |
Pre-Appeal Brief Request and Notice of Appeal filed Apr. 28, 2015 from U.S. Appl. No. 13/190,121, 8 pages. |
Final Office Action mailed Jan. 28, 2015 from U.S. Appl. No. 13/190,121, 12 pages. |
Response/Amendment and Reply filed Sep. 30, 2014 from U.S. Appl. No. 13/190,121, 15 pages. |
Non-Final Office Action mailed Jul. 1, 2014 from U.S. Appl. No. 13/190,121, 11 pages. |
Response/Amendment and Reply filed Apr. 15, 2014 from U.S. Appl. No. 13/190,121, 14 pages. |
Non-Final Office Action mailed Jan. 15, 2014 from U.S. Appl. No. 13/190,121, 9 pages. |
Response/Amendment and Reply filed Sep. 25, 2013 from U.S. Appl. No. 13/190,121, 11 pages. |
Non-Final Office Action mailed Jun. 27, 2013 from U.S. Appl. No. 13/190,121, 10 pages. |
Response/Amendment and Reply filed Mar. 11, 2013 from U.S. Appl. No. 13/190,121, 11 pages. |
Non-Final Office Action mailed Dec. 12, 2012 from U.S. Appl. No. 13/190,121, 8 pages. |
Notice of Allowance mailed Sep. 4, 2012 from U.S. Appl. No. 13/190,121, 8 pages. |
Response/Amendment and Reply filed Apr. 19, 2012 from U.S. Appl. No. 13/190,121, 9 pages. |
Non-Final Office Action mailed Jan. 19, 2012 from U.S. Appl. No. 13/190,121, 8 pages. |
Restriction Requirement mailed Feb. 26, 2009 from U.S. Appl. No. 11/733,701, 9 pages. |
Response to Restriction Requirement filed Mar. 5, 2009 from U.S. Appl. No. 11/733,701, 2 pages. |
Applicant Summary of Interview with Examiner filed Oct. 5, 2012 from U.S. Appl. No. 12/954,545, 2 pages. |
Applicant Initiated Interview Summary mailed Oct. 16, 2012 from U.S. Appl. No. 12/954,545, 3 pages. |
Notice of Allowance mailed Nov. 26, 2012 from U.S. Appl. No. 12/954,545, 9 pages. |
Goldstone et al., “Group Path Formation,” IEEE Transaction on Systems, Man and Cybernetics, Part A: Systems and Humans, 2006, vol. 36, Issue 3, pp. 611-620, 10 pages. |
Samaan et al., “A User Centric Mobility Prediction Approach Based on Spatial Conceptual Maps,” 2005 IEEE International Conference on Communications, vol. 2, pp. 1413-1417, 5 pages. |
Thiagarajan et al., “Cooperative Transit Tracking Using Smart-Phones,” SenSy'10, Zurich, Switzerland, Nov. 3-5, 2010, pp. 85-98, 14 pages. |
Request for Examination and Voluntary Amendment filed Sep. 2, 2011 in the Canadian Patent Application No. 2,620,587, 51 pages. |
Non-Final Office Action mailed Sep. 8, 2015 from U.S. Appl. No. 13/190,121, 12 pages. |
Supplemental Notice of Allowability mailed Aug. 27, 2015 from from U.S. Appl. No. 13/183,124, 2 pages. |
Response filed Feb. 25, 2015 to Final Office Action mailed Nov. 26, 2014 from U.S. Appl. No. 13/183,050, 17 pages. |
Non-Final Office Action mailed Jun. 18, 2015 from U.S. Appl. No. 13/183,050, 24 pages. |
Non-Final Office Action mailed Sep. 17, 2015 from U.S. Appl. No. 13/284,128, 22 pages. |
Notice of Allowance, Office Action Appendix and Applicant-Initiated Interview Summary mailed Oct. 20, 2015 from U.S. Appl. No. 13/183,050, 20 pages. |
Amin et al., “Fancy a Drink in Canary Wharf? A User Study on Location-Based Mobile Search,” In Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I, Aug. 24, 2009, 14 pages. |
Dissanayake et al., “A Solution to the Simultaneous Localization and Map Building (SLAM) Problem,” retrieved at <<http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=8,amumber=938381>>, Proceedings: IEEE Transactions on Robotics and Automation, vol. 17, No. 3, Jun. 2001, pp. 229-241, 13 pages. |
Jeong et al., “TBD: Trajectory-Based Data Forwarding for Light-Traffic Vehicular Networks,” 29th IEEE International conference on Distributed Computing Systems, Jun. 22-26, 2009, pp. 231-238, 8 pages. |
Liu et al., “Location Awareness through Trajectory Prediction,” Computers, Environment and Urban Systems, Elsevier, retrieved at http://www.sis.pitt.edu/˜xliu/papers/ceus.pdf, 2006, 38 pages. |
Renso et al., “Wireless Network Data Sources: Tracking and Synthesizing Trajectories,” retrieved at <<http://www.dsc.ufcg.edu.br/˜sampaio/Livros/mobility-data-mining-and-privacy-geographic-knowledge-discover.pdf#page=84>>, 2008, pp. 73-99, 28 pages. |
Subramanian et al., “Drive-by Localization of Roadside WiFi Networks,” IEEE Infocom Conference, Apr. 13-18, 2008, pp. 718-725, 9 pages. |
Wei et al., “PATS: A Framework of Pattern-Aware Trajectory Search,” in IEEE Eleventh International Conference on Mobile Data Management (MDM), May 23, 2010, pp. 372-377, 6 pages. |
Notice of Allowance mailed Nov. 16, 2015 from U.S. Appl. No. 13/183,124, 8 pages. |
Preliminary Amendment filed Aug. 23, 2013 from U.S. Appl. No. 13/606,029, 8 pages. |
Restriction Requirement mailed Jun. 25, 2015 from U.S. Appl. No. 13/606,029, 6 pages. |
Response filed Jul. 21, 2015 to Restriction Requirement mailed Jun. 25, 2015 from U.S. Appl. No. 13/606,029, 8 pages. |
Non-Final Office Action mailed Aug. 7, 2015 from U.S. Appl. No. 13/606,029, 16 pages. |
Applicant Initiated Interview Summary mailed Nov. 17, 2015 from US. Appl. No. 13/606,029, 3 pages. |
Response filed Nov. 17, 2015 to Non-Final Office Action mailed Aug. 7, 2015 from U.S. Appl. No. 13/606,029, 14 pages. |
Final Office Action mailed Dec. 4, 2015 from U.S. Appl. No. 13/606,029, 6 pages. |
International Search Report and Written Opinion mailed Dec. 20, 2013 from PCT Patent Application No. PCT/US2013/058350, 9 pages. |
Restriction Requirement mailed Mar. 21, 2014 from U.S. Appl. No. 13/551,613, 8 pages. |
Response filed Apr. 28, 2014 to Restriction Requirement mailed Mar. 21, 2014 from U.S Appl. No. 13/551,613, 13 pages. |
Non-Final Office Action mailed Aug. 13, 2014 from U.S. Appl. No. 13/551,613, 10 pages. |
Response filed Nov. 13, 2014 to Non-Final Office Action mailed Aug. 13, 2014 from U.S. Appl. No. 13/551,613, 17 pages. |
Final Office Action mailed Mar. 11, 2015 from U.S. Appl. No. 13/551,613, 15 pages. |
Response filed Jun. 16, 2015 to Final Office Action mailed Mar. 11, 2015 from U.S. Appl. No. 13/551,613, 16 pages. |
Non-Final Office Action mailed Jul. 10, 2015 from U.S. Appl. No. 13/551,613, 11 pages. |
International Search Report and Written Opinion mailed Nov. 8, 2013 from PCT Patent Application No. PCT/US2013/050963, 13 pages. |
Communication Pursuant to Rules 161(1) and 162 EPC mailed Feb. 26, 2015 from European Patent Application No. 13748129.7, 2 pages. |
Response filed Jul. 31, 2015 to the Communication mailed Feb. 26, 2015 from European Patent Application No. 137481298.7, 9 pages. |
Response mailed Dec. 12, 2015 to the Non-Final Office Action mailed Jul. 16, 2015 from U.S. Appl. No. 13/551,613, 13 pages. |
Response filed Dec. 8, 2015 to the Non-Final Office Action mailed Sep. 8, 2015 from U.S. Appl. No. 13/190,121, 15 pages. |
Response filed Jan. 15, 2016 to Non-Final Office Action mailed Sep. 17, 2015 from U.S. Appl. No. 13/284,128, 16 pages. |
Notification of the First Office Action mailed Dec. 31, 2015 from China Patent Application No. 201380038072.9 14 pages. |
Non-Final Office Action mailed Jun. 28, 2011 from U.S. Appl. No. 12/417,752, 15 pages. |
Response filed Oct. 27, 2011 to Non-Final Office Action mailed Jun. 28, 2011 from U.S. Appl. No. 12/417,752, 17 pages. |
Final Office Action mailed Sep. 13, 2012 from U.S. Appl. No. 12/417,752, 18 pages. |
Response filed Dec. 13, 2012 to Final Office Action mailed Sep. 13, 2012 from U.S. Appl. No. 12/417,752, 13 pages. |
Non-Final Office Action mailed May 24, 2013 from U.S. Appl. No. 12/417,752, 18 pages. |
Response filed Jul. 2, 2013 to Non-Final Office Action mailed May 24, 2013 from U.S. Appl. No. 12/417,752, 16 pages. |
Final Office Action mailed Jul. 17, 2013 from U.S. Appl. No. 12/417,752, 18 pages. |
Response filed Sep. 30, 2013 to Final Office Action mailed Jul. 17, 2013 from U.S. Appl. No. 12/417,752, 18 pages. |
Non-Final Office Action mailed Oct. 29, 2013 from U.S. Appl. No. 12/417,752, 17 pages. |
Response filed Dec. 23, 2013 to Non-Final Office Action mailed Oct. 29, 2013 from U.S. Appl. No. 12/417,752, 21 pages. |
Final Office Action and Applicant Initiated Interview Summary mailed Feb. 25, 2014 from U.S. Appl. No. 12/417,752, 26 pages. |
Notice on the First Office Action and Search Report mailed Mar. 3, 2016 from China Patent Application No. 201380046819.5, 13 pages. |
“Ignite Where & Launch Pad”, retrieved on Feb. 5, 2009 at <<http://en.oreilly.com/where2008/public/schedule/detail/2572>>, O'Reilly, Where 2.0 Conference 2008, May 2008, 4 pages. |
Aalto et al., “Bluetooth and WAP Push Based Location-Aware Mobile Advertising System”, retrieved on Feb. 5, 2009 at <<http://www.mediateam.oulu.fi/publications/pdf/496.pdf, ACM, MobiSYS '04, Jun. 6-9, 2004, Boston MA, 10 pages. |
Azizyan et al., “SurroundSense: Mobile Phone Localization Using Ambient Sound and Light”, retrieved on Feb. 5, 2009 at <<http://synrg.ee.duke.edu/papers/surroundsense-poster.pdf>>, Sep. 22, 2008, 1 page. |
Bahl et al., “Radar: An In-Building RF-based User Location and Tracking System”, retrieved on Feb. 5, 2009 at <<https://research.microsoft.com/en-us/um/people/padmanab/papers/infocom2000.pdf>>, Microsoft Research, Proceedings of IEEE Infocom 2000, Tel-Aviv, Israel, Mar. 2000, 10 pages. |
Balakrishnan et al., “ITR: Scalable Location-Aware Monitoring (SLAM) Systems”, retrieved on Feb. 5, 2009 at <<http://nms.lcs.mit.edu/projects/slam/prop.pdf>>, Laboratory for Computer Science & Department of EECS, MIT, Cambridge, MA, Nov. 9, 2001, 31 pages. |
Constandache et al., “Energy-Aware Localization Using Mobile Phones”, retrieved on Feb. 5, 2009 at <<http://www.cs.duke.edu/˜ionut/2008—mobisys.pdf>>, Poster, ACM MobiSys, Jun. 2008, 1 page. |
Flinn, Jason, “Extending Mobile Computer Battery Life through Energy-Aware Adaptation”, retrieved on Feb. 5, 2009 at <<http://reports-archive.adm.cs.cmu.edu/anon/2001/CMU-CS-01-171.pdf>>, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, Dec. 2001, 165 pages. |
Gaonkar et al., “Micro-Blog: Sharing and Querying Content Through Mobile Phones and Social Participation”, ACM, MobiSys 2008, Jun. 17-20, 2008, Breckenridge, CO, 13 pages. |
Kansal et al., “Location and Mobility in a Sensor Network of Mobile Phones”, retrieved on Feb. 5, 2009 at <<http://research.microsoft.com/apps/pubs/default.aspx?id=70416>>, Microsoft Research, Microsoft Corporation, Jun. 4, 2007, 1 page. |
Krumm et al., “Predestination: Inferring Destinations from Partial Trajectories”, retrieved on Feb. 5, 2009 at <<http://research.microsoft.com/en-us/um/people/horvitz/predestination.pdf>>, UbiComp 2006: The Eighth International conference on Ubiquitous Computing, Sep. 17-21, 2006, Orange County, CA, 18 pages. |
Krumm et al., “RightSPOT: A Novel Sense of Location for a Smart Personal Object”, retrieved on Feb. 5, 2009 at <<http://research.microsoft.com/en-us/um/people/horvitz/rightspot.htm>>, Proceedings of Ubicomp 2003, vol. 2864, pp. 36-43, 3 pages. |
Lamarca et al., “Place Lab: Device Positioning Using Radio Beacons in the Wild”, retrieved on Feb. 5, 2009 at <<http://www.placelab.org/publications/pubs/pervasive-placelab-2005-final.pdf>>, In Proceedings of Pervasive 2005, Munich, Germany, 18 pages. |
Liao et al., “Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields”, The International Journal of Robotics Research, vol. 26, No. 1, pp. 119-134, 2007, 17 pages. |
Lin et al., “Enabling Energy-Efficient and Quality Localization Services”, retrieved on Feb. 5, 2009 at <<http://nslab.ee.ntu.edu.tw/publication/conf/qols-percom06.pdf>>, National Taiwan University, 2006, 4 pages. |
Peng et al., “BeepBeep: A High Accuracy Acoustic Ranging System using COTS Mobile Devices”, ACM, SenSys 2007, Nov. 6-9, 2007, Sydney, Australia, 14 pages. |
Person, Jon, “Writing Your Own GPS Applications: Part 2”, retrieved on Feb. 5, 2009 from <<http://www.codeproject.com/KB/mobile/WritingGPSApplications2.aspx>>, The Code Project, Dec. 20, 2004, 15 pages. |
Ruairi et al., “An Energy-Efficient, Multi-Agent Sensor Network for Detecting Diffuse Events”, retrieved on Feb. 5, 2009 at <<http://www.aaai.org/Papers/IJCAI/2007/IJCA107-224.pdf>>, IJCAI-07, 2007, pp. 1390-1395, 6 pages. |
Schindler et al., “City-Scale Location Recognition”, retrieved on Feb. 5, 2009 at <<http://www.cc.gatech.edu/˜phlosoft/files/schindler07cvpr2.pdf>>, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2007, 7 pages. |
Kansal, Aman and Feng Zhao, “Location and Mobility in a Sensor Network of Mobile Phones,” ACM SIGMM 17th International Workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV), Association for Computing Machinery, Inc., Urbana, IL, 2007, 6 pages. |
Notice of Allowance mailed Feb. 29, 2016 from U.S. Appl. No. 13/183,124, 24 pages. |
Final Office Action mailed Mar. 4, 2016 from U.S. Appl. No. 13/190,121, 14 pages. |
Office Action and Examiner Initiated Interview Summary mailed Mar. 9, 2016 from U.S. Appl. No. 13/551,613, 5 pages. |
Notice of Allowance mailed Mar. 14, 2016 from U.S. Appl. No. 13/183,050, 49 pages. |
Response and After Final Request Pilot Program 2.0 filed Feb. 11, 2016 to Final Office Action mailed Dec. 4 2015 from U.S. Appl. No. 13/606,029, 11 pages. |
Advisory Action and After Final Consideration Pilot Program Decision mailed Feb. 23, 2016 from U.S. Appl. No. 13/606,029, 4 pages. |
Non-Final Office Action mailed Apr. 4, 2016 from U.S. Appl. No. 13/606,029, 15 pages. |
Final Office Action mailed May 12, 2016 from U.S. Appl. No. 13/284,128, 58 pages. |
Response to Ex Parte Quayle Action filed May 9, 2016 from U.S. Appl. No. 13/551,613, 5 pages. |
Smailagic et al., “Location Sensing and Privacy in a Context-Aware Computing Environment”, IEEE Wireless communications, Oct. 2002, pp. 10-17, 8 pages. |
Sun et al., “Signal Processing Techniques in Network-Aided Positioning—A survery of state-of-the-art positioning lesigns”, IEEE Signal Processing Magazine, Jul. 2005, 12 pages. |
Youssef et al., “The Horus WLAN Location Determination System”, retrieved on Feb. 5, 2009 at <<http://www.cs.umd.edu/˜moustafa/papers/horus—usenix.pdf>>, Department of Computer Science, University of Maryland, 2005, 14 pages. |
Zhang et al., “The Two Facets of the Exploration-Exploitation Dilemma”, Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT '06), 2006, 7 pages. |
Notice of Appeal and Pre-Brief Conference Request mailed Apr. 19, 2016 from U.S. Appl. No. 13/190,121, 10 pages. |
Notice of Allowability mailed Jun. 14, 2016 from U.S. Appl. No. 13/183,124, 10 pages. |
Notice of Allowability mailed Jun. 10, 2016 from U.S. Appl. No. 13/183,050, 19 pages. |
Preliminary Amendment filed Jun. 15, 2016 to U.S. Appl. No. 15/181,091, 8 pages. |
Notice of Allowance mailed Jun. 6, 2016 from U.S. Appl. No. 13/551,613, 7 pages. |
Notice of Panel Decision from Pre-Appeal Brief Review mailed Jun. 8, 2016 from U.S Appl. No. 13/190,121, 2 pages. |
Response filed May 16, 2016 to the Office Action mailed Dec. 31, 2015 from China Patent Application No. 201380038072.9, 6 pages. |
Request for Examination and Voluntary Amendment filed Jun. 15, 2016 from Japanese Patent Application No. 2015-523237, 8 pages. |
Response filed Jul. 18, 2016 to the Office Action mailed Mar. 3, 2016 from China Patent Application No. 201380046819.5, 10 pages. |
Response filed Jul. 19, 2016 to the Office Action mailed Apr. 4, 2016 from U.S. Appl. No. 13/606,029, 17 pages. |
Number | Date | Country | |
---|---|---|---|
20130158867 A1 | Jun 2013 | US |