Systems and methods for generating contextually relevant device compensation

Abstract

Disclosed herein are systems and methods that can detect the use of a consumer electronics device and can generate and provide insurance or compensation plans that determine, consider, and adjust for the use of the consumer electronics device and consumer trends while using the consumer electronics device.

Description

[Technical Field]

[0001] The present invention relates generally to consumer electronic devices, and more particularly to systems and methods for detecting usage of consumer electronic devices. [Background technology]

[0002] Many consumer electronic devices are sold at price points that are considered expensive for the average consumer. As a result, the average consumer sometimes chooses to purchase indemnification or other insurance plans to cover the consumer's consumer electronic device and to reimburse the consumer for replacing or repairing the consumer electronic device when it is lost or damaged.

[0003] Many consumers commonly purchase insurance or protection plans, but known insurance or protection plans are traditionally based on the retail price of the consumer electronic device, the cost of replacing the consumer electronic device, or the cost of repairing the consumer electronic device. However, known insurance or protection plans do not take into account the usage of the consumer electronic device or consumer habits while using the consumer electronic device. Summary of the Invention [Problem to be solved by the invention]

[0004] In light of the above, there is a need for a system and method for creating and providing insurance or compensation plans that determine, consider, and adjust for consumer electronic device usage and consumer trends while using the consumer electronic device. [Brief explanation of the drawings]

[0005] [Figure 1] FIG. 1 is a block diagram of a system according to a disclosed embodiment. [Figure 2] 1 is a flow diagram of a method for detecting whether an electronic device has been dropped, according to a disclosed embodiment. [Figure 3] 1 is a graph plotting accelerometer measurements according to a disclosed embodiment. [Figure 4] 10 is a graph plotting device drop propensity according to disclosed embodiments. [Figure 5] 1 is a flow diagram of a method for adjusting risk, according to a disclosed embodiment. [Figure 6] 1 is a flow diagram of a method for adjusting a risk and generating an alert, according to a disclosed embodiment. [Figure 7] 1 is a graph plotting device depreciation according to disclosed embodiments. [Figure 8] 1 is a flow diagram of a method for accounting for device depreciation, according to a disclosed embodiment; [Figure 9] 1 is a flow diagram of a method for considering device durability, according to a disclosed embodiment. [Figure 10] 1 is a flow diagram of a method for generating a compensation plan based on device diagnostics, according to a disclosed embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0006] While the present invention is susceptible of embodiment in many different forms, specific embodiments of the invention are shown in the drawings and will be described in detail below, with the understanding that the present disclosure is to be considered as an exemplification of the principles of the invention, and it is not intended to limit the invention to the specific illustrated embodiments.

[0007] Embodiments disclosed herein include systems and methods that can detect the use of a consumer electronics device and can generate and provide insurance or protection plans that determine, consider, and adjust for the use of the consumer electronics device and consumer trends while using the consumer electronics device.

[0008] In some examples, the systems and methods disclosed herein can receive or retrieve data from a sensor included in a consumer electronics device, analyze the data, and determine whether the data indicates that the consumer electronics device has been dropped. For example, in some examples, the systems and methods disclosed herein can determine whether data from an accelerometer included in a consumer electronics device indicates that acceleration of the consumer electronics device is consistent with the consumer electronics device being dropped, such as data that not only exceeds a first threshold but also falls below a second threshold within a predetermined time period, or data that first falls below a second threshold, then exceeds the first threshold, and then falls below the second threshold within a predetermined time period. Additionally or alternatively, in some examples, the systems and methods disclosed herein can determine whether data from a gyroscope included in a consumer electronics device indicates that rotation and orientation of the consumer electronics device are consistent with the consumer electronics device being dropped and impacting a surface.

[0009] In some examples, the systems and methods disclosed herein can identify activities involving a consumer electronics device that pose a potential risk of damage to the consumer electronics device. For example, in some examples, the systems and methods disclosed herein can identify activities that pose a potential risk of damage to the consumer electronics device based on location data of the consumer electronics device, intended location data of the consumer electronics device, or an intended event to be engaged in by a user of the consumer electronics device.

[0010] In some examples, the systems and methods disclosed herein can monitor user interactions with a consumer electronics device, including user interactions or lack of user interactions with applications executed by the consumer electronics device, to determine potential danger to the consumer electronics device or other items covered by an insurance or compensation plan. In some examples, the systems and methods disclosed herein can send an audible or visual warning message to the user indicating a user interaction identified as presenting a potential danger.

[0011] In some examples, the systems and methods disclosed herein can identify a replacement cost percentage for a consumer electronics device based on the depreciated value of the consumer electronics device and generate and offer a discounted insurance or protection plan when the replacement cost percentage exceeds a predetermined threshold.

[0012] In some examples, the systems and methods disclosed herein can identify a durability index rating for a consumer electronics device and generate and offer discounted insurance or compensation plans when the durability index rating exceeds a predetermined threshold. In some examples, the systems and methods disclosed herein can identify a durability index rating based on extensive testing of various makes and models of consumer electronics devices.

[0013] In some examples, the systems and methods disclosed herein may perform diagnostic tests on a consumer electronics device to determine whether components of the consumer electronics device are non-functional or broken, and generate and offer a discounted insurance or compensation plan when a predetermined number of components are identified as non-functional. In some examples, the value of the discounted insurance or compensation plan may be based on which components are identified as non-functional and how frequently the non-functional components break based on historical policy claims data.

[0014] FIG. 1 is a block diagram of a system 100 according to disclosed embodiments, capable of implementing the methods disclosed herein. As can be seen, the system 100 may include a consumer electronics device 3 that may be operated by a user 1 and that may execute a software application 2. In some embodiments, the software application 2 may communicate with one or more sensors 4 included within the consumer electronics device 3 and receive or retrieve data from the one or more sensors 4. In some embodiments, the consumer electronics device 3 may include a smartphone, a tablet, or a laptop computer. When the consumer electronics device 3 is a smartphone, the consumer electronics device may include up to eight of the sensors 4, including one or more of a touchscreen, an accelerometer, a gyroscope, a magnetometer, a Global Positioning System (GPS), a barometer, an ambient light sensor, a proximity sensor, and a fingerprint sensor. Additionally or alternatively, in some embodiments, the sensor 4 may include one or more cameras that may collect data when the software 2 includes video analytics software.

[0015] In some embodiments, the software application 2 may be stored and executed on the consumer electronics device 3. Alternatively, in some embodiments, the software application 2 may be web-based and may retrieve data from the sensor 4 when the consumer electronics device 3 navigates to a website Universal Resource Locator (URL) associated with the software application 2 or at periodic intervals identified by the software application 2.

[0016] In some embodiments, software application 2 may generate a user risk profile 5 based on data received from sensors 4 and store user risk profile 5 in a database device. For example, in some embodiments, software application 2 may use data from sensors 4 to determine whether consumer electronics device 3 has been dropped by user 1 a predetermined number of times indicative of a tendency to drop consumer electronics device 3. In response, software application 2 may generate user risk profile 5 to indicate that user 1 has a tendency to drop consumer electronics device 3 and is therefore associated with a predetermined level of risk that should be compensated for.

[0017] In some embodiments, the software application 2 and the consumer electronics device 3 may transmit the user risk profile 5 to the compensation and insurance offering system 7 via a network connection, such as Long Term Evolution (LTE), 4G, WiFi, or other internet-based connection, and in some embodiments, the compensation and insurance offering system 7 may include a cloud-based server that may be accessible at a predetermined URL. In some embodiments, the compensation and insurance offering system 7 may also receive or retrieve input data 6 from other sources. For example, the input data 6 may include identification of locations that present an increased risk to the safety of the consumer electronics device 3, identification of times and dates of events that present an increased risk to the safety of the consumer electronics device 3, identification of user 1's past interactions with another device, or identification of other factors that may affect the risk associated with user 1's ownership and use of the consumer electronics device 3.

[0018] Based on the user risk profile 5 and the input data 6, the coverage and insurance offering system 7 may generate a risk-based policy offering 8 customized for the user and the consumer electronic device 3. For example, in some embodiments, the risk-based policy offering 8 may include a custom price for covering the consumer electronic device 3 for the user 1, and in some embodiments, the risk-based policy offering 8 may include the terms and scope of coverage for an insurance or coverage plan associated with the user 1 and the consumer electronic device 3. In some embodiments, the risk-based policy offering 8 may include a provision in the terms of service associated with the risk-based policy offering 8 requiring that the software application 2 be installed on the consumer electronic device 2 at all times during the life of the risk-based policy offering 8 and that removing the software application 2 from the consumer electronic device 3 voids the insurance coverage associated with the risk-based policy offering 8.

[0019] As disclosed herein, a common constant risk to the consumer electronic device 3 is that the user 1 drops the consumer electronic device 3, thereby damaging the consumer electronic device 3. For example, if the user 1 drops the consumer electronic device 3 from a sufficient height and in a particular manner, the screen of the consumer electronic device 3 may shatter. Therefore, an important factor measured by the software application 2 and included in the user risk profile 5 is when and how often the user 1 drops the consumer electronic device 3.

[0020] In this regard, software application 2 may identify a trauma event whenever consumer electronics device 3 is dropped from a height that results in a high impact, and software application 2 may use the trauma event to create a user risk profile 5. In some examples, software application 2 may communicate with user 1, such as by generating a notification message (e.g., an email notification, a push notification) that includes one or more suggested proactive actions to prevent future falls. For example, the one or more suggested proactive actions may include user 1 purchasing an impact-absorbing case for consumer electronics device 3, a screen protector for the consumer electronics device, or gripping strips that increase the amount of friction against the housing of consumer electronics device 3 while held by user 1. In some examples, the notification message may include one or more reasons for the suggested proactive action, such as data suggesting that user 1 drops consumer electronics device 3 more often than average.

[0021] As disclosed herein, software application 2 may identify when consumer electronics device 3 has been dropped. For example, in some embodiments, software application 2 may monitor data from sensors 4, such as an accelerometer, to determine if consumer electronics device 3 has been dropped. In some embodiments, software application 2 may identify the impact level of dropped consumer electronics device 3 to distinguish between a damaging drop when consumer electronics device 3 hits a hard surface (e.g., a cement floor) and a harmless drop when consumer electronics device 3 hits a soft surface (e.g., a couch). In some embodiments, software application 2 may verify the impact level using data collected from sensors 4, such as an accelerometer or gyroscope.

[0022] 2 is a flow diagram of a method 200 for detecting whether a consumer electronics device 3 has been dropped, according to a disclosed embodiment. As can be seen, method 200 may include initiating a background service, similar to 3-1. For example, the background service may be initiated by installing a software application 2 on consumer electronics device 3 to continuously monitor data from sensors 4 to detect conditions indicative of a drop. In some embodiments, the background service may be unnoticed by user 1 during regular use of consumer electronics device 3.

[0023] Method 200 may also include setting lower and upper thresholds and time intervals, similar to 3-2. In some embodiments, the lower and upper thresholds and time intervals may be predetermined, and in some embodiments, the upper threshold may be greater than the lower threshold. For example, the upper threshold may be set to a height and corresponding acceleration value from which the consumer electronics device 3 must be dropped to qualify as a damaging drop. Additionally or alternatively, in some embodiments, the lower and upper thresholds may be based on the type of consumer electronics device 3 on which software application 2 is installed. For example, an iPhone 8 Plus may be heavier than an iPhone 8, and therefore, when dropped, the force of impact on the iPhone 8 Plus may be higher than that on an iPhone 8. Thus, software application 2 installed on an iPhone 8 Plus may set a higher upper threshold than software application 2 installed on an iPhone 8 sets the upper threshold. Additionally or alternatively, in some embodiments, the upper and lower thresholds may be identified from data from sensors 4, including acceleration values ​​measured by an accelerometer, angular velocity values ​​measured by a gyroscope, and / or orientation values ​​measured by a gyroscope and magnetometer. In any embodiment, the lower and upper thresholds may be set at values ​​that facilitate identifying falls that follow the same general patterns described herein.

[0024] Method 200 may also include software application 2 determining whether data from the accelerometer indicates a fall, i.e., whether the data indicates that the acceleration of consumer electronics device 3 exceeded an upper threshold and then fell below a lower threshold within a time interval, or, similar to 3-3, whether the data indicates that the acceleration of consumer electronics device 3 first fell below a lower threshold, then exceeded the upper threshold, and then fell below the lower threshold. In some embodiments, the accelerometer may include a tri-axis accelerometer with three axes (x-axis, y-axis, and z-axis) to measure data in three directions, and data from the accelerometer may be measured in meters per second per second. When the accelerometer is a tri-axis accelerometer, software application 2 may calculate a geometric mean of the data related to the three axes, i.e., |A T |=sqrt(a x 2 , a y 2 , a z 2 If the condition of 3-3 is not met, the software application 2 may repeat 3-3. However, if the condition of 3-3 is met, the method 200 may continue with 3-4.

[0025] According to method 200, FIG. 3 is a graph 300 plotting accelerometer measurements according to a disclosed embodiment, identifying an upper threshold 302, a lower threshold 304, and data indicative of a fall 306. As known by those skilled in the art, data from an accelerometer is subjected to gravity (e.g., 9.81 m / s 2). Thus, when the consumer electronics device 3 is resting on a surface, the data from the accelerometer may be 9.81. However, when the consumer electronics device is falling downward, the data from the accelerometer may be 0. In this regard, as seen in FIG. 3 , during a fall, the data from the accelerometer may first fall below the lower threshold 304 (e.g., during free fall, accelerometer data=0), then exceed the upper threshold 302 (e.g., upon impacting and bouncing off the surface, accelerometer data=36), and then fall below the lower threshold 304 within a time interval (e.g., 20 ms) (e.g., after bouncing off the surface, during free fall, accelerometer data=0).

[0026] In some examples, when the data from the accelerometer, after initially falling below the lower threshold 304, subsequently rises above an intermediate threshold below the upper threshold 302, the method 200 can determine that the consumer electronics device 3 was dropped onto a soft surface and therefore the drop was harmless.

[0027] Method 200 may also include software application 2 determining whether the drop ended in an impact that exceeds an impact threshold, similar to 3-4. For example, in some embodiments, method 200 may identify the impact level of a dropped consumer electronics device 3 to distinguish between a damaging drop when consumer electronics device 3 impacts a hard surface and a harmless drop when consumer electronics device 3 impacts a soft surface. In this regard, in some embodiments, method 200 may determine the impact level of a dropped consumer electronics device 3 in terms of azimuth (angles about the x-axis), pitch (angles about the y-axis), and roll (angles about the z-axis) directions ( θ X, θ Y, θA fall can be verified using data from sensors 4, such as data from a gyroscope indicating the rotation and / or orientation of consumer electronics device 3 in degrees per second (Z). In some embodiments, after data from the accelerometer exceeds an upper threshold, software application 2 can calculate the geometric mean of the rotation of consumer electronics device 3 in degrees per second as follows: ω T=sqrt( ω x 2 , ω y 2 , ω z 2 ). Software application 2 can then determine that the drop was a damaging drop when the geometric mean of the rotation and orientation exceeds an impact threshold. In some embodiments, the impact threshold can be set based on the rotation and orientation values ​​of consumer electronics device 3 that impact a hard surface during a drop and / or that result in damage during a drop, and such values ​​can be identified through modeling and testing of the consumer electronics device.

[0028] If method 200 determines that the drop was a damaging drop, method 200 may continue as in 3-5. However, if method 200 does not determine that the drop was a damaging drop, method 200 may continue as in 3-3, and software application 2 may determine that the drop was a harmless drop.

[0029] Finally, method 200 may include software application 2 registering the fall on a cloud server, such as compensation and insurance offering system 7, similar to 3-5. In some embodiments, registering the fall may include software application 2 updating a risk profile 5 for user 1 and consumer electronics device 3. In this regard, FIG. 4 is a graph 400 plotting a propensity to drop a device, identifying four falls over a time period, according to a disclosed embodiment.

[0030] In some embodiments, software application 2 may set a thrown threshold value that may be lower than the lower threshold value. In these embodiments, when data from the accelerometer falls below the thrown threshold value, software application 2 may determine that consumer electronics device 3 has been thrown, an event that may not be covered by risk-based policy offering 8. Additionally or alternatively, software application 2 may determine that consumer electronics device 3 has been thrown upward when data from the accelerometer increases before first falling below the lower threshold value.

[0031] When the software application 2 determines that the user 1 has a tendency to drop the consumer electronic device 3 (e.g., the number of drops within a time period exceeds a predetermined threshold), the compensation and insurance offering system 7 may generate a notification message to the consumer electronic device 3 that includes an offer to the user 1 to purchase a case or screen protector, and may be accompanied by data indicating that the user 1 has a tendency to drop the consumer electronic device 3. Additionally, the compensation and insurance offering system 7 may increase the price of the peril-based policy offering 8 in response to determining that the user 1 has a tendency to drop the consumer electronic device 3 and notify the user 1 as such.

[0032] FIG. 5 is a flow diagram of a method 500 for adjusting risk according to a disclosed embodiment, for example, by generating a risk profile for user 1 based on user events and user activities that may affect the risk involved in insuring or compensating for consumer electronics device 3.

[0033] As can be seen, method 500 may include initiating an event detection process, similar to 4-1. In some embodiments, the event detection process may include a background service operating in conjunction with the background service described with respect to FIG. 2. After initiating the event detection process, method 500 may include software application 2 or compensation and insurance offering system 7 identifying user events and user activities, similar to 4-2, to determine whether any of the user events and user activities match any of the identified risk scenarios, similar to 4-4, and retrieving the identified risk scenarios from the event monitoring database, similar to 4-3. If a match is not identified, similar to 4-4, method 500 may include software application 2 continuing to monitor for user events and user activities, similar to 4-2, and retrieving the identified risk scenarios, similar to 4-3. However, when method 500 identifies a match between one of the user events and user activities and one of the identified hazardous scenarios, method 500 may include software application 2 registering the identified one of the user events and user activities, as in 4-3, on a cloud server, as in 4-5.

[0034] By way of illustration, one of the identified risk scenarios may include user 1 attending a concert, sporting event, street festival, or political march that poses a high risk for consumer electronics device 3 because user 1 may capture video or photographs while holding consumer electronics device 3 at a high height, or because large crowds associated with such high-risk events increase the likelihood that consumer electronics device 3 will be stolen. Software application 2 may retrieve the identified risk scenario (e.g., concert attendance) and monitor user 1's activities through consumer electronics device 3 to determine whether user 1 has purchased or is purchasing concert tickets, for example, by monitoring user 1's internet browsing and determining that consumer electronics device 3 has received an email confirming a ticket purchase or by monitoring user 1's text messages. In response to detecting that user 1 has purchased a concert ticket, for example, software application 2 may identify a match with the identified risk scenario and may register the user's purchase of a concert ticket with the cloud server, similar to steps 4-5.

[0035] As another example, one of the identified risk scenarios may include user 1 traveling internationally or to another high-risk location. Software application 2 may retrieve the identified risk scenario (e.g., international travel) and monitor user 1's activities to determine whether user 1 has purchased a ticket to, booked lodging in, or is physically present in an international location, a specific country particularly associated with risk, or a dangerous or unsafe geographic location, for example, by monitoring destination addresses entered by user 1 into navigation software (e.g., Waze, Google Maps) or by monitoring the GPS coordinates of consumer electronics device 3 relative to the GPS coordinates of the international location, the specific country particularly associated with risk (e.g., a developing country), or the dangerous or unsafe geographic location (e.g., a high-crime neighborhood). In response to detecting that user 1 has purchased a ticket to an international location, software application 2 may identify a match with the identified risk scenario and register with the cloud server that user 1 has purchased a ticket to the international location, similar to steps 4-5.

[0036] In some embodiments, when software application 2 determines that one of the user events and user activities matches one of the identified hazard scenarios, compensation and insurance offering system 7 may generate a notification message to consumer electronics device 3 including an offer to user 1 to purchase additional compensation or insurance any time before the user attends or travels through one of the identified hazard scenarios to provide enhanced compensation or increased insurance for any or all portions of the user attending or traveling through one of the identified hazard scenarios.

[0037] 5, FIG. 6 is a flow diagram of a method 600 for adjusting risk and generating alerts, for example, by monitoring user activity of user 1 within other applications executed by consumer electronics device 3, according to a disclosed embodiment. In doing so, method 200 can identify risky behavior of user 1 through consumer electronics device 3 and offer insurance or compensation plans not only for consumer electronics device 3 but also through compensation and insurance offering system 7. For example, compensation and insurance offering system 7 can offer insurance or compensation for data stored on consumer electronics device 3, fixed electronic devices in user 1's home, or the actions of user 1.

[0038] As can be seen, method 600 can include initiating an activity monitoring process, similar to 10-1. In some embodiments, the activity monitoring process can include a background service operating in conjunction with the background service described with reference to FIG. 2 or the event detection process described with reference to FIG. 5. After initiating the activity monitoring process, method 600 can include software application 2 identifying applications and actions suitable for insurance from a database, similar to 10-2, to determine whether any of the user events and user activities match any of the applications and actions suitable for insurance, similar to 10-3, and identifying user events and user activities, similar to 4-2. Method 600 can determine user activity by monitoring a user interface or touchscreen of consumer electronics device 3. If none of the user events and user activities identified, similar to 4-2, match the applications and actions identified, similar to 10-2, method 600 can include software application 2 continuing to monitor for user events and user activities, similar to 4-2. However, if one of the user events and user activities identified as in 4-2 matches one of the applications and actions identified as in 10-2, method 600 may include software application 2 registering one of the user events and user activities identified as in 4-3 with a cloud server, as in 4-5.

[0039] Finally, method 600 may include, as in 10-5, determining whether one of the user events and user activities identified as in 4-2 requires a notification message to alert User 1. If so, as in 10-6, a notification message may be generated and audibly or visually presented to User 1.

[0040] As an illustrative example, one of the applications and actions identified as 10-2 may include an application that controls User 1's home security system. When Software Application 2 determines through GPS data that User 1 is away from home, Software Application 2 may determine whether User 1 has equipped the home security system via the application that controls the home security system. When User 1 has not equipped the home security system via the application that controls the home security system, Software Application 2 may generate a notification message to remind User 1 to equip the home security system via the application that controls the home security system. Failure to consistently equip the home security system or to respond to reminders to do so may increase costs under Risk-Based Policy Offering 8.

[0041] As another example, one of the applications and actions similarly identified as 10-2 may include an application for backing up data stored on the home electronic device 3. The software application 2 may monitor that the user 1 backs up the home electronic device 3 via the application for backing up data stored on the home electronic device 3, and if the user does not back up within a predetermined time period, the software application 2 may provide a service for backing up the data stored on the home electronic device 3 via the risk-based policy offering 8 and / or automatically back up the home electronic device 3.

[0042] Generally, the cost of repairing or replacing a consumer electronics device 3 drops sharply over time. For example, FIG. 7 is a graph plotting device depreciation for an iPhone 6s mobile device, an iPhone X mobile device, and a Samsung Galaxy S6 mobile device. As shown in FIG. 7, 70-80% of the device's value is lost after one year. Therefore, the systems and methods disclosed herein can provide discounted insurance plans based on device depreciation.

[0043] 8 is a flow diagram of a method 800 for taking device depreciation into account, according to a disclosed embodiment, for example, by basing the price of an insurance offering on the depreciated value. For example, a consumer electronics device 3 may depreciate in value from its release date, regardless of when the consumer electronics device 3 was purchased, because newer versions are constantly being developed. In this regard, the iPhone 8 was released in October 2017 at a release price of $750 and continued to be sold at that price for an extended period of time. That said, the value of the iPhone 8 depreciates by approximately 1% per week, with a lower limit determined by market demand.

[0044] 8, method 800 may include determining the make and model of the consumer electronics device, at 801, and identifying a replacement cost percentage for the consumer electronics device 3, at 802. In some embodiments, the replacement cost percentage may be identified as follows:

number

[0045] Method 800 may then include comparing the replacement cost percentage to a threshold, similar to 804. When the replacement cost percentage is above the threshold, method 800 may include extending a discounted insurance offering to User 1, similar to 806. For example, if the smartphone was purchased for $1,000 (e.g., release price) on January 1, 2018 and valued at $300 (e.g., ASP) on December 1, 2019, the replacement cost percentage may be 70%, and method 800 may provide a discounted insurance offering at a 50% discount.

[0046] Certain technologies for consumer electronic devices can increase the durability of consumer electronic devices 3. For example, some smartphones can include organic light emitting diode (OLED) displays. In addition to higher display quality, OLED displays can have higher durability and a lower tendency to crack and scratch. In fact, tests have shown that an iPhone 7 with an OLED screen breaks only 6% of the time when dropped from a distance of 10 feet, while an iPhone 6 with an LCD screen breaks 74% of the time when dropped from the same distance, and that the iPhone 7 has a reduced likelihood of damage to the rear glass, rear camera, front camera, and loudspeaker compared to the iPhone 6. Therefore, the systems and methods disclosed herein can offer discounted insurance plans based on device durability.

[0047] FIG. 9 is a flow diagram of a method 900 for taking device durability into account, according to disclosed embodiments, for example, by basing pricing of insurance offerings on device durability. As can be seen, method 900 may include initiating a risk assessment process, similar to 6-1. In some embodiments, the risk assessment process may include a background service operating in conjunction with the background service described with reference to FIG. 2, the event detection process described with reference to FIG. 5, or the activity monitoring process 10-1 described with reference to FIG. 7. After initiating the risk assessment process, method 900 may include determining the make and model of consumer electronic device 3, similar to 6-2, by referencing, for example, data stored on consumer electronic device 3, a profile of user 1 stored by compensation and insurance offering system 7, or TCP / IP packets sent over the Internet. Method 900 may then include retrieving a device durability index rating associated with the make and model from a device durability index database, similar to 6-3, and determining whether the device durability index rating exceeds a predetermined threshold, similar to 6-4. Similar to 6-4, when the device durability index rating is above a predetermined threshold, the method 900 may include the compensation and insurance offering system 7 offering a discounted rate.

[0048] In some examples, the systems and methods disclosed herein may also include creating and populating a device durability index database with a respective device durability index rating for each of the plurality of makes and each of the plurality of models based on meaningful diagnostic tests of the plurality of makes and models and aggregated data thereof. Additionally or alternatively, the systems and methods disclosed herein may distinguish the respective device durability ratings for each of the plurality of makes and each of the plurality of models from respective part durability ratings for each of the plurality of parts forming the respective devices.

[0049] In some situations, the consumer electronics device 3 may break, but the user 1 may want to cover the remaining functional components of the consumer electronics device 3. Figure 10 is a flow diagram of a method 1000 for generating a compensation plan based on device diagnostics according to disclosed embodiments, for example, by generating a dedicated insurance plan based on the results of a diagnostic test.

[0050] As can be seen, method 1000 may include software application 2 running a diagnostic test (similar to 9-2) and determining, based on the results of the diagnostic test, whether all components of consumer electronics device 3 are functional (similar to 9-3). When the diagnostic test indicates that all components of consumer electronics device 3 are fully functional, method 1000 may include software application 2 generating a report indicating so, and coverage and insurance offering system 7 may offer a standard rate insurance plan (similar to 9-4). However, when the diagnostic test indicates that one or more components of consumer electronics device 3 are not functional, software application 2 may create a report identifying an exclusion list (similar to 9-5) that includes components of consumer electronics device 3 that failed the diagnostic test. Method 1000 may then include software application 2 using the exclusion list to reference a coverage offering database (similar to 5-3) and transmitting the exclusion list to coverage and insurance offering system 7, which may offer a dedicated offer with a disclaimer (similar to 9-6).

[0051] For example, if a diagnostic test reveals that the front camera of consumer electronics device 3 is not functioning, compensation and insurance offering system 7 may offer an insurance plan that excludes coverage for the front camera and is discounted accordingly. In some embodiments, the amount of the discount may be based on the percentage of insurance claims that claim damage to such a non-functioning component (e.g., the front camera). For example, if a relatively small number of insurance claims claim damage to the front camera (e.g., 10%), the price of the insurance plan may be discounted a relatively small amount (e.g., 5%). Alternatively, if the screen of consumer electronics device 3 is cracked and therefore a non-functioning component, and a relatively high number of insurance claims claim screen damage (e.g., 75%), the discount may be higher (e.g., 45%).

[0052] In some embodiments, the discount may be based on the relative value of the non-functioning component to the overall value of the consumer electronics device 3. Additionally or alternatively, in some embodiments, the discount may be based on the price of repairing the non-functioning component. For example, if the price of repairing the non-functioning component is higher than the price of repairing the functioning component of the consumer electronics device 3, the discount may be higher than if the price of repairing the non-functioning component was lower than the price of repairing the functioning component.

[0053] The systems and methods disclosed herein represent a substantial advancement over the prior art by identifying a price to insure a consumer electronics device based on data from sensors on the consumer electronics device itself. Furthermore, the systems and methods disclosed herein improve upon the prior art by constantly monitoring and detecting risk-causing events and data regarding the operation of the consumer electronics device, the health of the consumer electronics device, and the overall condition of the consumer electronics device via a software application that executes and operates in the background of the consumer electronics device without interrupting other functions or applications performed by the consumer electronics device. Finally, the systems and methods disclosed herein are an improvement over the prior art because they interact with sensors on the consumer electronics device itself, thereby facilitating the consumer electronics device to periodically monitor its own health to protect itself from damage.

[0054] Although several embodiments have been described in detail above, other modifications are possible. For example, the logic flow described above does not require the particular order or sequential order described to achieve desirable results. Other steps may be provided, steps may be eliminated from the described flow, and other components may be added to or deleted from the described system. Other embodiments may be within the scope of the present invention.

[0055] From the foregoing, it will be appreciated that numerous variations and modifications may be made without departing from the spirit and scope of the present invention. It is to be understood that no limitations with respect to the specific systems or methods described herein are intended or should be inferred. It is, of course, intended to cover all such modifications that come within the spirit and scope of the present invention.

Claims

1. A software-implemented method executed by a software application stored on a consumer electronics device or that is web-based, comprising: receiving first data from a first sensor of the consumer electronics device, the first data including accelerometer data; Detecting that the first data indicates a fall event, the fall event being defined as the first data exceeding a first threshold and then falling below a second threshold within a first time period; storing the first data indicative of the fall event in a memory device if the first data indicates that the fall event has been detected; monitoring the stored first data to detect a number of the fall events from the stored first data; detecting that the number of fall events within a time period exceeds a trend threshold; A software-implemented method comprising:

2. The software-implemented method of claim 1 , wherein the first sensor is an accelerometer.

3. receiving second data from a second sensor of the consumer electronics device, the second data including an angular velocity value; Detecting that the second data exceeds a third threshold; storing the second data in the memory device as if the consumer electronic device had been dropped and subsequently struck a hard surface; The software-implemented method of claim 1 further comprising:

4. The software-implemented method of claim 3 , wherein the second sensor is a gyroscope.

5. A step of generating a notification message, the notification message being an email notification or a push notification, the notification message including a text suggestion for a user to purchase accessories for the home electronic device to prevent (i) a future drop of the home electronic device, or (ii) damage to the home electronic device caused by a future drop; displaying the notification message on a display of the consumer electronic device; The software-implemented method of claim 1 further comprising:

6. 10. The software-implemented method of claim 1, further comprising updating, in a database device, a risk profile for a user of the consumer electronics device if the first data indicates that the fall event has been detected.

7. detecting that the risk profile for the user indicates that the number of fall events exceeds the trend threshold; increasing the cost of insurance premiums from a standard rate, the premiums being the cost the user pays to insure the consumer electronic device; The software-implemented method of claim 6 further comprising:

8. 1. A consumer electronic device comprising: a memory device; a first sensor that generates first data; detecting that the first data indicates a fall event defined as the first data exceeding a first threshold and then falling below a second threshold within a first time period; storing first data indicative of the fall event in a memory device if the first data indicates that the fall event has been detected; monitoring the stored first data to detect a number of the fall events from the stored first data; Detecting when the number of said fall events within a time period exceeds a trend threshold. at least one processor executing a software application configured to:

1. A consumer electronics device comprising:

9. A software-implemented method executed by a software application stored on a consumer electronics device or that is web-based, comprising: receiving first data from a sensor of the consumer electronics device, the first data including accelerometer data; detecting that the first data indicates a fall event, the fall event being defined as the first data rising above a first threshold and then falling below a second threshold within a period of time; storing the first data indicative of the fall event in a memory device if the first data indicates that the fall event has been detected; monitoring the stored first data to detect a number of the fall events from the stored first data; updating a risk profile for the user of the consumer electronic device with the number of fall events from the stored first data; detecting whether the user has a tendency to drop the consumer electronic device based on the risk profile; increasing the cost of insurance premiums from a standard rate if it is detected that the user has the tendency to drop the consumer electronic device, the premium being a cost paid by the user to insure the consumer electronic device; A software-implemented method comprising:

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