1. A system for geography disaster monitoring comprising: a network of sensors distributed geographically to collect data on environmental parameters; a central processing unit to receive and analyse the data; and an alarm system to provide warnings in case of potential disasters.

2. The system of claim 1, wherein the network of sensors includes cameras, temperature sensors, humidity sensors, and air quality sensors.

3. The system of claim 1, wherein the central processing unit uses machine learning algorithms to detect patterns and anomalies in the collected data.

4. The system of claim 1, wherein the alarm system provides real-time alerts to local authorities and the general public.

5. The system of claim 1, wherein the central processing unit generates maps and visualizations of the collected data to aid in disaster response.

6. The system of claim 1, wherein the network of sensors are connected wirelessly to the central processing unit.

7. The system of claim 1, wherein the central processing unit includes a database for storing historical data and trends.

8. A method for geography disaster monitoring comprising: Collecting data on environmental parameters using a network of sensors distributed geographically; Analyzing the data using machine learning algorithms to detect patterns and anomalies; and Providing warnings and alerts in case of potential disasters.

9. The method of claim 8, further comprising generating maps and visualizations of the collected data to aid in disaster response.

10. The method of claim 8, wherein the collected data is stored in a database for historical analysis and trend detection.   GEOGRAPHY DISASTER MONITORING AND ALARM SYSTEM Abstract A system for geographical catastrophe monitoring is proposed. The system includes sensors which are dispersed over the globe to measure various environmental factors. A processing unit can be configured to receive and process data. A warning system in the event of an impending calamity is another possible component of embodiments. Fig. 1 , Claims:Claims :

1. A system for geography disaster monitoring comprising: a network of sensors distributed geographically to collect data on environmental parameters; a central processing unit to receive and analyse the data; and an alarm system to provide warnings in case of potential disasters.

2. The system of claim 1, wherein the network of sensors includes cameras, temperature sensors, humidity sensors, and air quality sensors.

3. The system of claim 1, wherein the central processing unit uses machine learning algorithms to detect patterns and anomalies in the collected data.

4. The system of claim 1, wherein the alarm system provides real-time alerts to local authorities and the general public.

5. The system of claim 1, wherein the central processing unit generates maps and visualizations of the collected data to aid in disaster response.

6. The system of claim 1, wherein the network of sensors are connected wirelessly to the central processing unit.

7. The system of claim 1, wherein the central processing unit includes a database for storing historical data and trends.

8. A method for geography disaster monitoring comprising: Collecting data on environmental parameters using a network of sensors distributed geographically; Analyzing the data using machine learning algorithms to detect patterns and anomalies; and Providing warnings and alerts in case of potential disasters.

9. The method of claim 8, further comprising generating maps and visualizations of the collected data to aid in disaster response.

10. The method of claim 8, wherein the collected data is stored in a database for historical analysis and trend detection.

Description:GEOGRAPHY DISASTER MONITORING AND ALARM SYSTEM
Field of the Invention
[0001] The present invention relates to a geological management. More specifically, disclosure pertains to disaster monitoring and early warning technique.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Geographically-based disasters, such as earthquakes, hurricanes, and wildfires, can cause significant damage to infrastructure and human life. Monitoring these disasters in real-time is critical for providing early warning to people in affected areas and facilitating emergency response efforts. Another important aspect of geographically-based disaster monitoring is collaboration with local emergency responders and other stakeholders. This ensures that the system is designed to meet their needs and requirements, and that they are able to use the data provided by the sensor network to make informed decisions during emergency response efforts.
[0004] Patent literature described solutions for monitoring geographically-based disasters. Few of them are discussed below.
[0005] KR102128708B1 (By: EL) - The present invention relates to an IoT-based river disaster monitoring and facility autonomous-inspection system using an intelligent remote terminal unit. More specifically, since an intelligent remote terminal unit (RTU, 200) is installed in every river disaster management facility, an autonomous measure is taken in regard to water level control, the operation condition of inspection targets installed in river disaster management facilities is autonomously inspected, and autonomous measure event information and malfunction information by inspection target are created and provided to a central management server (400) through an Internet-of-Things communication network. Therefore, the IoT-based river disaster monitoring and facility autonomous-inspection system is capable of enabling effective and efficient river management by taking a preemptive action when a necessary event for river management is generated.
[0006] WO2008153275A1 (By: KANGNUNG NATIONAL UNIVERSITY INDUSTRY AC) - A real-time monitoring system based on a wireless sensor network is provided. The real-time monitoring system includes: a wireless sensor network including a plurality of sensor nodes and a sink node, wherein each sensor node and the sink node receive and transmit a data packet therebetween; a gateway which receives and transmits a data packet from and to the sink node in the wireless sensor network; a central management server which receives and transmits a data packet from and to the gateway, extracts information on each sensor node and measure data or image data of the sensor node from the data packet received through the gateway, and stores and manages the extracted data in a database; and a monitoring computer or a Web server which receives the information on each sensor node and the measure data or image data of the sensor node from the central management server in real time and displays the information and the measure data or the image data on a screen, wherein the central management server can store and manage the measure data or the image data of each sensor node of the wireless sensor network, and the monitoring computer and the Web server can perform monitoring of situation of each sensor node in real time irrespective of location of each sensor node.
[0007] US20070043585A1 (By : Jeffrey A. Matos) - The present disclosure relates to systems and methods for: 1) displaying all vital central station (CS) information and controls on a single screen; 2) linking peripheral central stations (pCSs) to a master central station (mCS); 3) operating the system disclosed in U.S. Ser. No. 10/460,458, without medical professionals (MPs) in the mCS or without any mCS; 4) linking a remote controlled defibrillator (RCD™) unit to an arrest sensor; 5) operating an RCD unit in a motor vehicle and linking an RCD unit to a vehicle communications system; 6) linking an RCD unit to a CS through a network of: a) non-vehicle-based stationary units (SUs), b) vehicle-based SUs/vehicle communication systems, or c) non-vehicle-based SUs and vehicle-based SUs/vehicle communication systems; 7) using an RCD unit with a chest compression device; 8) using the network of RCD units and MPs for disaster monitoring; and 9) monitoring and treating hospital patients and motor vehicle passengers.
[0008] Despite the potential benefits of such geographically-based disaster monitoring, there are still many challenges that need to be addressed. For example, there is a need for more advanced data analysis techniques to improve the accuracy and reliability of disaster detection.
[0009] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

Summary
[00010] Various objects, features, and advantages of the disclosed subject matter can be more fully appreciated with reference to the following detailed description of the disclosed subject matter when considered in connection with the following drawings, in which like reference numerals identify like elements.
[00011] The following paragraphs provide additional support for the claims of the subject application.
[00012] The present invention relates to a geological management. More specifically, disclosure pertains to disaster monitoring and early warning technique.
[00013] The present disclosure may include a system for geography disaster monitoring including a network of sensors distributed geographically to collect data on environmental parameters. Embodiments may also include a central processing unit to receive and analyse the data. Embodiments may also include an alarm system to provide warnings in case of potential disasters.
[00014] In some embodiments, the network of sensors includes cameras, temperature sensors, humidity sensors, and air quality sensors. In some embodiments, the central processing unit uses machine learning algorithms to detect patterns and anomalies in the collected data. In some embodiments, the alarm system provides real-time alerts to local authorities and the general public.
[00015] In some embodiments, the central processing unit generates maps and visualizations of the collected data to aid in disaster response. In some embodiments, the sensors may be connected wirelessly to the central processing unit. In some embodiments, the central processing unit includes a database for storing historical data and trends.
[00016] Embodiments of the present disclosure may also include a method for geography disaster monitoring including collecting data on environmental parameters using a network of sensors distributed geographically. Embodiments may also include analyzing the data using machine learning algorithms to detect patterns and anomalies. Embodiments may also include providing warnings and alerts in case of potential disasters. Maps and visualizations can be generated by utilizing the collected data to aid in disaster response. In some embodiments, the collected data may be stored in a database for historical analysis and trend detection.

Brief Description of the Drawings
[00017] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00018] FIG. 1 is a block diagram illustrating a system for geography disaster monitoring, according to some embodiments of the present disclosure.
[00019] FIG. 2 is a detailed block diagram further illustrating the system (from FIG. 1) for geography disaster monitoring, according to some embodiments of the present disclosure.
[00020] FIG. 3 is a flowchart illustrating a method for monitoring of geographical disaster, according to some embodiments of the present disclosure.
Detailed Description
[00021] The following is a detailed description of exemplary embodiments to illustrate the principles of the invention. The embodiments are provided to illustrate aspects of the invention, but the invention is not limited to any embodiment. The scope of the invention encompasses numerous alternatives, modifications and equivalent; it is limited only by the claims.
[00022] In view of the many possible embodiments to which the principles of the present discussion may be applied, it should be recognized that the embodiments described herein with respect to the drawing figures are meant to be illustrative only and should not be taken as limiting the scope of the claims. Therefore, the techniques as described herein contemplate all such embodiments as may come within the scope of the following claims and equivalents thereof.
[00023] Following are more detailed descriptions of various concepts related to, and implementations of, methods, apparatuses, and systems of present disclosure. The various concepts introduced above and discussed in greater detail below may be implemented in any of numerous ways.
[00024] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different instances in the description and the figures may indicate similar or identical items.
[00025] The present invention relates to a geological management. More specifically, disclosure pertains to disaster monitoring and early warning technique.
[00026] FIG. 1 is a block diagram that describes a system 100 for geography disaster monitoring, according to some embodiments of the present disclosure. In some embodiments, the system 100 may include a network of sensors 110 distributed geographically to collect data on environmental parameters, a central processing unit 120 to receive and analyse the data, and an alarm system 130 to provide warnings in case of potential disasters. In some embodiments, the central processing unit 120 may use machine learning algorithms to detect patterns and anomalies in the collected data.
[00027] In some embodiments, the alarm system 130 may provide real-time alerts to local authorities and the general public. In some embodiments, the central processing unit 120 may generate maps and visualizations of the collected data to aid in disaster response. In some embodiments, the network of sensors 110 may be connected wirelessly to the central processing unit 120. In some embodiments, the central processing unit 120 may include a database for storing historical data and trends.
[00028] FIG. 2 is a detailed block diagram that further describes the system 100 (from FIG. 1) for geography disaster monitoring, according to some embodiments of the present disclosure. The network of sensors 110 can be selected from cameras, sensors for temperature and humidity, sensors for air quality, and other types of sensors. The data collected from the network of sensors 110 can be analysed by the central processing unit 120 and based on the analysis the central processing unit 120 activates the alarm system 130 to indicate regarding the event of possible hazardous conditions.
[00029] FIG. 3 is a flowchart that describes a method, according to some embodiments of the present disclosure. In some embodiments, at 310, the method may include collecting data on environmental parameters using the network of sensors 110 distributed geographically. At 320, the method may include analyzing the data using machine learning algorithms to detect patterns and anomalies. At 330, the method may include providing warnings and alerts in case of potential disasters. Maps and visualizations are generated by utilizing the collected data to aid in disaster response. In some embodiments, the collected data may be stored in a database for historical analysis and trend detection.
[00030] A system for geographical catastrophe monitoring may be included in certain embodiments of the present disclosure. This system may include the network of sensors 110 that are dispersed over the globe and are used to gather data on various environmental factors. The alarm system 130 that provides warnings in the event of possible calamities is another component that embodiments may feature.
[00031] Cameras, sensors for temperature and humidity, sensors for air quality, and other types of sensors may be included in the network of sensors 110 in certain implementations. In some implementations, the central processing unit 120 makes use of machine learning methods in order to identify patterns and abnormalities in the data that has been gathered. In certain implementations, the alarm system 130 communicates critical information to the appropriate authorities and the broader public in real time.
[00032] In certain implementations, the data that has been gathered is mapped out and shown by the central processing unit 120 in order to help with emergency response efforts. It is possible that the network of sensors 110 may communicate with the central processing unit 110 through wireless connections in some implementations. In some implementations, the central processing unit 120 is equipped with a database that may be used to store historical data as well as trends.
[00033] A method for geographical disaster monitoring may also be included in embodiments of the present disclosure. This technique may include the collection of data on environmental parameters via the use of a network of sensors 110 that are scattered geographically. Analyzing the data using machine learning algorithms in order to search for patterns and irregularities is another possible aspect of embodiments. The provision of warnings and alarms in the event of impending calamities is another possible aspect of embodiments. The data that has been gathered may be saved in a database for the purposes of doing historical research and identifying trends.
[00034] Variations of those preferred embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than as specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context
[00035] As used herein, the term “wireless communication network” or “network interface” refers to a network following any suitable wireless communication standards, such as LTE-Advanced (LTE-A), LTE, Wideband Code Division Multiple Access (WCDMA), High-Speed Packet Access (HSPA), and so on. Furthermore, the communications between network devices in the wireless communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1G), the second generation (2G), 2.5G, 2.75G, the third generation (3G), the fourth generation (4G), 4.5G, the fifth generation (5G) communication protocols, and/or any other protocols either currently known or to be developed in the future.
[00036] As used herein, the term “network device” refers to a device in a wireless communication network via which a terminal device accesses the network and receives services therefrom. The network device may refer to a base station (BS) or an access point (AP), for example, a node B (NodeB or NB), an evolved NodeB (eNodeB or eNB), a Remote Radio Unit (RRU), a radio header (RH), a remote radio head (RRH), a relay, a low power node such as a femto, a pico, and so forth, depending on the applied terminology and technology. The “network device” or “terminal device” or “computing device” may represent any suitable device (or group of devices) capable, configured, arranged, and/or operable to enable and/or provide a terminal device access to the wireless communication network or to provide some service to a terminal device that has accessed the wireless communication network. The terminal device may include, but not limited to, a mobile phone, a cellular phone, a smart phone, a tablet, a wearable device, a personal digital assistant (PDA), portable computers, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback appliances, wearable terminal devices, vehicle-mounted wireless terminal devices and the like. In the following description, the terms “terminal device”, “terminal”, “user equipment”, “computing device”, “network device” and “UE” may be used interchangeably.
[00037] Processing device may be provided by one or more processors such as a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00038] In addition, the present disclosure may also provide a memory containing the computer program as mentioned above, which includes machine-readable media and machine-readable transmission media. The machine-readable media may also be called computer-readable media, and may include machine-readable storage media, for example, magnetic disks, magnetic tape, optical disks, phase change memory, or an electronic memory terminal device like a random access memory (RAM), read only memory (ROM), flash memory devices, CD-ROM, DVD, Blue-ray disc and the like. The machine-readable transmission media may also be called a carrier, and may include, for example, electrical, optical, radio, acoustical or other form of propagated signals—such as carrier waves, infrared signals, and the like.
[00039] Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the subject matter described herein, but rather as descriptions of features that may be specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.
[00040] All references to “a/an/the element, apparatus, component, means, step, etc.” are to be interpreted as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated. The discussion above and below in respect of any of the aspects of the present disclosure is also in applicable parts relevant to any other aspect of the present disclosure.
[00041] The wordings such as “include”, “including”, “comprise” and “comprising” do not exclude elements or steps which are present but not listed in the description and the claims.
[00042] It also shall be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. This invention can be achieved by means of hardware including several different elements or by means of a suitably programmed computer. In the unit claims that list several means, several ones among these means can be specifically embodied in the same hardware item. The use of such words as first, second, third does not represent any order, which can be simply explained as names.
[00043] Various techniques may be described herein in the general context of software, hardware elements, or program modules. Generally, such modules include routines, programs, objects, elements, components, data structures, and so forth that perform particular tasks or implement particular abstract data types. The terms “module,” “functionality,” and “component” as used herein generally represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, meaning that the techniques may be implemented on a variety of commercial computing platforms having a variety of processors
 

Claims
I/We Claim:
1. A system for geography disaster monitoring comprising:
a network of sensors distributed geographically to collect data on environmental parameters;
a central processing unit to receive and analyse the data; and
an alarm system to provide warnings in case of potential disasters.

2. The system of claim 1, wherein the network of sensors includes cameras, temperature sensors, humidity sensors, and air quality sensors.

3. The system of claim 1, wherein the central processing unit uses machine learning algorithms to detect patterns and anomalies in the collected data.

4. The system of claim 1, wherein the alarm system provides real-time alerts to local authorities and the general public.

5. The system of claim 1, wherein the central processing unit generates maps and visualizations of the collected data to aid in disaster response.

6. The system of claim 1, wherein the network of sensors are connected wirelessly to the central processing unit.

7. The system of claim 1, wherein the central processing unit includes a database for storing historical data and trends.

8. A method for geography disaster monitoring comprising:
Collecting data on environmental parameters using a network of sensors distributed geographically;
Analyzing the data using machine learning algorithms to detect patterns and anomalies; and
Providing warnings and alerts in case of potential disasters.

9. The method of claim 8, further comprising generating maps and visualizations of the collected data to aid in disaster response.

10. The method of claim 8, wherein the collected data is stored in a database for historical analysis and trend detection.
 

GEOGRAPHY DISASTER MONITORING AND ALARM SYSTEM
Abstract
A system for geographical catastrophe monitoring is proposed. The system includes sensors which are dispersed over the globe to measure various environmental factors. A processing unit can be configured to receive and process data. A warning system in the event of an impending calamity is another possible component of embodiments.

Fig. 1

, Claims:Claims
I/We Claim:
1. A system for geography disaster monitoring comprising:
a network of sensors distributed geographically to collect data on environmental parameters;
a central processing unit to receive and analyse the data; and
an alarm system to provide warnings in case of potential disasters.

2. The system of claim 1, wherein the network of sensors includes cameras, temperature sensors, humidity sensors, and air quality sensors.

3. The system of claim 1, wherein the central processing unit uses machine learning algorithms to detect patterns and anomalies in the collected data.

4. The system of claim 1, wherein the alarm system provides real-time alerts to local authorities and the general public.

5. The system of claim 1, wherein the central processing unit generates maps and visualizations of the collected data to aid in disaster response.

6. The system of claim 1, wherein the network of sensors are connected wirelessly to the central processing unit.

7. The system of claim 1, wherein the central processing unit includes a database for storing historical data and trends.

8. A method for geography disaster monitoring comprising:
Collecting data on environmental parameters using a network of sensors distributed geographically;
Analyzing the data using machine learning algorithms to detect patterns and anomalies; and
Providing warnings and alerts in case of potential disasters.

9. The method of claim 8, further comprising generating maps and visualizations of the collected data to aid in disaster response.

10. The method of claim 8, wherein the collected data is stored in a database for historical analysis and trend detection.