Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a natural disaster management system and particularly to an earthquake prediction system.
Description of Related Art
[002] Earthquake prediction presents a critical and long-standing challenge in geophysics. Despite advancements in seismic monitoring systems, accurately predicting earthquakes in real-time is still elusive. Current methodologies primarily rely on data collected from single or multi-axis seismic sensors. These sensors measure ground motion and vibrations, which are analyzed to detect patterns indicative of seismic activity. However, the inherent unpredictability of earthquakes, combined with the limited capability of traditional sensors to process complex data patterns, results in delayed or inaccurate predictions.
[003] Traditional seismic monitoring systems analyze localized data, often lacking integration of information from multiple sources in real-time. Gaps in predictive capabilities arise due to the absence of sophisticated processing and rapid communication frameworks, impairing accuracy, and timeliness in seismic event predictions.
[004] The emergence of advanced technologies such as cloud computing and the Internet of Things (IoT) introduces new possibilities in seismic data analysis. Cloud computing enables storage and processing of vast amounts of data at high speeds, while IoT facilitates deployment of interconnected, distributed sensor networks. Integration of these technologies enhances collection, analysis, and integration of seismic data from diverse geographic locations. Real-time dissemination of early warnings becomes achievable, supporting efforts to mitigate the devastating effects of earthquakes.
[005] Despite these advancements, a need exists for a comprehensive system using cloud computing and IoT to achieve greater accuracy and reliability in earthquake prediction. Such a system improves real-time monitoring, prediction, and offers actionable insights for disaster preparedness and response.
[006] There is thus a need for an improved and advanced earthquake prediction system that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[007] Embodiments in accordance with the present invention provide an earthquake prediction system. The system comprising: tri-axial geophones, positioned in various geographic locations, adapted to detect seismic activity in three-dimensions. The system further comprising: seismic recorders, connected to the tri-axial geophones, adapted to receive, and store seismic data based on the detected seismic activity. The system further comprising: a processor communicatively connected to the seismic recorders. The processor is configured to: receive the seismic data from the seismic recorders; analyze the seismic data using a predictive algorithm to predict an occurrence of an earthquake; evaluate an intensity of the predicted earthquake on a Richter scale; and generate a severity alert and preventive measures based on the evaluated intensity of the earthquake on the Richter scale.
[008] Embodiments in accordance with the present invention further provide a method for predicting an earthquake using an earthquake prediction system. The method comprising steps of: detecting seismic activity at various geographic locations using tri-axial geophones; receiving seismic data, from the seismic activity detected by the tri-axial geophones, and storing the seismic data in seismic recorders; receiving the seismic data from the seismic recorders; analyzing the seismic data using a predictive algorithm to predict an occurrence of the earthquake; evaluating an intensity of the predicted earthquake on a Richter scale; and generating a severity alert and preventive measures based on the evaluated intensity of the earthquake on the Richter scale.
[009] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide an earthquake prediction system.
[0010] Next, embodiments of the present application may provide an earthquake prediction system that enables continuous monitoring and real-time prediction of seismic events with high accuracy.
[0011] Next, embodiments of the present application may provide an earthquake prediction system that allows scalability to scale across regions and process enormous amounts of data from different geophones simultaneously.
[0012] Next, embodiments of the present application may provide an earthquake prediction system that ensures that seismic activity is captured in all dimensions, improving the accuracy of predictions.
[0013] Next, embodiments of the present application may provide an earthquake prediction system that allows for data access and analysis from any location, providing flexibility to researchers and disaster response teams.
[0014] Next, embodiments of the present application may provide an earthquake prediction system that is powered by renewable energy sources, ensuring continuous operation even in remote or disaster-prone areas.
[0015] These and other advantages will be apparent from the present application of the embodiments described herein.
[0016] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0018] FIG. 1 illustrates a diagram of an earthquake prediction system, according to an embodiment of the present invention;
[0019] FIG. 2 illustrates a block diagram of a processor of the earthquake prediction system, according to an embodiment of the present invention; and
[0020] FIG. 3 depicts a flowchart of a method for predicting an earthquake using the earthquake prediction system, according to an embodiment of the present invention.
[0021] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0022] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0023] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0024] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0025] FIG. 1 illustrates a diagram of an earthquake prediction system 100 (hereinafter referred to as the system 100), according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to predict occurrence of an earthquake. Further, the system 100 may generate and transmit alerts and preventive measures upon predicting the occurrence of the earthquake.
[0026] The system 100 may be installed in locations such as, but not limited to, a school, a college, a skyscraper, a transportation infrastructure, and so forth. In a preferred embodiment of the present invention, the system 100 may be installed in the earthquake prone areas, for alerting residents and initiating quick evacuation-escape protocols. Embodiments of the present invention are intended to include or otherwise cover any location for installation of the system 100, including known, related art, and/or later developed technologies.
[0027] The system 100 may comprise tri-axial geophones 102a-102n (hereinafter referred individually to as the tri-axial geophone 102, and plurally to as the tri-axial geophones 102), seismic recorders 104a-104m (hereinafter referred individually to as the seismic recorder 104, and plurally to as the seismic recorders 104), a processor 106, a cloud-based storage platform 108, a communication unit 110, a user device 112, and a solar-based power supply 114.
[0028] In an embodiment of the present invention, the tri-axial geophones 102 may be positioned in various geographic locations. The tri-axial geophones 102 may be adapted to detect seismic activity. The tri-axial geophones 102 may further be adapted to detect ground motion. The tri-axial geophones 102 may detect the seismic activity and the ground motion in three-dimensions. The detection of the seismic activity and the ground motion in three-dimensions may enable comprehensive data collection for seismic activity. Further, the tri-axial geophones 102 may envision a three-dimensional perspective on detection of seismic activity and the ground motion.
[0029] The three-dimensions may be, but not limited to, an x-axis, a y-axis, a z-axis, and so forth. Embodiments of the present invention are intended to include or otherwise cover any number of dimension for detection of the seismic activity and the ground motion by the tri-axial geophones 102, including known, related art, and/or later developed technologies.
[0030] The tri-axial geophones 102 may be, but not limited to, a wireless geophone, a seismometer geophone, a geophysical geophone, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the tri-axial geophones 102, including known, related art, and/or later developed technologies.
[0031] In an embodiment of the present invention, the tri-axial geophones 102 may further transmit the seismic activity and the ground motion in real-time to the seismic recorders 104.
[0032] In an embodiment of the present invention, the seismic recorders 104 may be connected to the tri-axial geophones 102. The establishment of connectivity between the tri-axial geophones 102 and the seismic recorders 104 may be achieved by wired and/or wireless means. The seismic recorders 104 may be adapted to receive raw seismic data based on the detected seismic activity in real-time. Further, the seismic recorders 104 may be adapted to store the received raw seismic activity. The storage of the raw seismic data may be enabled and be placed on a memory unit (not shown).
[0033] In an embodiment of the present invention, the memory unit may be a non-transitory storage medium. In an embodiment of the present invention, non-limiting examples of the memory unit may be a Read Only Memory (ROM), a Random-Access Memory (RAM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a hard drive, a removable media drive for handling memory cards, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the memory unit, including known, related art, and/or later developed technologies.
[0034] Further, the seismic recorders 104 may be adapted to filter out noise data from the raw seismic data. Upon filtration of the noise data from the raw seismic data, the seismic recorders 104 may transmit a filtered seismic data (hereinafter interchangeably referred to as ‘seismic data’) to the processor 106. The transmission of the filtered seismic data may be conducted using communication modem and protocols such as, but not limited to, a mobile data communication, a Wireless Fidelity (Wi-Fi), and so forth. Embodiments of the present invention are intended to include or otherwise cover any communication modem and protocols, including known, related art, and/or later developed technologies, for transmission of the filtered seismic data to the processor 106.
[0035] In an embodiment of the present invention, the processor 106 may be connected to the seismic recorders 104. The establishment of connectivity between the processor 106 and the seismic recorders 104 may be achieved by the above explained communication modem and protocols. The processor 106 may be configured to receive the filtered seismic data. The processor 106 may further be configured to generate a severity alert and the preventive measures based on the received filtered seismic data.
[0036] In an embodiment of the present invention, the severity alert may be an alert regarding an intensity of the predicted earthquake on a Richter scale. The Richter scale may provide a magnitude-based framework for measuring the intensity of the predicted earthquake. The Richter scale may place the intensity of the predicted earthquake in a range from of 1 to 10, with 1 being a least intensive earthquake and 10 being a most intensive earthquake. Higher the intensity of the predicted earthquake on the Richter scale, more the severity alert may be generated by the processor 106. A magnitude of 2 on the Richter scale for the predicted earthquake may lead to a generation of a low severity alert. However, a magnitude of 8 on the Richter scale for the predicted earthquake may lead to a generation of high severity alert.
[0037] The preventive measures may be, but not limited to, escaping into an open space, shielding under strong and sturdy furniture, avoiding utilization of elevators, evacuating infants and kids, and so forth. Embodiments of the present invention are intended to include or otherwise cover any preventive measures that may be generated by the processor 106, including known, related art, and/or later developed technologies. Further, the generated severity alert and the preventive measures may be transmitted to the user device 112.
[0038] The processor 106 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. According to embodiments of the present invention, the processor 106 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processor 106 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processor 106 may further be explained in conjunction with FIG. 2.
[0039] In an embodiment of the present invention, the cloud-based storage platform 108 may be adapted to store the gathered historical seismic activity and historical seismic data obtained from the tri-axial geophones 102 and the seismic recorders 104. Further, the cloud-based storage platform 108 may enable a deployment of the processor 106.
[0040] In an embodiment of the present invention, the communication unit 110 may be adapted to establish a communicative link between the processor 106 and the user device 112. The communication unit 110 may be adapted to transmit the generated severity alert and the preventive measures to the user device 112. According to embodiments of the present invention, the communication unit 110 may be, but not limited to, a Wireless Fidelity (Wi-Fi) communication unit, a Bluetooth communication unit, a millimeter waves communication unit, an Ultra-High Frequency (UHF) communication unit, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the communication unit 110, including known, related art, and/or later developed technologies.
[0041] In an embodiment of the present invention, the user device 112 may be an electronic device used by a user. The user device 112 may be adapted to receive the severity alert and the preventive measures generated by the processor 106 through the communication unit 110. The user device 112 may be, but not limited to, a personal computer, a desktop, a server, a laptop, a tablet, a mobile phone, a notebook, a netbook, a smartphone, a wearable device, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the user device 112 including known, related art, and/or later developed technologies.
[0042] In an embodiment of the present invention, the solar-based power supply 114 to supply operational power to the tri-axial geophones 102 and the seismic recorders 104. The solar-based power supply 114 may be enabled by an array of solar panels. In an embodiment of the present invention, the array of solar panels may be arranged at an area illuminated by sunlight. The solar panel may be adapted to convert a solar energy received in from the sunlight to an electrical energy, in an embodiment of the present invention. The array of solar panels may be adjusted in a direction facing the sun, which in turn may increase an efficiency of generation of the electrical energy from the solar energy. The electrical energy generated by the array of solar panels may further be supplied to the tri-axial geophones 102 and the seismic recorders 104.
[0043] FIG. 2 illustrates a block diagram of the processor 106 of the system 100, according to an embodiment of the present invention. The processor 106 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data analysis module 202, a data generation module 204, and a data transmission module 206.
[0044] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the seismic data from the seismic recorders 104. The data receiving module 200 may further be configured to transmit the seismic data to the data analysis module 202.
[0045] The data analysis module 202 may be activated upon receipt of the seismic data from the data receiving module 200. In an embodiment of the present invention, the data analysis module 202 may be configured to analyze the seismic data using a predictive algorithm. The analysis of the seismic data using the predictive algorithm may enable the prediction of the occurrence of the earthquake. The prediction of the occurrence of the earthquake may involve metadata such as, but not limited to, a likelihood, a location, a magnitude, change in seismic wave behavior, stress accumulation, seismic patterns, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of metadata that may be involved with the prediction of the occurrence of the earthquake, including known, related art, and/or later developed technologies.
[0046] In an embodiment of the present invention, the predictive algorithm may be trained on the historical seismic activity and the historical seismic data stored in the cloud-based storage platform 108. Further, the predictive algorithm may be trained by performing large-scale data analysis using machine learning techniques. The machine learning techniques may further analyze the seismic data in real-time. Along-side analysis of the seismic data in real-time, the machine learning techniques may analyze the historical seismic activity and the historical seismic data for a corresponding location. The hybrid mode of analysis may refine predictions and may further improve accuracy over time. The predictive algorithm may further continue to evolve with continuous feedback from real seismic events, making it more accurate over-time.
[0047] In an embodiment of the present invention, the data analysis module 202 may further be configured to evaluate the intensity of the predicated earthquake on the Richter scale. The evaluated intensity of the earthquake on the Richter scale may further be transmitted to the data generation module 204.
[0048] The data generation module 204 may be configured to receive the evaluated intensity of the earthquake from the data analysis module 202. The evaluated intensity of the earthquake may be compared with a threshold value.
[0049] The data analysis module 202 may be configured to generate the severity alert and the preventive measures when the evaluated intensity is greater than the threshold value. The threshold value may be in range of 0 to 10. In a preferred embodiment of the present invention, the threshold value may be 2. Embodiments of the present invention are intended to include or otherwise cover any threshold value. In an exemplary scenario, if the evaluated intensity of the earthquake may have a magnitude in a range from 2 to 4, then the low severity alert may be generated, and preventive measures such as hiding under the furniture may be generated. However, if the evaluated intensity of the earthquake may have a magnitude in a range from 8 to 10, then the high severity alert may be generated, and preventive measures such as evacuating buildings and escaping to the open space may be generated.
[0050] Upon generation of the severity alert and the preventive measures, the data generation module 204 may transmit an activation signal to the data transmission module 206.
[0051] The data transmission module 206 may be activated upon receipt of the activation signal from the data generation module 204. In an embodiment of the present invention, the data transmission module 206 may be configured to transmit the generated severity alert and the preventive measures to the user device 112.
[0052] The severity alert and the preventive measures received on the user device 112 may be in a pre-defined form, in an embodiment of the present invention. The pre-defined form of the severity alert and the preventive measures received on the user device 112 may be, but not limited to a pop-up notification, a flash notification, a ringer notification, a silent notification, a push notification, a hidden notification, an electronic mail notification, a Short Message Service (SMS) notification, an always on-screen notification, and so forth. Embodiments of the present invention are intended to include or otherwise cover any pre-defined form of the severity alert and the preventive measures that may be received on the user device 112, including known, related art, and/or later developed technologies.
[0053] FIG. 3 depicts a flowchart of a method 300 for predicting the earthquake using the system 100, according to an embodiment of the present invention.
[0054] At step 302, the system 100 may detect the seismic activity at the various geographic locations using the tri-axial geophones 102.
[0055] At step 304, the system 100 may receive the seismic data from the tri-axial geophones 102 based on the seismic activity detected by the tri-axial geophones 102 and store the seismic data in the seismic recorders 104.
[0056] At step 306, the system 100 may receive the seismic data from the seismic recorders 104.
[0057] At step 308, the system 100 may analyze the seismic data using the predictive algorithm to predict the occurrence of the earthquake.
[0058] At step 310, the system 100 may evaluate the intensity of the predicted earthquake on the Richter scale.
[0059] At step 312, the system 100 may compare the intensity of the predicted earthquake with zero. If the intensity of the predicted earthquake may be greater than zero, then the method 300 may proceed to a step 314. Else, the method 300 may revert to the step 302.
[0060] At step 314, the system 100 may generate the severity alert and the preventive measures.
[0061] At step 316, the system 100 may transmit the generated severity alert and the preventive measures to the user device 112.
[0062] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0063] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An earthquake prediction system (100), the system (100) comprising:
tri-axial geophones (102a-102n), positioned in various geographic locations, adapted to detect seismic activity in three-dimensions;
seismic recorders (104a-104m), connected to the tri-axial geophones (102a-102n), adapted to receive, and store seismic data based on the detected seismic activity;
a processor (106) communicatively connected to the seismic recorders (104a-104m), characterized in that the processor (106) is configured to:
receive the seismic data from the seismic recorders (104a-104m);
analyze the seismic data using a predictive algorithm to predict an occurrence of an earthquake;
evaluate an intensity of the predicted earthquake on a Richter scale; and
generate a severity alert and preventive measures based on the evaluated intensity of the earthquake on the Richter scale.
2. The system (100) as claimed in claim 1, wherein the processor (106) is configured to transmit the generated severity alert and the preventive measures to a user device (112).
3. The system (100) as claimed in claim 1, comprising a communication unit (110) adapted to transmit the generated severity alert and the preventive measures to a user device (112).
4. The system (100) as claimed in claim 1, wherein the seismic recorders (104a-104m) are adapted to filter out noise data from the detected seismic activity.
5. The system (100) as claimed in claim 1, comprising a cloud-based storage platform (108) adapted for storage of historical seismic activity and historical seismic data.
6. The system (100) as claimed in claim 1, wherein the predictive algorithm is trained on historical seismic activity and historical seismic data using machine learning techniques.
7. The system (100) as claimed in claim 1, comprising a solar-based power supply (114) to supply operational power to the tri-axial geophones (102a-102n) and the seismic recorders (104a-104m).
8. The system (100) as claimed in claim 1, wherein the tri-axial geophones (102a-102n) are adapted to detect seismic activity and ground motion along an x-axis, a y-axis, a z-axis, or a combination thereof.
9. A method (300) for predicting an earthquake using an earthquake prediction system (100), the method (300) is characterized by steps of:
detecting seismic activity at various geographic locations using tri-axial geophones (102a-102n);
receiving seismic data, from the seismic activity detected by the tri-axial geophones (102a-102n), and storing in seismic recorders (104a-104m);
receiving the seismic data from the seismic recorders (104a-104m);
analyzing the seismic data using a predictive algorithm to predict an occurrence of the earthquake;
evaluating an intensity of the predicted earthquake on a Richter scale; and
generating a severity alert and preventive measures based on the evaluated intensity of the earthquake on the Richter scale.
10. The method (300) as claimed in claim 9, comprising a step of transmitting the generated severity alert and the preventive measures to a user device (112).
Date: December 23, 2024
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant