DESC:
FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(See section 10 and rule 13)
1. TITLE OF THE INVENTION
SYSTEM AND METHOD FOR MANAGING INSTALLATION OF OPTICAL FIBER DEVICES
2. APPLICANT(S)
NAME NATIONALITY ADDRESS
JIO PLATFORMS LIMITED INDIAN OFFICE-101, SAFFRON, NR. CENTRE POINT, PANCHWATI 5 RASTA, AMBAWADI, AHMEDABAD 380006, GUJARAT, INDIA
3.PREAMBLE TO THE DESCRIPTION

THE FOLLOWING SPECIFICATION PARTICULARLY DESCRIBES THE NATURE OF THIS INVENTION AND THE MANNER IN WHICH IT IS TO BE PERFORMED.

FIELD OF THE INVENTION
[0001] The present invention relates generally to optical fiber devices, and in particular the present invention provides a system and a method for managing installation of optical fiber devices.
BACKGROUND OF THE INVENTION
[0002] In general, the demand for optical fiber devices is increasing at a fast pace as digital connectivity has become the need of the hour. Due to the increase in demand for the optical fiber devices, service providers are busy in installation of the optical fiber devices in different locations. While installation of the optical fiber devices, site engineers are required to plan the installation as per customer’s demands. Further, the installation of the optical fiber devices is required to be compliant with predefined standards.
[0003] In certain use cases, the customers may order the optical fiber devices from the service providers for internet connectivity usage. Depending on the order provided by the customers, the service provider may install the optical fiber devices and may enable internet connectivity to the customer. The process of installing the optical fiber devices based on the customer’s demands is a cumbersome and time-consuming task. In order to overcome this issue, the optical fiber devices may be installed in a particular location by the service providers in advance speculating there may be a requirement/demand from customers from that location. These locations may be manually planned locations by the service providers that require high operational costs. Pursuant to advance installation, there may be a situation that the customers demand may actually not be as much as speculated by the service provider in that particular location. Therefore, the operational costs spent on that particular location will be a waste.
[0004] In view of the above, there is a dire need for a system and a method for managing installations of optical fiber devices, which enhances customer satisfaction by meeting demands for fiber installations optimally.
SUMMARY OF THE INVENTION
[0005] One or more embodiments of the present disclosure provide a system and a method of managing installation of optical fiber devices.
[0006] In one aspect of the present invention, the method of managing installation of optical fiber devices is disclosed. The method includes retrieving, by one or more processors, data pertaining to a plurality of customers from one or more sources. Further, the method includes feeding, by the one or more processors, the retrieved data to a model for training. Further, the method includes analyzing, by the one or more processors, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.
[0007] In an embodiment, the data pertaining to the plurality of customers includes at least one of, onboarding data, service usage data, deactivation data and historical data.
[0008] In an embodiment, retrieving, by one or more processors, data pertaining to the plurality of customers from one or more sources, further includes the steps of pre-processing, by the one or more processors, the retrieved data in order to utilize the pre-processed data for training the model, and storing, by the one or more processors, the pre-processed data in a storage unit.
[0009] In an embodiment, pre-processing the retrieved data includes at least one of, normalizing the retrieved data and cleaning the retrieved data.
[0010] In an embodiment, the model is at least one of, an Artificial Intelligence/Machine Learning (AI/ML) model.
[0011] In an embodiment, analysing, by the one or more processors, utilizing the trained model, the retrieved data to predict the future locations for installation of the optical fiber devices, includes the steps of: performing, by the one or more processors, utilizing the trained model, a trend/pattern analysis of the plurality of customers, and predicting, by the one or more processors, utilizing the trained model, the future locations for installation of the optical fiber devices based on the trend/pattern analysis.
[0012] In an embodiment, data of the predicted future locations for installation of the optical fiber devices are stored in the storage unit.
[0013] In an embodiment, the method includes generating, by the one or more processors, a visual representation of the predicted future locations for installation of the optical fiber devices based on the analysis. Further, the method includes displaying, by the one or more processors, the generated visual representation of the predicted future locations for installation of the optical fiber devices to a user.
[0014] In one aspect of the present invention, the system of managing installation of optical fiber devices is disclosed. The system includes a retrieving unit, a feeding unit, an analysing unit and a generating unit. The retrieving unit is configured to retrieve data pertaining to a plurality of customers from one or more sources. Further, the feeding unit is configured to feed the retrieved data to a model for training. The analysing unit is configured to analyse, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.
[0015] In one aspect of the present invention, a non-transitory computer-readable medium having stored thereon computer-readable instructions is disclosed. The computer-readable instructions cause the processor to retrieve, data pertaining to a plurality of customers from one or more sources. Further, the processor feeds the retrieved data to a model for training. Further, the processor analyses, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.
[0016] Other features and aspects of this invention will be apparent from the following description and the accompanying drawings. The features and advantages described in this summary and in the following detailed description are not all-inclusive, and particularly, many additional features and advantages will be apparent to one of ordinary skill in the relevant art, in view of the drawings, specification, and claims hereof. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes and may not have been selected to delineate or circumscribe the inventive subject matter, resort to the claims being necessary to determine such inventive subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
[0018] FIG. 1 is an exemplary block diagram of an environment for managing installation of optical fiber devices, according to various embodiments of the present disclosure;
[0019] FIG. 2 is a block diagram of a system of FIG. 1, according to various embodiments of the present disclosure;
[0020] FIG. 3 is an example schematic representation of the system of FIG. 1 in which various entities operations are explained, according to various embodiments of the present system;
[0021] FIG. 4 illustrates a system architecture for managing installation of the optical fiber devices, in accordance with some embodiments;
[0022] FIG. 5 is an exemplary flow diagram illustrating the method for managing installation of the optical fiber devices, according to various embodiments of the present disclosure; and
[0023] FIG. 6 is a flow diagram illustrating an internal call flow for managing installation of the optical fiber devices, in accordance with some embodiments.
[0024] Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.
[0025] The foregoing shall be more apparent from the following detailed description of the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0026] Some embodiments of the present disclosure, illustrating all its features, will now be discussed in detail. It must also be noted that as used herein and in the appended claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise.
[0027] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure including the definitions listed here below are not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
[0028] A person of ordinary skill in the art will readily ascertain that the illustrated steps detailed in the figures and here below are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0029] Before discussing example, embodiments in more detail, it is to be noted that the drawings are to be regarded as being schematic representations and elements that are not necessarily shown to scale. Rather, the various elements are represented such that their function and general purpose becomes apparent to a person skilled in the art. Any connection or coupling between functional blocks, devices, components, or other physical or functional units shown in the drawings or described herein may also be implemented by an indirect connection or coupling. A coupling between components may also be established over a wireless connection. Functional blocks may be implemented in hardware, firmware, software or a combination thereof.
[0030] Further, the flowcharts provided herein, describe the operations as sequential processes. Many of the operations may be performed in parallel, concurrently or simultaneously. In addition, the order of operations maybe re-arranged. The processes may be terminated when their operations are completed, but may also have additional steps not included in the figured. It should be noted, that in some alternative implementations, the functions/acts/ steps noted may occur out of the order noted in the figured. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
[0031] Further, the terms first, second etc… may be used herein to describe various elements, components, regions, layers and/or sections, it should be understood that these elements, components, regions, layers and/or sections should not be limited by these terms. These terms are used only to distinguish one element, component, region, layer or section from another region, layer, or a section. Thus, a first element, component, region layer, or section discussed below could be termed a second element, component, region, layer, or section without departing form the scope of the example embodiments.
[0032] Spatial and functional relationships between elements (for example, between modules) are described using various terms, including “connected,” “engaged,” “interfaced,” and “coupled.” Unless explicitly described as being “direct,” when a relationship between first and second elements is described in the description below, that relationship encompasses a direct relationship where no other intervening elements are present between the first and second elements, and also an indirect relationship where one or more intervening elements are present (either spatially or functionally) between the first and second elements. In contrast, when an element is referred to as being "directly” connected, engaged, interfaced, or coupled to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a like fashion (e.g., "between," versus "directly between," "adjacent," versus "directly adjacent," etc.).
[0033] The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
[0034] As used herein, the singular forms “a,” “an,” and “the,” are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the terms “and/or” and “at least one of” include any and all combinations of one or more of the associated listed items. It will be further understood that the terms “comprises,” “comprising,” “includes,” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
[0035] Unless specifically stated otherwise, or as is apparent from the description, terms such as “processing” or “computing” or “calculating” or “determining” of “displaying” or the like, refer to the action and processes of a computer system, or similar electronic computing device/hardware, that manipulates and transforms data represented as physical, electronic quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.
[0036] Various embodiments of the present invention provide a system and method managing installations of the optical fiber devices. The disclosed system and method aim at enhancing the experience of the customer. In other words, the present invention provides a unique approach of predicting and identifying future locations for fiber device installations based on customer’s requirements. This enhances customer satisfaction by meeting demands for fiber installations optimally.
[0037] FIG. 1 illustrates an exemplary block diagram of an environment (100) for managing installation of optical fiber devices (e.g., optical fiber cables, fiber optic amplifiers, optical splitters, fiber optic sensors, fiber optic transceivers, optical switches or the like), according to various embodiments of the present disclosure. The environment (100) comprises a plurality of user equipment’s (UEs) (102-1, 102-2, ……,102-n). The at least one UE (102-n) from the plurality of the UEs (102-1, 102-2, ……102-n) is configured to connect to a system (108) via a communication network (106). Hereafter, label for the plurality of UEs or one or more UEs is 102.
[0038] In accordance with yet another aspect of the exemplary embodiment, the plurality of UEs (102) may be a wireless device or a communication device that may be a part of the system (108). The wireless device or the UE (102) may include, but are not limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device (e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch, a computer device, and so on), a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and/or any other type of computer device with wireless communication or Voice Over Internet Protocol (VoIP) capabilities. In an embodiment, the UEs (102) may include, but are not limited to, any electrical, electronic, electro-mechanical or an equipment or a combination of one or more of the above devices such as smartphones, virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, where the computing device may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as camera, audio aid, a microphone, a keyboard, input devices for receiving input from a user such as touch pad, touch enabled screen, electronic pen and the like. It may be appreciated that the UEs (102) may not be restricted to the mentioned devices and various other devices may be used. A person skilled in the art will appreciate that the plurality of UEs (102) may include a fixed landline, and a landline with assigned extension within the communication network (106).
[0039] The communication network (106), may use one or more communication interfaces/protocols such as, for example, Voice Over Internet Protocol (VoIP), 802.11 (Wi-Fi), 802.15 (including Bluetooth™), 802.16 (Wi-Max), 802.22, Cellular standards such as Code Division Multiple Access (CDMA), CDMA2000, Wideband CDMA (WCDMA), Radio Frequency Identification (e.g., RFID), Infrared, laser, Near Field Magnetics, etc.
[0040] The communication network (106) includes, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof. The communication network (106) may include, but is not limited to, a Third Generation (3G) network, a Fourth Generation (4G) network, a Fifth Generation (5G) network, a Sixth Generation (6G) network, a New Radio (NR) network, a Narrow Band Internet of Things (NB-IoT) network, an Open Radio Access Network (O-RAN), and the like.
[0041] The communication network (106) may also include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The communication network (106) may also include, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, a VOIP or some combination thereof.
[0042] One or more network elements can be, for example, but not limited to a base station that is located in the fixed or stationary part of the communication network (106). The base station may correspond to a remote radio head, a transmission point, an access point or access node, a macro cell, a small cell, a micro cell, a femto cell, a metro cell. The base station enables transmission of radio signals to the UE (102) or a mobile transceiver. Such a radio signal may comply with radio signals as, for example, standardized by a 3rd Generation Partnership Project (3GPP) or, generally, in line with one or more of the above listed systems. Thus, a base station may correspond to a NodeB, an eNodeB, a Base Transceiver Station (BTS), an access point, a remote radio head, a transmission point, which may be further divided into a remote unit and a central unit. The 3GPP specifications cover cellular telecommunications technologies, including radio access, core network, and service capabilities, which provide a complete system description for mobile telecommunications.
[0043] The system (108) is communicatively coupled to a server (104) via the communication network (106). The server (104) can be, for example, but not limited to a standalone server, a server blade, a server rack, an application server, a bank of servers, a business telephony application server (BTAS), a server farm, a cloud server, an edge server, home server, a virtualized server, one or more processors executing code to function as a server, or the like. In an implementation, the server (104) may operate at various entities or a single entity (include, but is not limited to, a vendor side, a service provider side, a network operator side, a company side, an organization side, a university side, a lab facility side, a business enterprise side, a defense facility side, or any other facility) that provides service.
[0044] The environment (100) further includes the system (108) communicably coupled to the server (e.g., remote server or the like) (104) and each UE of the plurality of UEs (102) via the communication network (106). The remote server (104) is configured to execute the requests in the communication network (106).
[0045] The system (108) is adapted to be embedded within the remote server (104) or is embedded as an individual entity. The system (108) is designed to provide a centralized and unified view of data and facilitate efficient business operations. The system (108) is authorized to access to update/create/delete one or more parameters of their relationship between the requests for data (pertaining to a plurality of customers), which gets reflected in real-time independent of the complexity of network.
[0046] In another embodiment, the system (108) may include an enterprise provisioning server (for example), which may connect with the remote server (104). The enterprise provisioning server provides flexibility for enterprises, ecommerce, finance to update/create/delete information related to the requests for the data in real time as per their business needs. A user with administrator rights can access and retrieve the requests for the data and perform real-time analysis in the system (108).
[0047] The system (108) may include, by way of example but not limitation, one or more of a standalone server, a server blade, a server rack, a bank of servers, a business telephony application server (BTAS), a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof. In an implementation, system (108) may operate at various entities or single entity (for example include, but is not limited to, a vendor side, service provider side, a network operator side, a company side, an organization side, a university side, a lab facility side, a business enterprise side, ecommerce side, finance side, a defense facility side, or any other facility) that provides service.
[0048] However, for the purpose of description, the system (108) is described as an integral part of the remote server (104), without deviating from the scope of the present disclosure. Operational and construction features of the system (108) will be explained in detail with respect to the following figures.
[0049] FIG. 2 illustrates a block diagram of the system (108) provided for managing installation of optical fiber devices, according to one or more embodiments of the present invention. As per the illustrated embodiment, the system (108) includes the one or more processors (202), the memory (204), an user interface (206), a display (208), an input device (210), and the database (214). Further the system (108) may comprise one or more processors (202). The one or more processors (202), hereinafter referred to as the processor (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, single board computers, and/or any devices that manipulate signals based on operational instructions. As per the illustrated embodiment, the system (108) includes one processor. However, it is to be noted that the system (108) may include multiple processors as per the requirement and without deviating from the scope of the present disclosure.
[0050] An information related to the request related to the data may be provided or stored in the memory (204) of the system (108). Among other capabilities, the processor (202) is configured to fetch and execute computer-readable instructions stored in the memory (204). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as disk memory, EPROMs, FLASH memory, unalterable memory, and the like.
[0051] The memory (204) may comprise any non-transitory storage device including, for example, volatile memory such as Random-Access Memory (RAM), or non-volatile memory such as Electrically Erasable Programmable Read-only Memory (EPROM), flash memory, and the like. In an embodiment, the system (108) may include an interface(s). The interface(s) may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as input/output (I/O) devices, storage devices, and the like. The interface(s) may facilitate communication for the system. The interface(s) 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 unit/engine(s) and the database (214). The processing unit/engine(s) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s).
[0052] The information related to the requests related to the data may further be configured to render on the user interface (206). The user interface (206) may include functionality similar to at least a portion of functionality implemented by one or more computer system interfaces such as those described herein and/or generally known to one having ordinary skill in the art. The user interface (206) may be rendered on the display (208), implemented using Liquid Crystal Display (LCD) display technology, Organic Light-Emitting Diode (OLED) display technology, and/or other types of conventional display technology. The display (208) may be integrated within the system (108) or connected externally. Further the input device(s) (210) may include, but not limited to, keyboard, buttons, scroll wheels, cursors, touchscreen sensors, audio command interfaces, magnetic strip reader, optical scanner, etc.
[0053] The database (214) may be communicably connected to the processor (202) and the memory (204). The database (214) may be configured to store and retrieve the request pertaining to features, or services or workflow of the system (108), access rights, attributes, approved list, and authentication data provided by an administrator. In another embodiment, the database (214) may be outside the system (108) and communicated through a wired medium and a wireless medium.
[0054] Further, the processor (202), in an embodiment, may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processor (202). In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processor (202) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processor (202) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the memory (204) may store instructions that, when executed by the processing resource, implement the processor (202). In such examples, the system (108) may comprise the memory (204) storing the instructions and the processing resource to execute the instructions, or the memory (204) may be separate but accessible to the system (108) and the processing resource. In other examples, the processor (202) may be implemented by an electronic circuitry.
[0055] In order for the system (108) to manage installation of the optical fiber devices, the processor (202) includes a retrieving unit (216), a feeding unit (218), an analyzing unit (220), a generating unit (222) and a storage unit (224). The retrieving unit (216), the feeding unit (218), the analysing unit (220), the generating unit (222) and the storage unit (224) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processor (202). In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processor (202) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processor (202) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the memory (204) may store instructions that, when executed by the processing resource, implement the processor. In such examples, the system (108) may comprise the memory (204) storing the instructions and the processing resource to execute the instructions, or the memory (204) may be separate but accessible to the system (108) and the processing resource. In other examples, the processor (202) may be implemented by the electronic circuitry.
[0056] In order for the system (108) to manage installation of the optical fiber devices, the retrieving unit (216), the feeding unit (218), the analysing unit (220), the generating unit (222) and the storage unit (224) are communicably coupled to each other. In an embodiment, the retrieving unit (216) retrieves data pertaining to a plurality of customers from one or more sources (e.g., website, company report, or the like). The data pertaining to the plurality of customers includes at least one of: an onboarding data, a service usage data, deactivation data and historical data. In other words, the data may be the historical data of the customer’s orders of optical fiber device installations.
[0057] The onboarding data refers to the process of integrating new customers into a service. The consumer onboarding involves guiding them through the initial setup, providing necessary information, and ensuring they understand how to use the service effectively. The customer deactivation data refers to the process of formally terminating a customer’s relationship with a service. This can occur for various reasons, such as switching to a different provider or discontinuing use of a service. The service usage data refers to the information collected and managed by a network’s systems regarding customer interactions, preferences, and account status. This data is crucial for analysing customer behaviour and managing the services.
[0058] In an embodiment, the retrieving unit (216) pre-processes the retrieved data to utilize the pre-processed data for training of a model. The retrieved data is pre-processed by normalizing the retrieved data and cleaning the retrieved data. Further, the retrieving unit (216) stores the pre-processed data in the storage unit (224). In an example, the data normalization is the process of reorganizing data within the database (214) so that the users can utilize it for further queries and analysis. The data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within the dataset.
[0059] The feeding unit (218) feeds the retrieved data (i.e., pre-processed data) to the model for training. The model can be, for example, but not limited to an Artificial Intelligence/Machine Learning (AI/ML) model. Further, the analysing unit (220) analyses, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices. In an embodiment, the analysing unit (220) performs, utilizing the trained model, the trend/pattern analysis related to one or more parameters of the plurality of customers. The one or more parameters pertaining to the plurality of customers includes at least one of, historical data pertaining to the plurality of customer orders for installation of the optical fiber devices. Further, the analysing unit (220) predicts, utilizing the trained model, the future locations for installation of the optical fiber devices based on the trend/pattern analysis. The data of the predicted future locations for installation of the optical fiber devices are stored in the storage unit (224). In another embodiment, the analysing unit (220) performs, utilizing the trained model, the trend/pattern analysis of the plurality of customers. Further, the analysing unit (220) predicts, utilizing the trained model, the future locations for installation of the optical fiber devices based on the trend/pattern analysis.
[0060] The analyzing unit (220) may periodically monitor and collect all the data of the customers and stores the data in the database (214). This previously stored data may be the historical data of the customer’s orders of fiber device installations. The analysing unit (220) may utilize the historical data of customer’s orders of the fiber device installations and accordingly the ML model may perform trend analysis in order to predict future locations for fiber device installations. For example, a customer may have ordered a particular type of fiber device for installation at the residence in the past from a particular location A. Similarly, multiple customers may have ordered similar type of fiber optic devices from the same location A. Using this historical data of multiple orders from multiple customers, the AI/ML model predicts a trend such as correlation between the location A and the type of fiber optic devices ordered from the location A, thereby predicting future location planning. Advantageously, through this automated location planning, the service providers saves time and their operational cost.
[0061] The generating unit (222) generates a visual representation of the predicted future locations for installation of the optical fiber devices based on the analysis. In an embodiment, the generating unit (222) displays the generated visual representation of the predicted future locations for installation of the optical fiber devices to the user. The generated visual representation is displayed to the user in at least one of, a graphical format via the UE (102). The example for managing installation of optical fiber devices is explained in FIG. 4 to FIG. 6.
[0062] FIG. 3 is an example schematic representation of the system (300) of FIG. 1 in which various entities operations are explained, according to various embodiments of the present system. It is to be noted that the embodiment with respect to FIG. 3 will be explained with respect to the first UE (102-1) and the system (108) for the purpose of description and illustration and should nowhere be construed as limited to the scope of the present disclosure.
[0063] As mentioned earlier, the first UE (102-1) includes one or more primary processors (305) communicably coupled to the one or more processors (202) of the system (108). The one or more primary processors (305) are coupled with a memory (310) storing instructions which are executed by the one or more primary processors (305). Execution of the stored instructions by the one or more primary processors (305) enables the UE (102-1). The execution of the stored instructions by the one or more primary processors (305) further enables the UE (102-1) to execute the requests in the communication network (106).
[0064] As mentioned earlier, the one or more processors (202) is configured to transmit a response content related to a data call request to the UE (102-1). More specifically, the one or more processors (202) of the system (108) is configured to transmit the response content to at least one of the UE (102-1). A kernel (315) is a core component serving as the primary interface between hardware components of the UE (102-1) and the system (108). The kernel (315) is configured to provide the plurality of response contents hosted on the system (108) to access resources available in the communication network (106). The resources include one of a Central Processing Unit (CPU), memory components such as Random Access Memory (RAM) and Read Only Memory (ROM).
[0065] As per the illustrated embodiment, the system (108) includes the one or more processors (202), the memory (204), the user interface (206), the display (208), and the input device (210). The operations and functions of the one or more processors (202), the memory (204), the user interface (206), the display (208), and the input device (210) are already explained in FIG. 2. For the sake of brevity, we are not explaining the same operations (or repeated information) in the patent disclosure. Further, the processor (202) includes the retrieving unit (216), the feeding unit (218), the analysing unit (220), the generating unit (222) and the storage unit (224). The operations and functions of the retrieving unit (216), the feeding unit (218), the analysing unit (220), the generating unit (222) and the storage unit (224) are already explained in FIG. 2. For the sake of brevity, we are not explaining the same operations (or repeated information) in the patent disclosure.
[0066] FIG. 4 illustrates a system architecture (400) for managing installation of the optical fiber devices, in accordance with some embodiments. The system architecture (400) includes a Fault management system (FMS) (406). At the FMS (406), multiple types of data are fed. The data may be one of but not limited to, customer onboarding data, customer deactivation and system-based data. In other words, the data may be the historical data of the customers optical fiber orders. Further, the system architecture (400) includes a data integration unit (408) used for combining data from different sources into a single, unified view.
[0067] Further, the system architecture (400) includes an analysing engine (402). The analysing engine (402) includes the retrieving unit (216). The retrieved data from the FMS (406) is processed by the retrieving unit (216). The retrieving unit (216) may normalize and clean the retrieved data from the FMS (406). The data normalization is the process of reorganizing data within the database (214) so that the users can utilize it for training of an AI/ML model. The data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.
[0068] The analysing engine (402) further includes the feeding unit (218). The feeding unit (218) analyzes the integrated data to identify patterns and trends to predict future locations for fiber device installations by using the AI/ML model. The analysing engine (402) further includes the database (214) that may be a distributed data lake used to store the processed data and algorithm outputs.
[0069] The analysing engine (402) further includes a workflow manager (404). The workflow manager (404) manages the workflow. The workflow is the collection of the activities that must be performed in order to complete a task.
[0070] The analysing engine (402) further includes the analyzing unit (220) (e.g., trend analyzing unit (220)). The analyzing unit (220) is used to examine and predict future locations for fiber device installations using AI/ML model based on historical data of customer’s order of fiber device installations.
[0071] The system architecture (400) further includes the user interface (206). The future locations for fiber device installations detected by the analysing engine (402) are displayed in the form of trend pattern graph via the user interface (206) to the service providers. In an embodiment, the FMS (406) may comprise of AI/ML model. The AI/ML model may predict and identify future locations for fiber device installations using trend analysis and historical data historical data of customer’s orders of fiber device installations. Advantageously, the invention saves time and resources by automatically detecting future locations for fiber device installations.
[0072] FIG. 5 is an exemplary flow diagram (500) illustrating the method for managing installation of the optical fiber devices, according to various embodiments of the present disclosure.
[0073] At 502, the method includes retrieving the data pertaining to the plurality of customers from one or more sources. In an embodiment, the method allows the retrieving unit (216) to retrieve data pertaining to the plurality of customers from the one or more sources.
[0074] At 504, the method includes feeding the retrieved data to the model for training. In an embodiment, the method allows the feeding unit (218) to feed the retrieved data to the model for training.
[0075] At 506, the method includes analysing, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices. In an embodiment, the method allows the analyzing unit (220) to, analyze, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.
[0076] FIG. 6 is a flow diagram (600) illustrating an internal call flow for managing installation of the optical fiber devices, in accordance with some embodiments. The method disclosed below is purely exemplary in nature and should not be construed as limiting the scope of the present invention.
[0077] At step 602, the retrieving multiple types of data of customers from the external sources and feed the data to the FMS (406). The data may be one of but not limited to the historical data, the consumer onboarding, the customer deactivation and the system-based data. In other words, the data may be the historical data of the customer’s orders of optical fiber device installations.
[0078] At step 604, the data integration is performed and the retrieved data from the FMS (406) is processed by the retrieving unit (216). The retrieving unit (216) may normalize and clean the retrieved data from the FMS (406). The preprocessed data may be stored in the database (214). The data normalization is the process of reorganizing data within the database (214) so that the users can utilize it for further queries and analysis. The data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within the dataset.
[0079] At step 606, the method includes analyzing the data and performing the trend analysis for predicting future locations for fiber device installations. In an embodiment, the analyzing engine (402) (e.g., brain or the like) including the AI/ML model that may be designed to analyze multiple algorithms, trends, predictions, anomaly detection and provide generative the AI outputs. The analyzing engine (402) may periodically monitor and collect all the data of the customers and stores the data in the database (214). This previously stored data may be the historical data of the customer’s orders of fiber device installations. The analyzing engine (402) may utilize the historical data of customer’s orders of the fiber device installations and accordingly the ML model may perform trend analysis in order to predict future locations for fiber device installations. For example, a customer may have ordered a particular type of fiber device for installation at the residence in the past from a particular location A. Similarly, multiple customers may have ordered similar type of fiber optic devices from the same location A. Using this historical data of multiple orders from multiple customers, the AI/ML model predicts a trend such as correlation between the location A and the type of fiber optic devices ordered from the location A, thereby predicting future location planning. Advantageously, through this automated location planning, the service providers save time and their operational cost.
[0080] At step 608, the method includes storing the resulting output such as predicted future locations for fiber device installations in the database (214). The future locations for fiber device installations predicted by the analyzing engine (402) are stored in the database (214).
[0081] At step 610, the method includes generating the visual representation of the predicted future locations for fiber device installations provided by the analyzing engine (402). In an embodiment, the visual representation of the future locations for fiber device installations predicted by the analyzing engine (402) may be presented in the form of the trend pattern graph.
[0082] At step 612, the method includes displaying predicted future locations for fiber device installations and all the relevant data and insights derived from the analysis. The future locations for fiber device installations predicted by the analyzing engine (402) are displayed in the form of trend pattern graph via the user interface (206) to the service providers.
[0083] Below is the technical advancement of the present invention:
[0084] The proposed method provides a unique approach of predicting and identifying future locations for fiber device installations based on the prediction performed by the AI/ML model utilizing the historical data of customer fiber orders and trend analysis. This automated location planning for future installations of fiber devices reduce operational costs of service provides and ensures the customers satisfaction. The present invention provides data-driven insights for future installation trends for improved decision-making.
[0085] A person of ordinary skill in the art will readily ascertain that the illustrated embodiments and steps in description and drawings (FIGS. 1-6) are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0086] Method steps: A person of ordinary skill in the art will readily ascertain that the illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0087] The present invention offers multiple advantages over the prior art and the above listed are a few examples to emphasize on some of the advantageous features. The listed advantages are to be read in a non-limiting manner.

REFERENCE NUMERALS
[0088] Environment - 100
[0089] UEs– 102, 102-1-102-n
[0090] Server - 104
[0091] Communication network – 106
[0092] System – 108
[0093] Processor – 202
[0094] Memory – 204
[0095] User Interface – 206
[0096] Display – 208
[0097] Input device – 210
[0098] Database – 214
[0099] Retrieving unit– 216
[00100] Feeding unit – 218
[00101] Analyzing unit – 220
[00102] Generating engine – 222
[00103] Storage unit – 224
[00104] System - 300
[00105] Primary processors -305
[00106] Memory– 310
[00107] Kernel– 315
[00108] System architecture - 400
[00109] Analyzing engine – 402
[00110] Workflow manger– 404
[00111] FMS – 406
[00112] Data integration unit – 408
,CLAIMS:CLAIMS:
We Claim:
1. A method of managing installation of optical fiber devices, the method comprising the steps of:
retrieving, by one or more processors (202), data pertaining to a plurality of customers from one or more sources;
feeding, by the one or more processors (202), the retrieved data to a model for training; and
analysing, by the one or more processors (202), utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.

2. The method as claimed in claim 1, wherein the data pertaining to the plurality of customers includes at least one of, onboarding data, service usage data, deactivation data and historical data.

3. The method as claimed in claim 1, wherein the step of retrieving, by one or more processors (202), data pertaining to the plurality of customers from one or more sources, further includes the steps of:
pre-processing, by the one or more processors (202), the retrieved data in order to utilize the pre-processed data for training of the model; and
storing, by the one or more processors (202), the pre-processed data in a storage unit (224).

4. The method as claimed in claim 3, wherein pre-processing the retrieved data includes at least one of, normalizing the retrieved data and cleaning the retrieved data.

5. The method as claimed in claim 1, wherein the model is at least one of, an Artificial Intelligence/Machine Learning (AI/ML) model.

6. The method as claimed in claim 1, wherein the step of analysing, by the one or more processors (202), utilizing the trained model, the retrieved data to predict the future locations for installation of the optical fiber devices, includes the steps of:
performing, by the one or more processors (202), utilizing the trained model, a trend/pattern analysis of the plurality of customers; and
predicting, by the one or more processors (202), utilizing the trained model, the future locations for installation of the optical fiber devices based on the trend/pattern analysis.

7. The method as claimed in claim 1, wherein data of the predicted future locations for installation of the optical fiber devices are stored in the storage unit (224).

8. The method as claimed in claim 1, wherein the method further comprising the steps of:
generating, by the one or more processors (202), a visual representation of the predicted future locations for installation of the optical fiber devices based on the analysis; and
displaying, by the one or more processors (202), the generated visual representation of the predicted future locations for installation of the optical fiber devices to a user.

9. A system (108) of managing installation of optical fiber devices, the system (108) comprising the steps of:
a retrieving unit (216), configured to, retrieve data pertaining to a plurality of customers from one or more sources;
a feeding unit (218), configured to, feed, the retrieved data to a model for training; and
an analysing unit (220), configured to, analyse, utilizing the trained model, the retrieved data to predict future locations for installation of the optical fiber devices.

10. The system (108) as claimed in claim 9, wherein the data pertaining to the plurality of customers includes at least one of, onboarding data, service usage data, deactivation data and historical data.

11. The system (108) as claimed in claim 9, wherein the retrieving unit (216), retrieves, data pertaining to the plurality of customers from the one or more sources, by:
pre-process, the retrieved data in order to utilize the pre-processed data for training of the model; and
store, the pre-processed data in a storage unit (224).

12. The system (108) as claimed in claim 11, wherein pre-processing the retrieved data includes at least one of, normalizing the retrieved data and cleaning the retrieved data.

13. The system (108) as claimed in claim 9, wherein the model is at least one of, an Artificial Intelligence/Machine Learning (AI/ML) model.

14. The system (108) as claimed in claim 9, wherein the analysing unit (220), analyses, utilizing the trained model, the retrieved data to predict the future locations for installation of the optical fiber devices, by:
performing, utilizing the trained model, a trend/pattern analysis of the plurality of customers; and
predicting, utilizing the trained model, the future locations for installation of the optical fiber devices based on the trend/pattern analysis.

15. The system (108) as claimed in claim 9, wherein data of the predicted future locations for installation of the optical fiber devices are stored in the storage unit (224).

16. The system (108) as claimed in claim 9, wherein a generating unit (222) is configured to:
generate, a visual representation of the predicted future locations for installation of the optical fiber devices based on the analysis; and
display the generated visual representation of the predicted future locations for installation of the optical fiber devices to a user.

17. A User Equipment (UE) (102-1), comprising:
one or more primary processors (305) communicatively coupled to one or more processors (202) of a system (108), the one or more primary processors (305) coupled with a memory (310), wherein said memory (310) stores instructions which when executed by the one or more primary processors (305) causes the UE (102-1) to:
transmit, a request by a user to the one or more processors (202) for predicting the future locations for installation of the optical fiber devices;
wherein the one or more processors (202) is configured to perform the steps as claimed in claim 1.