Claims:WE CLAIM:
1. A contactless Seat Belt Monitoring (SBM) system for a vehicle, the SBM system comprising:
an Electronic Control Unit (ECU);
a sensor for generating frequency modulated continuous waves inside the vehicle, wherein the sensor sweeps the frequency modulated continuous waves in a direction of at least one seat in the vehicle;
at least one seat belt, for securing a plurality of occupants in the vehicle, wherein each of the at least one seat belt is coated with a predetermined material capable of absorbing the frequency modulated continuous waves; and
a receiver antenna, associated with the sensor, for receiving the frequency modulated continuous waves reflected,
wherein the ECU is configured to:
generate point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves received by the receiver antenna; and
analyze the point cloud rendering data using a pretrained learning model to determine a locking status of the at least one seat belt.

2. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the frequency modulated continuous waves are generated using a 4-Dimensional (4D) radar sensor.

3. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the predetermined material is Teflon.

4. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the at least one seat belt is made of woven narrow fabric comprising at least one of nylon filament yarns and high-tensile polyester filament yarns.

5. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the Teflon coating on the at least one seat belt increases a di-electric coefficient and an insulation coefficient of the at least one seat belt.

6. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the locking status of the at least one seat belt is at least one of ‘locked’ and ‘unlocked’.

7. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 6, wherein the locking status of the at least one seat belt is:
‘locked’ when there is no point cloud rendering data along a line of the at least one seat belt; or
‘unlocked’ when the point cloud rendering data is present along the line of the at least one seat belt.

8. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 7, wherein the at least one seat belt is designed with a predetermined surface pattern along the line of the at least one seat belt, wherein the predetermined surface pattern is not coated with Teflon.

9. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 8, wherein the line of the at least one seat belt is determined by performing a semantic analysis of images corresponding to the frequency modulated continuous waves reflected from the predetermined surface pattern.

10. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the ECU generates an alert when the locking status of the at least one seat belt is ‘unlocked’.

11. The contactless Seat Belt Monitoring (SBM) system as claimed in claim 1, wherein the point cloud rendering data comprises an azimuth measurement, an elevation angle, a range and a transmission time associated with the frequency modulated continuous waves received by the receiver antenna.

12. A method for contactless monitoring of seat belts in a vehicle, the method comprising:
generating, using a sensor configured in the vehicle, frequency modulated continuous waves inside the vehicle, wherein the sensor sweeps the frequency modulated continuous waves in a direction of at least one seat in the vehicle;
receiving, using a receiver antenna associated with the sensor, the frequency modulated continuous waves reflected, wherein a portion of the frequency modulated continuous waves generated by the sensor is absorbed by at least one seat belt coated with a predetermined material capable of absorbing the frequency modulated continuous waves;
generating, by an Electronic Control Unit (ECU) of the vehicle, a point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves received by the receiver antenna; and
analyzing, by the ECU, the point cloud rendering data using a pretrained learning model to determine a locking status of the at least one seat belt.

13. The method as claimed in claim 12, wherein the frequency modulated continuous waves are generated using a 4-Dimensional (4D) radar sensor.

14. The method as claimed in claim 12, wherein the predetermined material is Teflon.

15. The method as claimed in claim 12, wherein the at least one seat belt is made of woven narrow fabric comprising at least one of nylon filament yarns and high-tensile polyester filament yarns.

16. The method as claimed in claim 12, wherein the Teflon coating on the at least one seat belt increases a di-electric coefficient and an insulation coefficient of the at least one seat belt.

17. The method as claimed in claim 12, wherein the locking status of the at least one seat belt is at least one of ‘locked’ and ‘unlocked’.

18. The method as claimed in claim 17, comprises:
detecting the locking status of the at least one seat belt as ‘locked’ when there is no point cloud rendering data along a line of the at least one seat belt; and
detecting the locking status of the at least one seat belt as ‘unlocked’ when the point cloud rendering data is present along the line of the at least one seat belt.

19. The method as claimed in claim 18, comprises designing the at least one seat belt with a predetermined surface pattern along the line of the at least one seat belt, wherein the predetermined surface pattern is not coated with Teflon.

20. The method as claimed in claim 19, comprises performing a semantic analysis of images corresponding to the frequency modulated continuous waves reflected from the predetermined surface pattern for determining the line of the at least one seat belt.

21. The method as claimed in claim 12 further comprises generating an alert when the locking status of the at least one seat belt is ‘unlocked’.

22. The method as claimed in claim 12, wherein the point cloud rendering data comprises an azimuth measurement, an elevation angle, a range and a transmission time associated with the frequency modulated continuous waves received by the receiver antenna. , Description:TECHNICAL FIELD
[0001] The present disclosure relates in general to automobiles. Particularly the present disclosure relates to a method and system for contactless Seat Belt Monitoring (SBM) using point cloud and Artificial Intelligence (AI) models.
BACKGROUND
[0002] Seat belts are a standard safety device found in almost all vehicles. Despite their widespread adoption, seat belts are not always worn and used properly by passengers. For example, there are still instances when a passenger either forgets or chooses not to wear a seat belt. In the current system people use a dummy buckle to fake the system. As one would expect, in these instances, the seat belt is less effective. Not wearing the seat belts in the event of accidents can cause serious injuries to the passengers.
[0003] In the current-age vehicles, to detect lock/unlock status of the seat belts, the Electronic Control Unit (ECU) needs to be hardwired to receive digital signals from each seat position via connections routed inside the cabin floor for two or three rows seating. Further, harness design, which illustrates an electrical assembly of various components in a vehicle, is also more complex in case of fully modular seating arrangement, especially in vehicles having more than 7 seats. Moreover, the seat belt latch detection switches may be easily faked or subject to unreliability. For example, a person may buckle a seat belt into a seat belt latch and then seat on top of the seat belt. Also, a camera-based seat belt detection system may cause privacy concerns for persons inside the vehicle. A person may reject the usage of the camera inside the vehicle to maintain privacy. Further, the camera-based seat belt detection system may be faked as well, for example, when a passenger wears clothing with a pattern that imitates the seat belt, rather than using the seat belt.
[0004] The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY
[0005] Disclosed herein is a contactless Seat Belt Monitoring (SBM) system. The SBM system comprises an Electronic Control Unit (ECU), a sensor, at least one seat belt and a receiver antenna associated with the sensor. The sensor generates frequency modulated continuous waves inside the vehicle. Further, the sensor sweeps the frequency modulated continuous waves in a direction of at least one seat in the vehicle. The at least one seat belt is used for securing a plurality of occupants in the vehicle. Each of the at least one seat belt is coated with a predetermined material capable of absorbing the frequency modulated continuous waves. The receiver antenna receives frequency modulated continuous waves reflected. Further, the ECU is configured to generate point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves received by the receiver antenna and analyze the point cloud rendering data using a pretrained learning model to determine a locking status of the at least one seat belt.
[0006] Further, the present disclosure relates to a method for contactless monitoring of seat belts in a vehicle. The method comprises generating, using a sensor configured in the vehicle, frequency modulated continuous waves inside the vehicle. The sensor sweeps the frequency modulated continuous waves in a direction of at least one seat in the vehicle. Further, the method comprises receiving the frequency modulated continuous waves reflected. A portion of the frequency modulated continuous waves generated by the sensor is absorbed by at least one seat belt coated with a predetermined material capable of absorbing the frequency modulated continuous waves. Thereafter, the method comprises generating a point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves received by the receiver antenna. Finally, the method comprises analyzing the point cloud rendering data using a pretrained learning model to determine a locking status of the at least one seat belt.
[0007] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0008] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which:
[0009] FIG. 1 illustrates an exemplary arrangement for contactless Seat Belt Monitoring (SBM), in accordance with some embodiments of the present disclosure.
[0010] FIG. 2 shows a detailed block diagram of a Seat Belt Monitoring (SBM) system in a vehicle, in accordance with some embodiments of the present disclosure.
[0011] FIG. 3 shows a flowchart illustrating a method for contactless Seat Belt Monitoring (SBM) in a vehicle, in accordance with some embodiments of the present disclosure.
[0012] FIG. 4A shows a flowchart illustrating a method of processing point cloud data in accordance with some embodiments of the present disclosure.
[0013] FIG. 4B shows a flowchart illustrating a method of determining locking status of the seat belt and generating alerts in accordance with some embodiments of the present disclosure.
[0014] FIGS. 5A and 5B illustrate a method of determining locking status of the seat belt based on reflection pattern of reflected waves in accordance with some embodiments of the present disclosure.
[0015] FIG. 6 shows rendering of point cloud data corresponding to locking status of the seat belt in accordance with some embodiments of the present disclosure.
[0016] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown.
DETAILED DESCRIPTION
[0017] In the present document, the word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment or implementation of the present subject matter described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.
[0018] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the specific forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.
[0019] The terms “comprises”, “comprising”, “includes”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device, or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.
[0020] The present disclosure relates to a method and a system for contactless seat belt monitoring in a vehicle. In an embodiment, the proposed contactless Seat Belt Monitoring (SBM) system identifies the seat belt lock/unlock status in the vehicle using frequency modulated continuous waves. The frequency modulated continuous waves are generated inside the vehicle and are swept in a direction of occupants in the vehicle. The seat belts in the vehicle are coated with a predetermined material, such as Teflon, which absorbs the continuous waves. Also, the seat belts are designed with a predetermined surface pattern, along a line of the seat belts, such that the surface pattern is not coated with the predetermined material. In other words, the surface pattern ensures the seat belts do not fully absorb the continuous waves.
[0021] In an embodiment, the vehicle is configured with a receiver antenna that receives the frequency modulated continuous waves reflected from the occupants and the portion of seat belts with surface pattern. Further, the ECU generates point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves received by the receiver antenna. The point cloud rendering data is analyzed using a pretrained learning model to detect a locking status of the seat belts. The ECU generates an alert when the seat belts are determined to be ‘unlocked’.
[0022] In an embodiment, the method and system of the proposed disclosure aims to secure the occupants and/or passengers of the vehicle by ensuring that they are wearing seat belts. Also, the proposed disclosure suggests generating an alert when the occupants of the vehicle are not wearing the seat belt.
[0023] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
[0024] FIG. 1 illustrates an exemplary arrangement for contactless Seat Belt Monitoring (SBM), in accordance with some embodiments of the present disclosure.
[0025] In an embodiment, a vehicle 101, in which the contactless seat belt monitoring has to be performed, may be configured with a seat belt monitoring system 103. As an example, the vehicle 101 may be a passenger vehicle 101 such as a car, a van, a bus and/or a commercial vehicle 101 such as pick-up trucks. In an embodiment, the seat belt monitoring system 103 may include, without limiting to, an Electronic Control Unit (ECU), a sensor 105, one or more seat belts 109 (alternatively referred as seat belts 109 or at least one seat belt 109) and a receiver antenna 113. In an embodiment, the seat belt 109 monitoring system 103 may be a dedicated computing unit and/or an ECU dedicated for monitoring status of the seat belt 109s in the vehicle 101. Alternatively, an existing ECU of the vehicle 101 may be upgraded to perform functionalities of the seat belt monitoring system 103, in accordance with the embodiments of the present disclosure.
[0026] In an embodiment, the ECU of the seat belt monitoring system 103 may be configured for controlling and coordinating operations each of the other modules and/or components of the seat belt monitoring system 103. In an embodiment, the sensor 105 may be configured for generating frequency modulated continuous waves 107 inside the vehicle 101. As an example, the sensor 105 may be a 4-Dimensional (4D) radar sensor. In an embodiment, the sensor 105 may sweep the frequency modulated continuous waves 107 in a direction of a plurality of occupants, and/or the at least one seat belt 109 worn by the occupants.
[0027] In an embodiment, the at least one seat belt 109 may be specially designed and made of a woven narrow fabric comprising at least one of nylon filament yarns and/or high-tensile polyester filament yarns. Further, the at least one seat belt 109 may be coated with predetermined material that is capable of completely absorbing the frequency modulated continuous waves 107 generated by the sensor 105. As an example, the predetermined material may be Teflon. In an embodiment, coating the seat belt 109s with the predetermined material increases a di-electric coefficient and an insulation coefficient of the seat belts 109 and ensures that the seat belts 109 completely absorb the frequency modulated continuous waves 107 received from the sensor 105.
[0028] In an embodiment, the plurality of seat belts 109 are designed with a predetermined surface pattern along the line of the seat belts 109. The predetermined surface pattern may not be coated with the predetermined material, such that the plurality of seat belts 109 reflect the frequency modulated continuous waves 107 that are falling on the predetermined surface pattern. As an example, the predetermined surface pattern may be diamond-shape pattern, rectangle pattern or square pattern. Consequently, when the occupants are wearing the seat belt 109, the frequency modulated continuous waves 107 are reflected from the predetermined surface pattern, thereby clearly indicating that the occupants are wearing the seat belts 109. Alternatively, when the one or more occupants are not wearing the seat belt 109, the reflected frequency modulated continuous waves 111 do not indicate the pattern on the seat belts 109, based on which, it may be determined that the occupants are not wearing the seat belts 109.
[0029] In an embodiment, the receiver antenna 113 may be associated with the sensor 105. The receiver antenna 113 may be configured to receive the frequency modulated continuous waves 111 that are reflected from the occupants and/or the seat belts 109.
[0030] In an embodiment, the ECU may determine a pattern of the frequency modulated continuous waves 111 received at the receiver antenna 113 and generate a point cloud rendering data corresponding to the pattern of the frequency modulated continuous waves 107 received by the receiver antenna 113. In an embodiment, the point cloud rendering data may comprise, without limitation, an azimuth measurement, an elevation angle, a range, and a transmission time associated with the frequency modulated continuous waves 107 received by the receiver antenna 113.In an embodiment, the Azimuth measurement indicates the angular measurement of the frequency modulated continuous waves. The elevation angle indicates the angle between a horizontal plane and an axial direction of the sensor 105. The range comprises the frequency value of the modulated waves. The transmission time may indicate the time taken for transmitting the frequency modulated waves 107 from the sensor 105 and to receive the reflected frequency modulated waves 107 from the seat belt 109.
[0031] In an embodiment, the point cloud rendering data may be analyzed using a pretrained learning model associated with the ECU. As an example, the pretrained learning model may be, Region-based Convolutional Neural Network (RCNN). The pretrained learning model analysis the point cloud rendering data and determines a locking status of the at least one seat belt 109. As an example, the locking status of the seat belts 109 may be at least one of ‘locked’ or ‘unlocked’.
[0032] In an embodiment, the locking status of the at least one seat belt 109 may be determined as ‘locked’ when there is no point cloud rendering data along a line of the at least one seat belt 109. In other words, when the at least one seat belt 109 is in the ‘locked’ condition, the seat belt 109 and hence the predetermined surface pattern of the seat belt 109 would cover a portion of the occupant and there would not be any reflections from the predetermined surface pattern. Consequently, there would not be any point cloud rendering data available along the line of the seat belts 109.
[0033] In an embodiment, the locking status of the at least one seat belt 109 may be determined as ‘unlocked’ when there is point cloud rendering data present along a line of the at least one seat belt 109. In other words, when the at least one seat belt 109 is in the ‘unlocked’ condition, the seat belt 109 and hence the predetermined surface pattern of the seat belt 109 would not obstruct the reflections from the occupant. Consequently, there would be no point cloud rendering data available along the line of the seat belts 109. In an embodiment, when the locking status is determined as ‘unlocked’, the ECU may generate an alert to warn the occupants that the seat belts 109 are not locked. As an example, the alert may be provided as a sound notification using speakers of the vehicle. Alternatively, the alert may be provided as a visual notification on the infotainment unit of the vehicle.
[0034] FIG. 2 shows a detailed block diagram of a Seat Belt Monitoring (SBM) system in a vehicle, in accordance with some embodiments of the present disclosure.
[0035] In an embodiment, the Seat Belt Monitoring (SBM) 103 system may include an I/O Interface 201, a sensor 105, an Electronic Control Unit (ECU) 203, a receiver antenna 113 and a memory 205 storing at least one data and modules 209. The I/O interface 201 may be coupled with the ECU 203 for receiving and transmitting an input signal or/and an output signal related to one or more operations of the SMB 103 system. In an embodiment, the sensor 105 may be configured to generate frequency modulated continuous waves 107 inside the vehicle 101 and sweep the generated frequency modulated continuous waves 107 in a direction of at least one seat 109 in the vehicle 101. In an embodiment, the ECU 203 may be configured to generate and analyze the point cloud rendering data 211. In an embodiment, the receiver antenna 113 may be associated with the sensor 105 and configured for receiving the frequency modulated continuous waves 111 reflecting from either the at least one seat belt 109 or the occupants in the vehicle.
[0036] In an embodiment, the data 207 stored in the memory may include, without limitation, point cloud rendering data 211 and other data 213. In some implementations, the data 207 may be stored within the memory in the form of various data structures. Additionally, the data 207 may be organized using data models, such as relational or hierarchical data models. The other data 213 may include various temporary data and files generated by the one or more modules while performing various functions of the SBM 103 system.
[0037] In an embodiment, the point cloud rendering data 207 may be generated based on a pattern of the frequency modulated continuous waves 107 received by the receiver antenna 113. As an example, the point cloud rendering data 207 may include, but not limited to, an azimuth measurement, an elevation angle, a range, and a transmission time associated with the frequency modulated continuous waves 107 received by the receiver antenna 113.
[0038] In an embodiment, the data may be processed by the one or more modules 209 of the SBM 103 system. In some implementations, the one or more modules 209 may be communicatively coupled to the ECU for performing one or more functions of the SBM 103 system. In an implementation, the one or more modules 209 may include, without limiting to, a pretrained learning model 215, an alerting module 217 and other modules 219.
[0039] As used herein, the term module may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a hardware processor (shared, dedicated, or group) and memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. In an implementation, each of the one or more modules 209 may be configured as stand-alone hardware computing units. In an embodiment, the other modules 219 may be used to perform various miscellaneous functionalities of the contactless SBM 103 system. It will be appreciated that such one or more modules 209 may be represented as a single module or a combination of different modules.
[0040] In an embodiment, the pretrained learning model may be an Artificial Intelligence (AI) and/or Machine Learning (ML) model, which may be configured to perform semantic analysis of images corresponding to a pattern of the frequency modulated continuous waves reflected 111 and received from the receiver antenna 113.
[0041] In an embodiment, the alerting module may be configured to generate an audio and/or a visual alert when the locking status of the at least one seat belt 109 is determined to be ‘unlocked’. For example, the alerting module generates the alert when an occupant sitting in the vehicle 101 forgets to wear the seat belt 109. Further, the alerting module may generate alerts when the vehicle 101 ignition is ‘ON’ and the vehicle 101 has started moving, but one of the occupants in the vehicle 101 is not wearing the seat belt 109.
[0042] FIG. 3 shows a flowchart illustrating a method for contactless Seat Belt Monitoring (SBM) in a vehicle, in accordance with some embodiments of the present disclosure.
[0043] As illustrated in FIG. 3, the method 300 may include one or more blocks illustrating a method for contactless seat belt monitoring in a vehicle 101. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform specific functions or implement specific abstract data types.
[0044] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.
[0045] At block 301, the method 300 includes generating, using a sensor 105 configured in the vehicle 101, frequency modulated continuous waves 107 inside the vehicle 101, wherein the sensor 105 sweeps the frequency modulated continuous waves 107 in a direction of at least one seat in the vehicle 101. In an embodiment, when the vehicle 101 ignition is ‘ON’ and the doors are closed, the sensor 105 may generate the frequency modulated continuous waves 107 and sweep them in a direction of the occupants in the vehicle 101 to detect if all the occupants are wearing the seat belts 109.
[0046] At block 303, the method 300 includes receiving, by the receiver antenna 113 associated with the sensor 105, frequency modulated continuous waves reflected 111 from the plurality of occupants and/or the seat belts 109 worn by the occupants. In an embodiment, at least one seat belt 109 coated with the predetermined material, for example Teflon, absorb the frequency modulated continuous waves 107 received from the sensor 105. In an embodiment, the at least one seat belt 109 may be made of woven narrow fabric comprising at least one of nylon filament yarns and high-tensile polyester filament yarns. In an embodiment, the predetermined material coating on the at least one seat belt 109 may increase a di-electric coefficient and an insulation coefficient of the at least one seat belt 109. In other words, the predetermined coating ensures that the at least one seat belt 109 does not allow reflection of the frequency modulated continuous waves 107 received from the sensor 105.
[0047] At block 305, the method 300 includes generating, by an Electronic Control Unit (ECU) of the vehicle, point cloud rendering data corresponding to a pattern of the frequency modulated continuous waves 107 received by the receiver antenna 113.
[0048] At block 307, the method 300 includes analyzing, by the ECU, the point cloud rendering data using a pretrained learning model 215 to detect a locking status of the at least one seat belt 109. In an embodiment, the pretrained learning model 215 may analyse the point cloud rendering data by performing a semantic analysis of images corresponding to a pattern of the frequency modulated continuous waves 107 reflected from the predetermined surface pattern of the seat belts 109. In an embodiment, the point cloud rendering data comprises an azimuth measurement, an elevation angle, a range and a transmission time associated with the frequency modulated continuous waves 111 received by the receiver antenna 113.
[0049] In an embodiment, the locking status of the at least one seat belt 109 is at least one of ‘locked’ and ‘unlocked’. In an embodiment, the ECU may detect the locking status of the at least one seat belt 109 as ‘locked’ when there is no point cloud rendering data along a line of the at least one seat belt 109. Alternatively, the ECU may detect the locking status of the at least one seat belt 109 as ‘unlocked’ when the point cloud rendering data is present along the line of the at least one seat belt 109. In an embodiment, the at least one seat belt 109 are designed with a predetermined surface pattern along the line of the at least one seat belt 109, wherein the predetermined surface pattern is not coated with Teflon. In an embodiment, the ECU may generate an alert when the locking status of the at least one seat belt 109 is ‘unlocked’.
[0050] FIG. 4A shows a flowchart illustrating a method of processing point cloud data in accordance with some embodiments of the present disclosure.
[0051] In an embodiment, the flowchart 400 illustrates the process of processing the point cloud data. In an embodiment, at step 403, the point cloud data is captured and transmitted to a pretrained learning model. As an example, the point cloud rendering data comprises an azimuth measurement, an elevation angle, a range and a transmission time associated with the frequency modulated continuous waves 107 received by the receiver antenna 113. At step 405, the ECU may perform occupant detection and child presence detection, and also determine the locking status of the seat belt 109.
[0052] At step 407, the ECU checks if the locking status of the plurality of the seat belts 109 is ‘locked’. If the locking status of the at least one seat belt 109 is ‘locked’, then the ECU may generate alerts, as shown in step 411. On the other hand, when the locking status of the at least one seat belt 109 is ‘unlocked’, the ECU may not generate any alerts, as indicated in step 409.
[0053] FIG. 4B shows a flowchart illustrating a method of determining locking status of the seat belt and generating alerts in accordance with some embodiments of the present disclosure.
[0054] In an embodiment, the flowchart 450 illustrates the process of detecting the locking status of the seat belt 109 and generating warnings and/or alerts when the locking status of the plurality of the seat belts 109 is determined to be unlocked. In an embodiment, at step 453, the method comprises checking if the vehicle 101 ignition is ‘ON’ and the door of the vehicle 101 is closed. Further, at step 455, the method comprises checking if the vehicle 101 is moving. If the vehicle is not moving, then no alerts will be generated, as indicated in step 459, and the method comes to a halt at step 461. Alternatively, if is determined that the vehicle is in a moving condition, then at step 457, the method comprises performing occupant detection and child presence detection and additionally determining the locking status of the seat belt 109.
[0055] In an embodiment, if the locking status of the plurality of the seat belts 109 is determined to be ‘locked’ at step 463, then no warning may be generated, as indicated in step 469 and the method comes to a halt at step 471. Alternatively, if the locking status of the at least one seat belt 109 is ‘unlocked’, the ECU may generate an alert, as indicated in step 467.
[0056] FIGS. 5A and 5B illustrate a method of determining locking status of the seat belt based on reflection pattern of reflected waves in accordance with some embodiments of the present disclosure.
[0057] In an embodiment, as indicated in portion 501 of FIG. 5A, the occupant of the vehicle 101 may be wearing the seat belts 109 made of woven narrow fabric comprising at least one of nylon filament yarns and high-tensile polyester filament yarns. The at least one seat belt 109 may be coated with Teflon. The Teflon coating on the at least one seat belt 109 may increase a di-electric coefficient and an insulation coefficient of the at least one seat belt 109. In an embodiment, a semantic analysis may be performed on the images corresponding to a pattern of the reflected frequency modulated continuous waves 107 to determine if there is any point cloud rendering data along the line of the seat belt 109, as indicated in portion 503 of FIG. 5A.
[0058] In an embodiment, the plurality of seat belts 109 may be designed with a predetermined surface pattern, along the line of the at least one seat belt 109, as shown in part 505 of FIG. 5B. In an embodiment, the predetermined surface pattern may not be coated with Teflon. In an embodiment, the line of the at least one seat belt 109, as indicated in portion 507 of FIG. 5B, may be determined by performing a semantic analysis of the images corresponding to the pattern of the frequency modulated continuous waves 111 reflected from the predetermined surface pattern.
[0059] FIG. 6 shows rendering of point cloud data corresponding to locking status of the seat belt in accordance with some embodiments of the present disclosure.
[0060] In an embodiment, the FIG. 6 illustrates the point cloud rendering data obtaining from the reflected frequency modulated continuous waves. The point cloud rendering data may be used for determining the locking status of the at least one seat belt 109. The locking status of the at least one seat belt 109 is at least one of ‘locked’ and ‘unlocked’. In an embodiment, portion 601 of FIG. 6 depicts the point cloud rendering data corresponding to the ‘unlocked’ status of the seat belt 109. Similarly, portion 603 of FIG. 6 depicts point cloud rendering data corresponding to the ‘locked’ status of the seat belt 109.
[0061] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
[0062] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral Numerals:
Reference Number Description
101 Seat Belt Monitoring system (SBM)
103 Electronic Control Unit
105 Sensor
107 Frequency Modulated Continuous Waves (FCMW)
109 Seat Belts
111 Reflected FCMW
113 Receiver antenna
201 I/O Interface
205 Memory
207 Data
209 Modules
211 Point cloud rendering data
213 Other data
215 Pretrained learning Model
217 Alerting module
219 Other modules