TECHNICAL FIELD
[001] The present disclosure relates to the field of meteorology. More particularly the present disclosure relates to a weather forecast generating device and further provides system and method for generating weather forecast.
BACKGROUND
[002] 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.
[003] In this era of modern technology, where we have everything next to perfect and to support our needs leading to better living. One such technology is weather satellites. It's because of them that we are able to get information about the upcoming change in weather and can take certain steps to protect us from the severe weather conditions. But this technology is not precise enough for us. It can predict the time range of the weather; when it is about to change. Likewise, during the rainy season, it is not confirmed that when it will rain so we have to stop our outdoor tasks way before time wasting that time range which can be used to do our outdoor tasks or even other tasks if we know the exact time of when it is about to rain. We can solve this particular problem using basic tools and some advanced technologies like Machine Learning.
[004] The weather apps are commonly used for checking the climate change for the day or two. Image Processing with Advanced Machine Learning models is used to observe the visual change in sky and predict the possibilities of rain but it takes a lot of time to predict and precision isn’t that good. Also, it takes a lot of computation power for the same.
[005] There is therefore a need in the art to provide a weather forecasting device that fulfils the aforementioned needs and to address the occasional inefficacy of prior art or conventional devices. Further, provide system and method for generating weather forecast.
OBJECTS OF THE PRESENT DISCLOSURE
[006] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below. 2
[007] It is an object of the present disclosure to provide a weather forecast generating device.
[008] It is another object of the present disclosure to provide a weather forecast generating device that enhances accuracy of forecast.
[009] It is another object of the present disclosure to provide a weather forecast generating device that enables generating an alert based on sudden changes in weather conditions.
[0010] It is another object of the present disclosure to provide a weather forecast generating device that enables collecting temporal, spatial and diversified data leading to better and precise prediction of weather for a targeted area.
[0011] It is another object of the present disclosure to provide system and method for generating weather forecast.
[0012] It is yet another object of the present disclosure to provide a weather forecast generating device that is cost effective and easy to implement.
SUMMARY
[0013] The present disclosure relates to the field of meteorology. More particularly the present disclosure relates to a weather forecast generating device and further provides system and method for generating weather forecast.
[0014] An aspect of the present disclosure relates to a system for generating weather forecast. The system can include: a processor coupled with a memory, the memory storing instructions executable by the processor to: receive a signal from a weather forecast device (WFD), wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; extract signal strength from the received signal; compare the extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in the received signal is determined, and wherein based on the determined distortion weather forecast is generated; and store the generated weather forecast on forecast on any or a combination of the server, the first database and a second database.
[0015] In an embodiment, the system comprises a plurality of WFD, and wherein each of WFD is operatively coupled with the server, and wherein the generated weather forecast by each of plurality of WFD device is transmitted to the server and stored on the server. 3
[0016] In an embodiment, the one or more attributes is selected from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
[0017] In an aspect, the processor configured to monitor the generated weather forecast, and generate an alert in case an event of abrupt change in weather forecast is detected.
[0018] Another aspect of the present disclosure relates to a method for generating weather forecast comprising the steps of: receiving, by a processor, a signal from a weather forecast device (WFD), wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; extracting, by the processor, signal strength from the received signal; comparing, by the processor, the extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in the received is determined, and wherein based on the determined distortion weather forecast is generated; and storing, by the processor, the generated weather forecast on any or a combination of the server, the first database and a second database.
[0019] In an aspect, the method comprises a plurality of WFD, and wherein each of WFD is operatively coupled with the server, and wherein the generated weather forecast by each of plurality of WFD device is transmitted to the server and stored on the server.
[0020] In an aspect, the one or more attributes is selected from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
[0021] In an aspect, the method comprises monitoring the generated weather forecast, and generating an alert in case an event of abrupt change in the weather forecast is detected.
[0022] Yet another aspect of the present disclosure relates to a weather forecast device (WFD).The device can include: a first transceiver configured to receive a signal, wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; a decibel meter operatively coupled with the first transceiver adapted to extract signal strength from the received signal; a control unit configured to compare the extracted attribute with a pre-defined attribute stored in a first database, wherein based on the comparison, distortion in the received is determined, and wherein based on the determined distortion weather forecast is generated.
[0023] In an aspect, the device comprises a second transceiver configured to transmit the generated weather forecast to any or a combination of the server, the first database and a second database. 4
[0024] In an aspect, the device comprises a power storage unit to provide power to the first transceiver, the second transceiver, the decibel meter and the control unit.
[0025] In an aspect, the device comprises a housing to envelop the device and provide support to the device.
BRIEF DESCRIPTION OF THE DRAWINGS
[0026] In the figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[0027] FIG. 1 illustrates an exemplary network architecture in which or with which proposed system can be implemented in accordance with an embodiment of the present disclosure.
[0028] FIG.2 illustrates an exemplary representation of various modules of the proposed system for lane detection in accordance to an embodiment of the present disclosure.
[0029] FIG. 3 illustrates an exemplary flowchart representation of proposed method for generating weather forecast in accordance to an embodiment of the present disclosure.
[0030] FIG. 4 illustrates an exemplary representations of weather forecast generating device in accordance with an embodiment of the present disclosure.
[0031] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
DETAILED DESCRIPTION
[0032] 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.
[0033] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be 5
apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0034] Embodiments of the present invention include various steps, which will be described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, steps may be performed by a combination of hardware, software, and firmware and/or by human operators.
[0035] Various methods described herein may be practiced by combining one or more machine-readable storage media containing the code according to the present invention with appropriate standard computer hardware to execute the code contained therein. An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with various methods described herein, and the method steps of the invention could be accomplished by modules, routines, subroutines, or subparts of a computer program product.
[0036] If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0037] 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.
[0038] Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. These exemplary embodiments are provided only for illustrative purposes and so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. The invention disclosed may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Various modifications will be readily apparent to persons skilled in the art. The general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the invention. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that 6
such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure). Also, the terminology and phraseology used is for the purpose of describing exemplary embodiments and should not be considered limiting. Thus, the present invention is to be accorded the widest scope encompassing numerous alternatives, modifications and equivalents consistent with the principles and features disclosed. For purpose of clarity, details relating to technical material that is known in the technical fields related to the invention have not been described in detail so as not to unnecessarily obscure the present invention.
[0039] Thus, for example, 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 element.
[0040] Embodiments of the present invention may be provided as a computer program product, which may include a machine-readable storage medium tangibly embodying thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The term “machine-readable storage medium” or “computer-readable storage medium” includes, but is not limited to, fixed (hard) drives, magnetic tape, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, PROMs, random access memories (RAMs), programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).A machine-readable medium may include a non-transitory medium in which data may be stored and that does not include carrier waves and/or transitory electronic signals propagating wirelessly or over wired connections.
7
Examples of a non-transitory medium may include, but are not limited to, a magnetic disk or tape, optical storage media such as compact disk (CD) or digital versatile disk (DVD), flash memory, memory or memory devices. A computer-program product may include code and/or machine-executable instructions that may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc.
[0041] Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks (e.g., a computer-program product) may be stored in a machine-readable medium. A processor(s) may perform the necessary tasks.
[0042] Systems depicted in some of the figures may be provided in various configurations. In some embodiments, the systems may be configured as a distributed system where one or more components of the system are distributed across one or more networks in a cloud computing system.
[0043] 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.
[0044] All methods described herein may 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. 8
[0045] Various terms as used herein are shown below. 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.
[0046] The present disclosure relates to the field of meteorology. More particularly the present disclosure relates to a weather forecast generating device and further provides system and method for generating weather forecast.
[0047] An aspect of the present disclosure relates to a system for generating weather forecast. The system can include: a processor coupled with a memory, the memory storing instructions executable by the processor to: receive a signal from a weather forecast device (WFD), wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; extract signal strength from the received signal; compare the extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in the received signal is determined, and wherein based on the determined distortion weather forecast is generated; and store the generated weather forecast on forecast on any or a combination of the server, the first database and a second database.
[0048] In an embodiment, the system comprises a plurality of WFD, and wherein each of WFD is operatively coupled with the server, and wherein the generated weather forecast by each of plurality of WFD device is transmitted to the server and stored on the server.
[0049] In an embodiment, the one or more attributes is selected from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
[0050] Another aspect of the present disclosure relates to a method for generating weather forecast comprising the steps of: receiving, by a processor, a signal from a weather forecast device (WFD), wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; extracting, by the processor, signal strength from the received signal; comparing, by the processor, the extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in the received is determined, and wherein based on the determined distortion weather forecast is generated; and storing, by the processor, the generated weather forecast on any or a combination of the server, the first database and a second database. 9
[0051] In an aspect, the method comprises a plurality of WFD, and wherein each of WFD is operatively coupled with the server, and wherein the generated weather forecast by each of plurality of WFD device is transmitted to the server and stored on the server.
[0052] In an aspect, the one or more attributes is selected from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
[0053] Yet another aspect of the present disclosure relates to a weather forecast device (WFD). The device can include: a first transceiver configured to receive a signal, wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel; a decibel meter operatively coupled with the first transceiver adapted to extract signal strength from the received signal; a control unit configured to compare the extracted attribute with a pre-defined attribute stored in a first database, wherein based on the comparison, distortion in the received is determined, and wherein based on the determined distortion weather forecast is generated.
[0054] In an aspect, the device comprises a second transceiver configured to transmit the generated weather forecast to any or a combination of the server, the first database and a second database.
[0055] In an aspect, the device comprises a power storage unit to provide power to the first transceiver, the second transceiver, the decibel meter and the control unit.
[0056] In an aspect, the device comprises a housing to envelop the device and provide support to the device.
[0057] FIG. 1 illustrates an exemplary network architecture in which or with which proposed system can be implemented in accordance with an embodiment of the present disclosure.
[0058] As illustrated, in a network implementation, the system 102 can be communicatively coupled with plurality of weather forecast devices (WFDs) 106-1, 106-2….106-N (collectively referred to as weather forecast devices 106 or WFDs 106 and individually referred to as weather forecast device 106 or WFD 106 hereinafter) through network 104. The system 102 can be implemented using any or a combination of hardware components and software components such as server, a computing device, a security device and the like, such that embodiments of the present disclosure can generate weather forecast.
[0059] The network 104 can be a wireless network, a wired network or a combination thereof that can be implemented as one of the different types of networks, such as Intranet, Local Area Network (LAN), Wide Area Network (WAN), Internet, and the like. Further, the 10
network 104 can either be a dedicated network or a shared network. The shared network can represent an association of the different types of networks that can use variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like.
[0060] In an embodiment, the system 102 can accept the signals received by the WFDs 106. It would be appreciated by the person skilled in the art that the signals generally broadcasted using an active channel can be received by the WFDs 106 for analysis and can be analysed for distortion in the received signals. Further, based on analysis the weather forecast can be generated.
[0061] In an embodiment, the broadcasted signal can include any or a combination of UHF signals, VHF signals, RF signals and the like that are generally commercially and privately used for long range communications. In an embodiment, the system 102 can be used to detect the strength of the received signals and based on analysis and the detected strength of the signals the weather forecast can be generated.
[0062] It would be appreciated by the person skilled in the art that based on the analysis of the received signals a weather forecast can be generated with enhanced accuracy that can be used to predict precisely the expected change in weather conditions or detect expected change in weather conditions.
[0063] FIG.2 illustrates an exemplary representation of various modules of the proposed system for lane detection in accordance to an embodiment of the present disclosure.
[0064] In an aspect, the system 102 may comprise one or more processor(s) 202. The one or more processor(s) 202 may 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) 202 are configured to fetch and execute computer-readable instructions stored in a memory 206 of the system 102. The memory 206 may 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 206 may comprise 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.
[0065] The system 102 may also comprise an interface(s) 204. The interface(s) 204 may comprise 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) 204 may facilitate communication of system 102 with various devices coupled to the system 102. The 11
interface(s) 204 may also provide a communication pathway for one or more components of the system 102. Examples of such components include, but are not limited to, processing engine(s) 208 and data 210.
[0066] The processing engine(s) 208 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) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may comprise 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 processing engine(s) 208. In such examples, the system 102 may comprise 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 processing engine(s) 208 may be implemented by electronic circuitry.
[0067] The data 210 may comprise data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 208.
[0068] In an exemplary embodiment, the processing engine(s) 208 may comprise a signal acquisition module 212, a signal processing module 214, a signal collating module 216, a weather forecasting module 218 and other module(s) 220.
[0069] It would be appreciated that modules being described are only exemplary modules and any other module or sub-module may be included as part of the system 102. These modules too may be merged or divided into super-modules or sub-modules as may be configured.
[0070] In an embodiment, the signal acquisition module 212 configured to acquire the signals by the WFDs 106. The signals received can include any or a combination of UHF signals, VHF signals, RF signals and the like that can be generally commercially and privately used for long range communications.
[0071] In an embodiment, the acquired signals are filtered to remove noise signals from the received signals. Further, the filtered signals are optimized. The optimization of the signals can include amplification of the signals and the like. In an embodiment, the signal can be amplified then filtered or filtered then amplified as per requirement. 12
[0072] In an embodiment, the signal processing module 214 can be configured to process the received signals. The signal processing comprises extracting one or more attributes and based on the extracted one or more parameters determine the signal strength.
[0073] In an embodiment, the acquired signals can include various noise signals blended with the original broadcasted signal that needs to be removed to improve the quality of the signals for better accuracy of the system 102.
[0074] In an embodiment, the signal collating module 216 can be configured to collate one or more attributes from the WFDs 106 to create a set of temporal and spatial data that can be used for creating multi-dimensional data. In an embodiment, the WFDs 106 can be associated with the location information of respective WFD 106.
[0075] For example, in a system with plurality of WFDs 106 each WFD 106 can be operatively coupled with the system 102. The WFD 106 can be located at various locations. The system 102 can receive one or more attributes from various WFDs to generate a multi-dimensional data. The multi-dimensional data can be created from the spatial and temporal data.
[0076] It would be appreciated by the person skilled in the art that the multi-dimensional data created due to input from plurality of WFDs 106 can be used to increase accuracy of the system 102.
[0077] In an embodiment, the weather forecasting module 218 can be configured to compare the processed signal with a pre-defined signal stored in a first database. Based on comparison the weather forecast can be generated.
[0078] In an embodiment, based on the created multi-dimensional data a processor can be configured to execute a set of instructions to determine the weather parameters accurately thereby forecasting the weather.
[0079] In an embodiment, the weather forecasting module 218 can be configured to monitor the generated weather forecast in real-time. Further, based on monitoring if an event of change in weather forecast in near future is detected an alert can be generated based on the detected event. In an embodiment, the generated alert can be communicated to a computing device associated with a user.
[0080] For example, whenever there is a change in the weather it brings distortion in Signals that we use for different purposes. Similarly, satellite TV does face the same when it comes to weather change. So, why not use this distortion for our own benefit. Using this signal disruption and set of instructions, we can predict the change in weather with far more accuracy than the billion-dollar satellite. The data is collected on temporal basis from a node 13
and is shared with server and nearby node creating a set of temporal and spatial data which is then shared with other nodes thus creating multi-dimensional data which is best for Advanced Machine Learning Algorithm to make better prediction.
[0081] FIG. 3 illustrates an exemplary flowchart representation of proposed method for generating weather forecast in accordance to an embodiment of the present disclosure.
[0082] In an aspect, the proposed method may be described in general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, etc., that perform particular functions or implement particular abstract data types. The method can also be practiced in a distributed computing environment where functions are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, computer executable instructions may be located in both local and remote computer storage media, including memory storage devices.
[0083] The order in which the method as described is not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement the method or alternate methods. Additionally, individual blocks may be deleted from the method without departing from the spirit and scope of the subject matter described herein. Furthermore, the method may be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below, the method may be considered to be implemented in the above described system.
[0084] In an embodiment, step 302 pertains to receiving a signal from a weather forecast device (WFD), wherein said signal comprises one or more attributes, and wherein said signal is broadcast using an active channel. Further, step 304 pertains to extracting signal strength from said received signal.
[0085] Step 306 pertains to comparing said extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in said received is determined, and wherein based on said determined distortion weather forecast is generated. Further, step 308 pertains to storing said generated weather forecast on any or a combination of the server, the first database and a second database.
[0086] FIG. 4 illustrates an exemplary representations of weather forecast generating device in accordance with an embodiment of the present disclosure.
[0087] In an exemplary embodiment, the weather forecast device WFD 400 comprises a first housing 402 for enveloping various components. Shape of the first housing 402 can 14
include cuboidal, square, cylindrical and the like. In an exemplary embodiment, the device 400 comprises a top cover 404 and a bottom cover 406.
[0088] In an exemplary embodiment, the device 400 comprises a first transceiver (not shown) configured to receive a signal, wherein the signal comprises one or more attributes, and wherein the signal is broadcasted using an active channel. In an exemplary embodiment, the device 400 comprises a decibel meter 408 operatively coupled with the first transceiver adapted to extract signal strength from the received signal.
[0089] In an exemplary embodiment, the device 400 comprises a control unit 412 configured to compare the extracted attribute with a pre-defined attribute stored in a first database, wherein based on the comparison, distortion in the received is determined, and wherein based on the determined distortion weather forecast is generated. In an embodiment, the control unit 412 can include one or more processors or controllers. Examples of controllers include, but are not limited to PIC® 16F877A microcontroller, AVR® ATmega8& ATmega16, Renesas® microcontroller and the like. Examples of processor can 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. In a preferred embodiment, the control unit 412 comprises Arduino.
[0090] In an embodiment, the device 400 comprises a second transceiver 414 configured to transmit the generated weather forecast to any or a combination of the server, the first database and a second database. The first transceiver and the second transceiver 414 can include a Wifi module, a Bluetooth module and the like.
[0091] In an embodiment, the device comprises a power storage unit 410 to provide power to the first transceiver, the second transceiver, the decibel meter and the control unit.
[0092] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
[0093] Computer system 500 includes a bus 520 or other communication mechanism for communicating information, and a processor 570 coupled with bus 520 for processing information. Computer system 500 can also include a main memory 530 or other non-transitory computer-readable medium, such as a random-access memory (RAM) or other dynamic storage device, which can then be coupled to bus 520 for storing information and instructions to be executed by processor 570. Main memory 530 also may be used for storing temporary variables or other intermediate information during execution of instructions to be
15
executed by processor 570. Computer system 500 may further include a read only memory (ROM) 540 or other static storage device coupled to bus 520 for storing static information and instructions for processor 570. A data/external storage device 510, such as a magnetic disk or optical disk, is provided and coupled to bus 520 for storing information and instructions.
[0094] Computer system 500 may be coupled via bus 520 to a display (not shown), such as a cathode ray tube (CRT), for displaying information to a user. An input device (not shown), including alphanumeric and other keys, can be coupled to bus 520 for communicating information and command selections to processor 570. Another type of user input device can be cursor control, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 570 and for controlling cursor movement on display. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane.
[0095] The invention is related to the use of computer system 500 for creation and management of BOMs as elaborated above. According to some embodiments of the invention, such use may be provided by computer system 500 in response to processor 570 executing one or more sequences of one or more instructions contained in the main memory 530. Such instructions may be read into main memory 530 from another computer-readable medium, such as storage device 550. Execution of the sequences of instructions contained in main memory 530 causes processor 570 to perform the process steps described herein. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in main memory 530. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware circuitry and software.
[0096] The term “computer-readable medium” as used herein refers to any medium that participates in providing instructions to processor 570 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device 550. Volatile media includes dynamic memory, such as main memory 530. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 520. Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. 16
[0097] Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.
[0098] Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to processor 570 for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 500 can receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to bus 520 can receive the data carried in the infrared signal and place the data on bus 520. Bus 520 carries the data to main memory 530, from which processor 570 retrieves and executes the instructions. The instructions received by main memory 530 may optionally be stored on storage device 550 either before or after execution by processor 570.
[0099] Computer system 500 also includes a communication interface 560 coupled to bus 520. Communication interface 560 can provide a two-way data communication coupling to a network link (not shown) that can be connected to a local network (not shown). For example, communication interface 560 may be an integrated services digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 560 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, communication interface 560 sends and receives electrical, electromagnetic or optical signals that carry data streams representing various types of information.
[00100] Although the proposed system has been elaborated as above to include all the main parts, it is completely possible that actual implementations may include only a part of the proposed modules/engines or a combination of those or a division of those in various combinations across multiple devices that can be operatively coupled with each other, including in the cloud. Further the modules/engines can be configured in any sequence to achieve objectives elaborated. Also, it can be appreciated that proposed system can be configured in a computing device or across a plurality of computing devices operatively 17
connected with each other, wherein the computing devices can be any of a computer, a laptop, a smart phone, an Internet enabled mobile device and the like. All such modifications and embodiments are completely within the scope of the present disclosure.
[00101] Embodiments of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc.) or combining software and hardware implementation that may all generally be referred to herein as a “circuit,” “module,” “component,” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product comprising one or more computer readable media having computer readable program code embodied thereon.
[00102] 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.
[00103] 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. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean “communicatively coupled with” over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[00104] It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In 18
particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refers to at least one of something selected from the group consisting of A, B, C …. and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[00105] 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 people 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
[00106] The present disclosure provides a weather forecast generating device.
[00107] The present disclosure provides a weather forecast generating device that enhances accuracy of forecast.
[00108] The present disclosure provides a weather forecast generating device that enables generating an alert based on sudden changes in weather conditions.
[00109] The present disclosure provides a weather forecast generating device that enables collecting temporal, spatial and diversified data leading to better and precise prediction of weather for a targeted area.
[00110] The present disclosure provides system and method for generating weather forecast.
[00111] The present disclosure provides a weather forecast generating device that is cost effective and easy to implement.

We Claim:
1. A system for generating weather forecast, said system comprising:
a processor coupled with a memory, the memory storing instructions executable by the processor to:
receive a signal from a weather forecast device (WFD), wherein said signal comprises one or more attributes, and wherein said signal is broadcasted using an active channel;
extract signal strength from said received signal;
compare said extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in said received signal is determined, and wherein based on said determined distortion weather forecast is generated; and
store said generated weather forecast on forecast on any or a combination of the server, the first database and a second database.
2. The system as claimed in claim 1, wherein said system comprises a plurality of WFD, and wherein each of WFD is operatively coupled with said server, and wherein said generated weather forecast by each of plurality of WFD device is transmitted to said server and stored on said server.
3. The system as claimed in claim 2, wherein said one or more attributes is selected from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
4. The system as claimed in claim 1, wherein said processor configured to monitor the generated weather forecast, and generate an alert in case an event of abrupt change in weather forecast is detected.
5. A method for generating weather forecast comprising the steps of:
receiving, by a processor, a signal from a weather forecast device (WFD), wherein said signal comprises one or more attributes, and wherein said signal is broadcasted using an active channel;
extracting, by said processor, signal strength from said received signal;
comparing, by said processor, said extracted signal strength with a pre-defined signal strength stored in a first database, wherein based on the comparison, distortion in
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said received is determined, and wherein based on said determined distortion weather forecast is generated; and
storing, by said processor, said generated weather forecast on any or a combination of the server, the first database and a second database.
6. The method as claimed in claim 5, wherein said method comprises a plurality of WFD, and wherein each of WFD is operatively coupled with said server, and wherein said generated weather forecast by each of plurality of WFD device is transmitted to said server and stored on said server, and wherein said method comprises selecting one or more attributes from a group comprising any or a combination of a spatial and temporal data associated with location of respective WFD.
7. The method as claimed in claim 5, wherein said method comprises monitoring the generated weather forecast, and generating an alert in case an event of abrupt change in the weather forecast is detected.
8. A weather forecast device (WFD), said device comprising:
a first transceiver configured to receive a signal, wherein said signal comprises one or more attributes, and wherein said signal is broadcasted using an active channel;
a decibel meter operatively coupled with said first transceiver adapted to extract signal strength from said received signal;
a control unit configured to compare said extracted attribute with a pre-defined attribute stored in a first database, wherein based on the comparison, distortion in said received is determined, and wherein based on said determined distortion weather forecast is generated.
9. The device as claimed in claim 8, wherein said device comprises a second transceiver configured to transmit said generated weather forecast to any or a combination of the server, the first database and a second database.
10. The device as claimed in claim 8, wherein said device comprises a power storage unit to provide power to the first transceiver, the second transceiver, the decibel meter and the control unit.