TECHNOLOGY FOR ANALYZING IMAGE DATA TO AUTOMATICALLY ASSESS CUSTOMER OPPORTUNITIES

Abstract

Systems and methods for analyzing image data to assess customer opportunities is disclosed. According to certain aspects, a server may access aerial and other image data depicting a set of properties, and may analyze the aerial and other image data to identify the set of properties and determine relevant information associated with the set of properties. The server may further assess which of the set of properties represents a customer opportunity, and may identify a retail terminal that may be configured to facilitate the customer opportunity. The server may generate and transmit a communication to the retail terminal that includes relevant information associated with the customer opportunity.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

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.

TECHNICAL FIELD

The present disclosure is directed to analyzing image data to automatically assess customer opportunities. More particularly, the present disclosure is directed to systems and methods for analyzing digital image data that depicts a set of properties to identify which of the properties may represent customer opportunities, and communicating the customer opportunities to a relevant entity.

BACKGROUND

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 potential customer opportunities for businesses and retail entities. Instead, businesses and retail entities rely on conventional marketing (e.g., email campaigns) and sales (e.g., proactive agents) in efforts to identify customer opportunities. These conventional marketing and sales efforts are often challenging, costly, and time-consuming.

Accordingly, there is an opportunity to incorporate aerial image data to identify potential customer opportunities and automatically facilitate marketing and communication efforts associated with the customer opportunities.

BRIEF SUMMARY

In one embodiment, a computer-implemented method in a processing server of analyzing image data to automatically assess customer opportunities for an entity may be provided. According to some embodiments, the processing server may have access to an account database indicating a set of customers associated with the entity. The method may include, such as via one or more processors and/or transceivers associated with 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 set of properties depicted in the image data, and determining, for each property of the set of properties, an identifying characteristic; determining a subset of the set of properties based upon the set of identifying characteristics and according to information in the account database; generating a communication indicating the subset of the set of properties; and/or providing the communication to a terminal associated with the entity. The method may include additional, less, or alternate actions, including those discussed elsewhere herein.

In another embodiment, a system for analyzing image data to automatically assess customer opportunities for an entity may be provided. The system may have access to an account database indicating a set of customers associated with the entity, where the system may include a memory configured to store non-transitory computer executable instructions; and a processor interfacing with the transceiver and the memory. The processor may be configured to execute the non-transitory computer executable instructions to cause the processor to: access a set of digital image data depicting an aerial view of an area, analyze the set of digital image data, including: identify a set of properties depicted in the image data, and determine, for each property of the set of properties, an identifying characteristic, determine a subset of the set of properties based upon the set of identifying characteristics and according to information in the account database, generate a communication indicating the subset of the set of properties, and provide the communication to a terminal associated with the entity. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.

BRIEF DESCRIPTION OF THE DRAWINGS

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.

FIG. 1 depicts an overview of an exemplary system of components configured to facilitate various functionalities, in accordance with some embodiments.

FIG. 2 depicts an exemplary signal diagram associated with analyzing image data to assess customer opportunities, in accordance with some embodiments.

FIG. 3 depicts an exemplary visual map of properties, in accordance with some embodiments.

FIG. 4 depicts an exemplary communication indicating customer opportunities, in accordance with some embodiments.

FIG. 5 is an exemplary flow diagram associated with analyzing image data to assess customer opportunities, in accordance with embodiments.

FIG. 6 is a block diagram of an exemplary computer server, in accordance with some embodiments.

DETAILED DESCRIPTION

The present embodiments may relate to, inter alia, analyzing image data to assess customer opportunities. Conventionally, entities who pursue new or existing customer development must undergo manual sales and marketing efforts in an attempt to obtain new customers and offer additional products and services to existing customers. In these scenarios, the entities also lack certain information that may be useful in the sales and marketing effort. To alleviate these shortcomings, the present embodiments incorporate image analysis technologies to effectively and efficiently assess and communicate customer opportunities.

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 aerials images, such as digital images acquired via drones, in some embodiments, the digital image data may include digital images acquired via other sources, such as via cameras or video recorders mounted on homes, smart or autonomous vehicles, or mobile devices. In other words, 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 which of the set of properties may represent a customer opportunity. The systems and methods may further analyze the set of digital image data to assess additionally information associated with the determined properties, such as a risk associated therewith or a need for a particular product or service. The systems and methods may additionally generate and communicate, to a relevant entity, a communication (e.g., a sales lead) that may indicate the determined properties and any relevant information relating thereto. The relevant entity may assess and use the communication in any sales and marketing efforts to pursue the customer opportunity(ies).

The systems and methods therefore offer numerous benefits. In particular, entities are automatically provided with previously-unavailable and relevant information that may be used in customer sales and marketing efforts. Further, the systems and methods use digital image data to assess relevant information associated with properties and communicate the assessment to the entities, which reduces the time and effort that is required to pursue customer opportunities. Additionally, potential customers may be effectively notified of products or services that the potential customers may desire. It should be appreciated that other benefits are envisioned.

The systems and methods discussed herein address a challenge that is particular to technology associated with assessing and communicating revenue opportunities. In particular, the challenge relates to a difficulty in effectively and efficiently identifying revenue opportunities and notifying relevant entities of the revenue opportunities. This is particularly apparent when not enough relevant information is available or may be determined. In conventional situations, entities must use limited information in various sales and marketing efforts. In contrast, the systems and methods utilize network connections to access image data depicting properties, analyze the image data to assess customer opportunities, and communicate information relevant to the revenue opportunities to relevant entities. Therefore, because the systems and methods employ the collection, analysis, and communication of data associated with assessing revenue 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 communicating revenue 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 revenue 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 revenue opportunities in real-time or near-real-time.

Exemplary System and Components Thereof

FIG. 1 illustrates an overview of a system 100 of components configured to facilitate the systems and methods. It should be appreciated that the system 100 is merely an example and that alternative or additional components are envisioned.

As illustrated in FIG. 1, the system 100 may include a set of properties 102, each of which may be any type of building, structure, or the like. For example, the properties 102 may be any single- or multi-unit house, flat, townhome, apartment building, condo building, commercial building, auxiliary building for a property (e.g., a garage), or the like. In one implementation, the properties 102 may be void of a physical structure, and may instead consist of an empty lot or land. FIG. 1 depicts two properties 102, however it should be appreciated that fewer or more properties are envisioned.

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. FIG. 1 depicts two aerial vehicles 103, however it should be appreciated that fewer or more aerial vehicles are envisioned.

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 capture 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 analyzes 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 particular, the memory or storage 113 may store customer account data associated with accounts of the retail terminal(s) 112. As depicted in FIG. 1, the processing server 115 and/or the retail terminal(s) 112 may be configured to communicate with the set of aerial vehicles 103 via the network(s) 110.

According to 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 goods 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. FIG. 1 depicts two retail terminals 112, however it should be appreciated that fewer or more retail terminals are envisioned.

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 assess a condition or state of the property(ies) 102 depicted in the digital image data, or otherwise determine other information associated with the property(ies) 102 (e.g., address, owner, etc.). In certain embodiments, the processing server 115 may identify customer opportunities based upon the condition or state of the property(ies) 102, or based upon the determined information. Further, the processing server 115 may identify any of the retail terminal(s) 112 associated with a business or service that is relevant to the identified customer opportunities.

The processing server 115 may dynamically and automatically generate a communication(s) that indicates any of the relevant property(ies) 102 as well as information associated with the identified customer opportunity(ies), and may transmit the communication(s) to the relevant retail terminal(s) 112 via the network(s) 110. Accordingly, the retail terminal(s) 112 may review the communication(s) and facilitate appropriate functionalities. For example, a roofing service may initiate a direct marketing effort for a property that may be in need of roof repair or replacement. For further example, an insurance provider may underwrite a property insurance policy for a property that may not currently have a policy, and may initiate a direct marketing effort for the property insurance policy. These and additional functionalities are described in further detail with respect to FIG. 2.

Exemplary Signal Diagram for Assessing Customer Opportunities

FIG. 2 depicts a signal diagram 200 associated with certain functionalities related to analyzing image data to automatically assess customer opportunities. The signal diagram 200 includes various components including: an image source 220 (such as one of the image sensors or cameras of the aerial vehicle(s) 103 and/or other image sensors as discussed with respect to FIG. 1), a processing server 215 (such as the processing server 115 as discussed with respect to FIG. 1), and a retail terminal 225 (such as one of the retail terminals 112 as discussed with respect to FIG. 1). Although FIG. 2 depicts the processing server 215 as performing various of the image analyses and other processing elements, it should be appreciated that the functionalities may be performed by any combination of the image source 220, the processing server 215, and the retail terminal 225.

The signal diagram 200 may begin when the image source 220 captures (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) potential property(ies) that may represent customer opportunities. In particular, the processing server 215 may determine or ascertain one or more identifying characteristics for any of the property(ies) identified 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.

Based upon the identifying characteristics, the processing server 215 may identify which of the properties do or do not have a current service, product, policy, account, or the like (i.e., which of the properties may represent new customer opportunities and/or which of the properties may represent opportunities for existing customers). 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. If no such record or account exists, then the processing server 215 may deem that the identified property represents a new customer opportunity. In contrast, if a record or account exists, then the processing server 215 may deem that the identified property represents an opportunity for an existing customer.

For example, the processing server 215 may be associated with an internet service provider (ISP) and may determine that an address for a property is not included in a customer database. Accordingly, the processing server 215 may determine that the property represents an opportunity for an individual associated with the property (e.g., the owner of the property) to sign up for internet service. As another 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 represents an opportunity for the owner to purchase an upgraded security service.

The processing server 215 may assess (240) the potential property(ies) identified in (238). In particular, the processing server 215 may analyze respective portion(s) of the image data that correspond to the potential property(ies) to estimate or determine a condition or state of the potential 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.

The processing server 215 may perform (242) an analysis of the potential property(ies) based at least in part on the assessment of (240). Generally, the analysis may produce a viability metric indicating whether pursuing a marketing effort for the potential property(ies) may be worthwhile. For example, the processing server 215 may perform an underwriting of the potential property(ies) to assess a risk of insuring the potential property(ies). In another example, the processing server 215 may assess a need for a roof replacement for a house and a degree to which marketing to the homeowner may be worthwhile. It should be appreciated that the processing server 215 may use various calculations, techniques, algorithms, and the like in performing the analyses.

The processing server 215 may also identify any of the retail terminal(s) 225 that may be relevant to the opportunities of the potential property(ies). For example, if a potential property does not have a property insurance policy, the processing server 215 may identify an applicable insurance provider branch as the appropriate retail terminal. For further example, if a potential property has a yard in need of repair, the processing server 215 may identify a local landscaping service as the appropriate retail terminal.

The processing server 215 may generate (244) a communication corresponding to any of the potential property(ies), where generation of the communication may be based at least in part on the analysis of (242). In certain embodiments, the communication may be in the form of a set of leads that may identify any of the potential property(ies) and describe the customer opportunity. For example, the set of leads may identify property(ies) that do not currently have a home insurance policy with an insurance provider. For further example, the set of leads may identify property(ies) that do not currently have an outdoor deck and whose owner therefore may be interested in getting an outdoor deck.

In some embodiments, the processing server 215 may generate a visual map that depicts the potential property(ies), any surrounding property(ies), a description or information associated with the potential property(ies), and/or any other relevant information. The visual map may highlight or otherwise indicate the potential property(ies) relative to any other properties or depicted elements, thus enabling a reviewing component or individual to ascertain the potential property(ies) as well as information associated with the potential property(ies) (e.g., address, owner information, etc.). The processing server 215 may include the visual map as part of the communication.

The processing server 215 may transmit (246) the communication to the retail terminal 225 via a network connection, where the retail terminal 225 may be relevant to the identified property(ies). In some embodiments, the processing server 215 may transmit the communication via any type of network connection. After receiving the communication, the retail terminal 225 may process (248) the communication. In some embodiments, the retail terminal 225 and/or an individual associated with the retail terminal 225 may review the communication to assess any customer opportunities that may be identified in the communication. Accordingly, the retail terminal 225 and/or the individual may take appropriate action to pursue the customer opportunities.

For example, the retail terminal 225 may automatically generate and send sales and/or marketing materials, or initiate electronic communications or telephone calls, to individuals associated with the property(ies) identified in the communication. For further example, the individual may pursue an appropriate sales effort using the information included in the communication as he or she deems appropriate.

Exemplary Visual Map

FIG. 3 illustrates an example visual map 300 depicting a set of properties. An electronic device (e.g., a mobile device, such as a smartphone, or a computer terminal) may be configured to display the visual map 300 and/or receive selections and inputs via an interface, where the electronic device may be associated with a retail entity and/or a processing server. For example, a dedicated application that is configured to operate on the electronic device may display the visual map 300. It should be appreciated that the visual map is merely an example and that alternative or additional content is envisioned.

As depicted in FIG. 3, the visual map 300 depicts an aerial representation of an area, and more particularly a portion of a residential neighborhood. In particular, the visual map 300 depicts a set of roadways 310, 311, and 312 as well as a set of properties located adjacent to the roadways 310, 311, 312. According to some embodiments, a portion of the set of properties may be categorized or identified as a property for which there may be a customer opportunity, as discussed with respect to FIG. 2.

In generating the visual map 300, the electronic device may highlight any property(ies) having an associated customer opportunity to distinguish from those without an identified customer opportunity. For example, as depicted in FIG. 3, the visual map 300 highlights properties 302, 303, 304, 305, 306, and 307 as those with a customer opportunity, in contrast to a property 301 that is not highlighted (and is therefore not identified as a customer opportunity). Thus, an individual who reviews the visual map 300 may efficiently and effectively ascertain that the properties 302, 303, 304, 305, 306, and 307 represent customer opportunities, and may pursue appropriate actions. It should be appreciated that the individual may interact with the visual map 300 to access or request additional information associated with the properties, or to facilitate other processing.

Exemplary Communication Indicating Customer Opportunities

FIG. 4 illustrates an exemplary interface 400 depicting a set of sales leads. An electronic device (e.g., a mobile device, such as a smartphone, smart watch, wearable, or a computer terminal) may be configured to display the interface 400 and/or receive selections and inputs via the interface 400, where the electronic device may be associated with a retail entity. For example, a dedicated application that is configured to operate on the electronic device may display the interface 400. It should be appreciated that the interface 400 is merely an example and that alternative or additional content is envisioned.

As depicted in FIG. 4, the interface 400 includes a listing of potential new customer leads and details thereof. In particular, the interface 400 identifies a property 401, an owner 402 of the property, an indication 403 of whether the property has been underwritten, and a contact 404 for the property (as shown: selections to access certain contact channels). For example, the property at 265 Main St. has an owner T. Smith, has been underwritten, and includes selections for a phone number and email address. An individual may access and review the interface 400 to pursue new insurance policy sales opportunities. Thus, the interface 400 provides the individual with tailored information effective in enabling the individual to pursue sales leads.

Exemplary Flow Chart for Assessing Customer Opportunities

FIG. 5 depicts a block diagram of an exemplary computer-implemented method 500 of automatically assessing customer opportunities for an entity. According to some embodiments, the processing server may have access to an account database indicating a set of customers associated with the entity. The method 500 may be facilitated by a processing server (such as the processing server 115) that may communicate with a set of image capture components and a set of retail terminals via one or more network connections.

The method 500 may begin with the processing server accessing (block 505) 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. 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 510) a set of properties depicted in the set of digital image data. According to embodiments, in identifying the set of properties, the processing server may analyze the set of digital image data to identify a set of property characteristics from the set of digital image data and compare the set of property characteristics to stored property data.

The processing server may determine (block 515), for each property in the set of properties, an identifying characteristic. In some embodiments, the processing server may determine, for each property in the set of properties, at least one of an address, an owner, and a location-based designation (e.g., a zone). The processing server may determine (block 520) a subset of the set of properties based upon the set of identifying characteristics and according to information in the account database. In some embodiments, the processing server may determine the subset as those property(ies) that do not match a record in the account database (i.e., property(ies) that do not have an account with the entity). In other embodiments, the processing server may determine the subset as those propery(ies) that match a record in the account database but do not have an active or existing product or service or may otherwise benefit from additional products or services that may be offered by the entity.

The processing server may optionally assess (block 525) a risk for each property in the subset of the set of properties. In particular, the processing server may analyze the set of digital image data to determine, for each property in the subset of the set of properties, a set of visual characteristics, and for each property in the subset of the set of properties, assess a risk based upon the corresponding set of visual characteristics. In one embodiment, the processing server may determine an exterior condition of the corresponding property based upon the corresponding set of visual characteristics and assess the risk based upon the exterior condition. Generally, the processing server may determine or calculate a viability metric indicating whether pursuing a marketing effort for each property in the subset of the set of properties may be worthwhile.

The processing server may optionally generate (block 530) a visual map using at least a portion of the set of digital image data and highlighting each property in the subset of the set of properties. In certain embodiments, highlighting may emphasize the subset of the set of properties in relation to the remaining properties in the set of properties.

The processing server may generate (block 535) a communication indicating the subset of the set of properties. In some embodiments, the communication may include information associated with the subset of the set of properties, such as respective addresses, owners, contact information, conditions of property features or components, and/or other information. According to an optional implementation, the communication may include the visual map generated in block 530 and/or may indicate the assessed risk for each property in the subset of the set of properties.

The processing server may provide (block 540) the communication to a terminal associated with the entity. In certain embodiments, the processing server may transmit the communication to the terminal. After receiving the communication, the terminal or an accessing individual may process the communication and initiate appropriate processing based upon the information included in the communication.

Exemplary Hardware Diagram

FIG. 6 illustrates a diagram of an example server 615 (such as the processing server 115 as discussed with respect to FIG. 1) in which the functionalities as discussed herein may be implemented. It should be appreciated that the server 615 may be configured to be connect to and communicate with various entities, components, and devices, as discussed herein.

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 to assess customer opportunities, and a notification application 691 configured to generate and transmit notifications and communications. 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 retail terminals 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 FIG. 6, the user interface 681 may include a display screen 682 and I/O components 683 (e.g., ports, capacitive or resistive touch sensitive input panels, keys, buttons, lights, LEDs, speakers, microphones). According to some embodiments, the user may access the server 615 via the user interface 681 to review information and/or perform other functions. In some embodiments, the server 615 may perform the functionalities as discussed herein as part of a “cloud” network or may otherwise communicate with other hardware or software components within the cloud to send, retrieve, or otherwise analyze data.

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.

Exemplary Computer-Implemented Method

In one aspect, a computer-implemented method in a processing server of analyzing image data to automatically assess customer opportunities for an entity may be provided. The processing server having access to an account database indicating a set of customers associated with the entity. The method may include, via one or more processors and/or transceivers associated with the processing server, accessing a set of digital image data depicting one or more views of an area; and analyzing the set of digital image data, including: identifying a set of properties depicted in the image data, and determining, for each property of the set of properties, an identifying characteristic. The method may also include determining a subset of the set of properties based upon the set of identifying characteristics and according to information in the account database; generating a communication indicating the subset of the set of properties; and/or providing the communication to a terminal associated with the entity. The method may include additional, less, or alternate actions, including those discussed elsewhere herein.

For instance, the method may include analyzing the set of digital image data to determine, for each property in the subset of the set of properties, a set of visual characteristics; and for each property in the subset of the set of properties, assessing a risk based upon the corresponding set of visual characteristics.

Generating the communication may include generating the communication further indicating the assessed risk for each property in the subset of the set of properties. Assessing the risk based upon the corresponding set of visual characteristics may include determining an exterior condition of the property based upon corresponding set of visual characteristics, and assessing the risk based upon the exterior condition.

The method may include generating a visual map using at least a portion of the set of digital image data, the visual map highlighting each property in the subset of the set of properties. Generating the communication may include generating the communication including the visual map.

Determining, for each property of the set of properties, the identifying characteristic may include determining, for each property of the set of properties, at least one of: an address, an owner, and a location-based designation.

Accessing the set of digital image data depicting one or more views of the area may include receiving the set of digital image data from a component that captured the set of digital image data. Identifying the set of properties depicted in the image data may include, for each of the set of properties: identifying a set of property characteristics from the set of digital image data, and comparing the set of property characteristics to stored property data.

Determining the subset of the set of properties may include determining the subset of the set of properties based upon the identifying characteristic of each property in the subset of the set of properties not matching a record in the account database.

The set of digital image data depicting one or more views of the area may include digital image data collected from image sensors mounted on one or more sources, the one or more sources comprising a drone, an autonomous vehicle, an intelligent home, or a mobile device. For instance, the digital image data may include drone image data depicting one or more aerial views of a property. The digital image data may also include, in some embodiments, image data collected from vehicle-mounted image sensors or cameras (such as autonomous vehicle mounted cameras), and depict ground-based views of the property. The digital image data may also include image data collected from cameras mounted on the exterior of homes or neighboring homes, including home security system image data. Mobile device image data may also be included in the digital image data. The sources of data may show images of the exterior, as well as interior, of one or more homes or other properties.

Additional Considerations

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 mobile device, smart home controller, or other smart devices—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 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.

Claims

1. A computer-implemented method in a processing server of analyzing image data to automatically assess customer opportunities for an entity, the processing server having access to an account database stored in memory and indicating a set of customers associated with the entity, the method comprising:

capturing, by at least one image sensor, a set of digital image data depicting an aerial view of an area;

analyzing, by a processor, the set of digital image data, including: identifying a set of properties depicted in the set of digital image data, and determining, for each property of the set of properties, an address for the property;

determining, by the processor, a subset of the set of properties based upon the address of each property in the subset of the set of properties not matching a record in the account database;

determining, by the processor, a terminal associated with the entity based on the terminal being local to the address of each property in the subset of the set of properties;

generating, by the processor, a communication indicating the subset of the set of properties;

generating, by the processor using at least a portion of the set of digital image data captured by the at least one sensor, a visual map;

transmitting, via a network connection, the communication and the visual map to the terminal associated with the entity; and

displaying, in a graphical user interface of the terminal, (i) the communication including, for each property in the subset of the set of properties, the address and a contact information, and (ii) the visual map, the visual map highlighting each property in the subset of the set of properties not matching the record in the account database.

2. The computer-implemented method of claim 1, further comprising:

analyzing the set of digital image data to determine, for each property in the subset of the set of properties, a set of visual characteristics; and

for each property in the subset of the set of properties, assessing a risk based upon the corresponding set of visual characteristics.

3. The computer-implemented method of claim 2, wherein generating the communication comprises:

generating the communication further indicating the assessed risk for each property in the subset of the set of properties.

4. The computer-implemented method of claim 2, wherein assessing the risk based upon the corresponding set of visual characteristics comprises:

determining an exterior condition of the property based upon the corresponding set of visual characteristics, and

assessing the risk based upon the exterior condition.

5-6. (canceled)

7. The computer-implemented method of claim 1, further comprising:

determining, for each property of the set of properties, at least one of: an owner or a location-based designation.

8. (canceled)

9. The computer-implemented method of claim 1, wherein identifying the set of properties depicted in the set of digital image data comprises, for each of the set of properties:

identifying a set of property characteristics from the set of digital image data, and

comparing the set of property characteristics to stored property data.

10. (canceled)

11. A system for analyzing image data to automatically assess customer opportunities for an entity, the system having access to an account database indicating a set of customers associated with the entity, comprising:

a terminal associated with the entity;

a transceiver configured to connect, via a network connection, to the terminal associated with the entity;

at least one image sensor configured to capture a set of digital image data depicted an aerial view of an area;

a memory configured to store non-transitory computer executable instructions;

a processor interfacing with the transceiver, the at least one image sensor, and the memory, and configured to execute the non-transitory computer executable instructions to cause the processor to: analyze the set of digital image data, including: identify a set of properties depicted in the set of digital image data, and determine, for each property of the set of properties, an address for the property, determine a subset of the set of properties based upon the address of each property in the subset of the set of properties not matching a record in the account database, determine a terminal associated with the entity based on the terminal being local to the address of each property in the subset of the set of properties, generate a communication indicating the subset of the set of properties, generate, using at least a portion of the set of digital image data captured by the at least one sensor, a visual map, and transmit, via the transceiver, the communication and the visual map to the terminal associated with the entity;

and wherein the terminal displays, in a graphical user interface, (i) the communication including, for each property in the subset of the set of properties, the address and a contact information, and (ii) the visual map, the visual map highlighting each property in the subset of the set of properties not matching the record in the account database.

12. The system of claim 11, wherein the processor is configured to execute the non-transitory computer executable instructions to further cause the processor to:

analyze the set of digital image data to determine, for each property in the subset of the set of properties, a set of visual characteristics, and

for each property in the subset of the set of properties, assess a risk based upon the corresponding set of visual characteristics.

13. The system of claim 12, wherein to generate the communication, the processor is configured to:

generate the communication further indicating the assessed risk for each property in the subset of the set of properties.

14. The system of claim 12, wherein to assess the risk based upon the corresponding set of visual characteristics, the processor is configured to:

determine an exterior condition of the property based upon the corresponding set of visual characteristics, and

assess the risk based upon the exterior condition.

15-16. (canceled)

17. The system of claim 11, wherein the processor is further configured to:

determine, for each property of the set of properties, at least one of: an owner or a location-based designation.

18. (canceled)

19. The system of claim 11, wherein to identify the set of properties depicted in the set of digital image data, the processor is configured to, for each of the set of properties:

identify a set of property characteristics from the set of digital image data, and

compare the set of property characteristics to stored property data.

20. (canceled)