The present disclosure is directed to analyzing image data to automatically manage customer policies. More particularly, the present disclosure is directed to systems and methods for analyzing digital image data that depicts a property to determine eligibility to manage an associated policy of the property.
Aerial imagery generally includes image data that is captured from a vantage point located above an object that is depicted in the image data. The use of aerial imagery is increasing as the amount of devices and components used to capture aerial imagery increases. For instance, unmanned aerial vehicles (UAVs; i.e., “drones”) and satellites are increasing in amount and usage. Generally, aerial imagery may be used in certain applications, such as supplementing mapping applications and creating graphical and video productions including promotional materials and movies.
The existing uses of aerial imagery do not, however, extend to assessing whether customer policies associated with properties are eligible for processing or management. Instead, entities that offer customer policies must manually gather information to determine whether the customer policies are eligible for processing or management. These conventional efforts are often inconvenient, costly, and time-consuming, and may include additional drawbacks as well.
The present embodiments relate to aerial image and/or other data analysis techniques to identify policy management opportunities and automatically facilitate the management of the policies. For customers that opt into an automatic policy management program, aerial images of their properties may be acquired, their properties (and/or the present condition thereof) may be identified from the images acquired, and one more actions may be performed based upon the property identified, a present condition thereof, and a difference between a previous condition thereof, such as automatic insurance policy renewal and/or premium or discount adjustment based upon the present condition of the property.
In one aspect, a computer-implemented method in a processing server of analyzing image data to automatically manage existing policies for an entity may be provided. The processing server may have access to an account database indicating a set of policies associated with a set of properties (such as properties with property owners that have opted into an automatic policy renewal program), and the method may include, such as via one or more processors and/or transceivers associated with, within, and/or under the direction/control of the processing server: (1) accessing a set of digital image data depicting an aerial view of an area; (2) analyzing the set of digital image data, including: identifying a property depicted in the set of digital image data, and determining at least one condition of the property; (3) determining that the property has an associated policy that is reflected in the account database, the associated policy indicating at least one previous condition of the property; (4) comparing the at least one condition of the property to the at least one previous condition of the property; (5) determining, based upon the comparing, a difference between the at least one condition and the at least one previous condition; and/or (6) managing the associated policy of the property based upon the difference. The method may include additional, less, or alternate actions, including those discussed elsewhere herein.
In another aspect, a computer system for analyzing image data to automatically manage existing policies for an entity may be provided. The system may have access to an account database indicating a set of policies associated with a set of properties, and may include: a memory configured to store non-transitory computer executable instructions; and a processor interfacing with the memory and configured to execute the non-transitory computer executable instructions to cause the processor to: (1) access a set of digital image data depicting an aerial view of an area; (2) analyzing the set of digital image data, including: identify a property depicted in the set of digital image data, and determine at least one condition of the property; (3) determine that the property has an associated policy that is reflected in the account database, the associated policy indicating at least one previous condition of the property; (4) compare the at least one condition of the property to the at least one previous condition of the property; (5) determine, based upon the comparing, a difference between the at least one condition and the at least one previous condition; and/or (6) manage the associated policy of the property based upon the difference. The computer system may include additional, less, or alternate functionality, including that discussed elsewhere herein.
The figures described below depict various aspects of the system and methods disclosed herein. It should be understood that each figure depicts an embodiment of a particular aspect of the disclosed system and methods, and that each of the figures is intended to accord with a possible embodiment of thereof. Further, wherever possible, the following description refers to the reference numerals included in the following figures, in which features depicted in multiple figures are designated with consistent reference numerals.
The present embodiments may relate to, inter alia, analyzing image data to assess automatic policy processing and managing opportunities, such as policy renewal opportunities and other processing. Conventionally, entities who pursue efforts to manage policies associated with properties must undertake some form of manual assessment of the conditions of the properties. These efforts are considered inconvenient, time-consuming, and costly, among other drawbacks. To alleviate these shortcomings, the present embodiments incorporate image analysis technologies to effectively and efficiently assess policy management eligibility and automatically facilitate the managing of policies.
According to certain aspects, systems and methods may retrieve or otherwise access a set of digital image data that depicts an aerial view of an area or neighborhood in which a set of properties is located. Although the digital image data may primarily or solely include aerial images, such as digital images acquired via drones or other UAVs (unmanned aerial vehicles), in some embodiments, the digital image data may include digital images acquired via other sources, such as via cameras or video recorders (or other sensors) mounted on homes, smart or autonomous vehicles, or mobile devices. In other words, in some embodiments, the digital image data may include drone image data, smart or intelligent home image data, smart or autonomous vehicle image data, and/or mobile device and/or social media image data.
The systems and methods may analyze the set of digital image data to identify the set of properties and determine at least one condition for each of the set of properties. The systems and methods may further reference a listing of accounts associated with an entity to determine if any of the set of properties has a policy with the entity (e.g., a property insurance policy issued by an insurance provider). Each policy may indicate a previous condition(s) of the associated property. The systems and methods may further determine, based upon a comparison of the determined condition(s) to the previous condition(s), whether to automatically managing a policy of a given property; and if so, to automatically manage the policy.
The systems and methods therefore offer numerous benefits. In particular, customers who hold the policies are afforded the benefit of automatic managing (e.g., renewal) without the drawbacks associated with a manual assessment. Further, these customers are presented with the option to opt-in or opt-out of managing assessment and automatic managing. Additionally, the systems and methods reduce the efforts required for entities to assess whether a policy is eligible for managing, as well as to facilitate policy management. It should be appreciated that other benefits are envisioned.
The systems and methods discuss policies associated with properties and issued by entities and purchased by customers associated with the properties. These policies may be, for example, property insurance policies issued by insurance providers and purchased by owners of the properties. Generally, the policies are in force for a specified term (e.g., six (6) months or one (1) year), and have an associated premium (e.g., $50/month). When a policy is renewed, a new term may be appended to an existing term, where the new term may be the same or different time period as the existing term and may have an associated premium that may be the same as or different from the premium of the existing term. It should be appreciated that additional types of policies other than property insurance policies are envisioned.
Further, the systems and methods may extend to services offered by entities and purchased by or subscribed to by customers. For example, an owner of a property may purchase a home security service from a security company.
The systems and methods discussed herein address a challenge that is particular to technology associated with assessing and processing policy management opportunities. In particular, the challenge relates to a difficulty in effectively and efficiently identifying policy renewal opportunities and automatically processing renewals. This is particularly apparent when necessary information is not easily obtained. In conventional situations, entities must undertake manual efforts to obtain information necessary to determine eligibility for policy renewal. In contrast, the systems and methods utilize network connections to access image data depicting properties, analyze the image data to assess conditions of the properties, and automatically facilitate policy renewals based upon the property conditions. Therefore, because the systems and methods employ the collection, analysis, and processing of data associated with assessing renewal opportunities, the systems and methods are necessarily rooted in computer technology in order to overcome the noted shortcomings that specifically arise in the realm of technology associated with assessing and processing policy renewal opportunities.
According to implementations, the systems and methods may support a dynamic, real-time or near-real-time collection, analysis, and communication of any data that may be associated with managing opportunities. In particular, the systems and methods may dynamically and automatically access image data from components in real-time or near-real-time, may automatically and dynamically analyze the image data, and may automatically and dynamically generate and transmit communications that indicate relevant information in real-time or near-real-time. In this regard, individuals are afforded the benefit of effective and relevant information associated with renewal opportunities in real-time or near-real-time.
As illustrated in
The system 100 may further include a set of aerial vehicles 103 capable of any type of air travel or flight. According to embodiments, the aerial vehicle(s) 103 may be unmanned aerial vehicles (UAVs; aka “drones”) or may be manned by a pilot (e.g., airplane, helicopter, etc.). If the aerial vehicle(s) 103 is a UAV(s), the UAV(s) may be autonomously controlled or may be controlled remotely. Each of the set of aerial vehicles 103 may be configured with one or more image sensors that may be capable of capturing digital image data, where the image sensor(s) may be controlled autonomously, or locally or remotely by an individual. It should be appreciated that each of the set of aerial vehicles 103 may be configured with one of more image sensors, video recorders, and/or cameras. In some embodiments, each of the set of aerial vehicles 103 may be configured with a memory device for storing any image data.
In operation, the image sensor(s) (or cameras) of the set of aerial vehicles 103 may be configured to capture digital images that depict various portions of the property(ies) 102. In particular, the digital images may depict exterior portions of the property(ies) 102, such as roofs, entryways, exterior materials, foundations, yards, auxiliary buildings, and/or any other physical structures or elements associated with the property(ies) 102 that may be visible.
In addition to aerial digital images of a property 102 captured by one or more drones or aerial vehicles 103, other digital images of a property 102 may be acquired. For instance, digital images of the property 102 may be acquired by one or more image sensors or cameras of a smart or autonomous vehicle 104, a vehicle dashboard mounted camera, a user mobile device 105, surrounding smart or intelligent homes 102, and/or internet websites or social media 106. All the digital images acquired of a property 102 may be organized into a data set for the property 102 and transmitted to a processor for analysis via the network 110.
Further, the system 100 may also include a processing server 115 and a set of retail terminals 112 that may be in communication via one or more networks 110. In certain embodiments, the network(s) 110 may support any type of data communication via any standard or technology (e.g., GSM, CDMA, TDMA, WCDMA, LTE, EDGE, OFDM, GPRS, EV-DO, UWB, Internet, IEEE 802 including Ethernet, WiMAX, Wi-Fi, Bluetooth, and others). The processing server 115 may be configured to interface with or support a memory or storage 113 capable of storing various data. In a particular embodiment, the memory or storage 113 may store customer account data associated with accounts of the retail terminal(s) 112. As depicted in
According to certain embodiments, the retail terminal(s) 112 may be associated with an entity, business, company, enterprise, operation, individual, or the like, that may offer or provide policies, goods, and/or services for customers or clients. For example, one of the retail terminals 112 may be associated with an internet service provider (ISP), another of the retail terminals 112 may be associated with a roofing service, and another of the retail terminals 112 may be associated with an insurance provider. In certain embodiments, the processing server 115 may be affiliated with or unaffiliated with the retail terminal(s) 112.
In one implementation, the processing server 115 may be incorporated into any of the retail terminal(s) 112. In another implementation, the processing server 115 may be separate from the retail terminal(s) 112, where the retail terminal(s) 112 may have an existing agreement, contract, or partnership with the processing server 115.
In operation, the image sensor(s) (or cameras) of the aerial vehicle(s) 103 may capture digital image data that depicts various portions of the property(ies) 102, and may transmit the digital image data to the processing server 115 via the network(s) 110. The processing server 115 may analyze the aerial digital image data (either solely or in conjunction with digital image data acquired via other sources, such as website, mobile device, autonomous vehicle, or neighboring smart home or security system data) to identify the property(ies) 102 depicted in the digital image data and to assess a condition or state of the property(ies) 102 depicted in the digital image data.
Additionally, the processing server 115 may determine that the property(ies) 102 have associated active policy(ies), such as property insurance policy(ies), where the policy(ies) may indicate a previous condition(s) of the associated property. The processing server 115 may compare the determined condition(s) of a property to the previous condition(s) of the property to determine whether there is an opportunity to automatically manage (e.g., renew) a corresponding policy. If the policy(ies) are eligible for automatic managing, the processing server 115 may automatically manage the policy(ies) by, for example, renewing the policy(ies) and extending the in-force term(s) of the policy(ies). The processing server 115 may further generate and provide communications related to the automatic managing to the proper customers. For example, the processing server 115 may send a communication to the mobile device 105 associated with a customer whose property insurance policy was automatically renewed. These and additional functionalities are described in further detail with respect to
It should be appreciated that a user of the customer device 226 (i.e., a customer) has an active policy or agreement with an entity associated with the processing server 215. In some embodiments, the active policy may be active or in force until a specified time or date. The terms of the active policy may be based at least in part on the existing condition(s) of the underlying asset. For example, the customer may own a property that is insured via a property insurance policy issued by an insurance provider, where the property insurance policy may be active until April 1 of a specific year. Generally, the policy may be eligible for renewal upon expiration of the policy at the specified time or date, where renewal eligibility may be assessed or determined based upon one or more factors, such as the condition of the underlying asset (e.g., a home) or other factor(s). Further, the terms of the policy (e.g., a premium amount) upon renewal may be subject to modification.
The signal diagram 200 may begin when the customer associated with the customer device 226 selects, using the customer device 226, whether to opt-in or opt-out of automatic policy renewal. If the customer selects to opt-in, then the customer is enabling the processing server 215 to automatically renew the policy, where the terms of the renewed policy may or may not change; in contrast, if the customer selects to opt-out, then the processing server 215 is not permitted to automatically renew the policy. It should be appreciated that opt-out (or opt-in) may be the default option absent a customer selection. After the customer makes his/her selection, the customer device 226 may transmit (229) the opt-in or opt-out selection to the processing server 215.
Concurrently with, before, or after (229), the image source 220 may capture (230) image data. According to embodiments, the image data may be digital image data that consists of aerial image data of an area in which a set of properties may be located. In one implementation, there may be one or more of the image source 220, where the image source(s) 220 may be associated with a manned or unmanned aerial vehicle capable of airborne flight. Other image sources may be used, such as home-mounted, vehicle-mounted, and/or mobile device-mounted image sources or cameras. In one optional implementation, the image source 220 may access image data that was previously captured by the image source 220 itself or by another component. The image source 220 may be configured to store the image data, such as in a memory component.
In one optional implementation, the processing server 215 may request (232) image data from the image source 220. According to embodiments, the processing server 215 may automatically request the image data periodically (e.g., once every ten seconds, once every minute, once every hour), or a user of the processing server 215 may cause the processing server 215 to request the image data. Additionally, the processing server 215 may request specific image data, such as image data captured within a specified timeframe, image data of a specific location or area, and/or image data according to other parameters.
After the image source 220 captures or otherwise accesses the image data, or receives a request from the processing server 215, the image source 220 may transmit (234) or provide the image data to the processing server 215. In certain embodiments, the image source 220 may transmit the image data via any type of network connection, and optionally according to any request received from the processing server 215.
After receiving the image data, the processing server 215 may analyze (236) the image data. It should be appreciated that the processing server 215 may use any type of image processing, machine learning, or computer vision process, technique, calculation, algorithm, and/or the like to analyze the image data. Generally, the processing server 215 may be configured to analyze the image data to identify or recognize certain objects, as well as portions or sections of the objects, that may be depicted in the image data.
In particular, the processing server 215 may identify property(ies), and portions or sections of the property(ies), that may be depicted in the image data. For example, the processing server 215 may identify one or more houses, townhomes, buildings, apartments, condos, and/or the like, along with certain exterior features of the properties, such as roofs, decks, patios, driveways, yards, windows, building materials, landscaping, foundations, garages, fencing, and/or the like.
The processing server 215 may identify (238) property(ies) that may represent policy renewal opportunities. In particular, the processing server 215 may determine or ascertain one or more identifying characteristics for any of the property(ies) depicted in the image data. For example, the identifying characteristics may be one or more of an address of the property, an owner of the property, a location of the property, a zone or other location-based designation for the property, and/or other identifying characteristics. In determining the identifying characteristic(s), the processing server 215 may access various databases, records, or the like. For example, the processing server 215 may determine an address of a property depicted in the image data, and may determine, from publicly-available information, an owner of the property located at that address.
The processing server 215 may determine or assess (240) a condition(s) of the property(ies) identified in (238). In particular, the processing server 215 may analyze respective portion(s) of the image data that correspond to the property(ies) to estimate or determine a condition or state of the property(ies). For example, the processing server 215 may assess a condition or state of a roof, a deck, a patio, a driveway, a yard, a window(s), an exterior material, an auxiliary building, landscaping, and/or any other physical structure or element associated with the property. In some embodiments, the processing server 215 may calculate a set of metrics, scores, or parameters for certain portions or aspects of the property that may represent a set of conditions of the portions or aspects. For example, the processing server 215 may calculate a score of 9/10 for a roof of a property and a score of 3/10 for a deck of a property.
Additionally or alternatively, the processing server 215 may determine the extent to which the property is properly being maintained, including whether the windows, siding, doors, and roof of the house are in good or excellent condition, and may generate a score to indicate the degree to which the house is being maintained. In this manner, risk averse home owners that properly maintain their homes may be entitled to an insurance discount or other insurance-cost savings.
The processing server 215 may determine (242) whether there is an active policy associated with the property(ies) identified in (238). In particular, based upon the identifying characteristics of the property(ies), the processing server 215 may identify which of the properties do or do not have a current service, product, policy, agreement, account, or the like (i.e., which of the properties may represent renewal or reassessment opportunities and/or which of the properties may not represent renewal or reassessment opportunities). In particular, the processing server 215 may examine an account database (or similar register or record) using an identifying characteristic of an identified property to determine whether a record or account associated with the identifying characteristic exists, and whether the record or account indicates an existing or in-force policy. If no such record or account exists, then the processing server 215 may deem that the identified property does not represent a renewal or reassessment opportunity. In contrast, if a record or account exists, then the processing server 215 may deem that the identified property represents a renewal or reassessment opportunity.
For example, the processing server 215 may be associated with a security system company and may determine that an owner of a property has subscribed to a basic security service. Accordingly, the processing server 215 may determine that the property may be eligible for a renewal or reassessment of the basic security service. As another example, the processing server 215 may be associated with an insurance provider and may determine that an owner of a property may have an insurance policy on the property. Accordingly, the processing server 215 may determine that the property may be eligible for a renewal or reassessment of the insurance policy.
In some embodiments, the policy or account of a given property may indicate a set of previous or existing conditions associated with the property, where the previous or existing conditions may be representative of the conditions of the property when the policy or account is put into force or otherwise while the policy or account is in force. The previous or existing conditions may be automatically and/or manually determined, at the time when the policy or account is put into force, based upon certain property information or data.
For example, relevant existing conditions for a basic security service may be the size and footprint of the buildings that make up the property, conditions of any entryway(s), the presence (or absence) of door and/or window locks, and/or other conditions that may be relevant to the security of the property. For further example, relevant existing conditions for a property insurance policy may be a condition or state of a roof, a deck, a patio, a driveway, a yard, a window(s), an exterior material, an auxiliary building, landscaping, and/or any other physical structure or element associated with the property, including general overall condition or state of the property and/or the need for maintenance or repairs, or lack thereof. In certain embodiments, each of the set of previous or existing conditions may have an associated metric, score, or parameter. For example, a policy for a property may indicate a score of 7/10 for a roof of the property and a score of 5/10 for a deck of the property.
If the processing server 215 determines that the property does not have an active policy (“NO”), processing may end or proceed to other functionality. In contrast, if the processing server 215 determines that the property does have an active policy (“YES”), the processing server 215 may compare (244) the current condition(s) of the property determined in (240) to the existing or previous condition(s) of the property that are indicated in the policy of the property. Based upon the comparison, the processing server 215 may determine or calculate a difference between the previous condition(s) of the property and the current condition(s) of the property.
For example, assume that the previous condition(s) for a property, as indicated in an active policy of the property, include a previous roof score of 6/10, a previous exterior score of 8/10, and a previous deck score of 6/10. Further, assume that the processing server 215 determines that current condition(s) of the property indicate a current roof score of 7/10, a current exterior score of 8/10, and a current deck score of 8/10. Accordingly, the processing server 215 may determine that each of the roof score and the deck score improved, while the exterior score remained unchanged.
The processing server 215 may manage (246) the policy based upon the comparison of (244). In particular, the processing server 215 may determine if and how any terms or conditions of the policy may change upon renewal of the policy. For example, if the processing server 215 determines that the conditions of a property improve, then the processing server 215 may calculate a corresponding premium decrease for a property insurance policy to be applied upon renewal of the policy. For further example, if the processing server 215 determines that a fence was installed along the boundary of a property, then the processing server 215 may calculate a pricing decrease for a security service to be applied upon renewal of the service. It should be appreciated that the processing server 215 may employ any technique, calculation, algorithm, or processing in determining how to manage the policy or service.
In managing the policy, the processing server 215 may also automatically renew the policy according to any determined changes to the terms or conditions of the policy. Before renewing the policy, the processing server 215 may determine whether the customer has opted into automatic policy renewal, and may automatically renew a policy of the associated customer has opted in. If the associated customer has not opted in, the processing server 215 may request approval from the associated customer before renewing the policy.
In some embodiments, the processing server 215 may consider various terms of the policy itself before automatically renewing the policy. For example, if the processing server 215 determines that a property insurance policy does not expire for another fifteen (15) months, then the processing server 215 may determine that the policy is not currently eligible for automatic renewal; in contrast, if the processing server 215 determines that a property insurance policy expires in one (1) month, then the processing server 215 may determine that the policy is eligible for automatic renewal. It should be appreciated that the processing server 215 may perform any analysis, calculation, technique, algorithm, or combination thereof, to determine automatic renewal eligibility. Generally, the processing server 215 may automatically renew the policy for a specified period of time (which may or may not be the same as the period of time for the original policy) and for a specified amount or premium (which may or may not be the same as the amount or premium for the original policy).
In one implementation, the processing server 215 may request confirmation or approval for policy renewal from the customer, regardless of whether the period of time and/or the specified amount or premium is the same or different from the original period of time and/or the original specified amount or premium. In another implementation, the processing server 215 may automatically renew the policy without interaction with or confirmation from the customer. After automatically renewing the policy, the processing server 215 may update an appropriate record or account corresponding to the policy to reflect the renewal.
The processing server 215 may generate (248) a communication indicating that the policy was renewed. According to certain embodiments, the communication may include any combination of information as well as certain options for the customer to select. The processing server 215 may transmit (250) the communication to the customer device 226 via a network connection. After receiving the communication, the customer device 226 may present (252) the notification for review by the customer. In some embodiments, the customer may use the customer device 226 to make certain selections and/or review additional information.
The method 500 may begin with the processing server optionally receiving (block 505), from an electronic device of a customer associated with a property, a request to opt-in to automatic policy management. According to certain embodiments, the customer may own a policy associated with the property (e.g., a property insurance policy), and may select to either opt-in or opt-out of automatic management of the policy (e.g., automatic policy renewal). In some embodiments, in return for opting into a program that acquires and analyzes images of their property, or otherwise providing affirmative consent or permission to an insurance provider to acquire and analyze digital images of their property, the customer may receive various insurance or other benefits, including automatic renewal, insurance discounts, lower premiums, or other insurance-cost savings.
The processing server may access (block 510) a set of digital image data that may depict an aerial (or side, ground, or other) view of an area. For instance, the digital image data may include aerial digital images or image data acquired via one or more drones. The digital image data may or may not also include digital images or image data acquired via one or more home-mounted, vehicle-mounted, and/or mobile device-mounted image sensors or cameras.
In certain embodiments, the area may include at least a portion of a neighborhood, region, zone, and/or the like, that may be populated by a set of properties (i.e., one or more properties). The processing server may access the set of digital image data locally, or may request and/or receive the set of digital image data from a component that captured the set of digital image data.
The processing server may identify (block 515) a property depicted in the set of digital image data. According to some embodiments, in identifying the property, the processing server may determine one or more identifying characteristics, such as at least one of an address, an owner, and a location-based designation (e.g., a zone). The processing server may also determine (block 520) at least one condition of the property. For example, the processing server may assess a condition or state of a roof, a deck, a patio, a driveway, a yard, a window(s), an exterior material, an auxiliary building, landscaping, and/or any other physical structure or element associated with the property.
The processor server may identify the property (block 515) and/or determine the one or more conditions thereof (block 520) by performing image processing, machine learning, or other computer vision process, technique, calculation, algorithm, and/or the like on the image data collected from various sources (e.g., drones, intelligent homes, autonomous vehicles, mobile devices, security systems, and smart infrastructure). For instance, an initial image data set may be gathered for a home using drones, mobile device, smart vehicles, security systems, etc., such as when a home is new, 5 years old, 10 years old, or other ages. The initial image data set for the property may be fed into a machine learning algorithm that may be trained to identify, assess, or determine the property, the type of property, location of the property, characteristics of the property, and/or one or more conditions associated with the property, including those discussed elsewhere herein (e.g., status of yard work, roof, siding, windows, doors, garage doors, pools, fences, trees, drive way, sidewalk, etc.). The machine learning algorithm may be trained with historical or current images of the property, similar properties, and/or other types properties. Other means of artificial intelligence may be employed to identify a property and one or more conditions (and the status thereof) and characteristics of the property, including those discussed elsewhere herein.
Additionally, the processing server may determine (block 525) that the property has an associated policy that is reflected in the account database, where the associated policy may indicate at least one previous condition of the property. For example, the at least one previous condition may be a condition or state of a roof, a deck, a patio, a driveway, a yard, a window(s), an exterior material, an auxiliary building, landscaping, and/or any other physical structure or element associated with the property. In some embodiments, the processing server may determine that the determined identifying characteristic(s) of the property is included in one of the policies stored in the account database, and may determine that the associated policy is active or in-force.
The processing server may compare (block 530) the at least one condition to the at least one previous condition, and in particular may determine a difference between the at least one condition and the at least one previous condition. In some embodiments, the processing server may calculate at least one metric corresponding to the at least one condition, and may compare the at least one metric to a respective at least one previous metric corresponding to the at least one previous condition, and may calculate a metric difference between the at least one metric and the at least one previous metric.
In one embodiment, the processor server may compare (block 530) the at least one condition to the at least one previous condition, and/or determine a difference between the condition and the previous condition (and/or determine various metrics) performing image processing, machine learning, or other computer vision process, technique, calculation, algorithm, and/or the like on (i) a current set and (ii) a previous set of image data of the property collected from various sources (e.g., drones, intelligent homes, autonomous vehicles, mobile devices, security systems, and smart infrastructure).
For instance, an initial image data set may be gathered for a home using drones, mobile devices, smart vehicles, security systems, etc. to establish a baseline, such as at the time of policy issuance. After which, a current or real-time image data set may be gathered and fed into a machine learning algorithm that is trained to identify, assess, or determine the property, the type of property, location of the property, characteristics of the property, one or more initial and/or current conditions associated with the property, including those discussed elsewhere herein (e.g., status of yard work, roof, siding, windows, doors, garage doors, pools, fences, trees, driveway, sidewalk, etc.), and differences between initial and present conditions of the property (such as shown by the initial and current image data sets of the property). As noted, the machine learning algorithm may be trained with historical or current images of the property, similar properties, and/or other types properties. Other means of artificial intelligence may be employed to identify one or more initial and current conditions (and the status thereof), and/or differences between the initial and current conditions of the property, including those discussed elsewhere herein.
The processing server may determine (block 535) whether to manage the policy associated with the property, such as automatically renew the policy or facilitate another policy management feature. In one implementation, the processing server may identify an expiration date of the associated policy, and may determine, based upon the difference determined in block 530 and the expiration date of the associated policy (e.g., whether the expiration date is within a threshold time period of a current date), that the associated policy of the property is eligible for renewal. If the processing server determines to not manage the policy (“NO”), processing may end, repeat, or proceed to other functionality.
In contrast, if the processing server determines to manage the policy (“YES”), the processing server may optionally retrieve (block 540), from the electronic device, a confirmation to manage the associated policy. In some embodiments, the processing server may communicate, to the electronic device, a proposed modification to the policy (e.g., a renewal and particulars thereof). Further, the processing server may request and receive the confirmation by default, or may request and receive the confirmation when a proposed modification alters the associated policy (e.g., a renewal rate for the associated policy is different from a previous rate for the associated policy).
The processing server may proceed to automatically manage (block 545) the associated policy, where the policy management may be based upon the difference determined in block 530. In particular, if the processing server automatically renews the associated policy, a renewal rate may be the same as or different from a previous rate, and a policy term may be the same as or different from a previous policy term. The processing server may generate (block 550) a communication indicating that the associated policy was managed. In some embodiments, if the associated policy was renewed, the communication may include information such as a renewal rate, renewal period, and/or other information.
The processing server may provide (block 555) the communication to the electronic device associated with the customer. The customer may use the electronic device to review the communication, request additional information, initiate contact with an appropriate entity, and/or facilitate other functionalities.
The server 615 may include a processor 672 as well as a memory 678. The memory 678 may store an operating system 679 capable of facilitating the functionalities as discussed herein as well as a set of applications 675 (i.e., machine readable instructions). For example, one of the set of applications 675 may be an image analysis application 690 configured to analyze images, and a policy processing application 691 configured to process and manage policies, and communicate relevant notifications relating thereto. It should be appreciated that one or more other applications 692 are envisioned.
The processor 672 may interface with the memory 678 to execute the operating system 679 and the set of applications 675. According to some embodiments, the memory 678 may also include image data 680 that the image analysis application 690 may access and analyze. The memory 678 may include one or more forms of volatile and/or non-volatile, fixed and/or removable memory, such as read-only memory (ROM), electronic programmable read-only memory (EPROM), random access memory (RAM), erasable electronic programmable read-only memory (EEPROM), and/or other hard drives, flash memory, MicroSD cards, and others.
The server 615 may further include a communication module 677 configured to communicate data via one or more networks 610. According to some embodiments, the communication module 677 may include one or more transceivers (e.g., WWAN, WLAN, and/or WPAN transceivers) functioning in accordance with IEEE standards, 3GPP standards, or other standards, and configured to receive and transmit data via one or more external ports 676. For example, the communication module 677 may receive, via the network 610, digital image data captured by a set of components (e.g., image sensors, such as cameras or video recorders). For further example, the communication module 677 may transmit notifications and communications to electronic devices via the network 610.
The server 615 may further include a user interface 681 configured to present information to a user and/or receive inputs from the user. As shown in
In general, a computer program product in accordance with an embodiment may include a computer usable storage medium (e.g., standard random access memory (RAM), an optical disc, a universal serial bus (USB) drive, or the like) having computer-readable program code embodied therein, wherein the computer-readable program code may be adapted to be executed by the processor 672 (e.g., working in connection with the operating system 679) to facilitate the functions as described herein. In this regard, the program code may be implemented in any desired language, and may be implemented as machine code, assembly code, byte code, interpretable source code or the like (e.g., via C, C++, Java, Actionscript, Objective-C, Javascript, CSS, XML). In some embodiments, the computer program product may be part of a cloud network of resources.
In one aspect, a computer-implemented method in a processing server of analyzing image data to automatically manage existing policies for an entity may be provided. The method may include, via one or more processors and/or transceivers associated with, within, and/or under the direction/control of the processing server: accessing a set of digital image data depicting an aerial view of an area; analyzing the set of digital image data, including: identifying a property depicted in the set of digital image data, and determining at least one condition of the property; determining that the property has an associated policy that is reflected in the account database, the associated policy indicating at least one previous condition of the property; comparing the at least one condition of the property to the at least one previous condition of the property; determining, based upon the comparing, a difference between the at least one condition and the at least one previous condition; and/or managing the associated policy of the property based upon the difference.
Managing the associated policy of the property based upon the difference may include automatically renewing the associated policy of the property, wherein a set of terms of the associated policy is based upon the difference.
Automatically renewing the associated policy may include automatically renewing the associated policy at a renewal rate that is different from a previous rate for the associated policy. Additionally or alternatively, automatically renewing the associated policy at the renewal rate may include retrieving, from an electronic device of a customer associated with the property, a confirmation to renew the associated policy at the renewal rate.
The method may include generating a notification indicating that the associated policy was renewed, and providing the notification to an electronic device of a customer associated with the property. The method may further include receiving, from an electronic device of a customer associated with the property, a request to opt-in to automatic policy renewal.
Automatically renewing the associated policy may include identifying an expiration date of the associated policy, and determining, based upon the difference and the expiration date of the associated policy, that the associated policy of the property is eligible for automatic renewal.
Comparing the at least one condition of the property to the at least one previous condition of the property may include calculating at least one metric corresponding to the at least one condition, and comparing the at least one metric to a respective at least one previous metric corresponding to the at least one previous condition. Determining the difference between the at least one condition and the at least one previous condition may include calculating a metric difference between the at least one metric and the at least one previous metric.
Identifying the property depicted in the set of digital image data may include determining, for the property, at least one of: an address, an owner, and a location-based designation. The method may include additional, less, or alternate actions, including those discussed elsewhere herein.
In one aspect, a computer-implemented method in a processing server of analyzing image data to automatically manage existing policies for an entity may be provided. The processing server may have access to an account database indicating a set of policies associated with a set of properties. The method may include (1) accessing, via one or more processors, a set of digital image data depicting an aerial view of an area stored in a memory unit, and/or receiving, via one or more processors and/or associated transceivers (such as via wireless communication or data transmission over one or more radio frequency links or digital communication channels), the set of digital image data depicting the aerial view of the area from one or more drone-mounted, vehicle-mounted, mobile device-mounted, or home-mounted transceivers; (2) analyzing, via the one or more processors, the set of digital image data, including: identifying, via the one or more processors, a property depicted in the set of digital image data, and/or determining, via the one or more processors, at least one condition of the property; (3) determining, via the one or more processors, that the property has an associated policy that is reflected in the account database, the associated policy indicating at least one previous condition of the property; (4) comparing, via the one or more processors, the at least one condition of the property to the at least one previous condition of the property; (5) determining, based upon the comparing, via the one or more processors, a difference between the at least one condition and the at least one previous condition; and/or (6) managing, updating, or adjusting, via the one or more processors, the associated policy of the property based upon the difference. The method may include additional, less, or alternate actions, including those discussed elsewhere herein.
In another aspect, a computer system configured to analyze image data to automatically manage existing policies for an entity may be provided. The computer system may include one or more processors, processing servers, sensors, and/or transceivers having access to an account database indicating a set of policies associated with a set of properties. The one or more processors, processing servers, sensors, and/or transceivers may be configured to: (1) access a set of digital image data depicting an aerial view of an area stored in a memory unit, and/or receive (such as via wireless communication or data transmission over one or more radio frequency links or digital communication channels) the set of digital image data depicting the aerial view of the area from one or more drone-mounted, vehicle-mounted, mobile device-mounted, or home-mounted transceivers; (2) analyze the set of digital image data, including: identify a property depicted in the set of digital image data, and/or determine at least one condition of the property, and/or status thereof; (3) determine that the property has an associated policy that is reflected in the account database, the associated policy indicating at least one previous condition of the property; (4) compare the at least one condition of the property to the at least one previous condition of the property; (5) determine, based upon the comparing, a difference between the at least one condition and the at least one previous condition; and/or (6) manage, update, or adjust, the associated policy of the property based upon the difference. The computer system may include additional, less, or alternate functionality, including that discussed elsewhere herein.
With the foregoing, an insurance customer may opt-in to a rewards, insurance discount, or other type of program. After the insurance customer provides their affirmative consent, an insurance provider remote server may collect data from the customer's drone, mobile device, smart home controller, or other smart devices, or may collect data using insurance provider's drones—such as with the customer's permission or affirmative consent. The data collected may be related to certain functionalities or profiles, and/or insured assets before (and/or after) an insurance-related event, including those events discussed elsewhere herein. In return, risk averse insureds, home owners, or home or apartment occupants may receive discounts or insurance cost savings related to home, renters, personal articles, auto, and other types of insurance from the insurance provider.
In one aspect, drone data, smart or interconnected home data, autonomous or smart vehicle data, mobile device data, social media data, and/or other data, including the types of data discussed elsewhere herein, may be collected or received by an insurance provider remote server, such as via direct or indirect wireless communication or data transmission from an insurance provider or customer drone, a smart home controller, smart or autonomous vehicle, mobile device, other customer computing device, or customer social media content after a customer affirmatively consents or otherwise opts-in to an insurance discount, reward, or other program. The insurance provider may then analyze the data received with the customer's permission to provide benefits to the customer. As a result, risk averse customers may receive insurance discounts or other insurance cost savings based upon data that reflects low risk behavior and/or technology that mitigates or prevents risk to (i) insured assets, such as homes, personal belongings, or vehicles, and/or (ii) home or apartment occupants.
Although the text herein sets forth a detailed description of numerous different embodiments, it should be understood that the legal scope of the invention is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possible embodiment, as describing every possible embodiment would be impractical, if not impossible. One could implement numerous alternate embodiments, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims.
It should also be understood that, unless a term is expressly defined in this patent using the sentence “As used herein, the term ‘ ’ is hereby defined to mean . . . ” or a similar sentence, there is no intent to limit the meaning of that term, either expressly or by implication, beyond its plain or ordinary meaning, and such term should not be interpreted to be limited in scope based upon any statement made in any section of this patent (other than the language of the claims). To the extent that any term recited in the claims at the end of this disclosure is referred to in this disclosure in a manner consistent with a single meaning, that is done for sake of clarity only so as to not confuse the reader, and it is not intended that such claim term be limited, by implication or otherwise, to that single meaning. Finally, unless a claim element is defined by reciting the word “means” and a function without the recital of any structure, it is not intended that the scope of any claim element be interpreted based upon the application of 35 U.S.C. § 112(f).
Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.
Additionally, certain embodiments are described herein as including logic or a number of routines, subroutines, applications, or instructions. These may constitute either software (code embodied on a non-transitory, tangible machine-readable medium) or hardware. In hardware, the routines, etc., are tangible units capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a module that operates to perform certain operations as described herein.
In various embodiments, a module may be implemented mechanically or electronically. Accordingly, the term “module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which modules are temporarily configured (e.g., programmed), each of the modules need not be configured or instantiated at any one instance in time. For example, where the modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different modules at different times. Software may accordingly configure a processor, for example, to constitute a particular module at one instance of time and to constitute a different module at a different instance of time.
Modules can provide information to, and receive information from, other modules. Accordingly, the described modules may be regarded as being communicatively coupled. Where multiple of such modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the modules. In embodiments in which multiple modules are configured or instantiated at different times, communications between such modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple modules have access. For example, one module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further module may then, at a later time, access the memory device to retrieve and process the stored output. Modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.
Similarly, the methods or routines described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.
The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the one or more processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the one or more processors or processor-implemented modules may be distributed across a number of geographic locations.
Unless specifically stated otherwise, discussions herein using words such as “processing,” “computing,” “calculating,” “determining,” “presenting,” “displaying,” or the like may refer to actions or processes of a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or a combination thereof), registers, or other machine components that receive, store, transmit, or display information. Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. For example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other. The embodiments are not limited in this context.
As used herein any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment. In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the description. This description, and the claims that follow, should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise.
As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).
This detailed description is to be construed as exemplary only and does not describe every possible embodiment, as describing every possible embodiment would be impractical, if not impossible. One could implement numerous alternate embodiments, using either current technology or technology developed after the filing date of this application. Upon reading this disclosure, those of skill in the art will appreciate still additional alternative structural and functional designs for system and a method for assigning mobile device data to a vehicle through the disclosed principles herein. Thus, while particular embodiments and applications have been illustrated and described, it is to be understood that the disclosed embodiments are not limited to the precise construction and components disclosed herein. Various modifications, changes and variations, which will be apparent to those skilled in the art, may be made in the arrangement, operation and details of the method and apparatus disclosed herein without departing from the spirit and scope defined in the appended claims.
The particular features, structures, or characteristics of any specific embodiment may be combined in any suitable manner and in any suitable combination with one or more other embodiments, including the use of selected features without corresponding use of other features. In addition, many modifications may be made to adapt a particular application, situation or material to the essential scope and spirit of the present invention. It is to be understood that other variations and modifications of the embodiments of the present invention described and illustrated herein are possible in light of the teachings herein and are to be considered part of the spirit and scope of the present invention.
While the preferred embodiments of the invention have been described, it should be understood that the invention is not so limited and modifications may be made without departing from the invention. The scope of the invention is defined by the appended claims, and all devices that come within the meaning of the claims, either literally or by equivalence, are intended to be embraced therein. It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention.
This application claims benefit of the filing dates of U.S. Provisional Patent Application No. 62/463,371 (filed Feb. 24, 2017 and entitled “TECHNOLOGY FOR ANALYZING IMAGE DATA TO AUTOMATICALLY ASSESS CUSTOMER OPPORTUNITIES”); U.S. Provisional Patent Application No. 62/468,806 (filed Mar. 8, 2017 and entitled “TECHNOLOGY FOR AUTOMATICALLY ENSURING CONSISTENT DIGITAL IMAGE CAPTURE PARAMETERS”); U.S. Provisional Patent Application No. 62/473,014 (filed Mar. 17, 2017 and entitled “TECHNOLOGY FOR ANALYZING IMAGE DATA TO AUTOMATICALLY PROCESS CUSTOMER RENEWALS”); and U.S. Provisional Patent Application No. 62/483,786 (filed Apr. 10, 2017 and entitled “TECHNOLOGY FOR ANALYZING IMAGE DATA TO AUTOMATICALLY MANAGE CUSTOMER POLICIES”)—which are hereby incorporated by reference in their entireties.
Number | Date | Country | |
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62483786 | Apr 2017 | US | |
62473014 | Mar 2017 | US | |
62468806 | Mar 2017 | US | |
62463371 | Feb 2017 | US |