System and method for generating contextually relevant device protection

Abstract

To provide methods that can detect use of a consumer electronics device and that can generate and offer insurance or protection plans that measure, account, and adjust for the use of the consumer electronics device and consumer tendencies while using the consumer electronics device.SOLUTION: A method includes the steps of: receiving first data from a first sensor of a consumer electronics device; and determining whether the first data indicates a risk to the consumer electronics device or relates to the risk and stores, in response the determination, first information indicating that the consumer electronics device has been exposed to risk.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates generally to consumer electronic devices, and more particularly to a system and method for detecting usage of a consumer electronic device. [Background technology]

[0002] Many consumer electronic devices are sold at price points that are considered expensive to 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's consumer electronic device when the consumer electronic device is lost or damaged.

[0003] Many consumers commonly purchase insurance or compensation plans, but known insurance or compensation 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 compensation plans do not take into account the usage of the consumer electronic device or the consumer's habits while using the consumer electronic device. Summary of the Invention [Problem to be solved by the invention]

[0004] In view of the above, there is a need for a system and method for creating and providing insurance or compensation plans that determine, take into account, and adjust for the use of consumer electronic devices and consumer trends while using the consumer electronic devices. [Brief description of the drawings]

[0005] [Figure 1] FIG. 1 is a block diagram of a system according to a disclosed embodiment. [Diagram 2] 1 is a flow diagram of a method for detecting whether an electronic device has been dropped, according to a disclosed embodiment. [Diagram 3] 1 is a graph plotting accelerometer measurements according to disclosed embodiments. [Figure 4] 1 is a graph plotting device drop propensity according to disclosed embodiments. [Diagram 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 PREFERRED EMBODIMENTS

[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 usage of a consumer electronics device and can generate and provide insurance or compensation plans that determine, take into account, and adjust for usage 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 the 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 the consumer electronics device indicates that the acceleration of the consumer electronics device is consistent with the consumer electronics device being dropped, such as data that is above a first threshold but also below a second threshold within a predetermined time period, or data that is first below a second threshold and then above the first threshold and then 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 the consumer electronics device indicates that the rotation and orientation of the consumer electronics device is consistent with the consumer electronics device being dropped and impacting a surface with force.

[0009] In some examples, the systems and methods disclosed herein can identify activities involving a consumer electronics device that present 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 present 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 a 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 can perform diagnostic tests on a consumer electronics device to determine if 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 can 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 that can implement the methods disclosed herein. As can be seen, the system 100 can include a consumer electronics device 3 that can be operated by a user 1 and can execute a software application 2. In some embodiments, the software application 2 can 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 can include a smartphone, a tablet, or a laptop computer. When the consumer electronics device 3 is a smartphone, the consumer electronics device can include up to eight of the sensors 4, including one or more of a touch screen, 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 can include one or more cameras that can 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, the software application 2 may generate a user risk profile 5 based on the data received from the sensor 4 and store the user risk profile 5 in a database device. For example, in some embodiments, the software application 2 may use the data from the sensor 4 to determine whether the household electronic device 3 has been dropped by the user 1 a predetermined number of times indicative of a tendency to drop the household electronic device 3. In response, the software application 2 may generate a user risk profile 5 to indicate that the user 1 has a tendency to drop the household electronic device 3 and is therefore associated with a predetermined level of risk to 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 over 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 predefined 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 past interactions of the user 1 with another device, or identification of other factors that may affect the risk associated with the user 1 owning and using 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 can 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 can include a custom price for insuring the consumer electronic device 3 for the user 1, and in some embodiments, the risk based policy offering 8 can include terms and coverage for an insurance or protection plan associated with the user 1 and the consumer electronic device 3. In some embodiments, the risk based policy offering 8 can include a provision in the terms of service associated with the risk based policy offering 8 that requires 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 certain 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 certain manner, the screen of the consumer electronic device 3 may shatter. Thus, 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, the software application 2 may identify a trauma event whenever the consumer electronics device 3 is dropped from a height that would result in a strong impact, and the software application 2 may use the trauma event to create a user risk profile 5. In some examples, the software application 2 may communicate with the 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 the user 1 purchasing an impact absorbing case for the 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 the consumer electronics device 3 while being held by the user 1. In some examples, the notification message may include one or more reasons for the suggested proactive action, such as data suggesting that the user 1 drops the consumer electronics device 3 more than average.

[0021] As disclosed herein, the software application 2 can identify when the consumer electronics device 3 has been dropped. For example, in some embodiments, the software application 2 can monitor data from a sensor 4, such as an accelerometer, to determine if the consumer electronics device 3 has been dropped. In some embodiments, the software application 2 can identify the impact level of the dropped consumer electronics device 3 to distinguish between a damaging fall when the consumer electronics device 3 hits a hard surface (e.g., a cement floor) and a harmless fall when the consumer electronics device 3 hits a soft surface (e.g., a couch). In some embodiments, the software application 2 can verify the impact level using data collected from a sensor 4, such as an accelerometer or a 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, the method 200 can include initiating a background service, similar to 3-1. For example, the background service can be initiated by installing a software application 2 on the consumer electronics device 3 to continuously monitor data from a sensor 4 to detect conditions indicative of a drop. In some embodiments, the background service can be unnoticed by a user 1 during regular use of the 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 that the consumer electronics device 3 must be dropped to 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 the 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 the impact on the iPhone 8 Plus may be higher than an iPhone 8. Thus, a software application 2 installed on an iPhone 8 Plus may set an upper threshold higher than a software application 2 installed on an iPhone 8 sets an 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] The method 200 may also include the software application 2 determining whether the data from the accelerometer is indicative of a fall, i.e., whether the data indicates that the acceleration of the 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 the 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 three-axis accelerometer with three axes (x-axis, y-axis, and z-axis) to measure data in three directions, and the data from the accelerometer may be measured in meters per second per second. When the accelerometer is a three-axis accelerometer, the software application 2 may calculate a geometric mean of the data associated with the three axes as follows, i.e., |A T |=sqrt(a x 2 , a y 2 , a z 2 When the condition of 3-3 is not met, the software application 2 may repeat 3-3. However, when the condition of 3-3 is met, the method 200 may continue to 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 correlated with 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 impact with the surface 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, then 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 that the drop was harmless.

[0027] Method 200 may also include software application 2 determining whether the drop ended in an impact above an impact threshold, similar to 3-4. For example, in some embodiments, method 200 may identify an impact level of a dropped consumer electronics device 3 to distinguish between a damaging fall when consumer electronics device 3 impacts a hard surface and a harmless fall when consumer electronics device 3 impacts a soft surface. In this regard, in some embodiments, method 200 may determine an impact level of a dropped consumer electronics device 3 in an azimuth (angle about the x-axis), pitch (angle about the y-axis), and roll (angle about the z-axis) orientation ( 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 the consumer electronics device 3 in degrees per second (Z). In some embodiments, after the data from the accelerometer exceeds an upper threshold, the software application 2 can calculate the geometric mean of the rotation of the consumer electronics device 3 in degrees per second as follows: ω T = sqrt( ω x 2 , ω y 2 , ω z 2 ). The software application 2 may 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 may be set based on rotation and orientation values ​​of the consumer electronics device 3 that impact a hard surface during a drop and / or fall causing damage, and such values ​​may 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 the software application 2 registering the fall on a cloud server, such as a compensation and insurance offering system 7, similar to 3-5. In some embodiments, registering the fall may include the software application 2 updating a risk profile 5 for the user 1 and the 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 period of time, 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, software application 2 may determine that consumer electronics device 3 has been thrown when data from the accelerometer falls below the thrown threshold value, 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 upwards 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 risk-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, the method 500 can include initiating an event detection process, as in 4-1. In some embodiments, the event detection process can include a background service operating in conjunction with the background service described with respect to FIG. 2. After initiating the event detection process, the method 500 can include the software application 2 or the compensation and insurance offering system 7 identifying user events and user activities, as in 4-2, to determine whether any of the user events and user activities match any of the identified risk scenarios, as in 4-4, and retrieving the identified risk scenarios from the event monitoring database, as in 4-3. If a match is not identified, as in 4-4, the method 500 can include the software application 2 continuing to monitor for user events and user activities, as in 4-2, and retrieving the identified risk scenarios, as in 4-3. However, when method 500 identifies a match between one of the user events and user activities and one of the identified hazard scenarios, method 500 may include software application 2 registering, as in 4-5, one of the identified user events and user activities, as in 4-3, on a cloud server.

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

[0036] In some embodiments, when the software application 2 determines that one of the user events and user activities matches one of the identified hazard scenarios, the compensation and insurance offering system 7 may generate a notification message to the home electronics device 3 including an offer to the 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 warnings, for example by monitoring user activity of user 1 within other applications executed by the consumer electronic device 3, according to a disclosed embodiment. In doing so, the method 200 can identify risky behavior of user 1 through the consumer electronic device 3 and provide insurance or compensation plans not only for the consumer electronic device 3, but also through the compensation and insurance offering system 7. For example, the compensation and insurance offering system 7 can provide insurance or compensation for data stored on the consumer electronic device 3, fixed electronic devices in the home of user 1, or actions of user 1.

[0038] As can be seen, the method 600 can include initiating an activity monitoring process, as in 10-1. In some embodiments, the activity monitoring process can include a background service operating in conjunction with the background service described with respect to FIG. 2 or the event detection process described with respect to FIG. 5. After initiating the activity monitoring process, the method 600 can include the software application 2 identifying applications and actions having suitability for insurance from a database, as in 10-2, to determine whether any of the user events and user activities match any of the applications and actions having suitability for insurance, as in 10-3, and identifying user events and user activities, as in 4-2. The method 600 can determine user activities by monitoring a user interface or touch screen of the consumer electronic device 3. If any of the user events and user activities identified, as in 4-2, match any of the applications and actions identified, as in 10-2, the method 600 can include the software application 2 continuing to monitor for user events and user activities, as in 4-2. However, if one of the user events and user activities identified as 4-2 matches one of the applications and actions identified as 10-2, method 600 may include software application 2 registering one of the user events and user activities identified as 4-3 with a cloud server, as in 4-5.

[0039] Finally, method 600 may include determining, as in 10-5, whether one of the identified user events and user activities 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 acts identified as 10-2 may include an application that controls a home security system for user 1. 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 a home security system via the application that controls the home security system. When user 1 has not equipped a 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 a home security system via the application that controls the home security system. Failure to consistently equip a 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 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 off exponentially 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. Thus, 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 into account device depreciation 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, since newer versions are constantly being developed. In this regard, the iPhone 8 was released in October 2017 with a release price of $750 and continued to be sold at that price for an extended period of time thereafter. However, the value of the iPhone 8 depreciates by approximately 1% per week, with a lower limit determined by demand in the market.

[0044] 8, method 800 may include determining the make and model of the consumer electronics device, as at 801, and identifying a replacement cost percentage of the consumer electronics device 3, as 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, as in 804. When the replacement cost percentage is above the threshold, method 800 may include extending a discounted insurance offering to User 1, as in 806. For example, if the smartphone was purchased for $1000 (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] Some 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 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 the iPhone 7 has a reduced possibility of damage to the rear glass, rear camera, front camera, and loudspeaker compared to the iPhone 6. Thus, the systems and methods disclosed herein can provide 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 a disclosed embodiment, for example, by basing pricing of insurance offerings on device durability. As can be seen, the method 900 can include initiating a risk assessment process, similar to 6-1. In some embodiments, the risk assessment process can include a background service operating in conjunction with the background service described with respect to FIG. 2, the event detection process described with respect to FIG. 5, or the behavior monitoring process 10-1 described with respect to FIG. 7. After starting in the risk assessment process, the method 900 can include determining the make and model of the consumer electronic device 3, similar to 6-2, for example, by referencing data stored in the consumer electronic device 3, a profile of the user 1 stored by the compensation and insurance offering system 7, or TCP / IP packets sent over the Internet. The method 900 can 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 is above 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 multiple makes and models based on the meaningful diagnostic tests and aggregate data thereof. Additionally or alternatively, the systems and methods disclosed herein may distinguish the respective device durability rating for each of the multiple makes and models from a respective part durability rating for each of the multiple parts forming the respective device.

[0049] In some situations, the consumer electronics device 3 may be broken, 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, the method 1000 can include the software application 2 performing a diagnostic test, similar to 9-2, and determining whether all components of the consumer electronic device 3 are functional, similar to 9-3, based on the results of the diagnostic test. When the diagnostic test indicates that all components of the consumer electronic device 3 are fully functional, the method 1000 can include the software application 2 generating a report indicating so, and the compensation and insurance offering system 7 can offer a standard rate insurance plan, similar to 9-4. However, when the diagnostic test indicates that one or more of the components of the consumer electronic device 3 are not functional, the software application 2 can create a report identifying an exclusion list, similar to 9-5, that includes components of the consumer electronic device 3 that failed the diagnostic test. The method 1000 can then include the software application 2 transmitting the exclusion list to the compensation and insurance offering system 7, which can use the exclusion list to reference a coverage offering database, similar to 5-3, and provide a dedicated offer with a disclaimer, similar to 9-6.

[0051] For example, if a diagnostic test reveals that the front camera of the consumer electronics device 3 is not functioning, the compensation and insurance offering system 7 may provide 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% discount). Alternatively, if the screen of the consumer electronics device 3 is cracked and is therefore a non-functioning component and a relatively high number of insurance claims claim damage to the screen (e.g., 75%), the discount may be higher (e.g., 45% discount).

[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 functioning components 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 functioning components.

[0053] The systems and methods disclosed herein offer a substantial advancement over the prior art by identifying price guarantees for a consumer electronics device based on data from sensors on the consumer electronics device itself. Additionally, the systems and methods disclosed herein improve upon the prior art by constantly monitoring and detecting hazardous 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 disrupting 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 implementations 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 implementations may be within the scope of the invention.

[0055] From the above, 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 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. 1. A method for automatically securing a consumer electronic device, comprising: detecting, by at least one processor, at least one activity by analyzing text from operations of the consumer electronics device, the at least one activity being identified by the at least one processor as occurring in the future; determining, by the at least one processor, that the at least one activity is consistent with a hazard scenario; A method comprising:

2. The method of claim 1 , wherein the at least one activity is detected by analyzing the text from at least one of a text message, an email, or a destination address.

3. The method of claim 1 , wherein the at least one activity is detected by monitoring a user interface of the consumer electronics device to detect the text to be analyzed.

4. 2. The method of claim 1, wherein determining, by the at least one processor, that the at least one activity matches the hazard scenario comprises determining that the at least one activity matches at least one hazard scenario of a list of defined hazard scenarios.

5. The method of claim 4 , wherein each hazard scenario in the list of defined hazard scenarios represents a consumer activity that is indicated as a risk of physical damage or loss to the consumer electronic device during the consumer activity.

6. 2. The method of claim 1 , wherein detecting the at least one activity by analyzing the text by the at least one processor comprises programmatically reading the text and identifying public events or international locations in the text.

7. 2. The method of claim 1, wherein detecting the at least one activity by analyzing the text, by the at least one processor, comprises determining that the text includes a confirmation of the purchase of tickets to a public event or an international location.

8. 2. The method of claim 1, further comprising: automatically initiating, via a first software application, registration of the at least one activity on a cloud server in response to determining that the at least one activity conforms to the danger scenario.

9. 2. The method of claim 1, further comprising the step of automatically generating, via a first software application, a notification message (i) in response to determining that the at least one activity is consistent with the hazard scenario, and (ii) before the at least one activity occurs.

10. 2. The method of claim 1, further comprising: automatically initiating, via a first software application, a new backup of the consumer electronic device (i) in response to determining that the at least one activity is consistent with the danger scenario and (ii) before the at least one activity occurs.

11. monitoring the consumer electronic device to determine when a time since a last backup of the consumer electronic device exceeds a time threshold; automatically initiating, via the first software application, the new backup of the consumer electronic device in response to determining that the time of the last backup of the consumer electronic device exceeds the time threshold; The method of claim 10 further comprising:

12. 1. A system for automatically protecting a consumer electronic device, comprising: Detecting at least one activity identified as occurring in the future by analyzing text from the operation of the consumer electronics device; determining that the at least one activity is consistent with a hazard scenario; and (ii) automatically initiating a new backup of the consumer electronic device via a first software application in response to determining that the at least one activity is consistent with the danger scenario and before the at least one activity occurs. At least one processor configured to A system comprising:

13. 13. The system of claim 12, wherein the at least one processor detects the at least one activity by analyzing the text indicated by at least one of a text message, an email, or a destination address.

14. The system of claim 12 , wherein the at least one processor detects the at least one activity by monitoring a user interface of the consumer electronics device to detect the text to be analyzed.

15. 13. The system of claim 12, wherein the at least one processor determines that the at least one activity matches at least one hazard scenario by determining that the at least one activity matches at least one hazard scenario of a list of defined hazard scenarios.

16. The system of claim 12 , wherein each hazard scenario in the list of defined hazard scenarios represents a consumer activity that is indicated as a risk of physical damage or loss to the consumer electronic device during the consumer activity.

17. The at least one processor programmatically reading the text and identifying public events or international locations in the text; or Determining that the text includes a confirmation of a purchase of a ticket to a public event or international location. The system of claim 12 , wherein the at least one activity is detected by:

18. 13. The system of claim 12, wherein the at least one processor is further configured to, via the first software application, automatically initiate registration of the at least one activity on a cloud server in response to determining that the at least one activity conforms to the danger scenario.

19. 13. The system of claim 12, wherein the at least one processor, via the first software application, is further configured to automatically generate a notification message (i) in response to determining that the at least one activity is consistent with the danger scenario and (ii) before the at least one activity occurs.

20. The at least one processor monitoring the consumer electronic device to determine when a time since a last backup of the consumer electronic device exceeds a time threshold; automatically initiating a new backup of the consumer electronic device via the first software application in response to determining that the time of the last backup of the consumer electronic device exceeds the time threshold. The system of claim 12 further configured to:

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