Patent Application
20120129544
The problem of mobile devices being used by people while operating vehicles is well-known. Drivers become distracted by these devices, and are at a higher risk of being involved in a driving-related incident. As discussed in co-pending U.S. patent application Ser. No. 11/956,067, filed Dec. 13, 2007, one useful approach to mitigating this problem involves monitoring the speed at which a mobile device is traveling. When the mobile device is in transit (typically determined by comparing the speed of the mobile device to a predetermined threshold), access control messages are transmitted either by the mobile communications device itself or a vehicle associated with the mobile device. The access control messages indicate to the mobile device communications network that communication with the mobile communications device should be prevented or deflected until the mobile device is no longer in transit. Another useful approach is described in co-pending U.S. patent application Ser. No. 12/040,581, filed Feb. 29, 2008, which includes a mobile phone-based system for disabling a cellular phone when the phone is known to be moving at a predetermined speed. These co-pending applications are incorporated by reference herein in their entireties.
In some embodiments of the mobile device control technologies described in the above pending applications, positioning systems, such as GPS, are used to determine where the mobile device is located and/or how fast the mobile device is moving. Such positioning systems typically have high power requirements. Consequently, when these systems are included within a battery-powered mobile device, the battery is quickly drained, especially when the positioning system is operated continuously or frequently. Additionally, many such systems rely on a line-of-sight communication path between the mobile device and a satellite or other transmitter. When the mobile device is being used indoors, or in urban areas, no sufficient communication path may exist. To mitigate power consumption, other less “power hungry” motion detection devices are sometimes used. For example, the location technique described by Horvitz et al. in U.S. Patent Application Publication No. 2007/0005243, published Jan. 4, 2007, only turns on the GPS when an accelerometer indicates that, for example, “the velocity of a user is seen to decelerate from 60 miles per hour to 40 to 30 to 10 to 5 to 2 miles per hour.” In the examples described by Gopinath in U.S. Patent Application Publication No. 2009/0278738, published Nov. 12, 2009, microelectromechanical devices, such an accelerometer or gyroscope, are used to determine relative positions (instead of using GPS to obtain absolute positions).
Applicants have identified a number of shortcomings of existing mobile device control technologies, which are addressed by the systems and methods disclosed herein. In particular, existing technologies fail to address the variations between different devices and uses of those devices. For example, any of a number of different mechanical attachment techniques may be used to mount an accelerometer to a mobile device, each of which may have different damping properties that affect the accelerations detected by the accelerometer when the device undergoes routine handling. When a single, predetermined acceleration rule is applied to all of these different devices, the result is likely to be less than satisfactory for all of them. In another example, some users carry their mobile devices with them while jogging, and an accelerometer within such a device may register frequent periods of acceleration when the user's foot impacts the ground. If each of these accelerations triggers a GPS reading or a speed calculation, the utility of the mobile device control technology is undermined and the operating time reduced.
To address these and other shortcomings of existing mobile device control technologies, systems and methods are provided herein for controlling a mobile device in motion while reducing power consumption of positioning systems such as GPS. In particular, the systems and techniques described herein intelligently identify the points in time at which it is particularly advantageous to make a position measurement by automatically classifying accelerometer readings to distinguish vehicular travel from non-vehicular travel.
In one aspect, a method is provided for controlling a mobile device. A processor receives a first accelerometer signal representative of motion of the mobile device, and determines a characteristic variation in the first accelerometer signal. In some embodiments, the first accelerometer signal includes a plurality of discrete accelerometer signals at approximately periodic points in time. In some embodiments, the processor determines a characteristic variation by calculating a deviation from a central value of the accelerometer signals (such as a mean). The processor sets an acceleration threshold based at least in part on the characteristic variation. In some embodiments, an absolute value of the acceleration threshold is greater than or equal to the characteristic variation. The processor then compares a second accelerometer signal to the acceleration threshold. The second accelerometer signal may be a portion of the first accelerometer signal. When the second accelerometer signal exceeds the acceleration threshold, a position of the mobile device is measured using a positioning system (such as a GPS system) and the processor determines whether a user of the mobile device is likely in control of a vehicle. When the processor determines that the user is likely in control of a vehicle, the processor disables one or more mobile device features. When the processor determines that the second accelerometer signal does not exceed the acceleration threshold, the processor may enable one or more features of the mobile device.
In some embodiments, the processor identifies one or more portions of the first accelerometer signal that are determined to have smaller variations than other portions of the first accelerometer signal. In some such embodiments, the processor determines a characteristic variation in the first accelerometer signal by determining a characteristic variation in the identified one or more portions of the first accelerometer signal that are determined to have smaller variations. In some embodiments, an absolute value of the acceleration threshold is less than or equal to a maximum of an absolute value of a small variation portion of the first accelerometer signal. In some embodiments, the processor determines the characteristic variation by analyzing portions of the first accelerometer signal received when the mobile device is not traveling in a vehicle. The processor may set the acceleration threshold by analyzing portions of the first accelerometer signal received when the mobile device is traveling in a vehicle. In some embodiments, the processor compares the second accelerometer signal to the acceleration threshold by comparing the absolute value of the second accelerometer signal to the absolute value of the acceleration threshold. In some embodiments, the processor sets the acceleration threshold by receiving a plurality of acceleration signals over two or more days, identifying a pattern within the plurality of acceleration signals received over two or more days, and selecting a value for the acceleration threshold based at least in part on the identified pattern.
In some embodiments, the processor determines whether a user of the mobile device is likely in control of a vehicle based at least in part on the measured position. For example, the processor may determine that the mobile device has traveled beyond a predetermined distance in a particular amount of time. In a second example, the processor compares a speed of the mobile device to a speed threshold. In a third example, the processor detects a signal from a vehicle.
In another aspect, a method is provided for controlling a mobile device. A processor receives an accelerometer signal representative of the motion of the mobile device and compares the accelerometer signal to an acceleration threshold stored in a memory. When the comparison indicates that the accelerometer signal exceeds the acceleration threshold, a position of the mobile device is measured using a positioning system. The processor uses the position measurement to determine whether a user of the mobile device is likely in control of a vehicle, and in response to determining that the user is likely in control of a vehicle, the processor disables one or more features of the mobile device.
In another aspect, a system is provided for controlling a mobile device, including a control unit configured to receive a first accelerometer signal representative of motion of the mobile device, determine a characteristic variation in the first accelerometer signal, set an acceleration threshold based at least in part on the characteristic variation, and compare a second accelerometer signal to the acceleration threshold. When the second accelerometer signal exceeds the acceleration threshold, the control unit is configured to measure a position of the mobile device using a positioning system and determine whether a user of the mobile device is likely in control of a vehicle. When the user is likely in control of a vehicle, the control unit is configured to disable one or more mobile device features. In another aspect, a system is provided for controlling a mobile device, including a control unit configured to receive an accelerometer signal representative of the motion of the mobile device and compare the accelerometer signal to an acceleration threshold stored in a memory. When the accelerometer signal exceeds the acceleration threshold, the control unit is configured to measure a position of the mobile device using a positioning system and determine whether a user of the mobile device is likely in control of a vehicle, based at least in part on the measured position. When the user is likely in control of a vehicle, the control unit is configured to disable one or more mobile device features.
The above and other objects and advantages of the systems and methods of the present disclosure will be apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout, and in which:
Described herein are systems and methods for selectively permitting use of a mobile device while the device is in motion. As used herein, “motion” of the mobile device may refer to any information regarding the context and movement of the mobile device, an associated vehicle and/or its user such as physical displacement, a geographic location, bearing, speed or acceleration. These systems and methods can be implemented in a number of different configurations. Several exemplary configurations are discussed below with reference to
In particular,
The controller 104 is described herein as a general purpose processor included in the mobile device 102 that has been programmed with software (i.e., one or more modules of computer executable instructions) configured to perform the monitoring and control techniques described herein. The software may be a downloadable application (e.g., one that can be purchased from an online source and transmitted to the mobile device 102). Alternatively, the controller 104 may be implemented via any combination of hardware, firmware, and software executing on a general purpose processor.
The user interface 106 includes interface elements such as an audio element 110, an input element 112, and a visual display element 114. The audio element 110 may include a microphone and speaker, and other audio transducers for generating alerts, music, audible messages and ringing sounds. The input element 112 may include, for example, a keypad, a software-based graphical user interface, a mechanical or optical mouse or trackball, a touch screen, voice recognition components, or other button/entry elements. The visual display element 114 may include, for example, a graphical display such as a liquid crystal display.
The mobile device 102 may use any of a number of techniques to determine that it is moving at a sufficient speed to indicate that is in a vehicle, or is in some other condition under which use of the mobile device 102 should be selectively permitted or restricted. For example, in a cellular communication application, the controller 104 may track the received signal strength indicator (RSSI) 118 of nearby serving cells (such as the serving cell 209 and the neighbor cell 211 of the mobile device support system 200 of
Upon determining that the mobile device 102 is in transit, the controller 104 processes data indicative of the device's movement to determine whether usage of the device should be restricted. In one embodiment, such processing includes comparing the motion information to data stored in a mobility access profile (“MAP”) 123 stored therein. The MAP 123 is a file or record including information for setting the permitted uses of the mobile device 102. The MAP 123 may be stored or recorded in any suitable format or data structure. The MAP 123 includes two types of information about the mobile device 102: control criteria and permitted use parameters. Control criteria are criteria against which the motion of the mobile device 102 is compared to determine what operations and functions of the mobile device 102 should be enabled, disabled, or restricted. Each set of control criteria may be associated with a set of permitted use parameters. During use, controller 104 compares the motion of the mobile device 102 against the control criteria of the MAP 123 and applies the permitted use parameters associated with any control criteria that are met.
As a result, certain functions of the mobile device 102 may be modified or restricted; for example, the controller 104 may deny call setup requests; prohibit peer-to-peer and text messaging, Internet access, camera functionality, gaming applications, or the like; route incoming calls to a voice mail account associated with the mobile device 102 or provide a busy signal; divert an incoming communication to an e-mail, voicemail or other communications medium, or otherwise modify any other mobile device function or feature, or any combination thereof. In some implementations, calling and/or receiving one or more specific phone numbers, such as an emergency number, a home number or a parent's cellular phone number, or a dispatcher or supervisor's number, may be allowed while all other call setup requests are blocked. In some implementations, enforcing the permitted use parameters includes the controller 104 shutting off, blocking, or inhibiting certain interface elements, such as the elements 110, 112 and 114 (
In some mobile communications applications, the base stations 208 and 210 serve as intermediaries between the mobile device 102 and a mobile switching center (MSC) 212. The MSC 212 controls calling and other communication activity, and is connected to a public switched telephone network (PSTN) 214. The MSC 212 sets up communication circuits for various modes of communication, in accordance with request and authorization protocols as known in the art. The MSC 212 controls communication access for subscribing and authorized roaming mobile devices (such as the mobile device 102) in accordance with a home location register and visit location register (HLR/VLR) 214. The HLR/VLR 214 maintains subscriber information and other parameters relating to mobility management, access control, and so on, which governs the manner in which the mobile device 102 operates within the communication system 204.
In certain implementations, the communication system 204 is informed of the apparent travel of the mobile device 102. The communication system 204 may be informed from any one of at least two sources. First, the mobile device 102, itself, may report to the communication system 204 that the mobile device 102 appears to be traveling. Second, a vehicle module 218 disposed in vehicle 206 may report to the communication system 204 when the vehicle 206 is being operated or is traveling. The monitoring of the mobile device 102 or the vehicle 206 is performed continuously, periodically, or aperiodically.
When the mobile device 102 is in transit, the communication system 204 receives an access control message (ACM). An ACM is an information signal which includes information regarding the mobile device 102, such as its position, velocity, relative position with respect to a communications cell, relative position with respect to a beacon or marker, geographical coordinates, bearing, acceleration, altitude, or information derived from one or more thereof (such as rates of change, higher-order derivatives, and statistical measures like averages, standard deviations, and medians). The ACM is created by the mobile device 102, the vehicle module 218, the base station 208 or 210, or by another component of the mobile device support system 200 used to determine movement of the mobile device 102 or the vehicle 206 (as discussed in other implementations below). In some implementations, the ACM also includes identifying information about the user, the mobile device 102 or the vehicle 206, such as a communication address for the mobile device 102 or the vehicle 206 (i.e., a telephone number, an IP address, an e-mail address). Utilizing this information, the ACM enables the MSC 212 to determine whether or not the communication circuit needs to be reconfigured to selectively permit use of the mobile device 102 while the device is in motion.
The MSC 212 recognizes the ACM and routes it to an access control processor (ACP) 220 as a function of the information contained in the ACM. The ACP 220 then accesses an access database 222 to retrieve a MAP 123, (e.g., a cellular system mobility access profile (MAP)) stored therein. As described above, the MAP 123 includes control criteria and permitted use parameters for a given user. The ACP 220 provides the information in the MAP 123 to the MSC 212, which then applies the permitted use parameters associated with the mobile device 102. More particularly, access to communication resources of the communication system 204 by the mobile device 102 is selectively permitted by comparing the motion of the mobile device 102 or the vehicle 206 to the control criteria stored in the MAP 123. The communication system 204 may, for example, deny call setup requests, peer-to-peer and text messaging usage, Internet access; route incoming calls to a voice mail account associated with the mobile device 102; provide a busy signal upon receipt of an incoming call; divert an incoming communication to an e-mail, voicemail or other communications address, and so on as a function of the permitted use parameters stored in the MAP 123 and processed by the MSC 212 and the ACP 220. The communication system 204 may further allow exceptions to any restrictions imposed. For example, calling or receiving calls from one or more specific phone numbers, such as an emergency number, a home number or a parent's cellular phone number, a dispatcher, or supervisor, may be allowed while all other call setup requests are blocked. In some implementations, generic instructions to allow all emergency calls (911, for example), may be executed by default at the MSC 212 or the ACP 220. This methodology applies whether the mobile device functions are triggered by actions originating at the mobile device 102 (e.g., outgoing calls) or are aimed at the mobile device 102 (e.g., incoming calls). Note that if a profile for the mobile device 102 associated with the generated ACM does not exist in the access database 222, then the user or another authorized party (such as the user's parent) may be notified by e-mail or an Internet site and a MAP may be created for a particular mobile device.
Once the information in the MAP 123 is provided to the MSC 212, the MSC 212 then updates the present permitted use parameters associated with the mobile device 102. The present permitted use parameters may be stored, for example, in the VLR 214, and may be accessed by the MSC 212 when the mobile device 102 requests communication resources, or when incoming communications are received which are bound for the mobile device 102.
In other implementations, the vehicle module 218 may use the modem 302 (or other communication device) to transmit an ACM or other communication including motion data directly to the mobile device 102, instead of transmitting such information to the communications system 204. In such implementations, the mobile device 102 is configured to receive messages regarding the motion of the vehicle 206 and use its own internal hardware and software (e.g., a controller similar to controller 104 of
In some implementations, the vehicle controller 306 is interfaced though a vehicle interface 308 (e.g., via a cable connected to an OBD-compliant data port) to the vehicle control system 310. The vehicle control system 310 is the system in the vehicle 206 that controls, for example, instrumentation, engine operation, diagnostics, and other vehicle operation and monitoring functions. The vehicle control system 310 may be configured to provide information to the vehicle controller 306 as, for example, vehicle speed, vehicle access, the identity of a specific key or other access device used to operate the vehicle, and so on. The vehicle module 218 may use this information to determine when to transmit an ACM or motion information message, and what the contents of the ACM are to be. For example, when the vehicle speed reaches a preselected threshold, or if a key associated with a restricted user is used to access and operate the vehicle 206, the vehicle module 218 may transmit an ACM or other motion information message to the mobile device.
In some implementations, the vehicle module 218 may operate independently of the vehicle control system 310 and determine use of the vehicle by other means, such as, for example, a satellite positioning system receiver 312, which receives positioning signals from positioning satellites via an antenna 314. By using position information, the vehicle controller 306 can determine when the vehicle is moving, at what speed and subsequently transmit the ACM or other motion information message. Other means of triggering the transmission of an ACM may be used, such as pairing the vehicle module 218 with the mobile device 102 via a personal area network link. The vehicle module 218 may be installed such that pairing the mobile device 102 with the vehicle module 218 is required before the vehicle module 218 allows the vehicle 206 to start, for example, by using the personal area network media access information of the mobile device 102 as a sort of key.
The vehicle module 218 may, upon installation in the vehicle 206, be programmed with information to identify the mobile device 102 to the ACP 220 of the communications system 204 (discussed above with reference to
In some implementations, a wireless key 406 may be used to access the vehicle 206 (instead of or in addition to the key 402). The wireless key 406 may transmit a code to the vehicle control system 310 over a short-range wireless link. This causes the vehicle control system 310 to cause the vehicle module 218 to transmit an ACM as discussed above (e.g., to the communications network 104 or the mobile device 102). In certain implementations, the mobile device 102 is itself configured as a wireless key (such as the wireless key 406), using a personal area network interface such as that known in the industry by the trade name Bluetooth™, for example.
At decision block 504, the processor determines whether any of the control criteria has been met. As indicated above, this determination can be made by the mobile device controller 104 or by the MSC 212, or a combination of the two. The determination could also be made by the vehicle module 218. Upon determining that sufficient control criteria have been met to justify limiting mobile device functionality, the mobile device 102 and/or the MSC 212 begin enforcing the permitted use parameters described above (Step 506).
The processor continues to monitor the motion of the mobile device (Step 508). Upon a determination that sufficient control criteria sufficient to restrict device usage are no longer met, the mobile device 102 and/or MSC 212 restores full device operation (Step 510).
At Step 702, the mobile device 102 is turned on, powered up or “awoken” from a sleep or hibernation mode. At Step 704, settings regarding operation of the mobile device 102 are initialized or retrieved from the MAP 123 (which may be stored in the communications system 204, the vehicle module 218, and/or the mobile device 102). These settings may be initialized to a default value (e.g., at the time of manufacture or sale), customized according to user preferences or local laws, or entered as part of HLR/NLR 214 or MAP 123 by the user (see e.g., the discussion of
At Step 706, a processor activates a tracking system. The tracking system may be located in the mobile device 102, the vehicle module 218, the communications system 204, or distributed between two or more of these components. In certain implementations, the tracking system is a position tracking system included in the mobile device 102. In preferred implementations, the tracking system is a global positioning system (GPS) that is configured to determine the position of the mobile device 102. In some implementations, the tracking system is a position tracking system included in the vehicle module 218 (e.g., a GPS system). In certain implementations, the tracking system is a speed monitoring system that does not necessarily rely on position measurements (e.g., an accelerometer-based or signal strength tracking system). In the following discussion, GPS is used as the tracking system by way of non-limiting example to facilitate discussion, but non-GPS and non-position-based tracking systems may be used to implement the heavy traffic detection and response techniques described here. In implementations that do not include position-based tracking systems, the steps of the flow diagrams of
At Step 708, the processor receives a GPS reading indicative of the position of the mobile device 102. At decision block 710, the processor compares the GPS reading to a map stored in a memory accessible to the processor. Such maps are provided by Internet-based technologies including MAPQUEST and Google Maps, and can be downloaded to the memory in advance of decision block 710 or in conjunction with decision block 710 based on the GPS reading. This memory may be local or remote. Comparing the GPS reading to the stored map allows the processor to determine whether the mobile device 102 is positioned at a valid street location. If the position of the mobile device 102 is not a valid street location, then it is likely that the user of the mobile device 102 is not driving a vehicle (e.g., the user is on a train, or walking at an off-street location) and thus restricted use of the mobile device 102 is not required. In this case, the processor executes a “clear” Step 711 and sends an unlock software control signal to the mobile device 102 to reset any software locks that were set previously (discussed below), then executes Step 708 again to take further GPS readings until it is determined that the mobile device 102 is located at a valid street location.
At decision block 710, if the processor determines that the mobile device 102 is in a valid street location, a second GPS reading is received at Step 712. This second GPS reading is taken at a predetermined time interval from the first GPS reading (received at Step 708), and can be used in to determine the speed of motion of the mobile device 102 by dividing the distance traveled between the first and second GPS readings by the duration of the time interval. As discussed above with reference to
Step 708 and continues to take GPS readings to monitor the motion of the mobile device 102.
If the processor determines at decision block 714 that the speed of the mobile device 102 exceeds the safe speed threshold, the processor performs a heavy traffic detection technique at decision block 716. If the processor determines that the mobile device 102 is not in heavy traffic at decision block 716, then the control criteria are set to (or maintained at) their “normal traffic” values at Step 718, and the processor proceeds to decision block 722 (discussed below). However, if the processor determines that the mobile device 102 is in heavy traffic, the processor assesses whether the current control criteria are set to their heavy traffic values at decision block 720. If not, the control criteria are altered to their heavy traffic values at Step 721. Heavy traffic detection techniques are discussed in detail below, as are the techniques performed at Step 721 when a heavy traffic condition is detected. After the heavy traffic condition is detected and responded to (if necessary), the processor determines at decision block 722 whether the permitted uses of the mobile device 102 are to be changed as a result of the excessive speed detected at decision block 714. If the use of the mobile device 102 is already appropriately restricted (e.g., because the mobile device 102 has previously exceeded the safe speed threshold), the processor returns to execute Step 708 and receive another GPS reading.
If the use of the mobile device 102 is not appropriately restricted, the processor determines at decision block 724 whether the mobile device 102 is currently in use. For example, the user may be making use of the mobile device 102 to watch a video or send/receive a text message. If the mobile device 102 is not in use, the permitted use parameters are applied at Step 726 to the operation of the mobile device 102 to restrict or block operation. In some implementations, the permitted use parameters prevent access to the communication functions of the mobile device 102, and incoming calls are either re-routed, met with a busy signal, a voicemail message or the like as discussed above. The permitted use parameters may also cause the output of a software control signal to the mobile device 102 to “lock down” the keyboard and, in particular, a “send” button of the mobile device 102. At Step 728, the processor causes any camera capability of the mobile device 102 to be disabled. The permitted use parameters may also cause a software control signal to be transmitted to lock down access to the camera activation controls on the mobile device 102 and/or lock the display screen. The processor returned to Step 708 to take another GPS reading.
Returning to decision block 724, if the mobile device 102 is currently engaged in a voice communication, then the processor determines at decision block 730 whether or not the other party is on an exception list as stored in the MAP 123. The exception list includes phone numbers such as 911, for which the risk of using the mobile device 102 in transit is outweighed by the necessity to have such communications maintained. If the other party is on the exception list, then the communication session is allowed to continue at Step 732, and the processor returns to execute Step 708. If processor determines at decision block 730 that the other party is not on the exception list, then the restricted operation imposed by the permitted use parameters begins in order to ensure the safety of the user. Accordingly, at Step 734, the processor executes an “End Call” technique in which an “End Call” software signal generated by the mobile device 102 or the MSC 212 to activate the “hang-up” function of the mobile device 102. In this way, a communication session is ended without dropping the connection (i.e., the antenna is not turned off) and the stoppage of communication is handled as a normal “End Call,” not as a dropped call. In some implementations, the antenna may be turned off at Step 734, forcing an end to wireless communication with the mobile device 102.
In some implementations, rather than terminating an in-progress call or other audio communication, the processor may cause a disruptive noise (e.g., white noise, loud repeated beeps, automobile accident sounds, etc.) or an audible message (e.g., “PLEASE HANG UP. IT IS UNSAFE TO CONTINUE SPEAKING”) to be generated so that the user and/or the remote party can hear it. This noise or message may be repeated at a sufficient frequency, at a high enough volume, or otherwise be disruptive enough that it is very difficult for the user or remote party to continue the conversation, forcing one of the parties to manually end the call. The disruptive noise or message may persist for the duration of the audio communication, and may end when the audio communication ends, the mobile device 102 is no longer in transit, or both. The disruptive noise may be provided directly to communications circuitry within the mobile device 102, such as microphone circuitry and/or speaker circuitry. In some implementations, a web interface (e.g., the web interface for generating a mobility access profile described with reference to
Once the communication session has ended, the remaining permitted use parameters are used to adjust the operation of the mobile device support system 200 at Step 726 (as described above). Adjusting the mobile device 102 in accordance with the permitted use parameters may include configuring the mobile device 102 to prevent communication with the communication system 204 by turning off the transmit side of the antenna circuitry of the mobile device 102, by locking the keyboard of the mobile device 102, or any of the other permitted use adjustments described herein. Adjusting the communications system in accordance with the permitted use parameters may include causing the communication system 204 to re-route calls to an on- or off-device voicemail repository, a forwarding phone number, an e-mail or alternate device, or providing a busy signal. In this way, incoming and outgoing communication functions may not be used by the user of the mobile device 102. After Step 728, at which the processor disables a camera included in the mobile device 102, the processor returns to Step 708 to take another GPS reading.
At Step 716, a heavy traffic detection and response technique is executed. In one implementation, the heavy traffic detection technique performed at Step 716 includes determining a variation of the speed of the mobile device 102. The speed variation may be determined by any one or more of the following exemplary techniques:
ACP 220, HLR/NLR 214 (
Another exemplary technique for determining a variation of the speed of the mobile device 102 includes determining a first representative speed of the mobile device 102 over a first interval of time, and determining a second representative speed of the mobile device 102 over a second interval of time. The first and second intervals of time may be contiguous or separate. A representative speed over an interval may be an average speed over the interval, a maximum speed over the interval, a minimum speed over the interval, or any other speed that represents the motion of the mobile device 102 over the interval. Once the first and second representative speeds have been determined, the variation of the speed of the mobile device 102 is measured by comparing the first and second representative speeds. In some implementations, this comparison is the ratio of the first and second representative speeds. In other implementations, this comparison is the absolute difference of the first and second representative speeds. In some implementations of this technique, the first and second representative speeds are only compared when at least one of them is greater than a predetermined threshold speed. In some implementations, both the first and second representative speeds when must be greater than a predetermined threshold speed before they are compared. The threshold speed may correspond to a walking speed, for example. By “discarding” representative speeds that are too slow to indicate travel in a vehicle, this implementation advantageously reduces the erroneous detection of a heavy traffic condition when a user is simply walking and occasionally stopping.
Any one or all of the above techniques may be utilized to determine a variation of the speed of the mobile device 102. In each technique, the determined variation is then compared to a threshold to determine whether the recorded speed pattern is indicative of heavy traffic. For example, when the number of times that a speed threshold is crossed exceeds a threshold number, a heavy traffic condition is identified. In another example, when the distance traveled in a particular time interval exceeds a threshold, a heavy traffic condition is not identified.
If the processor determines that the mobile device 102 is not in heavy traffic at decision block 716, then the control criteria are set to (or maintained at) their “normal traffic” values at Step 718, and the processor proceeds to decision block 722 (discussed below). However, if the processor determines that the mobile device 102 is in heavy traffic, the processor assesses whether the current control criteria are set to their heavy traffic values at decision block 720. If not, the control criteria are altered to their heavy traffic values at Step 721. In preferred implementations, altering the control criteria at Step 721 includes increasing the safe speed threshold against which the speed of the mobile device 102 is compared to determine whether the permitted uses should be changed. Increasing the safe speed threshold advantageously allows the control criteria to adapt to periodic small accelerations without triggering the transmission of an ACM or the potential disruption caused by frequent changes of the permitted uses of the mobile device 102. For example, to accommodate for periodic quick bursts of acceleration, the safe speed threshold may be altered from 10 miles per hour to 20 miles per hour. The processor may make use of web- or feed-based traffic control information about the location at which the mobile device 102 is traveling, to adjust the safe speed threshold to an appropriate heavy traffic level of 20 miles per hour.
In some implementations, altering the control criteria at Step 721 comprises extending a time interval over which the speed must exceed a speed threshold in order for the use of the mobile device 102 to be selectively permitted. For example, in normal traffic, the processor may be configured to transmit an ACM when it determines that the speed of the mobile device 102 exceeds ten miles per hour for five seconds. In heavy, stop-and-go traffic, the control criteria may be altered so that the mobile device 102 must exceed ten miles per hour (or a higher threshold speed) for ten seconds before the control criteria are met and use of the mobile device 102 is selectively permitted.
In some implementations, altering the control criteria at Step 721 comprises applying additional signal processing steps to a motion signal (such as a location, speed, acceleration or bearing signal), then applying one or more criteria to the processed motion signal. For example, when heavy traffic is detected, the control criteria may be altered to require that a filtered version of a motion signal exceeds or falls below a threshold. In some such implementations, once a heavy traffic condition has been identified, the motion signal is low-pass filtered (e.g., by a moving average) and the low-pass filtered signal compared to a second speed threshold that is lower than the safe speed threshold. When the low-pass filtered signal exceeds the second speed threshold, the use of the mobile device 102 is selectively permitted. In such an implementation, the speed threshold at which mobile device use restriction occurs is lowered due to the presence of heavy traffic. Additional or different signal processing techniques may also extract other frequency information from the motion signal that can be used to alter the control criteria to adapt appropriately to heavy traffic situations.
Once the control criteria are altered at Step 721, the processor returns to execute
Step 708 by taking another GPS reading. As long as the heavy traffic condition is maintained, the altered control criteria will be used to determine how and when the permitted uses of the mobile device 102 will change. Once the traffic condition clears (e.g., as indicated by the traffic control information or some of the speed variation measures described above), the processor will revert the control criteria to their nominal settings (i.e., the safe speed threshold will be decreased to its previous value of 10 miles per hour). Failure to receive an ACM for a predetermined period of time may also indicate a maintained high speed or low traffic condition, and thus cause the control criteria to revert to their nominal “normal traffic” values.
In some implementations, information about the motion patterns of the mobile device 102 are stored in a database (e.g., the access database 222) and are used to “learn” habitual traveled conditions of the mobile device 102. Using known pattern recognition techniques, such implementations account for rush hour traffic experienced on a repeated basis, such as a commute to work or to school. For example, if the user of the mobile device 102 travels in New York City on 5th Avenue, Monday through Friday at 7:00 A.M., the processor stores identified heavy traffic conditions as discussed above in the database and utilizes that information to alter the control criteria to include a heavy traffic safe speed threshold in the MAP 123 during that time period. In this way, one of the criteria now stored as part of the MAP 123 would include an automatic alteration of the control criteria to the heavy traffic settings at a predetermined time period during predetermined days of the week, when the processor identifies that the mobile device 102 is within a radius of a predetermined location.
Many useful techniques for controlling mobile device operation were described above and illustrated with reference to
At Step 802, the processor receives a first signal from a first non-position-based sensor. Such a signal may be, for example, an accelerometer signal, an electromagnetic compass signal, a wireless network environment signal, an anemometer signal, or a vibration detector signal. At Step 804, the processor receives a second signal from a second non-position-based sensor (which may take the form of any of the non-position-based sensors described herein). In some embodiments, the first and second non-position-based sensors are the same types of sensor.
At decision block 808, the processor determines whether the first and second signals are indicative of motion of the device. The processor may make this determination by evaluating one or both of the first and second signals (or more in embodiments in which there are more than two signals). Some exemplary techniques that the processor may execute at decision block 808 include:
If the processor determines at decision block 806 that the mobile device 102 is not in motion, the processor returns to Step 802 to receive additional signals from the non-position-based sensors. If the processor determines at decision block 806 that the mobile device 102 is in motion, the processor proceeds to execute Step 808 and invokes a positioning system to receive a measurement of the position of the mobile device 102. In preferred embodiments, the positioning system is a GPS, but other positioning systems, such as GSM and cell tower localization, may be used.
The processor then proceeds to decision block 810 to determine whether a user of the mobile device 102 is likely in control of a vehicle. In some embodiments, the processor receives a signal from the vehicle controller 306 (
After the processor determines whether the user mobile device 102 is traveling in a vehicle at decision block 810, the processor proceeds to dynamically adapt a prioritization scheme associated with the non-position-based sensors. In particular, if the processor determines that the mobile device 102 is not traveling in a vehicle (based on the position measurement of Step 808) at decision block 810, the processor proceeds to Step 812 to decrease the priority of one or more of the sensors that indicated that the mobile device 102 was in motion at decision block 806. Alternately, if the processor determines that the mobile device 102 is traveling in a vehicle (based on the position measurement of Step 808) at decision block 810, the processor proceeds to Step 812 to increase the priority of one or more of the sensors that indicated that the mobile device 102 was in motion at decision block 806. These priorities are part of a prioritization scheme maintained by the processor, which includes a priority for each of the non-position-based sensors that provide motion-indicative measurements. The processor can use this prioritization scheme in the method of
Proceeding to Step 816, once the processor has determined that the mobile device 102 is traveling in a vehicle (decision block 810) and adjusted sensor priorities accordingly (Step 814), the processor evaluates control criteria and applies the resulting controls to the mobile device 102. The operations performed by the processor at Step 816 can include any of the mobile device control techniques described herein (e.g., disabling/enabling one or more features of the mobile device 102 when the mobile device 102 is traveling faster than a predetermined speed threshold). For example, if the speed of the mobile device 102 exceeds a safe speed threshold, one or more features of the mobile device 102 may be disabled.
(Step 806 of
In the description of
At Step 902, the processor begins by receiving a first accelerometer signal representative of motion of the mobile device 102. As described above, an accelerometer may be embedded within controller 104, or may be in electronic or wireless communication with controller 104. The accelerometer may be embedded within the mobile device 102 itself, or may be mechanically attached to mobile device 102 (e.g., by an adhesive or screw-mount). The accelerometer may have one, two, three or more axes, and may be capable of generating scalar-valued signals or vector-valued signals representative of magnitude and/or direction of linear acceleration and/or rotation. The accelerometer may include piezoelectric, piezoresistive, Hall effect, magnetoresistive, capacitance, resonance, optical or any other suitable components used in any known accelerometer. The accelerometer may be digital or analog, or capable of generating digital and analog signals. The accelerometer may be part of a package that includes signal processing circuitry configured to identify particular kinds of motion, including falling, impact, step-counting, and orientation. An accelerometer package may also include a power supply, a memory device for storing accelerometer signals (e.g., an EEPROM or Flash memory), and an interface for outputting the accelerometer signals to another circuit or device (e.g., a USB or serial interface). Many examples of suitable accelerometers are manufactured by Analog Devices of Norwood, Mass.
In some implementations, the processor receives the first accelerometer signal at Step 902 as a plurality of discrete samples at periodic time intervals. These intervals may correspond to the sampling rate of the accelerometer, or the processor may down-sample signals generated by the accelerometer (e.g., by only receiving every ten or fifty accelerometer signal samples). In some implementations, discrete samples of the first accelerometer signal are not received at regular time intervals, and instead are received at varying time intervals (e.g., only when the accelerometer signal exceed a noise floor, or when another motion-sensing modality, such as a compass, triggers the accelerometer). In some implementations, the processor may interpolate the discrete samples of the first accelerometer signal and treat the first accelerometer signal as a continuous waveform. For example, a continuous accelerometer signal waveform 1002 is illustrated in
In some instances, a portion of the first accelerometer signal received at Step 902 is received when mobile device 102 is traveling in a vehicle, or is not traveling in a vehicle. The processor may distinguish between these conditions in any of a number of ways. In preferred implementations, the processor automatically distinguishes intervals of vehicular travel from intervals of non-vehicular travel by analyzing the variation in the accelerometer signal during these intervals. Such implementations are described in additional detail below with respect to Step 904. In some implementations, a user may use input interface 112 (
At Step 904, the processor determines a characteristic variation in the first accelerometer signal. This characteristic variation is used by the processor to identify a “background” or “expected” amount of variation in acceleration that characterizes time periods in which the user's speed is not changing enough to warrant invoking the positioning system or implementing the mobile device controls described elsewhere herein. Examples of such time periods include when a user is walking, jogging, playing a sport, working around the house or office, or riding in a steady train. The characteristic variation determined at Step 904 may be a variation in only a portion or portions of the first accelerometer signal. For example, in some embodiments, a user may indicate start and end times for a period of walking, and the characteristic variation is a variation of the accelerometer signals received between the start and end times. In some embodiments, the first accelerometer signal may be automatically divided into two or more contiguous or non-contiguous portions (e.g., several two-second intervals), and the processor may calculate a variation associated with some of or all of the portions and designate that variation to be the characteristic variation. For example, the accelerometer signal 1002 of
The processor may determine a characteristic variation at Step 904 in any of a number of ways, including the following:
In some embodiments, one or more of the foregoing variation determination techniques, or any other variation determination technique, may be combined in Step 904 when determining the characteristic variation. The processor may calculate, for example, a weighted average of two or more variations to determine a characteristic variation to use in the remainder of the technique 900 of
As illustrated in several of the examples discussed above, in some embodiments of Step 904, the processor calculates the characteristic variation of the first accelerometer signal by determining a variation in two or more portions of the first accelerometer signal. In some instances, one or more of the portions may represent accelerometer signals received when the mobile device 102 was traveling in a vehicle. In this case, a characteristic variation that is determined based on those portions may be indicative of the amount of variation that is expected when the mobile device 102 is traveling in a vehicle. More specifically, the variations determined during these portions may be indicative of different stages of vehicular travel; for example, onset, cruising, and stopping. In
In some embodiments of Step 904, the processor analyzes one or more portions of the first accelerometer signal, determines a variation of each of the portions, and identifies some of the portions that have larger variations and some of the one or more portions that have smaller variations. The portions with smaller variations are used to determine the characteristic variation. Any known clustering or classification technique may be used to identify the portions accordingly. For example, the processor may identify a fixed number of portions that have the smallest variations and classify those portions as smaller variation portions. In another example, the processor may identify a fixed number of portions that have the largest variations and classify those portions as larger variation portions; the remaining portions are classified as smaller variation portions. The foregoing are simply examples of the characteristic variation determination techniques that may be executed by the processor at Step 904, and many additional techniques are also suitable.
At Step 906, the processor sets an acceleration threshold based at least in part on the characteristic variation determined at Step 904. The processor may set the acceleration threshold by storing a value for the threshold in a memory for later retrieval. In some embodiments, the processor sets the acceleration threshold to be greater than or equal to the characteristic variation. For example, if the processor determines that a portion of the first accelerometer signal has a relatively small variation, the processor may set an acceleration threshold that is greater than or equal to a characteristic variation of that portion. In some embodiments, the processor sets the acceleration threshold to be less than or equal to a maximum of the absolute value of a portion of the first accelerometer signal (e.g., a small variation portion). In some embodiments, the processor sets the acceleration threshold to satisfy both of these conditions: greater than or equal to the characteristic variation, and less than or equal to a maximum absolute value of a portion of the first accelerometer signal.
In some embodiments, the processor sets the acceleration threshold by looking at multiple portions of the first accelerometer signal. For example, the processor may determine characteristic variations associated with accelerometer signals obtained at similar times of day for multiple days in order to learn a “typical” variation associated with the motion of the mobile device 102 at the particular time of day. In another example, the processor may identify one or more portions of the first accelerometer signal during which a user signaled to the controller 104 that the user was walking or was stationary with the mobile device 102. The processor may use the characteristic variations of these portions at Step 906 to set the acceleration threshold equal or greater to an average or maximum characteristic variation of these portions.
At decision block 908, the processor determines whether a second accelerometer signal exceeds the acceleration threshold set at Step 906. The second accelerometer signal may be a portion of the first accelerometer signal received at Step 902, or may be a newly received accelerometer signal. The second accelerometer signal may include one or more discrete accelerometer signal samples. The processor may determine that the second accelerometer signal exceeds the acceleration threshold at decision block 908 if the absolute value of the accelerometer signal exceeds an absolute value of the acceleration threshold.
If the processor determines at decision block 908 that the second accelerometer signal does not exceed the acceleration threshold, the processor returns to Step 902 to receive additional accelerometer signals. If the processor determines at decision block 908 that the second accelerometer signal exceeds the acceleration threshold, the processor proceeds to Step 910 and indicates that the mobile device 102 is in motion.
In some applications, an acceleration threshold can be supplied by an external source (e.g., a remote processor) or pre-programmed into the mobile device 102. The acceleration threshold can be predetermined by a manufacturer or software/hardware provider based on testing conducted with the particular model of the mobile device 102 and the accelerometer, when undergoing vehicular and non-vehicular travel. During this testing, an accelerometer signal can be analyzed in advance, and an appropriate acceleration threshold determined. In operation, the processor receives this acceleration threshold (e.g., from a memory), and proceeds with the technique of
The first measurement received at Step 1202 includes one or more measurement components. Each measurement component may be a distinct raw data signal received by the processor, or may be the result of intermediate processing (such as decoding, decryption, filtering, or counting). In some implementations, the processor may process the measurement signal received at Step 1202 to identify the total number of wireless networks in the environment of the mobile device 102 at the time of the measurement (see, e.g., row 1402 of
In some implementations of Step 1202, the first measurement includes a signal strength for each of the wireless networks in the environment of the mobile device at the time of the measurement (see, e.g., row 1406 of
In some implementations of Step 1202, the measurement received by the processor includes two or more measurement components (e.g., any of the components described above). As discussed in additional detail below, the processor may treat a multi-component measurement as a vector when conducting downstream processing operations.
Additional information can also be included in a multi-component measurement at Step 1202, including WHOIS query information for a particular detected IP address, validated location data for a particular detected IP address, environmental data (e.g., temperature, wind speed), time and date stamps, information from other motion sensors (e.g., accelerometers, acoustic sensors, imaging sensors), and user-provided information (e.g., an indication from a keypad that a particular location is underground).
After receiving a first measurement at Step 1202, the processor proceeds to Step 1204 and receives a second measurement representative of one or more wireless networks in an environment of the mobile device 102. The second measurement may include any of the components described above with reference to the first measurement, and may include the same components as the first measurement or different components. Returning to the illustrative scenario of
The processor may receive the first and second measurements at first and second times, respectively, spaced apart by a predetermined interval. The predetermined interval may correspond to a predetermined sampling frequency (e.g., once per minute). In some implementations, the first and second measurements are each triggered by a triggering event, such as a detection of a sudden acceleration or a change in temperature. In some implementations, the first and second measurements are not consecutive measurements, but are separated by intervening measurements that are disregarded by the processor.
When receiving measurements at Step 1202 or Step 1204, the processor may disregard certain types of measurement data. In some embodiments, the processor may identify certain access points or network hardware as mobile WiFi points (e.g., mobile “hotspots”) and disregard this wireless network information for the purposes of determining whether there is a substantial difference between the wireless networks in the environment of the mobile device 102 (e.g., Step 1206, discussed in detail below). For example, the processor may identify hardware as a mobile WiFi device by analyzing its MAC address and determining, for example, that the first three bytes of the MAC address (the Organizationally Unique Identifier, or OUI) correspond to a manufacturer of mobile WiFi devices. The MAC address may then be added to a blacklist and disregarded in future iterations of the technique of
At decision block 1206, the processor compares the first and second measurements to determine that the first and second measurements are substantially different and thus a substantial change in the wireless networks in an environment of the mobile device has occurred. The processor may perform the comparison at decision block 1206 in any of a number of ways, including the following:
Damerau-Levenshtein distance, Jaro-Winkler distance, and Wagner-Fischer distance.
A combination of any of the above comparison techniques may also be used. In some implementations, different comparison techniques may be used for different components of the measurements. The number and type of comparison techniques used can also be dynamically adapted to changing conditions. For example, when the quality of signal strength measurements is low, a new comparison technique that places less or no emphasis on the signal strength measurements may be used. In some implementations, the processor compares more than two measurements at decision block 1206. In such implementations, the processor may use any of the above comparison techniques, multiple sequence alignment techniques (e.g., progressive or iterative optimization methods), or clustering techniques.
The processor compares the first and second measurements at decision block 1206 to determine whether a change has occurred in the wireless networks in the environment of the mobile device 102. After performing the comparison (e.g., as described above), the processor determines whether the result of the comparison indicates that the first and second measurements are sufficiently similar to conclude that the mobile device 102 is in the same environment, or sufficiently different to conclude that the mobile device 102 has moved to a different environment. In some implementations, the processor evaluates the comparison between the first and second measurements against a threshold. For example, when the first and second measurements are treated as vectors, and the comparison includes calculating their correlation coefficient, the processor may conclude that the wireless networks are not substantially different if the value of the correlation coefficient is greater than 0.5; otherwise, a substantial change has occurred. In another example, when none of the wireless network identifiers of the first measurement are present in the wireless network identifiers of the second measurement, the processor may conclude that a change has occurred; otherwise, no change has occurred. In another example, when any of the wireless network identifiers have changed between the first and second measurements, the processor may conclude that the two measurements are substantially different; otherwise, no change has occurred.
Applying Step 1206 of
If the processor determines at decision block 1206 that the first and second measurements are substantially different, and thus a substantial change in the wireless network environment has occurred, the processor proceeds to decision block 1208 to determine whether the mobile device is in a positioning system “dead zone,” (i.e., an environment in which position measurements from the positioning system are unavailable or of low quality). In some embodiments, the processor evaluates decision block 1208 by comparing at least one of the first and second measurements to stored dead zone information that represents known environments in which position measurements are not available. The processor may make this determination by comparing a network measurement to a stored history of network measurements which were received at substantially the same time that position measurements were attempted.
If the stored history (e.g., table 1550 of
Step 1202. As a result of performing the assessment at decision block 1208, the processor will not expend the mobile device's resources in an attempt to make a position measurement that is not likely to succeed (e.g., because the mobile device is located indoors and cannot send or receive GPS transmissions). The processor can assess similarity at decision block 1208 in any of the ways described above for the comparison of measurements at decision block 806. In some embodiments, the processor executes decision block 1208 before decision block 806; if the processor determines that a position measurement is not likely to succeed (decision block 1208), the processor will return to execute Step 1202 and not proceed to decision block 806. In some embodiments, the processor only executes one of decision blocks 806 and 808.
If the processor does not determine from the history of previous measurements that the mobile device 102 is in a positioning system dead zone, and thus that an attempt to invoke a positioning system may succeed (decision block 1208), the processor proceeds to decision block 1210. At decision block 1210, the processor determines whether or not a measurement of the position of the mobile device 102 is available from the positioning system (i.e., the mobile device 102 is in a positioning system dead zone). In some implementations, the processor may wait until the positioning system has been invoked (e.g., at Step 808 of
When no position measurement is available (decision block 1210), the processor updates the stored dead zone information by storing information representative of the wireless networks in the environment of the mobile device 102 at or around the time that the unsuccessful position measurement attempt was made (Step 1212). This information can be used by the processor in future iterations of the method of
In some embodiments, the processor stores information about more than one failed position measurement in a particular wireless network environment before the processor will stop attempting position measurements in that environment. Because the success of a measurement from a positioning system such as GPS can depend on many factors (including environmental conditions, temporary channel variations, and maintenance downtime), the processor can be configured to make a number of positioning attempts in a wireless network environment before determining that future positioning attempts in the wireless network environment will not be worthwhile. This number of failed attempts may be a fixed number (e.g., three) or further analysis may be triggered once a fixed number of failed attempts is recorded. For example, once three position measurements fail, the processor may look to a history of attempted position measurements to determine whether the majority of position measurements attempted in the network environment were failures; if yes, no future position measurements will be made in the network environment, but if no, additional attempts will be made in the future. In some embodiments, the processor resets the list of wireless network environments in which no positioning system is available (e.g., clearing the records in table 1550 of
However, if the processor determines that a position measurement is available (decision block 1210), the processor proceeds to indicate that the mobile device is in motion at Step 1214. In parallel or in series with the indication at Step 1214, the processor returns to Step 1202 to receive another measurement of wireless networks in the environment of the mobile device 102. In some embodiments, the processor only makes one additional wireless network measurement before proceeding to decision block 1206, using the new wireless network measurement and the second measurement from the previous iteration of the technique of
In some applications, the user of the mobile device 102 is not the only party responsible for the mobile device 102 or the user. Other responsible or interested parties include administrators, parents and employers. In some implementations, when the mobile device 102 exceeds a threshold speed, a notification is sent to one or more of these interested parties (or friends or business associates of the user of the mobile device 102). Such a message notifies the receiving party that the user is traveling, and should not be contacted. It may be in these parties' interests to confirm that any control hardware or software (as described herein) has not been tampered with or removed. In some implementations, the controller 104 of the mobile device 102 is configured to detect whether any settings or functions of the mobile device 102 have been tampered with. In particular, the controller 104 may be configured to process identifying information about a mobile device control application (such as the name, size of the file, associated properties and identification of an associated mobile device such as the mobile device 102). On a periodic or triggered basis, the controller 104 may receive a “check application” query from a network server or other device to determine whether the control application is still active on the device. This check may include verifying whether the application has the appropriate identifying information; if not, notification may be provided to at least one of the mobile device 102 or a device or electronic communications account associated with an interested party. The device or electronic communications account information (such as an e-mail address) may be stored in the MAP 123. In some implementations, the controller 104 detects that a control application has been tampered with when the control application fails to operate during a predetermined time period. For example, if the control application is a tracking application, and a position of the mobile device 102 has not been reported to the communications network 404 within the previous 24-hour period, a “check application” query would be transmitted by the communications network 404. Tamper detection and notification techniques may be performed by any suitable processor or system involved in the configuring, monitoring or control of the mobile device 102.
Additional mobile device control features that may be used with the techniques provided herein are described in the following provisional patent applications, incorporated herein in their entirety by reference: U.S. Provisional Patent Application No. 61/245,556, filed Sep. 24, 2009; U.S. Provisional Patent Application No. 61/245,799, filed Sep. 25, 2009; U.S. Provisional Patent Application No. 61/246,737, filed Sep. 29, 2009; U.S. Provisional Patent Application No. 61/245,815, filed Sep. 25, 2009; U.S. Provisional Patent Application No. 61/245,820, filed Sep. 25, 2009; U.S. Provisional Patent Application No. 61/245,891, filed Sep. 25, 2009; U.S. Provisional Patent Application No. 61/245,839, filed Sep. 25, 2009; U.S. Provisional Patent Application No. 61/245,900, filed Sep. 25, 2009; and U.S. Provisional Patent Application No. 61/246,587, filed Sep. 29, 2009.
It is to be understood that while various illustrative embodiments have been described, the forgoing description is merely illustrative and does not limit the scope of the invention. While several examples have been provided in the present disclosure, it should be understood that the disclosed systems, components, and methods may be embodied in many other specific forms without departing from the scope of the present disclosure.
