SELECTION

BACKGROUND

FIELD OF THE INVENTION

[001] This invention relates to providing navigational aids to drivers.

BACKGROUND OF THE INVENTION

[002] Stress is an emotion that everyone experiences in various situations. Cognitive outcomes of stress may include poor decision-making, lack of concentration, forgetfulness, etc. Driving is a skill that requires a high level of concentration. Lack of concentration may lead to traffic accidents, which may be fatal.

[003] The systems and methods disclosed herein provide an improved approach for reducing stress while driving.

BRIEF DESCRIPTION OF THE DRAWINGS

[004] In order that the advantages of the invention will be readily understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered limiting of its scope, the invention will be described and explained with additional specificity and detail through use of the accompanying drawings, in which:

[005] Fig. 1 is a schematic block diagram of an environment in which to implement systems and methods in accordance with an embodiment of the present invention; [006] Fig. 2 is a schematic block diagram of an example computing device suitable for implementing methods in accordance with embodiments of the invention;

[007] Fig. 3 is a process flow diagram illustrating a method for characterizing stress of road segments in accordance with an embodiment of the present invention;

[008] Fig. 4 are plots illustrating heart rate measurements and other metrics in accordance with an embodiment with the present invention;

[009] Fig. 5 is a process flow diagram of a method for re-routing according to a driver's stress level in accordance with an embodiment of the present invention;

[0010] Fig. 6 is a diagram illustrating various routes including various segments; and

[0011] Fig. 7 is a process flow diagram of a method for selecting a route according to driver preferences in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

[0012] Referring to Fig. 1, an environment 100 in which methods described herein may be implemented may include a vehicle 102 hosting an in-vehicle infotainment (IVI) system 104. The IVI system 104 may have some or all of the attributes of a general purpose computing device. The IVI system 104 may include a screen 106 that may be embodied as a touch screen.

[0013] As known in the art, the IVI system 104 may be coupled to speakers or other audio outputs and be programmed to provide an interface for selecting audio content to be played back using the speakers or other audio outputs. Audio content may be selected from one or more sources of audio content coupled to the IVI system 104, such as radio, compact disc (CD) player, and the like. The IVI system 104 may further display video content on the screen 106 or one or more other screens disposed within the vehicle 102. The IVI system 104 may be display video content selected from one or more sources of video content, such as a DVD player, paired mobile device, or other source of video data.

[0014] The IVI system 104 may further be coupled to one or more systems of the vehicle 102 itself and enable the display of status information for the vehicle 102 and receiving inputs modifying the operation of one or more systems of the vehicle 102 itself, such a climate control, engine operating parameters, and the like.

[0015] A vehicle 102 typically conveys a driver and one or more passengers. A driver may bring a mobile device 108 in the vehicle 102. The mobile device 108 may pair with the IVI system 104, such as through BLUETOOTH or some other wireless protocol. [0016] At least one of the mobile device 108 and IVI 104 include a Global Positioning System (GPS) receiver such that a location of the vehicle 102 may be detected and used according to the methods disclosed herein. In particular, location data may be related to concurrently measured heart rate data to characterize driver stress, as discussed below.

[0017] Specifically, a heart rate sensor 110 may further be located within the vehicle 102. For example, the heart rate sensor 110 may be mounted to a chest strap, a wrist-worn fitness tracker, or other wearable device. The heart rate sensor 110 may include any other device known in the art for sensing the heart rate of a driver. For example, conductive surfaces may be mounted to a steering wheel and coupled to a heart rate tracking device. Heart rate sensing may be performed electrically, acoustically, or optically using any device known in the art either worn by the user or mounted within the vehicle 102, such as a portion of a seat in contact with a driver.

[0018] Heart rate data from the heart rate sensor 110 and location data may be transmitted to a server system 112 for processing according to the methods disclosed herein. Alternatively, processing according to the methods disclosed herein may be performed by one or both of the IVI system 104 and mobile device 108. In still other embodiments, processing according to the methods disclosed herein is distributed among two or more of the IVI 104, mobile device 108, and server system 112.

[0019] Communication with the server system 112 may be facilitated by a network of cellular communication towers 114 in data communication with one or both of the IVI system 104 and mobile device 108. The cellular communication towers may also be in data communication with the server system 112, such as by means of a network 116. The network 116 may be include some or all of a local area network (LAN), wide area network (WAN), the Internet, and any other wired or wireless network connection.

[0020] Fig. 2 is a block diagram illustrating an example computing device 200. Computing device 200 may be used to perform various procedures, such as those discussed herein. The IVI system 104, mobile device 108, heart rate monitor 110, and server system 112 may have some or all of the attributes of the computing device 200.

[0021] Computing device 200 includes one or more processor(s) 202, one or more memory device(s) 204, one or more interface(s) 206, one or more mass storage device(s) 208, one or more Input/Output (I/O) device(s) 210, and a display device 230 all of which are coupled to a bus 212. Processor(s) 202 include one or more processors or controllers that execute instructions stored in memory device(s) 204 and/or mass storage device(s) 208. Processor(s) 202 may also include various types of computer-readable media, such as cache memory.

[0022] Memory device(s) 204 include various computer-readable media, such as volatile memory (e.g., random access memory (RAM) 214) and/or nonvolatile memory (e.g., read-only memory (ROM) 216). Memory device(s) 204 may also include rewritable ROM, such as Flash memory.

[0023] Mass storage device(s) 208 include various computer readable media, such as magnetic tapes, magnetic disks, optical disks, solid-state memory (e.g., Flash memory), and so forth. As shown in Fig. 2, a particular mass storage device is a hard disk drive 224. Various drives may also be included in mass storage device(s) 208 to enable reading from and/or writing to the various computer readable media. Mass storage device(s) 208 include removable media 226 and/or non-removable media. [0024] I/O device(s) 210 include various devices that allow data and/or other information to be input to or retrieved from computing device 200. Example I/O device(s) 210 include cursor control devices, keyboards, keypads, microphones, monitors or other display devices, speakers, printers, network interface cards, modems, lenses, CCDs or other image capture devices, and the like.

[0025] Display device 230 includes any type of device capable of displaying information to one or more users of computing device 200. Examples of display device 230 include a monitor, display terminal, video projection device, and the like.

[0026] Interface(s) 206 include various interfaces that allow computing device 200 to interact with other systems, devices, or computing environments. Example interface(s) 206 include any number of different network interfaces 220, such as interfaces to local area networks (LANs), wide area networks (WANs), wireless networks, and the Internet. Other interface(s) include user interface 218 and peripheral device interface 222. The interface(s) 206 may also include one or more peripheral interfaces such as interfaces for printers, pointing devices (mice, track pad, etc.), keyboards, and the like.

[0027] Bus 212 allows processor(s) 202, memory device(s) 204, interface(s) 206, mass storage device(s) 208, I/O device(s) 210, and display device 230 to communicate with one another, as well as other devices or components coupled to bus 212. Bus 212 represents one or more of several types of bus structures, such as a system bus, PCI bus, IEEE 1394 bus, USB bus, and so forth.

[0028] For purposes of illustration, programs and other executable program components are shown herein as discrete blocks, although it is understood that such programs and components may reside at various times in different storage components of computing device 200, and are executed by processor(s) 202. Alternatively, the systems and procedures described herein can be implemented in hardware, or a combination of hardware, software, and/or firmware. For example, one or more application specific integrated circuits (ASICs) can be programmed to carry out one or more of the systems and procedures described herein.

[0029] Referring to Fig. 3, the illustrated method 300 may be executed within the environment 100 in order to characterize the stress induced by driving a particular road segment.

[0030] The method 300 may include measuring 302 a baseline heart rate of a driver. For example, the baseline heart rate may be measured prior to a vehicle setting off, e.g. during a time period between detecting closing of a driver door and detecting pressing on the accelerator pedal to set the vehicle 102 in motion. In such an approach, measuring 302 the baseline heart rate may be performed by the IVI system 104 in cooperation with the heart rate monitor 110. The IVI system 104 may therefore receive a heart rate estimate (or measured electrical signals from which such an estimate may be derived) from the heart rate monitor 110 as well as outputs of sensors sensing the state of the door and accelerator pedal in order to identify a time period for which measured heart rate data will be considered a baseline measurement.

[0031] The baseline heart rate measurement may be measurements of a driver's heart rate acquired from the heart rate monitor 110 during a predetermined time period immediately prior to detecting movement of the mobile device 108 at driving speeds, e.g. above 12 mph. [0032] The method 300 may further include measuring 304 the driver's heart rate while also tracking the location of the vehicle 102. For example, this may include receiving a stream of heart rate measurements H from the heart rate monitor 110 and receiving a stream of GPS readings from a GPS receiver in the mobile device 108 or IVI system 104. The streams of heart rate measurements and GPS readings may be time stamped either due to time markers for every N measurements (N >= 1) included in the stream of heart rate measurements or due to a known sampling rate and a known start time of the stream. Using the known time of measurement for each heart rate measurement and each GPS reading, the approximate location of each heart rate measurement may be determined based on the GPS reading received closest to the time of receipt of the GPS reading. Other techniques may also be used to relate a heart rate measurement to a corresponding GPS reading. For example, heart rate measurements and GPS readings may be simply stored in an interleaved fashion in files. For example, heart rate measurements may be stored in a file such that each heart rate measurement is tagged with an immediately preceding (or following) GPS reading.

[0033] In any of the above case, for each heart rate measurement H[n] a corresponding closest GPS reading L[n] may be identified as the GPS reading that was obtained immediately preceding that heart rate measurement H[n], immediately following that heart rate measurement H[n], or that is an interpolation between GPS readings occurring before and after that heart rate measurement H[n] was received.

[0034] Step 304 may continue until the end of a trip. A trip may be determined to have ended when the vehicle 102 is no longer running, the driver is no longer in the vehicle 102 (as determined from a loss of a wireless connection to the mobile device 108 or the heart rate monitor 110), or some other criteria.

[0035] The measurements of steps 302 and 304 may be transmitted to the server system 112 for processing according to the subsequent steps of the method 300. Alternatively, the subsequent steps of the method 300 may be performed by the IVI system 104, mobile device 108, or combination of the two.

[0036] The subsequent steps of the method 300 may be performed with respect to measurements from steps 302, 304 for multiple trips by the same driver. In some embodiments, the subsequent steps of the method 300 may be performed with respect to measurements from steps 302, 304 for multiple trips by multiple different drivers, e.g. a large population of drivers such that the confidence associated with determinations according to the method 300 is enhanced.

[0037] The method 300 may include, for each trip, normalizing 306 heart rate measurements for the trip. This may include dividing the heart rate measurements H of step 304 for a trip with the baseline heart rate measurement of step 302 for that trip to obtain normalized heart rate measurements. For example this may include calculating normalized heart rate measurements R = H/B, where B is derived from the baseline heart rate measurements for the trip. For example, B may be the minimum heart rate measured at step 302 or the average heart rate of the baseline measurements, or some other value derived from the baseline heart rate measurements. Step 306 may be performed for each trip being analyzed such that a set of normalized heart rate measurements is obtained for each trip.

[0038] The method 300 may further include, for each road segment traversed during a trip, calculating 308 a stress metric. A road segment may include any segment of road that may be traversed by a vehicle. For example, a road segment may be defined as a portion of a road between intersections, a portion of a highway between exits, or some other criteria. The stress metric may be calculated as a function of a portion of the normalized heart rate measurements R that were measured while the driver was located on that road segment. For example, the location measurements L may be evaluated to identify road segments traversed during a trip, such as by comparing GPS coordinates for the location measurements L to GPS coordinates defining the road segment.

[0039] Where L[p], p = a to b, are the detected locations lying on a road segment, then R[p] is the normalized heart rate measurements corresponding to the road segments. Accordingly, a stress metric S = f(R[p]) may be calculated as indicating a driver's stress for one traversal of that road segment. In some embodiments, S increases with one or both of an increasing maximum value of R[p] and an increasing average value for R[p]. For example, S may be set equal to either of the maximum value of R[p] or the average value for R[p]. Other functions of R[p] may also be used that provide for increasing values with increasing average and/or maximum values of R[p].

[0040] For each road segment of a trip, a corresponding stress metric S may be calculated. The stress metrics of multiple users for the road segment may be averaged to compute a global stress metric for that segment. Stress metrics calculated for multiple traversals of the same road segment by the same user may be averaged to compute an individual stress metric for that road segment.

[0041] In some embodiments, stress metrics calculated for traversals of a road segment occurring in a specific time window may be aggregated to obtain a window- specific stress metric. The window specific stress metric may be computed for stress metrics calculated for a single driver or for a plurality of drivers. For example, each hour of the day may be a time window or time windows may be defined for a region that include a morning rush hour window, an evening rush hour window, and an off peak window that includes times other than the morning rush hour window and the evening rush hour window.

[0042] In some embodiments, a current global stress metric is calculated based on stress metrics calculated for multiple drivers in a time window preceding a current time, e.g. the previous 30 minutes, one hour, or some other window.

[0043] The method 300 may further include assigning 310 the stress metric calculated for a segment to that segment. Specifically, a database may be maintained that includes stress metrics for a plurality of road segments. The database may store multiple stress metrics for the same road segment, e.g. a global stress metric, one or more individual stress metric, one or more window-specific stress metrics, and a current global stress metric, as these are defined above. The assigned stress metrics may be periodically updated based on new measurements from steps 302, 304 for an individual driver or group of drivers.

[0044] Referring to Fig. 4, the illustrated graphs illustrate the calculation of stress metrics based on heart rate measurements. In the lower graph, the vertical axis 400a represents a measured heart rate, such as in beats per minute (bpm). The horizontal axis 402a represents time. As shown, the horizontal axis 402a is divided into a baseline segment 404 and a plurality or segments 406a-406f. The baseline segment 404 may be the portion of heart rate measurements measured at step 302 at the beginning of a trip to establish a baseline measurement. Each segment 406a-406f corresponds to heart rate measurements detected while the driver is located on a particular road segment.

[0045] In the upper graph, the vertical axis 400b represents potential values for the stress metric and the horizontal axis 402b represents time. For each segment 406a- 406f a corresponding stress metric 408a-408f is calculated based on the heart rate measurements of the corresponding segment 406a-406f. The stress metrics 408a-408f for each road segment may be aggregated with other stress metrics calculated for other trips traversing the same road segments. As noted above, stress metrics 408a-408f of a single driver may be aggregated to calculate an individual stress metric for a road segment. Likewise, stress metrics 408a-408f of multiple driver may be aggregated to compute a global stress metric for a road segment.

[0046] Referring to Fig. 5, the illustrated method 500 may be used to select routes for a driver using stress metrics (individual, global, window-specific, or current global) calculated based on prior heart rate measurements according to the method 300 of Fig. 3.

[0047] The method 500 may include measuring 502 a baseline heart rate for a trip. Measuring 502 a baseline heart rate for a trip may be performed in the same manner as step 302 of the method 300. Likewise, during the trip the driver's heart rate may be measured 504 and the location tracked in the same manner as for step 304 of the method 300.

[0048] The method 500 may further include normalizing 506 the heart rate measurements and calculating 508 a stress metric based on the stress metric. Steps 506 and 508 may be performed in the same manner as steps 306 and 308 of the method 300.

[0049] The steps of measuring 504 heart rate, normalizing 506 heart rate measurements, and calculating 508 a stress metric may be performed periodically, e.g. every 10 seconds, 30 seconds, one minute, or some other interval. For each interval, the method 500 may include evaluating 510 whether the stress metric calculated for that interval exceeds a threshold condition. For example, a driver, or some authority (e.g. a parent), may specify a maximum stress metric value. If the stress metric for an interval is above this maximum value, then the threshold condition may be determined 510 to have been met.

[0050] In response to determining 510 that the stress metric exceeds the threshold condition, some or all of steps 512-518 may be performed.

[0051] Referring to Fig. 6, while still referring to Fig. 5, one or more alternative routes 600a-600c to a destination may be identified 512. For example, the destination may be received from a driver as an input to navigation software. The destination may be inferred, e.g. in the morning, the destination may be inferred to be the driver's place of work. In the evening, the destination may be inferred to be the driver's place of residence. Alternative routes 600a-600c to the destination may be identified 512 according to any method known in the art of navigation based on map data describing the locations of roads.

[0052] The method 500 may further include calculating 514 a stress metric for the alternative routes ("alternative stress metrics"). In particular, a type of stress metric (individual, global, window-specific, current global) for each road segment of an alternative route may be aggregated in some way to calculate the alternative stress metric. Where a window-specific stress metric for a road segment is used, it may be selected as the window-specific stress metric for a time window including the current time of execution of the method 500 or an expected time of traversal of the road segment. In some embodiments, multiple types of stress metrics for each road segment may be combined (summed, averaged, weighted and summed, weighted and averaged, etc.) and the combination used as the stress metric for the each road segment when calculating the alternative stress metric for a route.

[0053] In the example of Fig. 6, for route 600a, the alternative stress metric will be a function of the stress metrics for segments 602a, 602b. For route 600b, the alternative stress metric will be a function of the stress metrics for segments 602c-602h. For route 600c, the alternative stress metric will be a function of the stress metrics for segments 602i-602m and segment 602h.

[0054] Aggregating the stress metrics of the segments in an alternative route may include averaging. For example, a weighted average may be computed wherein the stress metric for each road segment is weighted according to its length. For example an alternative stress metric SA may be calculated from stress metrics Si, S ₂ , S ₃ for road segments having lengths Li, L ₂ , and L ₃ , respectively, as SA = (Si*Li+S ₂ *L ₂ +S ₃ *L ₃ )/(Li+L ₂ +L ₃ ). In some embodiments, the alternative stress metric increases with increasing of the sum of the stress metrics of individual road segments, e.g. a function that increases according to some function such that the alternative stress metric will increase with an increase in the value (Si+ S ₂ + S ₃ ). Calculating the aggregate stress metric may additionally or alternatively include identifying a maximum stress metric, or some other function of the stress metrics of the segments of the alternative route.

[0055] The method 500 may further include selecting 516 one of the alternative routes according to the alternative stress metrics. For example, the alternative route having the lowest alternative stress metric may be selected. In another example, the alternative route having the lowest alternative stress metric is selected if it is less than the stress metric for the current route.

[0056] In some embodiments, a user may specify a maximum stress metric. Accordingly, the alternative route may be selected as the shortest route among the alternative routes that has an alternative stress metric less than the maximum stress metric. Alternatively the alternative route may be selected as the shortest alternative route that has no individual segment with a stress metric thereof greater than the maximum stress metric.

[0057] The method 500 may then include 518 providing turn-by-turn guidance for the selected alternative route. The manner in which turn-by-turn guidance is performed may be according to any method for providing navigation guidance known in the art.

[0058] The method 500 may further include performing steps 504-510 with the selected alternative route as the current route. Accordingly, yet another alternative route may be selected based on the outcome of step 510 in some instances.

[0059] The illustrated method 500 may be performed by various components or a combination of components. For example, steps 502 and 504 may be performed by an IVI system 104 or mobile device 108 that is located in the vehicle 102 that a driver is driving. Steps 506-510 may also be performed by the IVI system 104 or mobile device 108. Alternatively, heart rate measurements and location data may be sent to the server system 112, which then performs steps 506-610.

[0060] Similarly, steps 512-516 may be performed by the server system 112 inasmuch as the stress metric data for the various road segments may be stored in a database accessible to the server system 112. For example, the IVI system 104 or mobile device 108 may invoke performance of steps 512-516 by the server system 112 in response to determining 510 that the driver's current stress metric exceeds the threshold condition. In such embodiments, the server system 112 may transmit the route selected at step 516 to the IVI system 104 or mobile device 108. The IVI system 104 and mobile device 108 may then provide 518 the guidance according to the selected route.

[0061] In some embodiments, the IVI system 104 or mobile device 108 may obtain the stress metric values for various road segments from the server system 112 such that steps 512-516 may be performed locally.

[0062] Referring to Fig. 7, in some embodiments, routes may be selected initially based on an aggregate stress metric for a route in place of, or in addition to, selection of an alternative route based on an estimate of a driver's stress.

[0063] For example, the method 700 may include receiving 702 a destination and receiving 704 a stress preference for the route. Step 704 may include retrieving a stored preference for a driver. For example, a driver may have a profile that specifies a preferred stress metric for routing and/or a maximum permitted stress metric for a route.

[0064] The method 700 may include identifying 706 potential routes between the driver's current location and the destination received at step 702. The manner in which routes are identified may include any method known in the art.

[0065] The method 700 may include calculating 708 stress metrics for the potential routes, such as in the same manner for step 514 of the method 500. One of the potential routes may then be selected 710 and guidance provided 712 according to the selected route. Selecting 710 and providing 712 guidance may be performed in the same manner as for steps 516 and 518 of the method 500.

[0066] Similar to the method 500 of Fig. 5, steps 702-710 may be performed by the server system 112 with the selected route being provide to the IVI system 104 or mobile device 108 for providing 712 turn-by-turn guidance.

[0067] Various other functions may be implemented using the network environment 100 of Fig. 1 in addition to the methods of Figs. 3 through 7. For example, the output of the heart rate monitor 110 may be monitored by the IVI system 104, mobile device 108, or server system 112. In response to detecting the measured heart rate exhibiting abnormal values, actions may be invoked. Abnormal values may include an abnormally high heart rate, an abnormally low heart rate, ventricular fibrillation, or other condition that may be detected using electrical signals detectable by a hear rate monitor 110.

[0068] Actions invoked may include sending a notification to a family member of the driver, outputting a notification to the driver, sending a notification to emergency services, or some other action. For example, the IVI system 104 may display on the screen 106 an instruction to pull over.

[0069] In the above disclosure, reference has been made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific implementations in which the disclosure may be practiced. It is understood that other implementations may be utilized and structural changes may be made without departing from the scope of the present disclosure. References in the specification to "one embodiment," "an embodiment," "an example embodiment," etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0070] Implementations of the systems, devices, and methods disclosed herein may comprise or utilize a special purpose or general-purpose computer including computer hardware, such as, for example, one or more processors and system memory, as discussed herein. Implementations within the scope of the present disclosure may also include physical and other computer-readable media for carrying or storing computer- executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media that store computer-executable instructions are computer storage media (devices). Computer-readable media that carry computer- executable instructions are transmission media. Thus, by way of example, and not limitation, implementations of the disclosure can comprise at least two distinctly different kinds of computer-readable media: computer storage media (devices) and transmission media.

[0071] Computer storage media (devices) includes RAM, ROM, EEPROM, CD- ROM, solid state drives ("SSDs") (e.g., based on RAM), Flash memory, phase-change memory ("PCM"), other types of memory, other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

[0072] An implementation of the devices, systems, and methods disclosed herein may communicate over a computer network. A "network" is defined as one or more data links that enable the transport of electronic data between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmissions media can include a network and/or data links, which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.

[0073] Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code. 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 described features or acts described above. Rather, the described features and acts are disclosed as example forms of implementing the claims. [0074] Those skilled in the art will appreciate that the disclosure may be practiced in network computing environments with many types of computer system configurations, including, an in-dash vehicle computer, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, tablets, pagers, routers, switches, various storage devices, and the like. The disclosure may also be practiced in distributed system environments where local and remote computer systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0075] Further, where appropriate, functions described herein can be performed in one or more of: hardware, software, firmware, digital components, or analog components. For example, one or more application specific integrated circuits (ASICs) can be programmed to carry out one or more of the systems and procedures described herein. Certain terms are used throughout the description and claims to refer to particular system components. As one skilled in the art will appreciate, components may be referred to by different names. This document does not intend to distinguish between components that differ in name, but not function.

[0076] It should be noted that the sensor embodiments discussed above may comprise computer hardware, software, firmware, or any combination thereof to perform at least a portion of their functions. For example, a sensor may include computer code configured to be executed in one or more processors, and may include hardware logic/electrical circuitry controlled by the computer code. These example devices are provided herein purposes of illustration, and are not intended to be limiting. Embodiments of the present disclosure may be implemented in further types of devices, as would be known to persons skilled in the relevant art(s). At least some embodiments of the disclosure have been directed to computer program products comprising such logic (e.g., in the form of software) stored on any computer useable medium. Such software, when executed in one or more data processing devices, causes a device to operate as described herein.

[0077] Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Smalltalk, C++, or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on a computer system as a stand-alone software package, on a stand-alone hardware unit, partly on a remote computer spaced some distance from the computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0078] The present invention is described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions or code. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0079] These computer program instructions may also be stored in a non- transitory computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.

[0080] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0081] While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various changes in form and detail can be made therein without departing from the spirit and scope of the disclosure. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents. The foregoing description has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. Further, it should be noted that any or all of the aforementioned alternate implementations may be used in any combination desired to form additional hybrid implementations of the disclosure.

[0082] What is claimed is: