The present disclosure relates to the field of landslide monitoring and
detection. More particularly, the present disclosure relates to a system for monitoring of shallow landslide.
BACKGROUND
[0002] 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] Movement of a mass of rock, debris, or earth down a slope is termed as
Landslide. Movement down the slope occurs when forces acting down-slope (mainly due to
gravity) exceed the strength of the earth materials that compose the slope. Debris flows, also
known as mudflows or mudslides, and rockfalls are common landslide types.
[0004] Based on soil displaced, Landslides could be classified into Shallow Landslide
and Deep-Seated Landslide. In case of Shallow Landslides, sliding surface is located within soil mantle or weathered bedrock having a depth from few decimeters to some meters. The surficial and sub-surficial landslide movements are associated with Shallow Landslides. Debris slides, debris flow, and failures of road cut-slopes are common examples of Shallow Landslides.
[0005] In case of Deep-Seated Landslides, sliding surface is generally deeply located,
with depth even more than the maximum rooting depth of trees (depths greater than ten
meters). Deep-Seated Landslides usually involve deep regolith, weathered rock,
and/or bedrock. Deep-Seated Landslides include large slope failure associated with
translational, rotational, or complex movement and potentially occur in an active tectonic
region like Zagros Mountain in Iran. These generally move slowly, only a few meters per
year, but occasionally move faster. Deep-Seated Landslidestend to be larger than shallow
landslides and form along a plane of weakness such as a fault or bedding plane.
[0006] Even though life loss due to landslides is minimal, landslides occurring on
national highways still cause an extreme socio-economic loss. These national highways are one of the most important trade routes. Unchecked landslides on these areas would still pose a great threat during emergency times. Study of existing landslides and providing mitigation

and remediation measures are as well as to analyse the future threats of these landslides is important. As rainfall, soil and structural characteristics is the primary cause of landslide initiation in hilly areas such as Himachal Pradesh; it is essential to study the rainfall-based landslides and causative factors behind them.
[0007] Currently, landslides monitoring and early warning systems require
government actions and need to mobilise a lot of manpower, material resources, the use of large, expensive monitoring equipment. The main monitoring methods: Macro observation method abnormality such as abnormal animals, significantly displaced Laid surface, subsidence, crack, swelling, geophysical method, displacement measurement, analysis abnormal water level and aerial remote sensing method. However, Macro observation methods monitoring equipment are bulky, need professionals to operate and other issues. Moreover, only a small number of key areas to monitor, cannot be extended to vast areas of security risk, it is difficult to meet rural businesses and individual geological disaster monitoring and early warning demand.
OBJECTS OF THE PRESENT DISCLOSURE
[0008] Some of the objects of the present disclosure, which at least one embodiment
herein satisfies are as listed herein below.
[0009] It is an object of the present disclosure to provide a system to detect landslide
movements.
[0010] It is another object of the present disclosure to provide a system to
detectshallow landslide movements.
[0011] It is another object of the present disclosure to provide a system to detect
landslide movements in a fast, reliable, efficient and cost-effective manner.
[0012] It is another object of the present disclosure to provide a system to save human
lives and livings by forecasting landslide movements.
[0013] It is another object of the present disclosure to provide a system that can help
the government to detect landslide efficiently to help lower down the casualties and damage
associated with landslides.
SUMMARY
[0014] The present disclosure relates to the field of landslide monitoring and
detection. More particularly, the present disclosure relates to a system for monitoring of shallow landslide.

[0015] An aspect of the present disclosure pertains to a system to monitor shallow
landslide at a location, the system comprising: a set of first sensors disposed at least partially in soil of an area of interest(AOI) and configured to generate a set of first signals pertaining to sensed geological parameters; a set of second sensors positioned at the AOI and configured to generate a set of second set of signals pertaining to sensed meteorological parameters; a computing unit operatively coupled to the set of first sensors and the set of second sensors, the computing unit comprising one or more processors coupled with memory, the memory storing instructions executable by the one or more processors, may be configured to: extract first parametric values associated with the geological parameters from the set of first signals; extract second parametric values associated with the meteorological parameters from the set of second signals; wherein the first parametric values and the second parametric values may pertain to attributes associated with likelihood of landslide; and, generate a weighted value of the first extracted parametric values and the second extracted parametric values based on one or more weighting factors, wherein the one or more weighing factors may pertain to topography of the AOI; wherein, when the generated weighted value exceeds the pre-determined weighted value, the system may be configured to generate a warning to indicate one or more metrics pertaining to probability, time, impact, strength and extent of occurrence of the landslide in the AOI.
[0016] In an aspect, the geological parameters associated with the AOI may be any or
a combination of soil moisture, rate of movement of soil particles, soil particle size, specific gravity, soil density, soil permeability and shear strength.
[0017] In an aspect, the meteorological parameters associated with the AOI may be
any or a combination amount of precipitation, humidity, temperature, atmospheric pressure, and wind velocity.
[0018] In an aspect, the system may compriseone or more communication units
operatively coupled to the computing unit to communicatively couple the system to one or
more mobile computing devices, and wherein computing unit may be configured to process
the set of warning signals to be represented on the one or more mobile computing devices.
[0019] In an aspect, the one or more communication unit may comprise any or a
combination of a Bluetooth module, a GSM module, a WIFI module, and wherein the system may be configured to transmit any or a combination of the first set of signals, the second set of signals, the first extracted parametric values, and the second extracted parametric values to the one or more mobile computing devices for data analysis.

[0020] In another aspect, the one or more mobile computing device may be
configured to transmit a set of control signals to enable configuration of any or a combination
of the one or more weighing factors, and the pre-determined weighted value.
[0021] In an aspect, the system may comprise a display unit operatively coupled to
the computing unit, and wherein the set of warning signals may be processed by the
computing unit to be represented on the display unit.
[0022] In an aspect, the display unit may be configured to display the extracted
parametric values of the one or more geotechnical parameters, the extracted parametric
values of the one or more meteorological parameters, and the generated weighted
combination.
[0023] In an aspect, the set of first sensors may comprise any or a combination of the
tensiometer, volumetric sensor. A tiltmeter, solid-state sensors, strain gauge piezometer,
vibrating wire piezometer, dielectric moisture sensor, and geophone.
[0024] In an aspect, the set of second sensors comprises any or a combination of
anemometer, thermometer, hygrometer, pluviometer, and barometer.
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] The accompanying drawings are included to provide a further understanding
of the present disclosure, and are incorporated in and constitute a part of this specification.
The drawings illustrate exemplary embodiments of the present disclosure and, together with
the description, serve to explain the principles of the present disclosure.
[0026] The diagrams are for illustration only, which thus is not a limitation of the
present disclosure, and wherein:
[0027] FIG. 1 illustrates an exemplary overall network architecture of the proposed
system for detection of shallow landslides to elaborate its working, in accordance with an
exemplary embodiment of the present disclosure.
[0028] FIG. 2 illustrates an exemplary overall architecture of a computing unit of the
proposed device, in accordance with an exemplary embodiment of the present disclosure.
[0029] FIG. 3 illustrates an exemplary flow diagram of the proposed method for
detection of shallow landslides, in accordance with an exemplary embodiment of the present
disclosure.

DETAILED DESCRIPTION
[0030] 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.
[0031] 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.
[0032] In some embodiments, the numerical parameters set forth in the written
description and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values presented in some embodiments of the invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
[0033] All publications herein are incorporated by reference to the same extent as if
each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
[0034] In some embodiments, the numbers expressing quantities of ingredients,
properties such as concentration, reaction conditions, and so forth, used to describe and claim certain embodiments of the invention are to be understood as being modified in some instances by the term "about." Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of

reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values presented in some embodiments of the invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
[0035] 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.
[0036] The recitation of ranges of values herein is merely intended to serve as a
shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[0037] Groupings of alternative elements or embodiments of the invention disclosed
herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all groups used in the appended claims.
[0038] The present disclosure relates to the field of landslide monitoring and
detection. More particularly, the present disclosure relates to a system for monitoring of shallow landslide.
[0039] An aspect of the present disclosure pertains to a system to monitor shallow
landslide at a location, the system including: a set of first sensors disposed at least partially in soil of an area of interest(AOI) and configured to sense geological parameters and generate a set of first signals pertaining to the sensed geological parameters; a set of second sensors

positioned at the AOI and configured to sense meteorological parameters and generate a set of second set of signals pertaining to the sensed meteorological parameters; a computing unit operatively coupled to the set of first sensors and the set of second sensors, the computing unit including one or more processors coupled with memory, the memory storing instructions executable by the one or more processors, may be configured to: extract first parametric values associated with the geological parameters from the set of first signals; extract second parametric values associated with the meteorological parameters from the set of second signals; wherein the first parametric values and the second parametric values may pertain to attributes associated with likelihood of landslide; and, generate a weighted value of the first extracted parametric values and the second extracted parametric values based on one or more weighting factors, wherein the one or more weighing factors can pertain to topography of the AOI; wherein, when the generated weighted value exceeds the pre-determined weighted value, the system can be configured to generate a warning to indicate one or more metrics pertaining to probability, time, impact, strength and extent of occurrence of the landslide in the AOI.
[0040] In an embodiment, the geological parameters associated with the AOI can be
any or a combination of soil moisture, rate of movement of soil particles, soil particle size,
specific gravity, soil density, soil permeability shear strength, and the likes.
[0041] In an embodiment, the meteorological parameters associated with the AOI can
be any or a combination amount of precipitation, humidity, temperature, atmospheric pressure, and wind velocity.
[0042] In an embodiment, the system can include one or more communication units
operatively coupled to the computing unit to communicatively couple the system to one or more mobile computing devices, and wherein computing unit can be configured to process the set of warning signals so as to be represented on the one or more mobile computing devices.
[0043] In an embodiment, the one or more communication unit can include any or a
combination of a Bluetooth module, a GSM module, a WIFI module, and wherein the system can be configured to transmit any or a combination of the first set of signals, the second set of signals, the first extracted parametric values, and the second extracted parametric values to the one or more mobile computing devices for data analysis.
[0044] In an embodiment, the one or more mobile computing device can be
configured to transmit a set of control signals to enable configuration of any or a combination of the one or more weighing factors, and the pre-determined weighted value.

[0045] In an embodiment, the system can include a display unit operatively coupled
to the computing unit, and wherein the set of warning signals can be processed by the
computing unit so as to be represented on the display unit.
[0046] In an embodiment, the display unit can be configured to display the extracted
parametric values of the one or more geotechnical parameters, the extracted parametric
values of the one or more meteorological parameters, and the generated weighted
combination.
[0047] In an embodiment, the set of first sensors can include any or a combination of
tensiometer, volumetric sensor, a tiltmeter, solid-state sensors, strain gauge piezometer,
vibrating wire piezometer, dielectric moisture sensor, and geophone.
[0048] In an embodiment, the set of second sensors can include any or a combination
of anemometer, thermometer, hygrometer, pluviometer, and barometer.
[0049] FIG. 1 illustrates an exemplary overall network architecture 100 of the
proposed system for detection of shallow landslides to elaborate its working, in accordance
with an exemplary embodiment of the present disclosure.
[0050] As illustrated, in an aspect, the proposed system can include a set of first sensors
102-1, 102-2... 102-N (collectively referred to as the set of first sensors 102, or first sensors
102,hereinafter) disposed at least partially in soil of an area of interest(AOI). The set of first
sensors 102 can facilitate sensing of geological parameters and generate a set of signals
pertaining to sensed geological parameters. The geological parameters associated with the
AOI can be any or a combination of soil moisture, rate of movement of soil particles, soil
particle size, specific gravity, soil density, soil permeability shear strength, and the likes. In
an exemplary embodiment, the set of first sensors 102 can be any or a combination of
tensiometer, volumetric sensor. A tilt-meter, solid-state sensors, strain gauge piezometer,
vibrating wire piezo-meter, dielectric moisture sensor, geophone, and the likes.
[0051] In an embodiment, the proposed system can include one or more second
sensors 104-1, 104-2... 104-N (collectively referred to as a set of second sensors 104 or
second sensors 104, hereinafter) positioned at the AOI. The set of second sensors 104 can
facilitate sensing of meteorological parameters and generate a set of signals pertaining to
sensedmeteorological parameters. The meteorological parameters associated with the AOI
can be any or a combination amount of precipitation, humidity, temperature, atmospheric
pressure, wind velocity, and the likes. In an exemplary embodiment, the set of second sensors
104 can include any or a combination of anemometer, thermometer, hygrometer,
pluviometer, barometer, and the likes.

[0052] In an embodiment, the proposed system can include a computing unit
108operatively coupled to the set of first sensors 102 and the set of second sensors 104 through a network 106. The computing unit 108 can be operatively coupled to a server 110.The computing unit 108can be configured to receive the set of first signals and the set of second signals and further configured to generate a warning signal to indicate one or more metrics pertaining to probability, time, impact, strength, extent of occurrence of the landslide in the AOI, and the likes.
[0053] In an exemplary embodiment, the network 106 can be a wireless network, a
wired network or combination thereof. The network 106 can be implemented as one of the
different types of networks, such as an intranet, local area network (LAN), wide area network
(WAN), the internet, Wi-Fi, LTE network, CDMA network, and the like. Further, the
network 106 can either be a dedicated network or a shared network. The shared network
represents an association of the different types of networks that use a variety of protocols, for
example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet
Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, to communicate with
one another. Further the network 106 can include a variety of network devices, including
routers, bridges, servers, computing devices, storage devices, and the like.
[0054] In an embodiment, one or more mobile computing devices 112-1, 112-2...
112-N (collectively referred to as mobile computing devices 112, hereinafter) can be operatively coupled to the computing unit 108. The mobile computing devices 112 can represent the set of warning signals transmitted by the computing unit 108. The mobile computing devices 112 can be configured to transmit a set of control signals to enable configuration of any or a combination of the one or more weighing factors, the pre¬determined weighted value, and the likes.
[0055] In an exemplary embodiment, the system can include a communication unit
operatively coupled to the computing unit 108 and configured to communicatively couple the system to the mobile computing devices 112. In an exemplary embodiment, the communication unit can include a WIFI module, Bluetooth module, Transceiver, and wired connections, but not limited to the likes
[0056] In an exemplary embodiment, the mobile computing devices 112 can include
any or a combination of smartphone, laptop, and computer, but not limited to the likes.
[0057] In an embodiment, the system can include a display unit 114 operatively
coupled to the computing unit 108. The set of warning signals can be processed by the computing unit so as to be represented on the display unit. The display unit 114 can be

configured to display the extracted parametric values of the one or more geotechnical parameters, the extracted parametric values of the one or more meteorological parameters, and the generated weighted combination.
[0058] In an exemplary embodiment, the display unit can be any or a combination of
LCD, LED, and OLED, monochromatic display but not limited to the likes.
[0059] In an exemplary embodiment, the system can be adapted to acquire real-time
geological parametric values and meteorological parametric values from third party sources. The system can acquire geological parametric values of an AOI from a weather satellite to detect for system-related errors. The acquired geological parametric values can be compared with the geological parametric values obtained from the second set of sensors to check accuracy of the system.
[0060] FIG. 2 illustrates an exemplary overall architecture of a computing unit of the
proposed device, in accordance with an exemplary embodiment of the present disclosure.
[0061] As illustrated, in an embodiment, the computing unit 102 can include one or
more processor(s) 202, the one or more processor(s) 202 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 202 can be configured to fetch and execute computer-readable instructions stored in a memory 204 of the computing unit. The memory 204 can store one or more computer-readable instructions or routines, which can be fetched and executed to create or share the data units over a network service. The memory 204 can be any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0062] The computing unit 108 can include an interface(s) 206. The interface(s) 206
can include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 can facilitate communication of the computing unit 108 with various devices coupled to the computing unitl08 such as an input unit and an output unit. The interface(s) 206 can also provide a communication pathway for one or more components of the computing unit and the proposed system 100. Examples of such components include, but not limited to, processing engine(s) 208 and database 216.
[0063] The processing engine(s) 208can be implemented as a combination of
hardware and programming (for example, programmable instructions) to implement one or

more functionalities of the processing engine(s) 208. In examples described herein, such
combinations of hardware and programming may be implemented in several different ways.
For example, the programming for the processing engine(s) 208can be processor executable
instructions stored on a non-transitory machine-readable storage medium and the hardware
for the processing engine(s) 208 can include a processing resource (for example, one or more
processors), to execute such instructions. In the present examples, the machine-readable
storage medium may store instructions that, when executed by the processing resource,
implement the processing engine(s) 208. In such examples, the processing unit 208 can
include the machine-readable storage medium storing the instructions and the processing
resource to execute the instructions, or the machine-readable storage medium may be
separate but accessible to computing unit 108 and the processing resource. In other examples,
the processing engine(s) 208 can be implemented by electronic circuitry.
[0064] In an embodiment, the database 216 can include data that is either stored or
generated as a result of functionalities implemented by any of the components of the processing engine(s) 208.
[0065] In an embodiment, the processing engine(s) 208 can include a parametric
value extraction engine 210, classification engine 212, and other engine(s), but not limited to the likes.
[0066] In an embodiment, the parametric value extraction engine 210 can facilitate
extraction of first parametric values associated with the geological parameters from the set of first signals. In another embodiment, the parametric value extraction engine 210 can facilitate extraction of second parametric values associated with the meteorological parameters from the set of second signals.
[0067] In an embodiment, the classification engine 212 can generate a weighted value
based on any or a combination of the first extracted parametric values and the second extracted parametric values. In another embodiment, the weighted value can be based on one or more weighting factors, the one or more weighing factors can pertain to topography of the AOI.
[0068] In an implementation, for a first AOI with loosely coupled soil particles, low
soil density and, a sloped terrain a rainfall of 30-40 mm in a day can result in a landslide. So, for the first AOI amount of rainfall can be the major factor associated with the landslide and hence, can be allocated a higher value. In another implementation, for a second AOI with high soil density and flat topology, a 100-150 mm rainfall in a day cannot be hazardous. Hence, for the second AOI weighting value allocated to rainfall could be minimal.

[0069] In an embodiment, the database 216 can include the pre-determined weighted
values associated with the geological parameters and the meteorological parameters. Each of the pre-determined weighted values can indicate a level of warning. In an exemplary implementation, the pre-determined weighted values can be scaled from 1 to 5. The pre-determined values 1 and 2 can indicate normal conditions. The pre-determined value 3can be associated with a low possibility of minor landslide having negligible impact. The pre-determined value 4 can be associated with a possibility of landslide with considerable impact. The pre-determined value 5 can be associated with a very high possibility of landslide with extreme impact.
[0070] FIG. 3 illustrates an exemplary flow diagram for detection of shallow
landslides, in accordance with an exemplary embodiment of the present disclosure.
[0071] As illustrated, in an exemplary embodiment, the flow diagram can include a
step 302, including installation of a set of first sensors 102 and a set of second sensors 104 at
predetermined positions at an AOL The set of first sensors 102 can sense geological
parameters and generate a set of first signals pertaining to the sensedgeological parameters.
The set of second sensors 104 can sense meteorological parameters and generate a set of
second set of signals pertaining to the sensedmeteorological parameters.
[0072] In an embodiment, the flow diagram can include a step 304 of transmission
ofthe sensed geological parameters and the sensed meteorological parameters. Aslave nodel, a slave node 2, and a slave node 3 can be operatively coupled to the first set of sensors 102 and the second set of sensors 104, and can be configured to transmit the sensed geological parameters and the sensed meteorological parameters to a master node. The master node can be operatively coupled to the slave nodel, slave node 2, and slave node 3 and can be configured to store and transmit the sensed geological parameters and the sensed meteorological parameters to a remote server.
[0073] In an embodiment, the flow diagram can include a step 306 in which the
remote servercan facilitate extraction of first parametric values associated with the geological parameters from the set of first signals and second parametric values associated with the meteorological parameters from the set of second signals. In another embodiment, the remote server can combine first extracted parametric values and the second extracted parametric values based on one or more weighting factors to generate a weighted parametric value. The one or more weighing factors can pertain to topography ofthe AOL

[0074] In an embodiment, the flow diagram can include a step 308 of comparison of
the generated weighted parametric value associated with the first parametric values and the second parametric values with a pre-determined weighted value.
[0075] In an embodiment, the flow diagram can include a step 31 Oof error detection
in the system. The remote server can compare the sensed geological parameters and the sensed meteorological parameters with the geological parameters and the meteorological parameters obtained from a third source to check accuracy of the system. In an exemplary embodiment, the remote server can be configured to generate a set of troubleshooting signals when the sensed geological parameters and the sensed meteorological parameters deviate from the geological parameters and the meteorological parameters obtained from the third source for resolving any error.
[0076] In an embodiment, the flow diagram can include a step 314of generating a
warning signal when the generated weighted parametric value exceeds the pre-determined
weighted value. The generated warning signals can indicate one or more metrics pertaining to
probability, time, impact, strength and extent of occurrence of the landslide in the AOL
[0077] 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 a person 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 INVENTION
[0078] The present disclosure provides a system to detect landslide movements.
[0079] The present disclosure provides a system to detect shallow landslide
movements.
[0080] The present disclosure provides a system to detect landslide movements in a
fast, reliable, efficient and cost-effective manner.
[0081] The present disclosure provides a system to save human lives and livings by
forecasting landslide movements.

[0082] The present disclosure provides a system that can help the government to
detect landslide efficiently to help lower down the casualties and damage associated with landslides.

We Claim:

1.A system to monitor shallow landslide at a location, the system comprising:
a set of first sensors disposed at least partially in soil of an area of interest(AOI) and configured to sensegeological parameters and generate a set of first signals pertaining to the sensedgeological parameters;
a set of second sensors positioned at the AOI and configured to sensemeteorological parameters and generate a set of second set of signals pertaining to the sensed meteorological parameters;
a computing unit operatively coupled to the set of first sensors and the set of second sensors, the computing unit comprising one or more processors coupled with memory, the memory storing instructions executable by the one or more processors, configured to:
extract first parametric values associated with the geological parameters from the set of first signals;
extract second parametric values associated with the meteorological parameters from the set of second signals, wherein the first parametric values and the second parametric values pertain to attributes associated with likelihood of landslide; and
generate a weighted value of the first extracted parametric values and the second extracted parametric values based on one or more weighting factors, wherein the one or more weighing factors pertain to a topography of the AOI, wherein, when the generated weighted value exceeds the pre-determined weighted value, the computing unit generates a set of warning signals to indicate at least one of one or more metrics pertaining to probability, time, impact, strength and extent of occurrence of the landslide in the AOI.
2. The system as claimed in claim 1, wherein the geological parameters associated with the AOI are any or a combination of soil moisture, rate of movement of soil particles, soil particle size, specific gravity, soil density, soil permeability and shear strength.
3. The system as claimed in claim 1, wherein the meteorological parameters associated with the AOI are any or a combination of amount of precipitation, humidity, temperature, atmospheric pressure, and wind velocity.
4. The system as claimed in claim 1, wherein the system comprises one or more communication units operatively coupled to the computing unit to communicatively

couple the system to one or more mobile computing devices, and wherein computing unit is configured to process the set of warning signals so as to be represented on the one or more mobile computing devices.
5. The system as claimed in claim 4, wherein the one or more communication unit comprises any or a combination of a Bluetooth module, a GSM module, a WIFI module, and wherein the system is configured to transmit any or a combination of the first set of signals, the second set of signals, the first extracted parametric values, and the second extracted parametric values to the one or more mobile computing devices for data analysis.
6. The system as claimed in claim 1, wherein the system comprises a display unit operatively coupled to the computing unit, and wherein the set of warning signals are processed by the computing unit so as to be represented on the display unit.
7. The system as claimed in claim 7, wherein the display unit is configured to display the extracted parametric values of the one or more geotechnical parameters, the extracted parametric values of the one or more meteorological parameters, and the generated weighted combination.
8. The system as claimed in claim 1, wherein the set of first sensors comprises any or a combination of tensiometer, volumetric sensor, a tiltmeter, solid-state sensors, strain gauge piezometer, vibrating wire piezometer, dielectric moisture sensor, and geophone.
9. The system as claimed in claim 1, wherein the set of second sensors comprises any or a combination of anemometer, thermometer, hygrometer, pluviometer, and barometer.