1. A method (200) of providing enhanced security of a physical asset (101) within a
physical infrastructure (114), the method (200) comprising:
receiving (201), by a security system (103), an overall layout of the physical infrastructure (114) and multi-modal input with respect to the physical asset (101) from a plurality of sensors (115) installed within the physical infrastructure (114), wherein the multi-modal input comprises acoustic signal generated by or reflected off the physical asset (101) and captured by a set of acoustic sensors (503);
generating (202), by the security system (103), a digital asset (505) corresponding to the physical asset (101) by determining an identification, a location, a shape, a size, and a behavior of the physical asset (101) based on the multi-modal input and the overall layout;
detecting (203), by the security system (103), one or more events of interest involving the digital asset (505) based on the behavior of the physical asset (101); and
simulating (204), by the security system (103), the one or more events of interest to evaluate a possible fault or a possible security threat.
2. The method (200) of claim 1, wherein the multi-modal input further comprises at
least one of biometric readings recorded by a set of biometric sensors, RFID readings
recorded by a set of RFID sensors, or camera feeds recorded by a set of cameras;
wherein the overall layout of the physical infrastructure (114) comprises at least one of
computer aided design (CAD) drawings of the physical infrastructure (114) and
computer aided manufacturing (CAM) drawings of the physical asset (101); and wherein
the behavior comprises at least one of a movement, a speech, an activity, a physical
state, and an emotional state.

3. The method (200) of claim 1, further comprising determining a positioning of each of
the set of acoustic sensors (503) to generate a three-dimensional view of the physical
asset (101) by:
placing a first set of acoustic sensors (401a-d) to determine a position of the physical asset (101) using a measure of signal difference recorded by at least two of the first set of acoustic sensors (401a-d); and
positioning each of a second set of acoustic sensors (402a-d), based on positions of the at least two of the first set of acoustic sensors (401a-d) with respect to the position of the physical asset (101), using triangularization.
4. The method (200) of claim 1, wherein generating (202) the digital asset (505) corresponding to the physical asset (101) comprises generating a digital twin of the physical asset (101) based on the location, a movement, an angle, an image, and the size of the physical asset (101).
5. The method (200) of claim 1, wherein simulating (204) the one or more events comprises:
identifying an imminent fault or an imminent security threat based on the multi-modal input using a machine learning model; and
in absence of the imminent fault or the imminent security threat, triggering the machine learning model to perform pattern recognition based on the multi-modal input or to perform learning.
6. A system (100) for providing enhanced security of a physical asset (101) within a
physical infrastructure (114), the system (100) comprising:
a processor; and
a memory communicatively coupled to the processor, wherein the memory
stores processor-executable instructions, which, on execution, causes the processor to:
receive (201) an overall layout of the physical infrastructure (114) and
multi-modal input with respect to the physical asset (101) from a plurality of
sensors (115) installed within the physical infrastructure (114), wherein the multi-

modal input comprises acoustic signal generated by or reflected off the physical asset (101) and captured by a set of acoustic sensors (503);
generate (202) a digital asset (505) corresponding to the physical asset (101) by determining an identification, a location, a shape, a size, and a behavior of the physical asset (101) based on the multi-modal input and the overall layout;
detect (203) one or more events of interest involving the digital asset (505) based on the behavior of the physical asset (101); and
simulate (204) the one or more events of interest to evaluate a possible fault or a possible security threat.
7. The system (100) of claim 6, wherein the multi-modal input further comprises at least one of biometric readings recorded by a set of biometric sensors, RFID readings recorded by a set of RFID sensors, or camera feeds recorded by a set of cameras; wherein the overall layout of the physical infrastructure (114) comprises at least one of computer aided design (CAD) drawings of the physical infrastructure (114) and computer aided manufacturing (CAM) drawings of the physical asset (101); and wherein the behavior comprises at least one of a movement, a speech, an activity, a physical state, and an emotional state.
8. The system (100) of claim 6, wherein the processor-executable instructions further cause the processor to determine a positioning of each of the set of acoustic sensors (503) to generate a three-dimensional view of the physical asset (101) by:
placing a first set of acoustic sensors (401a-d) to determine a position of the physical asset (101) using a measure of signal difference recorded by at least two of the first set of acoustic sensors (401a-d); and
positioning each of a second set of acoustic sensors (402a-d), based on positions of the at least two of the first set of acoustic sensors (401a-d) with respect to the position of the physical asset (101), using triangularization.
9. The system (100) of claim 1, wherein the processor generates (202) the digital asset
(505) corresponding to the physical asset (101) by generating a digital twin of the

physical asset (101) based on the location, a movement, an angle, an image, and the size of the physical asset (101).
10. The system (100) of claim 6, wherein the processor simulates (204) the one or more events by:
identifying an imminent fault or an imminent security threat based on the multi-modal input using a machine learning model; and
in absence of the imminent fault or the imminent security threat, triggering the machine learning algorithm to perform pattern recognition based on the multi-modal input or to perform learning.