Mobile platform and device travel correlation

Abstract

Methods and systems are provided for correlating mobile platform data with auxiliary device data. In an exemplary embodiment, mobile platform data and auxiliary device data are obtained. The mobile platform data is related to the mobile platform. The auxiliary device data originates from an auxiliary device movably disposed within the mobile platform at certain times. Obtaining the auxiliary device data is independent of obtaining the mobile platform data. The mobile platform data is correlated with the auxiliary device data via the processor.

Description

[0001] The technical field relates generally to mobile platforms, including vehicles and other platforms, and more particularly to systems and methods for correlating data from the mobile platform with data from auxiliary devices that may be temporarily disposed within the mobile platform. Background Art

[0002] Today's mobile platforms (such as vehicles) often collect data, such as acceleration, speed, braking, steering, and other events of the mobile platform. Ancillary devices (such as a user's mobile phone) may also collect data related to the mobile platform (including when inside the mobile platform). However, existing systems and methods may not provide optimal correlation of such data of the mobile platform with data of the device in all situations.

[0003] Therefore, it is desirable to provide improved methods and systems for correlating mobile platform data with auxiliary device data.Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description of the invention and the appended claims, taken in conjunction with the drawings and this background of the invention. Summary of the invention

[0004] In an exemplary embodiment, a method is provided, comprising: obtaining mobile platform data, the mobile platform data being related to a mobile platform; obtaining auxiliary device data, the auxiliary device data originating from an auxiliary device that is movably disposed within the mobile platform at certain times, wherein obtaining the auxiliary device data is independent of obtaining the mobile platform data; and correlating the mobile platform data with the auxiliary device data via a processor.

[0005] Furthermore, in the exemplary embodiment, the mobile platform data originates from one or more sensors built into the mobile platform.

[0006] Furthermore, in an exemplary embodiment, the mobile platform data originates from one or more additional devices configured to detect mobile platform events, collect sensor data during mobile platform operation, or both.

[0007] Furthermore, in an exemplary embodiment, the step of correlating mobile platform data with auxiliary device data includes: generating a mobile platform event space for the mobile platform data via a processor; generating an auxiliary device event space for the auxiliary device data via a processor; and performing a cross-correlation between the mobile platform event space and the auxiliary device event space via the processor.

[0008] Additionally, in an exemplary embodiment, the method further includes applying, via the processor, a preliminary restriction to the search space of the mobile platform event space and the auxiliary device event space prior to performing the cross-correlation.

[0009] Furthermore, in an exemplary embodiment, performing the cross-correlation step includes: performing, via the processor, DSP convolution on the auxiliary device event space to generate a filtered auxiliary device event space; and performing, via the processor, DSP cross-correlation between the mobile platform event space and the filtered auxiliary device event space.

[0010] Additionally, in an exemplary embodiment, the method further includes allocating, via the processor, a probability allocation matrix between the mobile platform data and the auxiliary device data based on the cross-correlation.

[0011] In another exemplary embodiment, a system is provided that includes a non-transitory computer-readable storage medium and a processor. The non-transitory computer-readable storage medium is configured to store: mobile platform data, the mobile platform data being related to the mobile platform; and auxiliary device data, the auxiliary device data originating from an auxiliary device that is removably disposed within the mobile platform at some time, wherein the mobile platform data is obtained separately from the auxiliary device data. The processor is coupled to the transceiver and is configured to at least facilitate correlating the mobile platform data with the auxiliary device data.

[0012] Furthermore, in the exemplary embodiment, the mobile platform data originates from one or more sensors built into the mobile platform.

[0013] Furthermore, in an exemplary embodiment, the mobile platform data originates from one or more additional devices configured to detect mobile platform events, collect sensor data during mobile platform operation, or both.

[0014] Moreover, in the exemplary embodiment, the processor is further configured to at least facilitate correlating the mobile platform data with the secondary device data without any prior association between the mobile platform and the secondary device.

[0015] Moreover, in an exemplary embodiment, the processor is further configured to facilitate at least generating a mobile platform event space for mobile platform data; generating an auxiliary device event space for auxiliary device data; and performing a cross-correlation between the mobile platform event space and the auxiliary device event space.

[0016] Moreover, in an exemplary embodiment, the processor is further configured to facilitate at least applying preliminary restrictions to the search spaces of the mobile platform event space and the auxiliary device event space prior to performing the cross-correlation.

[0017] Moreover, in an exemplary embodiment, the processor is further configured to facilitate at least performing a DSP convolution on the auxiliary device event space to generate a filtered auxiliary device event space; and performing a DSP cross-correlation between the mobile platform event space and the filtered auxiliary device event space.

[0018] Moreover, in an exemplary embodiment, the processor is further configured to facilitate at least allocating a probability allocation matrix between the mobile platform data and the auxiliary device data based on the cross-correlation.

[0019] In another exemplary embodiment, a system is provided that includes a transceiver, a non-transitory computer-readable storage medium, and a processor. The transceiver is configured to at least facilitate obtaining mobile platform data related to a mobile platform; and obtaining auxiliary device data from an auxiliary device that is remote from the system and at some time removably disposed within the mobile platform, wherein obtaining the auxiliary device data is independent of obtaining the mobile platform data. The non-transitory computer-readable storage medium is configured to store a program with the mobile platform data and the auxiliary device data. The processor is coupled to both the transceiver and the non-transitory computer-readable storage medium and is configured to execute the program and facilitate at least correlating the mobile platform data with the auxiliary device data according to the program.

[0020] Furthermore, in the exemplary embodiment, the mobile platform data originates from one or more sensors built into the mobile platform.

[0021] Furthermore, in an exemplary embodiment, the mobile platform data originates from one or more additional devices configured to detect mobile platform events, collect sensor data during mobile platform operation, or both.

[0022] Moreover, in an exemplary embodiment, the processor is further configured to facilitate at least according to the program: generating a mobile platform event space for mobile platform data; generating an auxiliary device event space for auxiliary device data; and performing a cross-correlation between the mobile platform event space and the auxiliary device event space. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present disclosure will hereinafter be described in conjunction with the following drawings, wherein like reference numerals refer to like elements, and wherein:

[0024] Figure 1 is a diagram of a system according to an exemplary embodiment, the system including a mobile platform (such as a vehicle), an auxiliary device within the mobile platform, and a remote server that correlates data obtained from the mobile platform with data obtained from the auxiliary device;

[0025] Figure 2 According to an exemplary embodiment, data obtained from a mobile platform may be correlated with data obtained from an auxiliary device within the mobile platform and may be combined with Figure 1 a flowchart of a process implemented by a system; and

[0026] Figures 3 to 9 Provided is a diagram illustrating an exemplary embodiment of the present invention. Figure 2 A representative illustration of an exemplary implementation of a process. DETAILED DESCRIPTION

[0027] The following detailed description is merely exemplary in nature and is not intended to limit the present disclosure or its application and uses. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description.

[0028] Figure 1 is a diagram of a system 100 configured for correlating data from a mobile platform with data from an auxiliary device disposed within the mobile platform, according to an exemplary embodiment. Figure 1 Depicted are a representative mobile platform 110 , a representative auxiliary device 112 , a remote server 114 , and one or more wireless communication networks 116 , in accordance with an exemplary embodiment.

[0029] In certain embodiments, such as Figure 1 As depicted, the mobile platform 110 includes a vehicle. In some embodiments, the mobile platform 110 may be any of a large number of different types of automobiles such as: for example, a sedan, a van, a truck, or a sports utility vehicle (SUV), and in some embodiments may be a two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), a four-wheel drive (4WD), or an all-wheel drive (AWD) and / or various other types of vehicles and / or other types of mobile platforms. In some embodiments, the mobile platform 110 may also include a motorcycle or other mobile platform, such as an aircraft, a spacecraft, a boat, a scooter, a bicycle, a skateboard, a hoverboard, a gyroscope-based transport device and other transport devices, and / or one or more other types of vehicles and / or other types of mobile platforms (e.g., a robot and / or other mobile platforms). In addition, in various embodiments, as used throughout this application, the term "mobile platform" may refer to the mobile platform itself or its components, or a device capable of detecting trip-related events or collecting sensor data related to the movement of the mobile platform. For example, but not limited to, throughout this application, references to "mobile platforms", "data" from mobile platforms, etc., such references may refer to the mobile platforms themselves or to one or more such components or devices capable of detecting travel-related events or collecting sensor data related to the movement of the mobile platforms. Thus, as described throughout this application and as illustrated in the accompanying drawings, correlation of data between mobile platforms with data from auxiliary devices may refer to (a) correlation of data between mobile platforms themselves with data from auxiliary devices (such as smartphones, tablet computers, smart watches, other wearable devices, etc., disposed within one or more mobile platforms); and / or (b) correlation of data between one such auxiliary device with data from one or more other such auxiliary devices, and so on, as well as other possible combinations.

[0030] In addition, in various embodiments, mobile platform 110 includes a representative mobile platform of a large number of different mobile platforms. In various embodiments, mobile platform 110 belongs to a fleet of mobile platforms (e.g., a fleet of vehicles in some embodiments), and / or another group or collection of mobile platforms from which data is collected.

[0031] Continue to refer to Figure 1 In some embodiments, the mobile platform 110 includes a body 120, a drive system 122, and a control system 124. Figure 1 As depicted, in various embodiments, the mobile platform 110 also includes one or more auxiliary devices 112 (eg, belonging to a user of the mobile platform 110 ) disposed within the mobile platform 110 and / or otherwise coupled to the mobile platform 110 .

[0032] In various embodiments, the drive system 122 is disposed within the body 120 and provides movement of the mobile platform 110 .

[0033] In various embodiments, a control system 124 is also disposed within the body 120 and controls the operation of the mobile platform 110. In various embodiments, the control system 124 controls the movement of the mobile platform 110 based on instructions provided to the drive system 122 and / or other mobile platform systems. Additionally, in various embodiments, the control system 124 controls the acquisition of data from the mobile platform 110 and the transmission of mobile platform data to the remote server 114 for processing.

[0034] like Figure 1 As depicted, in various embodiments, the control system 124 includes a sensor 126 , a transceiver 128 , a processor 130 , and a memory 132 .

[0035] In various embodiments, the sensors 126 obtain sensor data regarding the operation of the mobile platform 110, such as speed, acceleration, deceleration, braking, steering, and mobile platform events. For example, in various embodiments, the sensors 126 include various position sensors (e.g., global positioning system or "GPS" sensors), accelerometers, gyroscopes, speed sensors (e.g., wheel speed sensors), brake sensors (e.g., brake pedals and / or brake systems coupled to the mobile platform 110), steering sensors (e.g., steering angle sensors coupled to a steering wheel or steering column of the mobile platform 110), and / or other sensors configured to collect sensor data from the mobile platform. In various embodiments, the sensors 126 are built into the mobile platform 110 (e.g., during manufacture of the mobile platform 110), and are permanently disposed within the mobile platform 110 or otherwise carried on the mobile platform 110 (e.g., on or within the body 120 of the mobile platform 110). In various embodiments, the sensors 126 are configured to obtain sensor data that can be used to detect or determine the occurrence of various mobile platform events such as: sudden braking, sudden acceleration, sudden turns, speed changes, other speed and acceleration events, mobile platform contact events, etc.

[0036] Continue to refer to Figure 1 In various embodiments, transceiver 128 is utilized to communicate with remote server 114 and / or with one or more other remote entities via one or more wireless communication networks 116. In various embodiments, transceiver 128 transmits sensor data from sensors 126 (and, in some embodiments, determinations therefrom regarding mobile platform events) to remote server 114 for processing, and in particular for correlation with data obtained from auxiliary devices 112. In some embodiments, transceiver 128 may also transmit other mobile platform data (e.g., from one or more of auxiliary devices 112 onboard mobile platform 110).

[0037] Additionally, in various embodiments, processor 130 performs computing and control functions of control system 124 and for mobile platform 110, and may include any type of processor or multiple processors, a single integrated circuit such as a microprocessor, or any suitable number of integrated circuit devices and / or circuit boards that work together to accomplish the functions of a processing unit. During operation, processor 130 executes one or more programs 134 contained within memory 132, and thereby controls the overall operation of control system 124.

[0038] The memory 132 may be any type of suitable memory. For example, the memory 132 includes a non-transitory computer-readable storage medium. In some examples, the memory 132 is located and / or co-located on the same computer chip as the processor 130. In the depicted embodiment, the memory 132 stores the above-described program 134 and one or more stored values ​​136 (e.g., in some embodiments, stored sensor data values).

[0039] In addition, if Figure 1 As depicted, in various embodiments, the auxiliary device 112 is disposed within the mobile platform 110. For example, in some embodiments, the auxiliary device 112 belongs to a user of the mobile platform 110 and is removably disposed within the mobile platform 110 at certain times (such as when the user is disposed within the mobile platform 110). Furthermore, in various embodiments, the auxiliary device 112 includes a representative auxiliary device from a large number of auxiliary devices (e.g., each auxiliary device belongs to a respective user of a respective mobile platform 110 of a team, group, or collection of mobile platforms from which data is collected).

[0040] In some embodiments, auxiliary device 112 includes a mobile phone, such as a smart phone. However, in various embodiments, auxiliary device 112 may also include any number of other types of electronic devices, such as, by way of example only, tablet computers, laptop computers, smart watches and other wearable devices, and various other types of electronic devices.

[0041] In various embodiments, auxiliary device 112 includes functionality to collect data about mobile platform events that are similar to or correspond to mobile platform events related to sensor data collected by sensors 126 of mobile platform 110 (e.g., using built-in sensors). Further, in various embodiments, auxiliary device 112 independently collects data about these mobile platform events and transmits the auxiliary device data for processing. For example, in some embodiments, auxiliary device 112 transmits the auxiliary device data to remote server 114 via one or more wireless communication networks 116 for processing, including for correlation with mobile platform data from mobile platform 110.

[0042] In various embodiments, the remote server 114 communicates with a mobile platform (such as Figure 1 A representative mobile platform 110) and auxiliary devices (such as Figure 1 In various embodiments, the remote server 114 obtains mobile platform data from a plurality of different mobile platforms 110 and obtains auxiliary device data from a plurality of different auxiliary devices 112, and correlates the mobile platform data with the auxiliary device data. In various embodiments, the remote server 114 obtains mobile platform data from a plurality of different mobile platforms 110 and auxiliary device data from a plurality of different auxiliary devices 112, and correlates the mobile platform data with the auxiliary device data. Figures 2 to 9The processes and implementations set forth in and described in further detail below in conjunction therewith perform these functions.

[0043] like Figure 1 As depicted, in various embodiments, the remote server 114 includes a transceiver 138 , a processor 140 , and a memory 142 .

[0044] In various embodiments, transceiver 138 is utilized to communicate with mobile platform 110 (and other mobile platforms) and auxiliary device 112. In various embodiments, transceiver 138 receives mobile platform data from mobile platform 110 and also receives auxiliary device data from auxiliary device 112.

[0045] Furthermore, in various embodiments, processor 140 performs computing and control functions of remote server 114 and may include any type of processor or multiple processors, a single integrated circuit such as a microprocessor, or any suitable number of integrated circuit devices and / or circuit boards that work in conjunction to perform the functions of a processing unit. During operation, processor 140 executes one or more programs 144 contained within memory 142 and, therefore, controls the overall operation of remote server 114.

[0046] The memory 142 may be any type of suitable memory. For example, the memory 142 includes a non-transitory computer-readable storage medium. In some examples, the memory 142 is located and / or co-located on the same computer chip as the processor 140. In the depicted embodiment, the memory 142 stores the above-described program 144 and one or more stored values ​​146 (e.g., in some embodiments, stored mobile platform data values ​​and stored auxiliary device data values).

[0047] Now refer to Figure 2 , provides a flow chart of a method 200 for associating data of a mobile platform (e.g., a vehicle and / or other mobile platform) with data of an auxiliary device temporarily disposed within the mobile platform according to an exemplary embodiment. According to various embodiments, the method 200 may be combined with Figure 1 The system 100 is implemented, and the system 100 includes a mobile platform 110, an auxiliary device 112, a remote server 114 and components thereof. Figures 3 to 9 To describe method 200, Figures 3 to 9 An exemplary implementation thereof according to an exemplary embodiment is depicted.

[0048] like Figure 2As depicted, in some embodiments, method 200 includes certain steps (referred to as a first set of steps 201) performed by mobile platform 110; certain other steps (referred to as a second set of steps 202) performed by auxiliary device 112; and certain other steps (referred to as a third set of steps 203) performed by remote server 114. It should be understood that this may vary in other embodiments. It should also be understood that the order of execution of the steps need not be determined by the grouping described above.

[0049] Continue to refer to Figure 2 In various embodiments, method 200 begins at 204. In various embodiments, method 200 is performed on a mobile platform (such as Figure 1 The mobile platform 110 is in operation, such as when a mobile platform trip (e.g., a current mobile platform drive or ignition cycle) begins on a road, and one or more auxiliary devices (such as Figure 1 The auxiliary device 112 is arranged inside the mobile platform.

[0050] In various embodiments, the mobile platform detects the start of the trip (step 205 ). In various embodiments, this is performed via one or more sensors 126 of the mobile platform 110 .

[0051] In addition, in various embodiments, mobile platform data is generated (step 206). Specifically, in various embodiments, sensor data is obtained from the mobile platform sensors 126 throughout the duration of the trip. In various embodiments, the sensor data (also referred to herein as mobile platform data) includes the following in addition to other potential types of data types: speed, acceleration, deceleration, braking, steering, and mobile platform events (e.g., changes in any of the above values, and / or contact with another mobile platform or object, and / or any number of other types of mobile platform events). In various embodiments, the sensor data can be obtained by the following sensors 126 and various other possible sensors 126 of the mobile platform 110: position sensors (e.g., GPS sensors), gyroscopes, speed sensors (e.g., wheel speed sensors), accelerometers, brake sensors (e.g., brake pedals or brake systems coupled to the mobile platform 110), steering sensors (e.g., steering angle sensors coupled to the steering wheel or steering column of the mobile platform 110), and / or other sensors configured to collect sensor data from the mobile platform 110.

[0052] While in various embodiments, the mobile platform data (and detection of mobile platform travel) of steps 205 and 206 originate from mobile platform sensors 126 as described above (e.g., those built into the mobile platform); in certain other embodiments, the mobile platform data may also originate from one or more additional auxiliary devices 112 (e.g., different from the auxiliary devices 112 associated with steps 210 and 212 described below) that are onboard the mobile platform 110 and / or configured to detect mobile platform events, collect sensor data during mobile platform operation, or both.

[0053] Additionally, in various embodiments, the mobile platform data is transmitted (step 208). In various embodiments, using Figure 1 The sensor data of step 206 is transmitted from the mobile platform 110 to the remote server 114 via the transceiver 128 of the mobile platform 110 via one or more wireless communication networks 116 , and the sensor data of step 206 is received by the remote server 114 via its transceiver 138 .

[0054] In various embodiments, each of the above steps 205, 206, and 208 is performed by the mobile platform 110, and thus corresponds to the steps defined above and described in Figure 2 The first set of steps 201 is depicted in FIG.

[0055] Additionally, in various embodiments, the auxiliary device detects the start of a trip (step 210). In various embodiments, this is done via Figure 1 The auxiliary device 112 is performed (for example, via one or more embedded sensors thereof, not shown).

[0056] Additionally, in various embodiments, auxiliary device data is generated (step 212). Specifically, in various embodiments, auxiliary device data is obtained via the auxiliary device 112 throughout the duration of the trip. In various embodiments, the auxiliary device data of step 212 includes data regarding a number of parameters and events that are the same or similar to the mobile platform data of step 206; however, in various embodiments, certain parameters and / or events may be different for the auxiliary device data as compared to the mobile platform data. Furthermore, in various embodiments, certain parameters and / or events may be collected at different points in time for the auxiliary device data as compared to the mobile platform data, etc.

[0057] Additionally, in various embodiments, auxiliary device data is transmitted (step 214). In various embodiments, using Figure 1 The auxiliary device data of step 212 is transmitted from the auxiliary device 112 to the remote server 114 via one or more wireless communication networks 116 of the wireless communication network 116.

[0058] In various embodiments, each of the above steps 210, 212, and 214 is performed by the auxiliary device 112, and thus corresponds to the steps defined above and described in Figure 2 The second set of steps 202 is depicted in FIG.

[0059] In some embodiments, the remaining steps of the method described below (i.e., steps 216-242) are performed by the remote server 114 and thus correspond to Figure 2 The third set of steps 203 is depicted in FIG.

[0060] In various embodiments, the mobile platform data is stored (step 216). Specifically, in various embodiments, the mobile platform data of step 206 is stored in Figure 1 ’s memory 142 as its storage value 146.

[0061] In addition, in various embodiments, the auxiliary device data is stored (step 218). Specifically, in various embodiments, the auxiliary device data of step 212 is stored in Figure 1 ’s memory 142 as its storage value 146.

[0062] Additionally, in various embodiments, pre-filtering is applied (step 218). Specifically, in various embodiments, pre-filtering is applied to both the mobile platform data and the auxiliary device data in order to reduce the search space for correlating the mobile platform data with the auxiliary device data. For example, in various embodiments, this prevents every mobile platform trip data set from being compared to every device trip data set, but rather limits the comparison to corresponding data sets that are feasible or compatible with each other. In various embodiments, the pre-filtering is performed via a processor such as a processor. Figure 1 The processor 140 of the remote server 114) applies pre-filtering.

[0063] Additionally, in some embodiments, the pre-filtering of step 218 also combines a local geo-hashing space (step 220) and a temporal hashing of the start and end times (step 222). In some embodiments, the geo-hashing of step 220 and the temporal hashing of step 222 are performed before step 218 and then used as part of the pre-filtering. In some other embodiments, the geo-hashing and temporal hashing can be performed as part of step 218. In various embodiments, the geo-hashing and temporal hashing are processed by a processor such as a processor. Figure 1 The processor 140 of the remote server 114) is used for execution.

[0064] In various embodiments, after the pre-filtering of step 218, a mobile platform event sequence is generated (step 224). Specifically, in various embodiments, the mobile platform data as filtered during step 218 (and in some embodiments, also during steps 220 and 222) is utilized in generating the mobile platform event sequence based on the mobile platform data. In various embodiments, the mobile platform data is generated via a processor such as Figure 1 The processor 140 of the remote server 114 of the embodiment of the present invention generates a mobile platform event sequence. In addition, in some embodiments, the mobile platform event sequence is represented as follows: V = {A (t1), B (t2), C (t3), D (t4), E (t5)}, where "V" represents the mobile platform event sequence, "A" represents the first event detected at time "t1", "B" represents the second event detected at time "t2", "C" represents the third event detected at time "t3", "D" represents the fourth event detected at time "t4", "E" represents the fifth event detected at time "t5", and so on. It should be understood that this can be extended to any number of events detected at any number of different time points.

[0065] Additionally, as used herein, the term "event" refers to any number of mobile platform events, such as sudden braking, sudden acceleration, sudden turns, speed events (e.g., speed transitions), other speed and acceleration events, mobile platform contact events, and the like, such as with respect to both mobile platform event sequences (discussed above), auxiliary device event sequences (discussed below), and analysis and comparison thereof (e.g., as further described below).

[0066] Furthermore, in various embodiments, after the pre-filtering of step 218, an auxiliary device event sequence is generated (step 226). Specifically, in various embodiments, the auxiliary device data as filtered during step 218 (and in some embodiments, also during steps 220 and 222) is utilized in generating the auxiliary device event sequence based on the auxiliary device data. In various embodiments, the auxiliary device data is generated via a processor such as Figure 1 The processor 140 of the remote server 114 of the auxiliary device 112 generates an auxiliary device event sequence. In addition, in some embodiments, the auxiliary event sequence is represented as follows: P = {B (t2 + delta), D (t4 + delta), F (t5 + delta)}, where "P" represents the auxiliary event sequence, "B", "D" and "F" represent detected events, "t" values ​​represent time points, and "delta" values ​​represent the change in the corresponding event detection time of the auxiliary device 112 compared to the event detection of the mobile platform 110.

[0067] In various embodiments, the method utilizes the following assumptions: (i) mobile platform 110 does not necessarily detect every event detected by auxiliary device 112; (ii) auxiliary device 112 does not necessarily detect every event detected by mobile platform 110; (iii) mobile platform 110 and auxiliary device 112 are not necessarily synchronized in time; and (iv) each time point "t" (e.g., equal to one second in the exemplary embodiment) contains an event (i.e., "1") or does not contain an event (i.e., "0"). Therefore, in this exemplary embodiment, mobile platform 110 and auxiliary device 112 may detect common events (e.g., events "B" and "D"), but not at exactly the same time.

[0068] Reference Figure 3 , Figure 6 and Figure 7 , provides an exemplary illustration of the event space of steps 224 and 226 according to an exemplary embodiment. Specifically, according to various embodiments: (i) Figure 3 An exemplary auxiliary device sequence is depicted (corresponding to step 226); (ii) Figure 6 A first exemplary movement platform sequence of a first movement platform is depicted (corresponding to step 224); and (iii) Figure 7 A second exemplary movement platform sequence for a second movement platform is depicted (also corresponding to step 224 ).

[0069] first, Figure 3 3 depicts a diagram of an auxiliary device event sequence 300 according to an exemplary embodiment. Figure 3 As depicted, the graph includes an x-axis 302 corresponding to time (in seconds) and a y-axis 304 corresponding to an event indicator (e.g., equal to zero (0) for no event and equal to one (1) for an event). Figure 3 As shown, in the exemplary embodiment, five events are detected by auxiliary device 112 at different points in time, including events 306 (A), 306 (B), 306 (C), 306 (D), and 306 (E).

[0070] Next, Figure 6 6 is a diagram of a mobile platform event sequence 600 for the first mobile platform 110 according to an exemplary embodiment. Figure 6 As depicted, the graph includes an x-axis 602 corresponding to time (in seconds) and a y-axis 604 corresponding to an event indicator (e.g., equal to zero (0) for no event and equal to one (1) for an event). Figure 6 As shown, in the exemplary embodiment, five events are detected by first mobile platform 110 at different points in time, including events 606 (A), 606 (B), 606 (C), 606 (D), and 606 (E).

[0071] Figure 7 1 is a diagram of a mobile platform event sequence 700 for the first mobile platform 110 according to an exemplary embodiment. Figure 7 As depicted, the graph includes an x-axis 702 corresponding to time (in seconds) and a y-axis 704 corresponding to an event indicator (e.g., equal to zero (0) for no event and equal to one (1) for an event). Figure 7 As shown, in the exemplary embodiment, five events are detected by second mobile platform 110 at different points in time, including events 706 (A), 706 (B), 706 (C), 706 (D), and 706 (E).

[0072] Return to reference Figure 2 In various embodiments, filtering is performed (step 230). In various embodiments, filtering is performed on the mobile platform event sequence of step 224, the auxiliary device event sequence of step 226, or both. In various embodiments, filtering is performed by one or more processors (such as Figure 1 processor 140) to execute.

[0073] In certain embodiments, DSP (digital signal processing) convolution is applied to the auxiliary device event sequence as part of step 230 and / or as part of a separate pre-filtering step 228. In various embodiments, processor 140 applies DSP convolution to the auxiliary device event sequence to effectively "smear" the events in time.

[0074] Reference Figure 4 and Figure 5 , providing Figure 3 The second device event sequence 300 applies an exemplary implementation of DSP convolution. First, as Figure 4 As shown in diagram 400, for illustrative purposes, select Figure 3 One of the events (ie, event "306(E)") is selected as the event 406 to which DSP convolution is applied.

[0075] Next, refer to Figure 5 , a graphical representation 500 of the application of DSP convolution to the selected event 406 is provided. Specifically, the graphical representation 500 includes an x-axis 502 representing time (in seconds), but with a stretched focus on a particular time interval associated with the selected event 406. Figure 5 As depicted, the y-axis 504 corresponds to an event indicator, similar to the above with respect to Figure 3 Discussion. Figure 5 As shown, applying DSP convolution (and the stretched time focus on x-axis 502) widens event 406 for inspection and analysis purposes. In various embodiments, this is for Figure 3306 is performed for each of the detected events 306, thereby widening each event in time to allow "fuzzy" time comparison of the events.

[0076] Return to reference Figure 2 In various embodiments, signal correlation is performed (step 234). In various embodiments, signal correlation is provided between the auxiliary device event space and the mobile platform event space. In various embodiments, this is performed by one or more processors (such as Figure 1 processor 140) to execute.

[0077] In some embodiments, DSP cross-correlations are applied between various mobile platform event spaces and various auxiliary device event spaces (e.g., after performing the filtering of steps 228 and / or 230). In various embodiments, processor 140 performs DSP cross-correlations for each mobile platform event sequence relative to each auxiliary device event sequence. Further, in various embodiments, processor 140 provides pair-wise cross-correlations of auxiliary device event sequences and mobile platform event sequences. In some embodiments, DSP cross-correlations are performed as part of step 234; and in some embodiments, DSP cross-correlations may be performed as follows: Figure 2 Part of the individual step 232 shown.

[0078] Reference Figure 8 and Fig. 9 , provides an exemplary implementation of the signal correlation of step 234 (and cross-correlation including step 232) of an auxiliary device event sequence of an auxiliary device 112 with mobile platform event sequences of two different mobile platforms 110 according to an exemplary embodiment. Specifically: (i) Figure 8 Draw out Figure 3 The sequence of events for assistive devices (such as Figure 4 and Figure 5 Filtered) and Figure 6 an exemplary cross-correlation between a sequence of mobile platform events of a first mobile platform; and (ii) Fig. 9 Draw out Figure 3 The sequence of events for assistive devices (such as Figure 4 and Figure 5 Filtered) and Figure 7 FIG. 1 is an exemplary cross-correlation between a mobile platform event sequence of a second mobile platform.

[0079] First, in Figure 8 In the , the sequence of events for auxiliary devices is provided ( Figure 3-Figure 5 ) and the first mobile platform ( Figure 6 ) is a graphical representation 800 of the cross-correlation of Figure 8As depicted, cross-correlation graph 800 includes an x-axis 802 corresponding to a time lag between event identifications by the secondary device relative to the first mobile platform (eg, in seconds), and a y-axis 804 representing an autocorrelation function (ACF) for the cross-correlation. Figure 8 As shown, in this particular example, there are measurable and significant correlations between the various detected events 806(A), 806(B), 806(C), 806(D), 806(E), and 806(F), as well as various different time lags associated therewith (e.g., corresponding to the time difference between when the auxiliary device 112 detects the event and when the first mobile platform 110 detects the event). Figure 8 As depicted, in this exemplary embodiment, within a predetermined time lag threshold (e.g., plus or minus two seconds in the exemplary embodiment), the corresponding detected events are significantly correlated. Thus, in various embodiments, this will serve as an indication that the auxiliary device 112 has indeed been set within the first mobile platform 110.

[0080] Next, if Fig. 9 As shown, the auxiliary device event sequence ( Figure 3-Figure 5 ) and the second mobile platform ( Figure 7 ) is a graphical representation 900 of the cross-correlation of Fig. 9 As depicted, cross-correlation graph 900 similarly includes an x-axis 902 corresponding to a time lag between event identifications by the secondary device relative to the second mobile platform (e.g., in seconds), and a y-axis 904 represents an autocorrelation function (ACF) for the cross-correlation. Fig. 9 As shown, in this particular example, there is no significant correlation between the auxiliary device 112 and the various detected events of the second mobile platform 110. Therefore, in various embodiments, this will serve as an indication that the auxiliary device 112 has not been disposed within the second mobile platform 110.

[0081] Return to reference again Figure 2 In various embodiments, at step 235, it is determined whether there are one or more strong correlations between the signal correlations of step 234 (e.g., relative to the DSP cross-correlations of step 232). Specifically, in various embodiments, during step 235, a processor (such as Figure 1 The processor 140 of the embodiment of the present invention determines a relevant metric (such as the one described above with reference to FIG. 1 ) for each comparison between the corresponding auxiliary device event sequence and the mobile platform event sequence. Figure 8 and Fig. 9 Is the ACF mentioned above greater than a predetermined threshold (e.g., stored in Figure 1 in the memory 142 as its storage value 146).

[0082] In various embodiments, if it is determined in step 235 that there is no strong correlation for a particular comparison, then it is determined in step 236 that no association is established between the particular auxiliary device associated with the comparison and the particular mobile platform. Specifically, in this case, in various embodiments, it is determined that the auxiliary device currently being examined is unlikely to have been disposed inside the mobile platform currently being examined (e.g., similar to the above-described Fig. 9 In various embodiments, the determination is performed by a processor (such as Figure 1 In various embodiments, the method 200 then terminates at step 242.

[0083] In contrast, in various embodiments, if it is determined in step 235 that a strong correlation does exist for a particular comparison, an association is established between the particular auxiliary device associated with the comparison and the particular mobile platform (step 238). Specifically, in this case, in various embodiments, a probability distribution matrix is ​​created between the mobile platform and device data, and a determination is made that the auxiliary device currently being examined is likely to have been disposed within the mobile platform currently being examined (e.g., similar to the above-described Figure 8 In various embodiments, the association is performed by a processor such as Figure 1 The processor 140) is performed.

[0084] In various embodiments, one or more other actions may also be taken (step 240). For example, in some embodiments, the auxiliary device 112 may be linked to the mobile platform 110, such as for the purpose of collecting and analyzing future data, and / or for the purpose of providing future reports and / or information to the users of the auxiliary device 112 and the mobile platform 110, etc. In addition, in some embodiments, the mobile platform registration record may be updated accordingly. For example, in some embodiments, when a particular mobile platform 110 is now associated with a new (or different user's) auxiliary device 112, the mobile platform registration record may be updated accordingly to reflect the new user (or owner), and / or a query may be sent to the user of the auxiliary device 112 to confirm ownership of the mobile platform 110, etc. In some embodiments, the auxiliary device 112 may be linked to the mobile platform 110 based on a request received by a processor (such as Figure 1 This action may be taken in whole or in part by instructions provided by the processor 140).

[0085] In various embodiments, method 200 then terminates at step 242 .

[0086] Thus, in various embodiments, methods and systems are provided for correlating data obtained from a mobile platform (e.g., a vehicle and / or other mobile platform) with data obtained from an auxiliary device that may be disposed within the mobile platform and / or otherwise configured to detect mobile platform events, collect sensor data during mobile platform operation, or both. In various embodiments, separate event sequences are independently generated for different auxiliary devices and mobile platforms, and then correlated based on the data obtained from the auxiliary device. Figure 2 The steps of method 200 and the above Figures 3 to 9 In various embodiments, the correlation between the mobile platform and the auxiliary device (and their corresponding data and event sequences) is independent of and does not depend on any prior association, linking, or communication between the mobile platform and the auxiliary device. Rather, in various embodiments, the data correlation is based on the independent collection of data from the mobile platform and the auxiliary device and the subsequent analysis, inspection, and processing thereof.

[0087] In addition, similar to the description above, although in various embodiments, the correlation herein is between (a) mobile platform data from built-in sensors of mobile platform 110 and (b) auxiliary devices carried on the mobile platform, it should be understood that in certain other embodiments, the correlation may instead be between multiple auxiliary devices carried on mobile platform 110 (e.g., where "mobile platform data" may include data from additional auxiliary devices carried on mobile platform 110), and so on.

[0088] It should be understood that the systems, mobile platforms, methods, and implementations may differ from those depicted in the figures and described herein. For example, the system including the mobile platform 110, the auxiliary device 112, the remote server 114, and their components Figure 1 The system 100 can be used with Figure 1 is different from that described above. Similarly, it should be understood that Figure 2 The steps of method 200 and Figures 3 to 9 The implementation may be different from that depicted in the figures and described above, and / or the various steps may occur concurrently and / or in a different order than that depicted in the figures and described above.

[0089] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that there are a large number of variations. It should also be understood that the exemplary embodiment or multiple exemplary embodiments are only examples and are not intended to limit the scope, applicability or configuration of the present disclosure in any way. On the contrary, the foregoing detailed description will provide a convenient roadmap for implementing the exemplary embodiment or multiple exemplary embodiments for those skilled in the art. It should be understood that various changes can be made to the functions and arrangements of the elements without departing from the scope of the present disclosure as set forth in the attached claims and their legal equivalents.

Claims

1. A method comprising: obtaining mobile platform data, wherein the mobile platform data is related to the mobile platform; obtaining auxiliary device data originating from an auxiliary device that is at some time removably disposed within the mobile platform, wherein obtaining the auxiliary device data is independent of obtaining the mobile platform data; as well as The mobile platform data is correlated with the auxiliary device data via a processor.

2. The method according to claim 1, wherein: The mobile platform data originates from one or more sensors built into the mobile platform.

3. The method according to claim 1, wherein: The mobile platform data originates from one or more additional devices configured to detect mobile platform events, collect sensor data during operation of the mobile platform, or both.

4. The method according to claim 1, wherein: Correlating the mobile platform data with the secondary device data is performed via the processor without any prior association between the mobile platform and the secondary device.

5. The method according to claim 1, wherein: The step of correlating the mobile platform data with the auxiliary device data comprises: generating, via the processor, a mobile platform event space for the mobile platform data; generating, via the processor, an auxiliary device event space for the auxiliary device data; and A cross-correlation between the mobile platform event space and the auxiliary device event space is performed via the processor.

6. The method according to claim 5, further comprising: Prior to performing the cross-correlation, preliminary restrictions are applied, via the processor, to search spaces of the mobile platform event space and the auxiliary device event space.

7. The method of claim 5, wherein the step of performing the cross-correlation comprises: performing, via the processor, a DSP convolution on the auxiliary device event space to generate a filtered auxiliary device event space; as well as A DSP cross-correlation between the mobile platform event space and the filtered auxiliary device event space is performed via the processor.

8. The method according to claim 1, further comprising: A probability allocation matrix is ​​allocated, via the processor, between the mobile platform data and the secondary device data based on the cross-correlation.

9. A system comprising: A non-transitory computer-readable storage medium configured to store: Mobile platform data, the mobile platform data belonging to the mobile platform; as well as ancillary device data originating from an ancillary device removably disposed at certain times within the mobile platform, wherein the mobile platform data is obtained separately from the ancillary device data; as well as A processor is coupled to the non-transitory computer-readable storage medium and is configured to at least facilitate correlating the mobile platform data with the auxiliary device data.

10. The system according to claim 9, wherein: The mobile platform data originates from one or more sensors built into the mobile platform.

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