TECHNICAL FIELD

The present disclosure relates to a device, system, and method for landslide
detection, more particularly, towards real-time detection and intimation of a likelihood of a landslide like event.

BACKGROUND

The movement of a mass of rock, debris, or earth down a slope is known as
land sliding. Any down-slope movement of soil and rock under the direct influence of gravity is landslide. Landslides have caused massive damage of life and property during extremely heavy rain across India, and different parts of the world.
[0003] Relatively every landslide has various causes. Slope development happens
when powers acting down-slope (mainly because of gravity) surpass the quality of the earth
materials that create the slope. Causes include factors that increase the impacts of down-slope
powers and factors that add to low or diminished quality. Landslides can be initiated in slopes
as of now nearly development by rainfall, snowmelt, changes in water level, stream erosion,
changes in ground water, earthquakes, volcanic action, unsettling influence by human
exercises, or any combination of these elements. Earthquake shaking and different variables
can likewise induce landslides underwater. These landslides are called submarine landslides.
Submarine landslides now and again cause tsunamis that harm seaside territories.
[0004] Conventional solutions fail to provide a real-time detection and intimation of
likelihood of a landslide like event, as conventional solutions do not take into account various
factors that eventually lead to a landslide, and hence are only able to inform the concerned
agencies, like disaster management, metrological department, during or after the landslide has
occurred. This results in undesirable loss of life, injuries, and other casualties.
[0005] There is therefore a need in the art to provide real time detection and
intimation of likelihood of a landslide like event to people residing in landslide prone areas, and associated disaster management, metrological department authorities beforehand to take preventive measures before the occurrence of the landslide.
2

OBJECTS OF THE PRESENT DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one embodiment
herein satisfies are as listed herein below.
[0007] It is an object of the present disclosure to provide a device, system, and
method for landslide detection.
[0008] It is another object of the present disclosure to provide real-time detection and
intimation of a likelihood of a landslide like event.
[0009] It is another object of the present disclosure to provide landslide detection at
an earlier stage.
[00010] It is another object of the present disclosure to provide necessary alert to an
emergency authority like hospital, disaster management, and hospital about likelihood of a
landslide like event at an earlier stage.
[00011] It is another object of the present disclosure to provide exact location of place
where there is likelihood of a landslide like event to the emergency authority.
[00012] It is another object of the present disclosure to provide parameters associated
with soil of place where there is likelihood of a landslide like event to the metrological
department.
[00013] It is another object of the present disclosure to analyze the parameters based on
combination of deep learning, and artificial neural networks.
[00014] It is yet another object of the present disclosure to provide a device, system,
and method for landslide detection that is cost effective and easy to implement.
SUMMARY
[00015] The present disclosure relates to a device, system, and method for landslide
detection, more particularly, towards real-time detection and intimation of a likelihood of a
landslide like event.
[00016] An aspect of the present disclosure relates to a landslide detection device
(100). The device (100) includes a memory (102); a microprocessor (104) coupled to the
memory (102); a sensor module (106) communicatively coupled to the microprocessor (104)
and a plurality of sensors (204); a Global Positioning System module (GPS) (108)
communicatively coupled to the microprocessor (104), the plurality of sensors (204), and a
server (202); a Global System for Mobile communications module (GSM) (110)
communicatively coupled to the microprocessor (104) and the server (202), wherein the
3

microprocessor (104) is configured to collect, through the sensor module (106), data associated with an area gathered through the plurality of sensors (204), acquire, through the Global Positioning System module (GPS) (108), location parameters associated with the plurality of sensors (204), identify, based on analysis of the collected data at the server (202), likelihood of a landslide like event, and transfer, through the Global System for Mobile communications module (GSM) (110), the identified likelihood of landslide like event to an emergency authority.
[00017] In an aspect, the plurality of sensors (204) is any or a combination of a
temperature sensor, humidity sensor, pressure sensor, angle sensor, friction sensor.
[00018] In an aspect, the plurality of sensors (204) monitors parameters of soil of the
area where the sensors (204) are provided for detecting the likelihood of landslide like event.
[00019] In an aspect, the analysis of the collected data at the server (202) is based upon
any or a combination of deep learning, deep structured learning, hierarchical learning, artificial neural networks, deep neural networks, deep belief networks, recurrent neural networks, convolutional neural networks.
[00020] In an aspect, the emergency authority is any or a combination of disaster
management, metrological department, hospital.
[00021] In another aspect, a landslide detection system (200) includes a landslide
detection device (100); a server (202) communicably coupled to the landslide detection device (100); and a plurality of sensors (204) communicably coupled to the server (202) and the landslide detection device (100), wherein the landslide detection device (100) includes a memory (102); a microprocessor (104) coupled to the memory (102); a sensor module (106) communicatively coupled to the microprocessor (104) and a plurality of sensors (204); a Global Positioning System module (GPS) (108) communicatively coupled to the microprocessor (104), the plurality of sensors (204), and a server (202); a Global System for Mobile communications module (GSM) (110) communicatively coupled to the microprocessor (104) and the server (202), wherein the microprocessor (104) is configured to collect, through the sensor module (106), data associated with an area gathered through the plurality of sensors (204), acquire, through the Global Positioning System module (GPS) (108), location parameters associated with the plurality of sensors (204), identify, based on analysis of the collected data at the server (202), likelihood of a landslide like event, and transfer, through Global System for Mobile communications module (GSM) (110), the identified likelihood of landslide like event an emergency authority.
4

[00022] In an aspect, the landslide detection system (200) is an Internet of Things (IoT)
based system.
[00023] In another aspect, a landslide detection method (300) includes collecting,
through a sensor module (106) of a landslide detection device (100), data associated with an area gathered through a plurality of sensors (204), acquiring, through a Global Positioning System module (GPS) (108) of the landslide detection device (100), location parameters associated with the plurality of sensors (204), identifying, based on analysis of the collected data at a server (202) communicably coupled with the landslide detection device (100) and the plurality of sensors (204), likelihood of a landslide like event, and transferring, through a Global System for Mobile communications module (GSM) (110) of the landslide detection device (100), the identified likelihood of landslide like event to an emergency authority.
BRIEF DESCRIPTION OF THE DRAWINGS
[00024] 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.
[00025] FIG. 1 illustrates an environment where a landslide detection system 200,
hereinafter referred to as system 200, is implemented in accordance with an embodiment of
the present disclosure.
[00026] Fig. 2 illustrates a landslide detection method 300 in accordance with an
embodiment of the present disclosure.
DETAILED DESCRIPTION
[00027] 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.
5

[00028] 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 apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[00029] 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.
[00030] 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.
[00031] 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.
[00032] 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.
[00033] 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
6

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 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.
[00034] 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.
[00035] 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
7

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. 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.
[00036] 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.
[00037] 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.
[00038] 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.
[00039] 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
8

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.
[00040] 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.
[00041] The present disclosure relates to a device, system, and method for landslide
detection, more particularly, towards real-time detection and intimation of a likelihood of a landslide like event.
[00042] An aspect of the present disclosure relates to a landslide detection device
(100). The device (100) includes a memory (102); a microprocessor (104) coupled to the memory (102); a sensor module (106) communicatively coupled to the microprocessor (104) and a plurality of sensors (204); a Global Positioning System module (GPS) (108) communicatively coupled to the microprocessor (104), the plurality of sensors (204), and a server (202); a Global System for Mobile communications module (GSM) (110) communicatively coupled to the microprocessor (104) and the server (202), wherein the microprocessor (104) is configured to collect, through the sensor module (106), data associated with an area gathered through the plurality of sensors (204), acquire, through the Global Positioning System module (GPS) (108), location parameters associated with the plurality of sensors (204), identify, based on analysis of the collected data at the server (202), likelihood of a landslide like event, and transfer, through the Global System for Mobile communications module (GSM) (110), the identified likelihood of landslide like event to an emergency authority.
[00043] In an aspect, the plurality of sensors (204) is any or a combination of a
temperature sensor, humidity sensor, pressure sensor, angle sensor, friction sensor.
[00044] In an aspect, the plurality of sensors (204) monitors parameters of soil of the
area where the sensors (204) are provided for detecting the likelihood of landslide like event.
[00045] In an aspect, the analysis of the collected data at the server (202) is based upon
any or a combination of deep learning, deep structured learning, hierarchical learning, artificial neural networks, deep neural networks, deep belief networks, recurrent neural networks, convolutional neural networks.
9

[00046] In an aspect, the emergency authority is any or a combination of disaster
management, metrological department, hospital.
[00047] In another aspect, a landslide detection system (200) includes a landslide
detection device (100); a server (202) communicably coupled to the landslide detection device (100); and a plurality of sensors (204) communicably coupled to the server (202) and the landslide detection device (100), wherein the landslide detection device (100) includes a memory (102); a microprocessor (104) coupled to the memory (102); a sensor module (106) communicatively coupled to the microprocessor (104) and a plurality of sensors (204); a Global Positioning System module (GPS) (108) communicatively coupled to the microprocessor (104), the plurality of sensors (204), and a server (202); a Global System for Mobile communications module (GSM) (110) communicatively coupled to the microprocessor (104) and the server (202), wherein the microprocessor (104) is configured to collect, through the sensor module (106), data associated with an area gathered through the plurality of sensors (204), acquire, through the Global Positioning System module (GPS) (108), location parameters associated with the plurality of sensors (204), identify, based on analysis of the collected data at the server (202), likelihood of a landslide like event, and transfer, through Global System for Mobile communications module (GSM) (110), the identified likelihood of landslide like event an emergency authority.
[00048] In an aspect, the landslide detection system (200) is an Internet of Things (IoT)
based system.
[00049] In another aspect, a landslide detection method (300) includes collecting,
through a sensor module (106) of a landslide detection device (100), data associated with an
area gathered through a plurality of sensors (204), acquiring, through a Global Positioning
System module (GPS) (108) of the landslide detection device (100), location parameters
associated with the plurality of sensors (204), identifying, based on analysis of the collected
data at a server (202) communicably coupled with the landslide detection device (100) and
the plurality of sensors (204), likelihood of a landslide like event, and transferring, through a
Global System for Mobile communications module (GSM) (110) of the landslide detection
device (100), the identified likelihood of landslide like event to an emergency authority.
[00050] FIG. 1 illustrates an environment where a landslide detection system 200,
hereinafter referred to as system 200, is implemented in accordance with an embodiment of the present disclosure.
10

[00051] In an embodiment, the system 200 includes a landslide detection device 100.
In an example, the landslide detection device 100 is an inventive hardware device developed in accordance with an embodiment of the present disclosure. The system 200 further includes a server 202 communicably coupled to the landslide detection device 100. In an example, the server 202 may be a computer operated database server configured to retrieve, analyze, and provide data to one or more devices upon querying over a network. The network may be a wired or wireless network as known to a person skilled in the art.
[00052] In an embodiment, the system 200 further includes a plurality of sensors 204
communicably coupled to the server 202 and the landslide detection device 100. In an example, the plurality of sensors 204 is any or a combination of a temperature sensor, humidity sensor, pressure sensor, angle sensor, friction sensor, wherein the plurality of sensors 204 monitors parameters of soil of the area where the sensors 204 are provided for detecting the likelihood of landslide like event. In an example, the parameters of soil to be monitored may include temperature, humidity, pressure, angle or slope with respect to a terrain, friction with respect to sliding rocks or the like, etc.
[00053] In an embodiment, the landslide detection device 100 includes a memory 102
and a microprocessor 104 coupled to the memory 102. The landslide detection device 100 further includes a sensor module 106 communicatively coupled to the microprocessor 104 and the plurality of sensors 204. The landslide detection device 100 further includes a Global Positioning System module (GPS) 108 communicatively coupled to the microprocessor 104, the plurality of sensors 204, and a server 202. The landslide detection device 100 further includes a Global System for Mobile communications module (GSM) 110 communicatively coupled to the microprocessor 104 and the server 202.
[00054] In an embodiment, the microprocessor 104 of the landslide detection device
100 is configured to collect, through the sensor module 106, data associated with an area gathered through the plurality of sensors 204. The microprocessor 104 is further configured to acquire, through the Global Positioning System module (GPS) 108, location parameters associated with the plurality of sensors 204. The microprocessor 104 is further configured to identify, based on analysis of the collected data at the server 202, likelihood of a landslide like event. The microprocessor 104 is further configured to transfer, through the Global System for Mobile communications module (GSM) 110, the identified likelihood of landslide like event to an emergency authority in real time. In an example, the emergency authority is any or a combination of disaster management, metrological department, hospital.
11

[00055] In an embodiment, the analysis of the collected data at the server 202 is based
upon any or a combination of deep learning, deep structured learning, hierarchical learning,
artificial neural networks, deep neural networks, deep belief networks, recurrent neural
networks, convolutional neural networks to predict a landslide at an earlier stage. Further, the
retrieved prediction information is then sent to the meteorological department, so that they
can take necessary actions at an earlier stage and can prevent landslide disaster.
[00056] Fig. 2 illustrates a landslide detection method 300 in accordance with an
embodiment of the present disclosure.
[00057] In an embodiment, at step 302 the method 300 includes collecting, through a
sensor module 106 of a landslide detection device 100, data associated with an area gathered
through a plurality of sensors 204. At step 304 the method 300 includes acquiring, through a
Global Positioning System module (GPS) 108 of the landslide detection device 100, location
parameters associated with the plurality of sensors 204. At step 306 the method 300 includes
identifying, based on analysis of the collected data at a server 202 communicably coupled
with the landslide detection device 100 and the plurality of sensors 204, likelihood of a
landslide like event. At step 308 the method 300 includes transferring, through a Global
System for Mobile communications module (GSM) 110 of the landslide detection device
100, the identified likelihood of landslide like event to an emergency authority.
[00058] Although the proposed system 200 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
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.
[00059] In an implementation, the proposed system 200, discussed above, can be
embedded with/incorporated with one or more Internet of Things (IoT) devices. In a typical network architecture of the present disclosure can include a plurality of network devices such as transmitter, receivers, and/or transceivers that may include one or more IoT devices. An IOT device consisting of a Gateway (any Wi-Fi SOC) coupled with the landslide detection
12

device 100, the plurality of sensors 204, and the server 202. Each such device has a LED display and QR code (or NFC, RFID) associated with it.
[00060] As used herein, the IoT devices can be a device that includes sensing and/or
control functionality as well as a WiFi™ transceiver radio or interface, a Bluetooth™ transceiver radio or interface, a Zigbee™ transceiver radio or interface, an Ultra-Wideband (UWB) transceiver radio or interface, a Wi-Fi-Direct transceiver radio or interface, a Bluetooth™ Low Energy (BLE) transceiver radio or interface, and/or any other wireless network transceiver radio or interface that allows the IoT device to communicate with a wide area network and with one or more other devices. In some embodiments, an IoT device does not include a cellular network transceiver radio or interface, and thus may not be configured to directly communicate with a cellular network. In some embodiments, an IoT device may include a cellular transceiver radio, and may be configured to communicate with a cellular network using the cellular network transceiver radio.
[00061] A user may communicate with the network devices using an access device that
may include any human-to-machine interface with network connection capability that allows access to a network. For example, the access device may include a stand-alone interface (e.g., a cellular telephone, a smartphone, a home computer, a laptop computer, a tablet, a personal digital assistant (PDA), a computing device, a wearable device such as a smart watch, a wall panel, a keypad, or the like), an interface that is built into an appliance or other device e.g., a television, a refrigerator, a security system, a game console, a browser, or the like), a speech or gesture interface (e.g., a Kinect™ sensor, a Wiimote™, or the like), an IoT device interface (e.g., an Internet enabled device such as a wall switch, a control interface, or other suitable interface), or the like. In some embodiments, the access device may include a cellular or other broadband network transceiver radio or interface, and may be configured to communicate with a cellular or other broadband network using the cellular or broadband network transceiver radio. In some embodiments, the access device may not include a cellular network transceiver radio or interface.
[00062] User may interact with the network devices using an application, a web
browser, a proprietary program, or any other program executed and operated by the access device. In some embodiments, the access device may communicate directly with the network devices (e.g., communication signal). For example, the access device may communicate directly with network devices using Zigbee™ signals, Bluetooth™ signals, WiFi™ signals, infrared (IR) signals, UWB signals, WiFi-Direct signals, BLE signals, sound frequency
13

signals, or the like. In some embodiments, the access device may communicate with the network devices via the gateways and/or a cloud network.
[00063] Local area network may include a wireless network, a wired network, or a
combination of a wired and wireless network. A wireless network may include any wireless interface or combination of wireless interfaces (e.g., Zigbee™, Bluetooth™, WiFi™, IR, UWB, WiFi-Direct, BLE, cellular, Long-Term Evolution (LTE), WiMax™, or the like). A wired network may include any wired interface (e.g., fiber, Ethernet, powerline, Ethernet over coaxial cable, digital signal line (DSL), or the like). The wired and/or wireless networks may be implemented using various routers, access points, bridges, gateways, or the like, to connect devices in the local area network. For example, the local area network may include gateway and gateway. Gateway can provide communication capabilities to network devices and/or access device via radio signals in order to provide communication, location, and/or other services to the devices. The gateway is directly connected to the external network and may provide other gateways and devices in the local area network with access to the external network. The gateway may be designated as a primary gateway.
[00064] The network access provided by gateway may be of any type of network
familiar to those skilled in the art that can support data communications using any of a variety of commercially-available protocols. For example, gateways may provide wireless communication capabilities for the local area network 100 using particular communications protocols, such as WiFi™ (e.g., IEEE 802.11 family standards, or other wireless communication technologies, or any combination thereof). Using the communications protocol(s), the gateways may provide radio frequencies on which wireless enabled devices in the local area network can communicate. A gateway may also be referred to as a base station, an access point, Node B, Evolved Node B (eNodeB), access point base station, a Femtocell, home base station, home Node B, home eNodeB, or the like.
[00065] Gateways may include a router, a modem, a range extending device, and/or
any other device that provides network access among one or more computing devices and/or external networks. For example, gateway may include a router or access point or a range extending device. Examples of range extending devices may include a wireless range extender, a wireless repeater, or the like.
[00066] A router gateway may include access point and router functionality, and may
further include an Ethernet switch and/or a modem. For example, a router gateway may receive and forward data packets among different networks. When a data packet is received,
14

the router gateway may read identification information (e.g., a media access control (MAC) address) in the packet to determine the intended destination for the packet. The router gateway may then access information in a routing table or routing policy, and may direct the packet to the next network or device in the transmission path of the packet. The data packet may be forwarded from one gateway to another through the computer networks until the packet is received at the intended destination.
[00067] As in a typical network architecture of the present disclosure can include a
plurality of network devices such as transmitter, receivers, and/or transceivers that may
include one or more Internet of Things (IOT) devices. As used herein, an IOT devices can be
a device that includes sensing and/or control functionality as well as a Wi-Fi transceiver
radio or interface, a Bluetooth transceiver radio or interface, a Zigbee transceiver radio or
interface, an Ultra-Wideband (UWB) transceiver radio or interface, a Wi-Fi Direct
transceiver radio or interface, a Bluetooth Low Energy (BLE) transceiver radio or interface,
and/or any other wireless network transceiver radio or interface that allows the IOT device to
communicate with a wide area network and with one or more other devices. In some
embodiments, an IOT device may include a cellular transceiver radio, and may be configured
to communicate with a cellular network using the cellular network transceiver radio.
[00068] 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.
[00069] 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
15

herein are for illustrative purposes and, thus, are not intended to be limited to any particular named.
[00070] 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.
[00071] 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 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.
[00072] 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
[00073] The present disclosure provides a device, system, and method for landslide
detection.
16

[00074] The present disclosure provides real-time detection and intimation of a
likelihood of a landslide like event.
[00075] The present disclosure provides landslide detection at an earlier stage.
[00076] The present disclosure provides necessary alert to an emergency authority like
hospital, disaster management, and hospital about likelihood of a landslide like event at an
earlier stage.
[00077] The present disclosure provides exact location of place where there is
likelihood of a landslide like event to the emergency authority.
[00078] The present disclosure provides parameters associated with soil of place where
there is likelihood of a landslide like event to the metrological department.
[00079] The present disclosure analyses of the parameters based on combination of
deep learning, and artificial neural networks.
[00080] The present disclosure provides a device, system, and method for landslide
detection that is cost effective and easy to implement.

WE CLAIMS

1. A landslide detection device (100) comprising:
a memory (102);
a microprocessor (104) coupled to the memory (102);
a sensor module (106) communicatively coupled to the microprocessor (104) and
a plurality of sensors (204);
a Global Positioning System module (GPS) (108) communicatively coupled to
the microprocessor (104), the plurality of sensors (204), and a server (202);
a Global System for Mobile communications module (GSM) (110)
communicatively coupled to the microprocessor (104) and the server (202),
wherein the microprocessor (104) is configured to:
collect, through the sensor module (106), data associated with an area gathered
through the plurality of sensors (204),
acquire, through the Global Positioning System module (GPS) (108), location
parameters associated with the plurality of sensors (204),
identify, based on analysis of the collected data at the server (202), likelihood
of a landslide like event, and
transfer, through the Global System for Mobile communications module
(GSM) (110), the identified likelihood of landslide like event to an emergency
authority.
2. The device (100) as claimed in claim 1, wherein the plurality of sensors (204) is any or a
combination of a temperature sensor, humidity sensor, pressure sensor, angle sensor,
friction sensor.
3. The device (100) as claimed in claim 2, wherein the plurality of sensors (204) monitors
parameters of soil of the area where the sensors (204) are provided for detecting the
likelihood of landslide like event.
4. The device (100) as claimed in claim 1, wherein the analysis of the collected data at the
server (202) is based upon any or a combination of deep learning, deep structured
learning, hierarchical learning, artificial neural networks, deep neural networks, deep
belief networks, recurrent neural networks, convolutional neural networks.
5. The device (100) as claimed in claim 1, wherein the emergency authority is any or a
combination of disaster management, metrological department, hospital.
18
6. A landslide detection system (200) comprising:
a landslide detection device (100);
a server (202) communicably coupled to the landslide detection device (100); and
a plurality of sensors (204) communicably coupled to the server (202) and the
landslide detection device (100), wherein the landslide detection device (100)
includes:
a memory (102);
a microprocessor (104) coupled to the memory (102);
a sensor module (106) communicatively coupled to the microprocessor (104)
and the plurality of sensors (204);
a Global Positioning System module (GPS) (108) communicatively coupled to
the microprocessor (104), the plurality of sensors (204), and a server (202);
a Global System for Mobile communications module (GSM) (110)
communicatively coupled to the microprocessor (104) and the server (202),
wherein the microprocessor (104) is configured to:
collect, through the sensor module (106), data associated with an area
gathered through the plurality of sensors (204),
acquire, through the Global Positioning System module (GPS) (108),
location parameters associated with the plurality of sensors (204),
identify, based on analysis of the collected data at the server (202),
likelihood of a landslide like event, and
transfer, through Global System for Mobile communications module
(GSM) (110), the identified likelihood of landslide like event an emergency
authority.
7. The landslide detection system (200) as claimed in claim 6 is an Internet of Things (IoT)
based system.
8. A landslide detection method (300) comprising:
collecting, through a sensor module (106) of a landslide detection device (100), data
associated with an area gathered through a plurality of sensors (204),
acquiring, through a Global Positioning System module (GPS) (108) of the landslide
detection device (100), location parameters associated with the plurality of sensors (204),
19
identifying, based on analysis of the collected data at a server (202) communicably
coupled with the landslide detection device (100) and the plurality of sensors (204),
likelihood of a landslide like event, and
transferring, through a Global System for Mobile communications module (GSM)
(110) of the landslide detection device (100), the identified likelihood of landslide like event
to an emergency authority