TECHNICAL FIELD
[0001] The present disclosure relates to the field of exposure accumulation. More particularly, the present disclosure pertains to system and method for monitoring risk exposure accumulation against various disaster risk zones.

BACKGROUND
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Exposure is a critical component of any risk model. Primary elements of exposure that have been considered are population, household and buildings (residential, commercial and industrial). Since insurers in India are not tracking their exposure at policy level (but rather at aggregated levels like pincode, city, district, state), for any detailed exposure accumulation monitoring, it is important to disaggregate exposure to a resolution lower than pincode. This is important because site specific hazards like flood may not impact even a complete pincode. Also exposure is not equally distributed across a pincode or a city or district.
[0004] There is therefore a need in the art for a system and method that enables identification of a distribute exposure within a pincode or district or state in a manner that is representative of building and risk distribution on ground.

OBJECTS OF THE PRESENT DISCLOSURE
[0005] A general object of the present disclosure is to provide system and method for monitoring risk exposure accumulation over a defined area.
[0006] An object of the present disclosure is to provide system and method for monitoring risk exposure accumulation over a defined area such that distribution of risk exposure is representative of building distribution in the defined area.
[0007] Another object of the present disclosure is to provide system and method for monitoring risk exposure accumulation over a defined area that considers factors such as population, household and buildings.
[0008] A yet another object of the present disclosure is to provide system and method for monitoring risk exposure accumulation over a defined area that disaggregate risk exposure data to a resolution lower than area indicated by a pincode.

SUMMARY
[0009] The present disclosure relates to the field of exposure accumulation. More particularly, the present disclosure pertains to system and method for monitoring exposure accumulation against various disaster risk zones.
[00010] An aspect of the present disclosure pertains to a system comprising a non-transitory storage device having embodied therein one or more routines operable to monitor risk exposure over a defined area; and one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include: an aggregate data receive module, which when executed by the one or more processors, obtains aggregate data comprising risk exposure data pertaining to the defined region; an image receive module, which when executed by the one or more processors, obtains at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters; a building cluster classification module, which when executed by the one or more processors, associates each of the plurality of building clusters with at least one building category selected from plurality of categories; and a risk exposure data distribution module, which when executed by the one or more processors, distributes the risk exposure data pertaining to the defined region based on associated building category with each of the plurality of building clusters and determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region.
[00011] In an embodiment, the plurality of categories can comprise residential building cluster, commercial building cluster and industrial building cluster. In another embodiment, the plurality of categories can comprise low rise building cluster, medium rise building cluster and high rise building cluster.
[00012] In an embodiment, the aggregate data can further comprise population data, household data and building type information pertaining to the pre-defined location.
[00013] In an embodiment, the defined region can pertain to boundary of a region indicated by a pincode.
[00014] In an embodiment, the aggregate data receive module can obtain the aggregate data of a territory and can determine aggregate data of the defined region based on ratio of area pertaining to the defined region to area pertaining to the territory, and wherein the territory comprises any or a combination of a tehsil, a district, a state, a city, a town and a country.
[00015] In an embodiment, the building cluster classification module can associate each of the plurality of building clusters with the at least one building category using image processing techniques.
[00016] In an embodiment, the aggregate data receive module can obtain the aggregate data from any or a combination of census data or insurance exposure data.
[00017] Another aspect of the present disclosure pertains to a method including the steps of: obtaining, by one or more processors, an aggregate data comprising risk exposure data pertaining to a defined region; obtaining, by the one or more processors, at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters; associating, by the one or more processors, each of the plurality of building clusters with at least one building category selected from plurality of categories; and distributing, by the one or more processors, the risk exposure data pertaining to the defined region based on the associated building category of each of the plurality of building clusters and determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region.
[00018] Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF THE DRAWINGS
[00019] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[00020] FIG. 1 illustrates exemplary functional modules of a system for monitoring risk exposure accumulation in accordance with an embodiment of the present invention.
[00021] FIG. 2 illustrates process utilized for monitoring risk exposure accumulation over a defined area in accordance with an embodiment of the present disclosure.
[00022] FIG. 3 illustrates an exemplary computer system in which or with which embodiments of the present disclosure may be utilized in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[00023] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
[00024] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
[00025] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
[00026] Each of the appended claims defines a separate invention, which for infringement purposes is recognized as including equivalents to the various elements or limitations specified in the claims. Depending on the context, all references below to the "invention" may in some cases refer to certain specific embodiments only. In other cases it will be recognized that references to the "invention" will refer to subject matter recited in one or more, but not necessarily all, of the claims.
[00027] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[00028] Various terms are used herein. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[00029] In the following description, numerous details are set forth. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present invention.
[00030] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearance of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[00031] Throughout the following discussion, numerous references will be made regarding servers, services, interfaces, engines, modules, clients, peers, portals, platforms, or other systems formed from computing devices. It should be appreciated that the use of such terms is deemed to represent one or more computing devices having at least one processor (e.g., ASIC, FPGA, DSP, x86, ARM, ColdFire, GPU, multi-core processors, etc.) configured to execute software instructions stored on a computer readable tangible, non- transitory medium (e.g., hard drive, solid state drive, RAM, flash, ROM, etc.). For example, a server can include one or more computers operating as a web server, database server, or other type of computer server in a manner to fulfill described roles, responsibilities, or functions. One should further appreciate the disclosed computer-based algorithms, processes, methods, or other types of instruction sets can be embodied as a computer program product comprising a non-transitory, tangible computer readable media storing the instructions that cause a processor to execute the disclosed steps. The various servers, systems, databases, or interfaces can exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods. Data exchanges can be conducted over a packet-switched network, a circuit- switched network, the Internet, LAN, WAN, VPN, or other type of network.
[00032] The terms "configured to" and "programmed to" in the context of a processor refer to being programmed by a set of software instructions to perform a function or set of functions.
[00033] The following discussion provides many example embodiments. Although each embodiment represents a single combination of components, this disclosure contemplates combinations of the disclosed components. Thus, for example, if one embodiment comprises components A, B, and C, and a second embodiment comprises components B and D, then the other remaining combinations of A, B, C, or D are included in this disclosure, even if not explicitly disclosed.
[00034] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously.
[00035] In some embodiments, numerical parameters expressing quantities are used. It is to be understood that such numerical parameters may not be exact, and are instead to be understood as being modified in some instances by the term "about." Accordingly, in some embodiments, a numerical parameter is an approximation that can vary depending upon the desired properties sought to be obtained by a particular embodiment.
[00036] Unless the context dictates the contrary, ranges set forth herein should be interpreted as being inclusive of their endpoints and open-ended ranges should be interpreted to include only commercially practical values. The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value within a range is incorporated into the specification as if it were individually recited herein. Similarly, all lists of values should be considered as inclusive of intermediate values unless the context indicates the contrary.
[00037] Groupings of alternative elements or embodiments of the inventive subject matter disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all groups used in the appended claims.
[00038] The present disclosure relates to the field of exposure accumulation. More particularly, the present disclosure pertains to system and method for monitoring exposure accumulation against various disaster risk zones.
[00039] An aspect of the present disclosure pertains to a system comprising a non-transitory storage device having embodied therein one or more routines operable to monitor risk exposure over a defined area; and one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include: an aggregate data receive module, which when executed by the one or more processors, obtains aggregate data comprising risk exposure data pertaining to the defined region; an image receive module, which when executed by the one or more processors, obtains at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters; a building cluster classification module, which when executed by the one or more processors, associates each of the plurality of building clusters with at least one building category selected from plurality of categories; and a risk exposure data distribution module, which when executed by the one or more processors, distributes the risk exposure data pertaining to the defined region based on associated building category with each of the plurality of building clusters and determination of ratio of built-up area of each of the building cluster of the plurality of building clusters to sum of the built-up area of all the building clusters in the defined region.
[00040] In an embodiment, the plurality of categories can comprise residential building cluster, commercial building cluster and industrial building cluster. In another embodiment, the plurality of categories can comprise low rise building cluster, medium rise building cluster and high rise building cluster.
[00041] In an embodiment, the aggregate data can further comprise population data, household data and building type information pertaining to the pre-defined location.
[00042] In an embodiment, the defined region can pertain to boundary of a region indicated by a pincode.
[00043] In an embodiment, the aggregate data receive module can obtain the aggregate data of a territory and can determine aggregate data of the defined region based on ratio of area pertaining to the defined region to area pertaining to the territory, and wherein the territory comprises any or a combination of a tehsil, a district, a state, a city, a town and a country.
[00044] In an embodiment, the building cluster classification module can associate each of the plurality of building clusters with the at least one building category using image processing techniques.
[00045] In an embodiment, the aggregate data receive module can obtain the aggregate data from any or a combination of census data or insurance data.
[00046] Another aspect of the present disclosure pertains to a method including the steps of: obtaining, by one or more processors, an aggregate data comprising risk exposure data pertaining to a defined region; obtaining, by the one or more processors, at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters; associating, by the one or more processors, each of the plurality of building clusters with at least one building category selected from plurality of categories; and distributing, by the one or more processors, the risk exposure data pertaining to the defined region based on the associated building category of each of the plurality of building clusters and determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region.
[00047] According to an aspect of present disclosure the proposed system can utilize population, household, building structure type distribution data, risk exposure data, and the like (collectively referred to as aggregate data, hereinafter) from any source such as census. Census data for a country can be stored in any format, preferably a tabular format, wherein the census data can be utilized to perform analysis of specific hazards, for an instance, flood.
[00048] In an embodiment, the proposed system can utilize high resolution satellite images to determine spatial distribution of building exposure within a defined region that can be indicative of boundary of a pincode. Satellite images can be utilized to capture plurality of building clusters and classify the building clusters into various categories such as residential, commercial, and industrial building clusters or low, medium and high rise building clusters. In an aspect, clusters can aid to distribute the aggregate data over polygons for calculating the affected exposure for site specific hazards.
[00049] In an embodiment, the building clusters in an image can be classified by utilizing various image processing techniques. For example, classification can be performed based on the tone, texture, shape, size, pattern, and associations between buildings. The identified building agglomerations can be further improved using any suitable software such as GoogleTM Earth to view satellite imagery, maps, terrain, 3D buildings. Further, a triangulation mechanism based on shadow can be utilized for height bands.
[00050] In an embodiment, all the obtained aggregate data or any part thereof such as risk exposure data can be brought at a pincode level by intersecting the pincode boundary with territory boundary such as tehsil boundary and distribution of household and population to pincode boundary can be performed based on ratio of pincode area to total tehsil area. In an exemplary implementation, once the population and household data has been brought to pincode level, the data can be further distributed to building cluster based on the ratio of actual area of building cluster to sum of actual area of all the building cluster in that pincode.
[00051] In an exemplary embodiment, based on roof and wall material information of buildings that can be present in census data, a plurality of combinations, for an instance, 90 combinations can be created. The 90 combinations can be mapped to various prominent structure types, for an instance 33 structure types. In an aspect, a matrix can be developed based on the occupancy type and their sub category distributing buildings into 33 structural types within a pincode. For each particular sub category of building cluster, all the possible structure types can be marked as ‘1’ while the structure types which are not possible were marked as ‘0’ indicating discarded. The matrix can be multiplied with structure % at pincode level to obtain the final structural percentage at building cluster data. In an embodiment, a district to pincode risk exposure data distribution matrix can be generated using the industry penetration estimates as well as the building cluster data.
[00052] In another aspect, risk exposure data can be provided by insurers at pincode or district or state level. To distribute risk exposure data over building cluster, ratio of cluster area to sum of area of all cluster in particular pincode can be performed. In case data is provided at territory level such as district or state level then the data can be first disaggregated to pincode level and then to building cluster level. Following such disaggregation of risk exposure data, risk score zones can be overlaid on the building exposure at building cluster level to monitor the exposure accumulation against various risk levels.
[00053] FIG. 1 illustrates exemplary functional modules of a system for monitoring exposure accumulation in accordance with an embodiment of the present invention.
[00054] As illustrated, a system for monitoring risk exposure accumulation (referred to as the system 102, hereinafter) can include one or more processor(s) 104. The one or more processor(s) 104 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 104 are configured to fetch and execute computer-readable instructions stored in a memory 106 of the system. The memory 106 can store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 106 can include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like. In an example embodiment, the memory 106 may be a local memory or may be located remotely, such as a server, a file server, a data server, and the Cloud.
[00055] The system can also include an interface(s) 108. The interface(s) 108 may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 108 may facilitate communication of the system with various devices coupled to the system. The interface(s) 108 may also provide a communication pathway for one or more components of the system. Examples of such components include, but are not limited to, processing engine(s) 112 and data 110.
[00056] The engine(s) can be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the engine(s). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the engine(s) 112 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the engine(s) may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the engine(s) 112. In such examples, the system 102 can include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to system 102 and the processing resource. In other examples, the engine(s) 112 may be implemented by electronic circuitry. The data 110 can include data that is either stored or generated as a result of functionalities implemented by any of the components of the engine(s) 112.
[00057] In an example, the processing engine(s) 112 can include an aggregate data receive module 114, an image receive module 116, a building cluster classification module 118, a risk exposure data distribution module 120 and other module(s) 122. The other module(s) 122 can implement functionalities that supplement applications or functions performed by the system 102 or the processing engine(s) 112.
[00058] According to an aspect of the present disclosure, the aggregate data receive module 114 can obtain an aggregate data pertaining to a defined region. The aggregate data can include population data, household data, building structure data, risk exposure data and the like. In an embodiment, the aggregate data or any part thereof can be obtained from sources such as census, information from insurers, etc. For example, the aggregate data receive module 114 can obtain risk exposure data from insurers at pincode. Further, the defined region can pertain to boundary of a region indicated by a pincode.
[00059] In an embodiment, the aggregate data receive module 114 can obtain the aggregate data or any part thereof pertaining to a territory such as a tehsil, a district, a state, a city, a town, a country, and the like. Further, the aggregate data receive module 114 can determine the aggregate data pertaining to the defined ration based on ratio of area pertaining to the defined region and area pertaining to the territory. For example, the aggregate data receive module 114 can obtain risk exposure data of a tehsil and can bring it to a pincode level by intersecting pincode boundary with tehsil boundary. Further, distribution of household and population data to pincode boundary can be performed based on ratio of pincode area to total tehsil area.
[00060] In an aspect, the image receive module 116 can obtain an image or a set of images that can be high resolution satellite images pertaining to the defined region in order to determine spatial distribution of building exposure. Satellite images can capture plurality of building clusters in the defined region. Further, the building cluster classification module 118 can associate each of the building clusters with a building category that can be selected from plurality of categories. In one embodiment, the plurality of categories can include residential, commercial, and industrial building clusters. In another embodiment, the plurality of categories can include low, medium and high rise building clusters. It would be appreciated that building clusters can aid to distribute the aggregate data over polygons that indicate building clusters for calculating the affected exposure for site specific hazards.
[00061] In an embodiment, the building cluster classification module 118 can associate the building category with the building cluster techniques pertaining to image processing. For example, classification of the building cluster into building category can be performed based on tone, texture, shape, size, pattern, and associations between the buildings in the image. The identified building agglomerations can be further improved using any suitable software such as GoogleTM Earth to view satellite imagery, maps, terrain, 3D buildings. In an example, triangulation mechanism based on shadow can be utilized for height bands.
[00062] In an aspect, the risk exposure data distribution module 120 can distribute the risk exposure data pertaining to the defined region using the building category associated with each of the plurality of building clusters. Further, the risk exposure data distribution module 120 can determine ratio of area of a building cluster to sum of area of all the building clusters in the defined region in order to distribute the risk exposure data.
[00063] In an embodiment, the risk exposure data distribution module 120 can utilize based on roof and wall material information of buildings that can be present in the census data, and a plurality of combinations, for an instance, 90 combinations that can be created using said data. The combinations can further be mapped to various prominent structure types, for an instance 33 structure types. In an aspect, a matrix can be developed based on the occupancy type and their sub category distributing buildings into 33 structural types within the defined region pertaining to a pincode. For each particular sub category of building cluster, all the possible structure types can be marked as ‘1’ while the structure types which are not possible can be marked as ‘0’ indicating discarded. The matrix can then be multiplied with structure % at pincode level to obtain the final structural percentage at building cluster data. In an exemplary aspect, the risk exposure data distribution matrix can be generated using the industry penetration estimates as well as the building cluster data.
[00064] Thus, according to the embodiments of the present disclosure, in order to distribute risk exposure data over building cluster, ratio of cluster area to sum of area of all cluster in particular pincode can be performed. In case data is provided at district or state level then it is first disaggregated to pincode level and then to building cluster level. Following this exposure disaggregation, risk score zones based on risk exposure data can be overlaid on the building exposure at building cluster level to monitor the exposure accumulation against various risk levels.
[00065] FIG. 2 illustrates process utilized for monitoring risk exposure accumulation over a defined area in accordance with an embodiment of the present disclosure.
[00066] As illustrated, in an aspect, a method to monitor risk exposure over a defined area can include a step 202 pertaining to obtaining an aggregate data of a defined region that can be indicated by a pin code. The aggregate data can include population data, household data, building structure data, risk exposure data and the like and can be obtained from sources such as census data or information from insurers.
[00067] In an aspect, the method can include a step 204 pertaining to obtaining an image or set of images that can be satellite images capturing plurality of building clusters in the defined region. Further, at step 206 each of the building clusters can be associated with a building category that can be selected from plurality of categories such as residential, commercial, and industrial building clusters or low, medium and high rise building clusters.
[00068] Further, at step 208 the risk exposure data can be distributed based on the associated building category of each of the plurality of building clusters as well as determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region. Thus, the risk exposure data can be distributed proportionally by identification of a distributed risk exposure within a defined region in a manner that is representative of building distribution on ground.
[00069] Embodiments of the present disclosure include various steps, which have been described above. A variety of these steps may be performed by hardware components or may be tangibly embodied on a computer-readable storage medium in the form of machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with instructions to perform these steps. Alternatively, the steps may be performed by a combination of hardware, software, and/or firmware.
[00070] FIG. 3 illustrates an exemplary computer system in which or with which embodiments of the present disclosure may be utilized in accordance with embodiments of the present disclosure.
[00071] As shown in FIG. , computer system includes an external storage device 310, a bus 320, a main memory 330, a read only memory 340, a mass storage device 350, communication port 360, and a processor 370.
[00072] A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor 370 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor 370 may include various modules associated with embodiments of the present invention. Communication port 360 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port 360 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects.
[00073] Memory 330 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read only memory 340 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 370. Mass storage 350 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7200 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc.
[00074] Bus 320 communicatively couples processor(s) 370 with the other memory, storage and communication blocks. Bus 320 can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 370 to software system.
[00075] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus 320 to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 360. External storage device 310 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[00076] Thus, it will be appreciated by those of ordinary skill in the art that the diagrams, schematics, illustrations, and the like represent conceptual views or processes illustrating systems and methods embodying this invention. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing associated software. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the entity implementing this invention. Those of ordinary skill in the art further understand that the exemplary hardware, software, processes, methods, and/or operating systems described herein are for illustrative purposes and, thus, are not intended to be limited to any particular named.
[00077] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[00078] The present disclosure provides system and method for monitoring risk exposure accumulation over a defined area.
[00079] The present disclosure provides system and method for monitoring risk exposure accumulation over a defined area such that distribution of risk exposure is representative of building distribution in the defined area.
[00080] The present disclosure provides system and method for monitoring risk exposure accumulation over a defined area that considers factors such as population, household and buildings.
[00081] The present disclosure provides system and method for monitoring risk exposure accumulation over a defined area that disaggregate risk exposure data to a resolution lower than area indicated by a pincode.

CLAIMS:
1. A system comprising:
a non-transitory storage device having embodied therein one or more routines operable to monitor risk exposure over a defined area; and
one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include:
an aggregate data receive module, which when executed by the one or more processors, obtains aggregate data comprising risk exposure data pertaining to the defined region;
an image receive module, which when executed by the one or more processors, obtains at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters;
a building cluster classification module, which when executed by the one or more processors, associates each of the plurality of building clusters with at least one building category selected from plurality of categories; and
a risk exposure data distribution module, which when executed by the one or more processors, distributes the risk exposure data pertaining to the defined region based on associated building category with each of the plurality of building clusters and determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region.
2. The system of claim 1, wherein the plurality of categories comprise residential building cluster, commercial building cluster and industrial building cluster.
3. The system of claim 1, wherein the plurality of categories comprise low rise building cluster, medium rise building cluster and high rise building cluster.
4. The system of claim 1, wherein the aggregate data further comprises population data, household data and building type information pertaining to the pre-defined location.
5. The system of claim 1, wherein the defined region pertains to boundary of a region indicated by a pincode.
6. The system of claim 1, wherein the aggregate data receive module obtains the aggregate data of a territory and determines aggregate data of the defined region based on ratio of area pertaining to the defined region to area pertaining to the territory, and wherein the territory comprises any or a combination of a tehsil, a district, a state, a city, a town and a country.
7. The system of claim 1, wherein the building cluster classification module associates each of the plurality of building clusters with the at least one building category using image processing techniques.
8. The system of claim 1, wherein the aggregate data receive module obtains the aggregate data from any or a combination of census data or insurance data.
9. A method comprising the steps of:
obtaining, by one or more processors, an aggregate data comprising risk exposure data pertaining to a defined region;
obtaining, by the one or more processors, at least one image pertaining to the defined region, wherein the at least one image comprises a plurality of building clusters;
associating, by the one or more processors, each of the plurality of building clusters with at least one building category selected from plurality of categories; and
distributing, by the one or more processors, the risk exposure data pertaining to the defined region based on the associated building category of each of the plurality of building clusters and determination of ratio of area of each of the building cluster of the plurality of building clusters to sum of area of all the building clusters in the defined region.