Description:FIELD OF THE INVENTION

[0001] The present invention relates to vehicle monitoring. More particularly, the present invention relates to a system and a method to monitor an inertial measurement unit for detecting the fall of the vehicle and controlling operations of the vehicle.

BACKGROUND

[0002] In the rapidly evolving landscape of two-wheelers, particularly electric two-wheelers, ensuring rider safety remains a paramount concern. The potential hazards associated with vehicle falls necessitate technological solutions to preemptively detect and mitigate such incidents. However, existing methodologies for identifying vehicle falls exhibit significant shortcomings, often relying on mechanical mechanisms or rudimentary technologies that may be short in terms of accuracy and reliability.
[0003] Traditionally, the detection of a vehicle fall has been approached through mechanical means or rudimentary technologies lacking in robustness. The existing technologies, while functional to a certain extent, fail to provide the level of precision and efficiency required to ensure comprehensive safety of a rider and the two-wheeler. As a result, the need for a more advanced and reliable fall detection technology has become increasingly evident.
[0004] One of the primary challenges encountered with existing technologies lies in their inability to effectively account for vehicle movement during fall detection. While some solutions incorporate Inertial Measurement Unit (IMU) sensors to estimate vehicle orientation and predict the vehicle falls based on the IMU data, however, their efficacy is compromised by inherent limitations. For instance, the IMU sensors, characterized by their sensitivity to movement and orientation changes, often produce erroneous predictions, particularly in scenarios involving dynamic maneuvers such as sharp turns on banked roads. In such instances, false alarms may be triggered, leading to a loss of trust in the technological capabilities and potentially compromising rider safety.
[0005] Recognizing the shortcomings of existing methodologies, there arises a pressing need for a paradigm shift in fall detection technology for electric two-wheelers. The existing technologies fail in the development of an advanced fall detection system that not only integrates IMU sensor data but also incorporates sophisticated algorithms capable of accurately discriminating between genuine falls and transient fluctuations in vehicle orientation.
[0006] Further, the existing technologies fail to analyze the IMU sensor data in real-time, while taking into account the vehicle’s dynamic behavior and trajectory. Thus, there is a need for a system which encompasses various driving conditions and maneuvers and becomes adept at distinguishing between normal vehicle movements and indicative patterns associated with falls. Furthermore, the existing technologies due to inefficient vehicle fall detection, may not be able to deploy or initiate protocols aimed at minimizing damage to the vehicle and preventing injury to the rider.
[0007] Furthermore, some techniques propose implementing a vehicle fall detection comprising of a fall detection unit (FDU), a communication device and an accident server. The FDU is mounted on the two-wheeler vehicle and is in communication with a communication device associated with the rider. The communication device is in communication with the accident server. When the two-wheeler vehicle travelling at a high speed, trips or falls down in the event of an accident of the two-wheeler vehicle, the FDU detects the fall and transmits a message indicating the fall of the vehicle to the communication device associated with the rider. The communication device transmits an emergency message to the accident server. However, the FDU proposed in such techniques works merely on the IMU sensors which may often be noisy and provide false positive readings.
[0008] Furthermore, some techniques allow to determine falls in a two-wheeled vehicle and to notify said falls as an emergency signal or similar. The existing techniques makes use of various data obtainable from sensors such as accelerometers, gyroscopes or geographic positioning devices such as GPS to establish events that they allow to determine said fall based on series of calculations and parameterizations so that one can act with respect to said fall. However, such existing techniques fail to consider the vehicle motion or any other method steps to eliminate false positives given by the IMU sensor.
[0009] Therefore, in view of the problems mentioned above, it is advantageous to provide a method for detecting the fall of the vehicle, to overcome the limitations known in the method used in the state of the art and also to provide a system for achieving this method.

SUMMARY

[00010] This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify key or essential inventive concepts of the invention nor is it intended for determining the scope of the invention.
[00011] To overcome, or at least mitigate, one of the problems mentioned above in the state of the art, there is a requirement for a system and method for detecting a fall of a vehicle. It is preferable to have a robust method of detection, which involves monitoring at least one inertial measurement unit (IMU) integrated into the vehicle, combined with other sensors such as motor encoder sensor and throttle sensor. This ensures that users have access to more automated and intelligent systems while operating or engaging with the vehicle.
[00012] In an aspect of the present invention, a method for detecting a fall of a vehicle. The method includes calibrating at least one Inertial Measurement Unit (IMU) installed in the vehicle based on a vehicle frame of reference to compute a motion and an orientation of the vehicle relative to axes of the vehicle. Further, the method includes estimating a vehicle speed based on a correlation of an IMU value received from the at least one IMU, a motor encoder value received from a motor encoder sensor, and a throttle value received from a throttle sensor. Further, the method includes determining at least one of a motionless state or a motion state of the vehicle based on the estimated vehicle speed. Furthermore, the method includes determining the IMU value of the vehicle exceeding a predefined IMU threshold in response to the determination that the vehicle is in the motionless state. Furthermore, the method includes detecting the fall of the vehicle upon the determination that the IMU value of the vehicle exceeds the predefined IMU threshold.
[00013] In another aspect of the present invention, a system for detecting a fall of a vehicle is disclosed. The system includes a memory and at least one processor in communication with the memory. The at least one processor is configured to calibrate at least one Inertial Measurement Unit (IMU) installed in the vehicle based on a vehicle frame of reference to compute a motion and an orientation value of the vehicle relative to axes of the vehicle. Further, the at least one processor is configured to estimate a vehicle speed based on a correlation of an IMU value received from the at least one IMU, a motor encoder value received from a motor encoder sensor, and a throttle value received from a throttle sensor. Furthermore, the at least one processor is configured to determine at least one of a motionless state or a motion state of the vehicle based on the estimated vehicle speed. Furthermore, the at least one processor is configured to determine the IMU value of the vehicle exceeding a predefined IMU threshold in response to the determination that the vehicle is in the motionless state. Furthermore, the at least one processor is configured to detect the fall of the vehicle upon the determination that the IMU value of the vehicle exceeds the predefined IMU threshold.
[00014] To further clarify the advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[00015] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
[00016] Figure 1 illustrates an environment for an implementation of a system for detecting a fall of a vehicle, according to an embodiment of the present disclosure;
[00017] Figure 2 illustrates a block diagram of the system for detecting the fall of the vehicle and controlling operations of an illumination device and a vehicle motor, according to an embodiment of the present disclosure;
[00018] Figure 3 illustrates a detailed block diagram of the system for detecting the fall of the vehicle, according to an embodiment of the present disclosure;
[00019] Figure 4 illustrates a process flow for calibrating an Inertial Measurement Unit (IMU), by a calibrating module of the system, according to an embodiment of the present disclosure;
[00020] Figure 5 illustrates a process flow for determining one of a motionless state or a motion state of the vehicle, by a motion sub-module of the system, according to an embodiment of the present disclosure;
[00021] Figure 6 illustrates a process flow for detecting the fall of the vehicle, by a fall detection sub-module of the system, according to an embodiment of the present disclosure;
[00022] Figure 7 illustrates a process flow for controlling the operations of the illumination device and the vehicle motor, by a transmitting module of the system, according to an embodiment of the present disclosure;
[00023] Figure 8 illustrates a flowchart depicting an exemplary method for detecting the fall of the vehicle, according to an embodiment of the present disclosure; and
[00024] Figure 9a-9b illustrates an exemplary use case for detecting the fall of the vehicle, according to an embodiment of the present disclosure.
[00025] Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.
DETAILED DESCRIPTION OF FIGURES
[00026] For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the various embodiments and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the present disclosure is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the present disclosure as illustrated therein being contemplated as would normally occur to one skilled in the art to which the present disclosure relates.
[00027] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the present disclosure and are not intended to be restrictive thereof.
[00028] Whether or not a certain feature or element was limited to being used only once, it may still be referred to as “one or more features” or “one or more elements” or “at least one feature” or “at least one element.” Furthermore, the use of the terms “one or more” or “at least one” feature or element do not preclude there being none of that feature or element, unless otherwise specified by limiting language including, but not limited to, “there needs to be one or more…” or “one or more elements is required.”
[00029] Reference is made herein to some “embodiments.” It should be understood that an embodiment is an example of a possible implementation of any features and/or elements of the present disclosure. Some embodiments have been described for the purpose of explaining one or more of the potential ways in which the specific features and/or elements of the proposed disclosure fulfil the requirements of uniqueness, utility, and non-obviousness.
[00030] Use of the phrases and/or terms including, but not limited to, “a first embodiment,” “a further embodiment,” “an alternate embodiment,” “one embodiment,” “an embodiment,” “multiple embodiments,” “some embodiments,” “other embodiments,” “further embodiment”, “furthermore embodiment”, “additional embodiment” or other variants thereof do not necessarily refer to the same embodiments. Unless otherwise specified, one or more particular features and/or elements described in connection with one or more embodiments may be found in one embodiment, or may be found in more than one embodiment, or may be found in all embodiments, or may be found in no embodiments. Although one or more features and/or elements may be described herein in the context of only a single embodiment, or in the context of more than one embodiment, or in the context of all embodiments, the features and/or elements may instead be provided separately or in any appropriate combination or not at all. Conversely, any features and/or elements described in the context of separate embodiments may alternatively be realized as existing together in the context of a single embodiment.
[00031] Any particular and all details set forth herein are used in the context of some embodiments and therefore should not necessarily be taken as limiting factors to the proposed disclosure.
[00032] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by “comprises... a” does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
[00033] Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.
[00034] For the sake of clarity, the first digit of a reference numeral of each component of the present disclosure is indicative of the Figure number, in which the corresponding component is shown. For example, reference numerals starting with digit “1” are shown at least in Figure 1. Similarly, reference numerals starting with digit “2” are shown at least in Figure 2.
[00035] Embodiments of the present disclosure disclose a system for detecting a fall of a vehicle based on monitoring at least one inertial measurement unit (IMU) (hereinafter referred to as the IMU) installed in the vehicle. The components of the disclosed system are configured to detect the fall of the vehicle and control operations of at least one vehicle illumination device (hereinafter referred to as illumination device) and an electric motor (hereinafter referred to as vehicle’s motor) to ensure smarter and more responsive safety solutions.
[00036] Figure 1 illustrates an environment 100 for an implementation of a system for detecting a fall of a vehicle, according to an embodiment of the present disclosure.
[00037] In a non-limiting example, the system may be implemented in the vehicle, for instance, any mechanical means of transportation such as automobiles (car), motorcycles, trucks, buses, scooters, motorcycles, and bicycles. In one such embodiment, the present disclosure is explained by implementing the system in the vehicle alternatively referred to as an electric vehicle (EV) within the scope of the present disclosure. The Electric Vehicle (EV) or a battery-powered vehicle including, and not limited to two-wheelers such as scooters, mopeds, motorbikes/motorcycles; three-wheelers such as auto-rickshaws, four-wheelers such as cars and other Light Commercial Vehicles (LCVs) and Heavy Commercial Vehicles (HCVs) primarily work on the principle of driving an electric motor using the power from the batteries provided in the EV. Furthermore, the EV may have at least one wheel which is electrically powered to traverse such a vehicle. The term ‘wheel’ may be referred to any ground-engaging member which allows traversal of the electric vehicle over a path. The types of EVs include Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV) and Range Extended Electric Vehicle. However, the subsequent paragraphs pertain to the different elements of a Battery Electric Vehicle (BEV).
[00038] In construction, an EV 110 typically comprises a battery or battery pack 112 enclosed within a battery casing and includes a Battery Management System (BMS), an on-board charger 114, a Motor Controller Unit (MCU), an electric motor 116 (alternatively referred to as vehicle motor) and an electric transmission system 118. The primary function of the above-mentioned elements is detailed in the subsequent paragraphs: The battery 112 of the EV 110 (also known as Electric Vehicle Battery (EVB) or traction battery) is re-chargeable in nature and is the primary source of energy required for the operation of the EV 110, wherein the battery 112 is typically charged using the electric current taken from the grid through a charging infrastructure 120. The battery 112 may be charged using Alternating Current (AC) or Direct Current (DC), wherein in case of AC input, the on-board charger 114 converts the AC signal to DC signal after which the DC signal is transmitted to the battery via the BMS. However, in case of DC charging, the on-board charger 114 is bypassed, and the current is transmitted directly to the battery 112 via the BMS.
[00039] The battery 112 is made up of a plurality of cells which are grouped into a plurality of modules in a manner in which the temperature difference between the cells does not exceed 5 degrees Celsius. The terms “battery”, “cell”, and “battery cell” may be used interchangeably and may refer to any of a variety of different rechargeable cell compositions and configurations including, but not limited to, lithium-ion (e.g., lithium iron phosphate, lithium cobalt oxide, other lithium metal oxides, etc.), lithium-ion polymer, nickel metal hydride, nickel cadmium, nickel hydrogen, nickel-zinc, silver zinc, or other battery type/configuration. The term “battery pack” as used herein may refer to multiple individual batteries enclosed within a single structure or multi-piece structure. The individual batteries may be electrically interconnected to achieve the desired voltage and capacity for a desired application. The Battery Management System (BMS) is an electronic system whose primary function is to ensure that the battery 112 is operating safely and efficiently. The BMS continuously monitors different parameters of the battery such as temperature, voltage, current and so on, and communicates these parameters to an Electronic Control Unit (ECU) and the Motor Controller Unit (MCU) in the EV 110 using a plurality of protocols including and not limited to Controller Area Network (CAN) bus protocol which facilitates the communication between the ECU/MCU and other peripheral elements of the EV 110 without the requirement of a host computer.
[00040] The MCU primarily controls/regulates the operation of the electric motor based on the signal transmitted from the vehicle battery, wherein the primary functions of the MCU include starting the electric motor 116, stopping the electric motor 116, controlling the speed of the electric motor 116, enabling the EV 110 to move in the reverse direction and protect the electric motor 116 from premature wear and tear. The primary function of the electric motor 116 is to convert electrical energy into mechanical energy, wherein the converted mechanical energy is subsequently transferred to the transmission system of the EV to facilitate movement of the EV 110. Additionally, the electric motor 116 also acts as a generator during regenerative braking (i.e., kinetic energy generated during vehicle braking/deceleration is converted into potential energy and stored in the battery of the EV). The types of motors generally employed in EVs include, but are not limited to DC series motor, Brushless DC motor (also known as BLDC motors), Permanent Magnet Synchronous Motor (PMSM), Three Phase AC Induction Motors and Switched Reluctance Motors (SRM).
[00041] The transmission system 118 of the EV 110 facilitates the transfer of the generated mechanical energy by the electric motor 116 to the wheels 122a, 122b of the EV 110. Generally, the transmission systems 118 used in EVs 110 include a single-speed transmission system and a multi-speed (i.e., two-speed) transmission system, wherein the single-speed transmission system comprises a single gear pair whereby the EV 110 is maintained at a constant speed. However, the multi-speed/two-speed transmission system comprises a compound planetary gear system with a double-pinion planetary gear set and a single-pinion planetary gear set thereby resulting in two different gear ratios which facilitate higher torque and vehicle speed.
[00042] In one embodiment, all data pertaining to the EV 110 and/or charging infrastructure 120 may be collected and processed using a remote server 124 (known as cloud), wherein the processed data is indicated to the rider/driver of the EV 110 through a display unit present in the dashboard 126 of the EV 110. In an embodiment, the display unit may be an interactive display unit. In another embodiment, the display unit may be a non-interactive display unit.
[00043] In addition to the hardware components/elements, the EV 110 may be supported with software modules comprising intelligent features including and not limited to navigation assistance, hill assistance, cloud connectivity, Over-The-Air (OTA) updates, adaptive display techniques and so on. The firmware of the EV 110 may also comprise Artificial Intelligence (AI) and Machine Learning (ML) driven modules which enable the prediction of a plurality of parameters such as and not limited to driver/rider behaviour, road condition, charging infrastructures 120/charging grids 120 in the vicinity and so on. The data pertaining to the intelligent features may be displayed through the display unit present in the dashboard 126 of the EV 110. In one embodiment, the display unit may contain a Liquid Crystal Display (LCD) screen of a predefined dimension. In another embodiment, the display unit may contain a Light-Emitting Diode (LED) screen of a predefined dimension. The display unit may be a water-resistant display supporting one or more User-Interface (UI) designs. The EV 110 may support multiple frequency bands such as 2G, 3G, 4G, 5G, and so on. Additionally, the EV 110 may also be equipped with wireless infrastructure such as, and not limited to Bluetooth, Wi-Fi and so on to facilitate wireless communication with other EVs or the cloud. Further, the EV 110 may include a system 128 configured to monitor and acquire data/value from the IMU (not shown in Figure 1) installed in the EV 110, without departing from the scope of the present disclosure. In an embodiment, the system 128 may be further configured to detect the fall of the vehicle 110, as will be described in detail further below.
[00044] In an alternative embodiment, the system 128 may alternatively reside in the remote server 124, without departing from the scope of the present disclosure. Further, the system 128 may be configured to transmit the IMU value obtained or acquired from the IMU, to the remote server 124. Additionally, an application installed on a user device (not shown) and in communication with the remote server 124 may display the detection of the fall of the vehicle 110 and the subsequent operations performed for controlling the illumination device and the vehicle motor. Similarly, the dashboard 126 may also display an event indicating the detection of the fall of the vehicle 110 and the subsequent operations performed for controlling the illumination device and the vehicle motor. Further, the constructional and operational details of the system 128 are explained in subsequent paragraphs in conjunction with Figures 2 to 9, without departing from the scope of the present disclosure.
[00045] Figure 2 illustrates a block diagram of the system 128 for detecting the fall of the vehicle, according to an embodiment of the present disclosure. The system 128 may be deployed in the vehicle 110 to monitor the IMU 202 and control the operations of the illumination device 210. Accordingly, the system 128 may be in communication with the IMU 202, a motor encoder sensor 204, and a throttle sensor 206 for detecting the fall of the vehicle 110 and subsequently controlling the operations of the illumination device 210 and the vehicle motor 116. The system 128 may include, but is not limited to, the Electric Computation Unit (ECU) 208 installed within the vehicle 110. The ECU 208 may be responsible for controlling various aspects of the vehicle 110.
[00046] Referring to Figure 2, in an embodiment, the IMU 202 is a device consisting of a 6-axis sensor that integrates both an accelerometer 202a and a gyroscope 202b into a single unit (IMU). The IMU 202 may be installed within proximity to a center of gravity of vehicle 110. It may be apparent to an ordinary person skilled in the art, that though a single IMU is depicted, the vehicle 110 may include a plurality of IMUs, without departing from the scope of the present invention. Further, in an embodiment, the accelerometer 202a may be configured to provide measurement or output to estimate the linear acceleration value of the vehicle 110. The linear acceleration value may indicate a rate of change of velocity along a straight line. The gyroscope 202b may be configured to provide measurement or output to estimate the angular position of the vehicle 110. Furthermore, the IMU 202 may be in communication with the ECU 208. In an embodiment, the ECU 208 may be configured to acquire an IMU value (i.e., from accelerometer 202a and the gyroscope 202b) and determine an orientation value of the vehicle 110.
[00047] In an aspect of the present invention, implementing the IMU 202 in the vehicle 110 may offer several benefits by providing additional information about the vehicle’s 110 dynamics and environment. For instance, by monitoring acceleration and deceleration values, the IMU 202 may offer insights into the vehicle’s speed changes, enabling more accurate tracking of the vehicle’s 110 motion. Additionally, the IMU 202 may detect the completion of turns by analyzing the orientation changes, thus helping to improve safety and navigation for riders. Moreover, the IMU 202 may also detect events such as falls or collisions, allowing for rapid response and triggering of safety measures or alerts.
[00048] In an embodiment, the motor encoder sensor 204 may be coupled with the vehicle motor 116 and configured to communicate with the ECU 208. In an embodiment, the motor encoder sensor 204 may transmit a motor encoder value to the ECU 208. In the example, the motor encoder value may correspond to a rotation of the vehicle motor 116.
[00049] In an embodiment, the throttle sensor 206 may be coupled with a throttle of the vehicle 110 and configured to communicate with the ECU 208. In an embodiment, the throttle sensor 206 may be configured to transmit the throttle value to the ECU 208. In the example, the throttle value may correspond to the position or movement of the throttle mechanism, thus indicating a power value applied to the vehicle 110.
[00050] In an embodiment, the illumination device 210 installed in the vehicle 110 may be an integral component that ensures visibility and safety for both the driver and other road users. In a non-limiting example, the illumination device 210 may be a brake lamp, a headlamp, and a turn indicator lamp. Each of the illumination device 210 may be meticulously positioned and designed to fulfil specific functions in the vehicle 110.
[00051] Accordingly, the ECU 208 may be in communication with the illumination device 210 and the vehicle motor 116. In an embodiment, the ECU 208 may be adapted to control the operations of the illumination device 210 and the vehicle motor 116 based on detecting the fall of the vehicle 110, as explained in forthcoming paragraphs.
[00052] Figure 3 illustrates a detailed block diagram of the system 128 for detecting the fall of the vehicle 110, according to an embodiment of the present disclosure.
[00053] Referring to Figure 3, the ECU 208 of the vehicle 110 is responsible for detecting the fall of the vehicle 110 and subsequently controlling the operations of the illumination device 210 and the vehicle motor 116, wherein the key elements of the ECU 208 typically include (i) a microcontroller core (or processor unit) or a processor 302; (ii) a memory unit or a memory 304; (iii) a set of modules 306 and (iv) communication protocols including, but not limited to CAN protocol, Serial Communication Interface (SCI) protocol and so on. The sequence of programmed instructions and data associated therewith can be stored in a non-transitory computer-readable medium such as the memory unit 304 or storage device which may be any suitable memory apparatus such as, but not limited to read-only memory (ROM), programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random-access memory (RAM), flash memory, disk drive and the like. In one or more embodiments of the disclosed subject matter, non-transitory computer-readable storage media can be embodied with a sequence of programmed instructions for monitoring and controlling the operation of different components of the vehicle 110.
[00054] The processor 302 may include any computing system which includes, but is not limited to, Central Processing Unit (CPU), an Application Processor (AP), a Graphics Processing Unit (GPU), a Visual Processing Unit (VPU), and/or an AI-dedicated processor such as a Neural Processing Unit (NPU). In an embodiment, the processor can be a single processing unit or several units, all of which could include multiple computing units. The processor 302 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor is configured to fetch and execute computer-readable instructions and data stored in the memory. The instructions can be compiled from source code instructions provided in accordance with a programming language such as Java, C++, C#.net or the like. The instructions can also comprise code and data objects provided in accordance with, for example, the Visual Basic™ language, LabVIEW, or another structured or object-oriented programming language. The one or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning algorithms which include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.
[00055] Furthermore, the modules, processes, systems, and devices can be implemented as a single processor or as a distributed processor. Also, the processes, modules, and sub-modules described in the various figures of and for embodiments herein may be distributed across multiple computers or systems or may be co-located in a single processor or system. Further, the modules can be implemented in hardware, instructions executed by a processing unit, or by a combination thereof. The processing unit can comprise a computer, a processor, such as the processor, a state machine, a logic array, or any other suitable devices capable of processing instructions. The processing unit can be a general-purpose processor which executes instructions to cause the general-purpose processor to perform the required tasks or, the processing unit can be dedicated to performing the required functions. In another embodiment of the present disclosure, the modules may be machine-readable instructions (software) which, when executed by a processor/processing unit, perform any of the described functionalities. In an embodiment, the modules may include an acquisition module 310, a calibrating module 312, a determining module 314, and a transmitting module 316. The acquisition module 310, the calibrating module 312, the determining module 314, and the transmitting module 316 may be in communication with each other. The determining module 314 may further include a motion sub-module 314a and a fall detection sub-module 314b. The data serves, amongst other things, as a repository for storing data processed, received, and generated by one or more of the modules. Exemplary structural embodiment alternatives suitable for implementing the modules, sections, systems, means, or processes described herein are provided below.
[00056] In an embodiment, the acquisition module 310 may be adapted to receive the IMU value from the IMU 202 (i.e., the combination of the accelerometer 202a and the gyroscope 202b). In an example, the IMU value may thus correspond to the linear acceleration value and the orientation value of the vehicle 110. Further, the acquisition module 310 may be adapted to acquire the motor encoder value from the motor encoder sensor 204 and the throttle value from the throttle sensor 206.
[00057] In an example, the linear acceleration value may be referred to as the measurement or output from the accelerometer 202a of the IMU 202. The accelerometer 202a may measure acceleration i.e., a rate of change of the vehicle’s 110 velocity over time. Thus, the linear acceleration value typically includes values for acceleration along the three axes of the vehicle 110, i.e., acceleration along the x-axis (ax), acceleration along the y-axis (ay), and acceleration along the z-axis (ay). Consequently, the acquisition module 310 may be adapted to acquire or receive the linear acceleration from the IMU 202.
[00058] In an example, the IMU 202 measures the angular position value of the vehicle 110 along at least one of its axes, such as the x-axis via the gyroscope 202b. The angular position corresponds to determining the vehicle’s 110 spatial alignment or rotation, typically corresponding to the longitudinal axis, which typically represents tilting from side to side, in relation to a reference point. Therefore, the angular position along the x-axis provides information about the positioning or rotation of the vehicle 110 in the lateral plane. Consequently, the acquisition module 310 may be adapted to acquire or receive the angular position value from the IMU 202, which may be eventually used to determine a roll angle based on an orientation value estimated by fusing the linear acceleration (accelerometer 202a) and the angular position value (gyroscope 202b). The roll angle may refer to the rotation of the vehicle 110 around the lateral axis (x-axis), thereby representing the vehicle’s 110 lateral tilt. The acquisition module 310 may be in communication with the calibrating module 312.
[00059] In an embodiment, the calibrating module 312 may be adapted to calibrate the IMU 202 based on the orientation value, such that the calibration enables accurate measurement of the vehicle’s 110 motion and the orientation. The acquisition module 310 and the calibrating module 312 may be in communication with the determining module 314.
[00060] In an embodiment, the determining module 314 may be adapted to estimate a vehicle speed to determine a motionless state or a motion state of the vehicle 110. Further, the determining module 314 may be adapted to detect the fall of the vehicle 110 if the vehicle 110 is in the motionless state and simultaneously the IMU value exceeds a predefined IMU threshold (IMUPTH). The predefined IMU threshold (IMUPTH) may correspond to a pre-stored IMU value signifying a limit beyond which the vehicle 110 may be deemed to have fallen.
[00061] In an embodiment, to estimate the vehicle speed the determining module 314 may be adapted to receive the IMU value, which includes the linear acceleration value and the orientation value, from the IMU 202. Additionally, the determining module 314 may be adapted to receive the motor encoder value from the motor encoder sensor 204 and the throttle value from the throttle sensor 206. The determining module 314 then computes the vehicle’s 110 velocity change by correlating the linear acceleration value and the orientation value over time with the motor encoder value and the throttle value.
[00062] In an aspect of the invention, thus, the system 128 utilizes three different sensors (the IMU 202, the motor encoder sensor 204, and the throttle sensor 206) to determine whether the vehicle 110 is in a state of motion (i.e., with the vehicle speed more than zero) or at rest (motionless i.e., with the vehicle speed equal to zero). Further, in the embodiment, the determining module 314 may be adapted to detect the fall of the vehicle 110 based on the IMU value upon detecting that the vehicle 110 is at rest or motionless.
[00063] In an aspect of the invention, thus the system 128 is capable of avoiding false positive fall detections. For instance, if the vehicle 110 is being driven on a banked road with the roll angle (along the x-axis) exceeding the predefined IMU threshold (IMUPTH), but the vehicle 110 maintains its speed (i.e., remains in motion), the system 128 may not mistakenly interpret this as the fall, as the vehicle 110 is still considered to be in motion. The detailed working of the determining module 314 to detect the fall of the vehicle 110 is explained with reference to Figure 5-6.
[00064] The acquisition module 310, the calibrating module 312, and the determining module 314 may be in communication with the transmitting module 316.
[00065] In an embodiment, the transmitting module 316 may be adapted to transmit a notification to a user device (not shown), a Human Machine Interface (HMI) of the vehicle 110, and the cloud 124. In an embodiment, the HMI may be the dashboard 126 of the vehicle 110. In an example, the notification may correspond to the operation performed by controlling the illumination device 210.
[00066] The detailed working of the calibrating module 312, the determining module 314 and the transmitting module 316 is explained with reference to Figure 4-7.
[00067] Figure 4 illustrates a process flow for calibrating the IMU 202, by the calibrating module 312 of the system 128, according to an embodiment of the present disclosure.
[00068] At step 402, the acquisition module 310 may be adapted to receive the IMU value from the IMU 202 (i.e., from the accelerometer 202a and the gyroscope 202b), wherein the IMU value may include the linear acceleration value and the orientation value of the vehicle 110.
[00069] At step 404, in an embodiment, the calibrating module 312 may be adapted to receive the IMU value from the acquisition module 310 while the vehicle 110 has a pitch angle (i.e., tilting forward or backward) and the roll angle (i.e., tilting side to side) of zero degrees. Consequently, aligning a global or world reference frame with a vehicle reference frame. In an aspect of the invention, such alignment may be crucial for accurately interpreting the measurements from the IMU 202 in relation to the vehicle’s 110 actual orientation and motion.
[00070] At step 406, the calibrating module 312 may be adapted to determine the orientation of the IMU 202 relative to the world reference frame based on the IMU value.
[00071] At step 408, the calibrating module 312 may be adapted to calibrate the IMU 202 based on the orientation, such that the calibration enables accurate measurement of the vehicle’s motion and the orientation value. The calibration aims to compensate for any misalignments or inaccuracies in the IMU 202 readings (i.e., the IMU value) caused by factors such as sensor placement or manufacturing variations. Thus, by calibrating the IMU 202, the system 128 ensures that subsequent measurements accurately reflect the vehicle’s 110 actual motion and the orientation relative to the world reference frame. Thus, in an aspect of the invention, the calibration of the IMU 202 may enable reliable detection of events such as falls or changes in the vehicle’s state.
[00072] Figure 5 illustrates a process flow for determining one of, the motionless state or the motion state of the vehicle 110, by the motion sub-module 314a of the system 128, according to an embodiment of the present disclosure.
[00073] At step 502, in an embodiment, the motion sub-module 314a may be adapted to create a moving array. The moving array may include two separate arrays for the IMU value i.e., each corresponding to the output from the accelerometer 202a and the gyroscope 202b. In an embodiment, the moving array may correspond to a data structure adapted to hold a sequence of values from the IMU 202 (accelerometer 202a and gyroscope 202b) over a predefined time duration. In an alternative embodiment, the motion sub-module 314a may be adapted to create the moving array based on fusing the IMU value with the motor encoder value and the throttle value. In an aspect of the invention the moving array with the fused IMU value may provide a corrected or refined representation of the vehicle’s motion dynamics, incorporating both inertial measurements and motor control inputs.
[00074] In the example, the IMU 202, generate values (data) at specific intervals, and the values may be stored in the moving array. For instance, if the IMU 202 is sampled every second, each element (value) in the moving array may represent the readings from the IMU 202 at each second. In an aspect of the invention, thus, the moving array may serve as a dynamic record of the vehicle’s state over time. Further, the moving array may be continuously updated as new values from the IMU 202 become available, thereby providing a chronological view of the vehicle’s 110 changing parameters.
[00075] Further, in the example, each value in the moving array relating to a predefined time interval captures the state of the vehicle 110 at that time instance. For example, if the system 128 samples the IMU 202 for values every second, each value in the moving array represents a one-second interval. In a preferred embodiment, the moving array corresponding to each of the IMU value may store at least four values, collecting values (data) for every 1-second (the predefined time duration). In an aspect of the invention, the moving array forms the basis for determining the state of the vehicle 110 - whether the vehicle 110 is motionless or in motion.
[00076] At step 504, the motion sub-module 314a may be adapted to determine that the vehicle 110 may be in the motionless state if a plurality of the one or more values in the moving array is less than a predefined speed threshold (PSTH). In an embodiment, the motion sub-module 314a may be adapted to evaluate the values recorded in the moving array over the predefined time duration or a predefined number of values.
[00077] For instance, the motion sub-module 314a may be adapted to evaluate up to four values in the moving array. In a preferred embodiment, upon determining that at least three values out of the four values in the moving array may be less than the predefined speed threshold (PSTH), the motion sub-module 314a may be adapted to determine that the vehicle 110 may be in the motionless state.
[00078] At step 506, the motion sub-module 314a may be adapted to determine that the vehicle 110 may be in the motion state if the plurality of the one or more values in the moving array exceeds the predefined speed threshold (PSTH).
[00079] For instance, the motion sub-module 314a may be adapted to evaluate up to four values in the moving array. In a preferred embodiment, upon determining that at least three values out of the four values in the moving array may exceed the predefined speed threshold (PSTH), the motion sub-module 314a may be adapted to determine that the vehicle 110 may be in the motion state.
[00080] In an aspect of the invention, the motion sub-module 314a may be adapted to continuously determine one of the motionless state or the motion state of the vehicle 110 in real-time as the system 128 continuously updates the moving array with fresh readings from the IMU 202. Consequently, the real-time determination of the motionless state or the motion state of the vehicle 110 enables the system 128 to respond dynamically to changes in the vehicle’s behavior, thereby providing timely and accurate information about the vehicle’s 110 motion status.
[00081] Figure 6 illustrates a process flow for detecting the fall of the vehicle 110, by the fall detection sub-module 314b of the system 128, according to an embodiment of the present disclosure.
[00082] At step 602, in an embodiment, the fall detection sub-module 314b may be adapted to create an IMU moving array corresponding to each of the linear acceleration and the orientation value of the vehicle 110 based on the IMU value.
[00083] In an example, the IMU moving array may indicate one or more values associated with each of the linear acceleration and the orientation value respectively, for the predefined time duration. In the example, the IMU moving array may correspond to the data structure adapted to hold a sequence of values (the IMU values) over the predefined time duration.
[00084] For instance, if the IMU 202 is sampled every second, each element in the IMU moving array would represent the readings from the IMU 202 at each second. In an aspect of the invention, thus, the IMU moving array may serve as a dynamic record of the linear acceleration and the orientation value of the vehicle 110 over time. Further, the IMU moving array may be continuously updated in real-time as new values from the IMU 202 become available, thereby providing a chronological view of the vehicle’s 110 changing orientation. Furthermore, in another instance, post processing the IMU value in the IMU moving array, any detected falls may also be stored in form of the moving array, thereby addressing memory-related constraints.
[00085] Further, in the example, each value in the IMU moving array relating to the predefined time interval captures the orientation of the vehicle 110 at that time instance. For example, if the system 128 samples the IMU 202 for values every second, each value in the IMU moving array may represent a one-second interval. In a preferred embodiment, the IMU moving array may store at least four values, for every 1-second (the predefined time duration). In an aspect of the invention, the IMU moving array forms the basis for detecting the fall of the vehicle 110.
[00086] At step 604, the fall detection sub-module 314b may be adapted to determine that the IMU value of the vehicle 110 exceeds the predefined IMU threshold (IMUPTH) in response to computing that a plurality of the one or more values in the IMU moving array exceeds the predefined IMU threshold (IMUPTH).
[00087] In an embodiment, the fall detection sub-module 314b may be adapted to evaluate the values recorded in the IMU moving array over the predefined time duration to determine if the IMU value of the vehicle 110 exceeds the predefined IMU threshold (IMUPTH).
[00088] In the embodiment, the fall detection sub-module 314b may be adapted to compute whether a plurality of the values, preferably three values out of the four values within the IMU moving array, corresponding to either linear acceleration and the orientation value, exceeds the predefined IMU threshold (IMUPTH). Thus, if three values out of the four values in the IMU moving array exceeds the predefined IMU threshold (IMUPTH), the system 128 concludes that the IMU value of the vehicle 110 has indeed surpassed the predefined IMU threshold (IMUPTH).
[00089] At step 606, in an embodiment, the fall detection sub-module 314b may be adapted to detect the fall of the vehicle 110 upon the determination indicating that the IMU value of the vehicle 110 exceeds the predefined IMU threshold (IMUPTH).
[00090] In an embodiment, the detection of the fall may be triggered by the determination that the IMU readings (IMU value) have exceeded a critical threshold (IMUPTH), indicating a significant deviation from the vehicle’s 110 normal operating parameters. For instance, the fall detection sub-module 314b may be adapted to detect whether there has been an increase in both the roll angle and the linear acceleration within the vehicle’s frame of reference. Consequently, once the IMUPTH is exceeded and the vehicle is in the motionless state, the system 128 identifies this as a potential fall of the vehicle 110.
[00091] Figure 7 illustrates a process flow for controlling the operations of the illumination device 210 and the vehicle motor 116, by the transmitting module 316 of the system 128, according to an embodiment of the present disclosure.
[00092] At step 702, in an embodiment, the transmitting module 316 may be adapted to control operations associated with the at least one of, the illumination device 210 and the vehicle motor 116, upon detecting the fall of the vehicle 110. In an example, the operations indicate initiating an illumination pattern of the illumination device 210 and disabling the vehicle motor 116. In an aspect of the invention, the operations thus may be accorded as safety measures performed in response to detecting the fall of the vehicle 110.
[00093] At step 704, the transmitting module 316 may be adapted to transmit a notification to a user device or a Human Machine Interface (HMI) of the vehicle 110 upon detecting the fall.
[00094] At step 706, the transmitting module 316 may be adapted to revert the operations associated with the illumination device 210 and the vehicle motor 116 in response to receiving a user input indicating instructions to override the operations.
[00095] For example, when the vehicle 110 falls, the vehicle motor 116 could be automatically disabled, halting power delivery and preventing any unintended movement of the fallen vehicle. Concurrently, the illumination devices 210 such as hazard lamps and headlights may activate in distinct illumination patterns, signaling the vehicle’s 110 fall. Further, the operations, including activating the illumination devices 210 and deactivating the vehicle motor 116, may persist until manually overridden by the user, such as after lifting the fallen vehicle by providing the user-input via the HMI or the user device.
[00096] Figure 8 illustrates a flowchart depicting an exemplary method 800 for detecting the fall of the vehicle 110, according to an embodiment of the present disclosure. The method 800 may be a computer-implemented method executed, for example, by the system 128 and the modules 306. For the sake of brevity, the constructional and operational features of the system 128 that are already explained in the description of Figure 1, Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, and Figure 7, are not explained in detail in the description of Figure 8.
[00097] At step 802, the method 800 may include calibrating the IMU 202 installed in the vehicle 110 based on the vehicle frame of reference to compute the motion and the orientation of the vehicle 110 relative to axes of the vehicle 110.
[00098] At step 804, the method 800 may include estimating the vehicle speed based on correlation of the IMU value received from the IMU 202, using the motor encoder value received from the motor encoder sensor 204, and the throttle value received from the throttle sensor 206.
[00099] At step 806, the method 800 may include determining the motionless state or the motion state of the vehicle 110 based on the estimated vehicle speed.
[000100] At step 808, the method 800 may include determining the IMU value of the vehicle 110 exceeding the predefined IMU threshold in response to the determination that the vehicle 110 is in the motionless state.
[000101] At step 810, the method 800 may include detecting the fall of the vehicle 110 upon the determination that the IMU value of the vehicle 110 exceeds the predefined IMU threshold.
[000102] While the above-discussed steps in Figures 2-7 are shown and described in a particular sequence, the steps may occur in variations to the sequence in accordance with various embodiments. Further, a detailed description related to the various steps of Figure 8 is already covered in the description related to Figures 2-7 and is omitted herein for the sake of brevity.
[000103] Figure 9a-9b illustrates an exemplary use case for detecting the fall of the vehicle 110, according to an embodiment of the present disclosure.
[000104] In Figure 9a, the vehicle 110 is depicted traversing the banked road, leaning towards the lateral axis (x-axis) while in motion state. In a scenario where the IMU value (?) exceeds the predefined IMU threshold (IMUPTH), the system 128 may not detect the vehicle 110’s fall due to the continuous motion state of the vehicle 110. Consequently, the system 128 effectively mitigates false positive occurrences, avoiding erroneous detection of the vehicle’s fall.
[000105] In Figure 9b, the vehicle 110 is depicted as having fallen on the road, resulting in the IMU value (?) exceeding the predefined IMU threshold (IMUPTH), while the vehicle 110 remains in the motionless state. As a result, the system 128 can identify this event as a vehicle fall and subsequently control the operations of both the illumination device 210 and the vehicle motor 116 as safety measures to alert nearby surroundings of the fall event.
[000106] In some of the advantages of the present invention, the integration of additional sensor modalities, such as the accelerometers 202a and the gyroscopes 202b along with the motor encoder sensor 204, and the throttle sensor 206, further enhances the system’s 128 robustness and reliability. Further, by fusing data from multiple sources, the fall detection system of the present invention gains a comprehensive understanding of the vehicle’s 110 states, thus enabling the system to make informed decisions with a high degree of confidence.
[000107] Furthermore, the present invention incorporates preemptive measures to mitigate the consequences of a potential fall, thereby enhancing overall rider safety.
[000108] In conclusion, the development of an advanced fall detection system represents a leap forward in enhancing the safety features of two-wheelers, particularly electric vehicles. Thus, by addressing the limitations of existing methodologies, the present invention provides efficient detection of the vehicle falls and ensures a safer and more secure riding experience for users.
[000109] It will be appreciated that the modules, processes, systems, and devices described above can be implemented in hardware, hardware programmed by software, software instruction stored on a non-transitory computer-readable medium or a combination of the above. Embodiments of the methods, processes, modules, devices, and systems (or their sub-components or modules), may be implemented on a general-purpose computer, a special-purpose computer, a programmed microprocessor or microcontroller and peripheral integrated circuit element, an ASIC or other integrated circuit, a digital signal processor, a hardwired electronic or logic circuit such as a discrete element circuit, a programmed logic circuit such as a programmable logic device (PLD), programmable logic array (PLA), field-programmable gate array (FPGA), programmable array logic (PAL) device, or the like. In general, any process capable of implementing the functions or steps described herein can be used to implement embodiments of the methods, systems, or computer program products (software program stored on a non-transitory computer readable medium).
[000110] Furthermore, embodiments of the disclosed methods, processes, modules, devices, systems, and computer program products may be readily implemented, fully or partially, in software using, for example, object or object-oriented software development environments that provide portable source code that can be used on a variety of computer platforms. Alternatively, embodiments of the disclosed methods, processes, modules, devices, systems, and computer program products can be implemented partially or fully in hardware using, for example, standard logic circuits or a very-large-scale integration (VLSI) design. Other hardware or software can be used to implement embodiments depending on the speed and/or efficiency requirements of the systems, the particular function, and/or particular software or hardware system, microprocessor, or microcomputer being utilized.
[000111] In this application, unless specifically stated otherwise, the use of the singular includes the plural and the use of “or” means “and/or.” Furthermore, use of the terms “including” or “having” is not limiting. Any range described herein will be understood to include the endpoints and all values between the endpoints. Features of the disclosed embodiments may be combined, rearranged, omitted, etc., within the scope of the invention to produce additional embodiments. Furthermore, certain features may sometimes be used to advantage without a corresponding use of other features.
[000112] List of reference numerals:
Components Reference Numerals
Electric Vehicle or vehicle 110
Battery 112
On-board charger 114
Electric motor or vehicle motor 116
Electric Transmission System 118
Charging Infrastructure 120
Wheels 122a, 122b
Remote Server or cloud 124
Dashboard 126
System 128
Inertial Measurement Unit (IMU) 202
Accelerometer 202a
Gyroscope 202b
Motor Encoder Sensor 204
Throttle Sensor 206
Vehicle illumination device or Illumination device 210
Electronic Control Unit (ECU) 208
Processor 302
Memory 304
Set of Modules 306
Data 308
Acquisition Module 310
Calibrating Module 312
Determining Module 314
Motion Sub-Module 314a
Fall Detection Sub-Module 314b
Transmitting Module 316
Method 800 , Claims:1. A method for detecting a fall of a vehicle, the method (800) comprising the steps of:
calibrating at least one Inertial Measurement Unit (IMU) (202) installed in the vehicle (110) based on a vehicle frame of reference to compute a motion and an orientation of the vehicle (110) relative to axes of the vehicle (110);
estimating a vehicle speed based on correlation of an IMU value received from the at least one IMU (202), a motor encoder value received from a motor encoder sensor (204), and a throttle value received from a throttle sensor (206);
determining at least one of a motionless state or a motion state of the vehicle (110) based on the estimated vehicle speed;
determining the IMU value of the vehicle (110) exceeding a predefined IMU threshold in response to the determination that the vehicle (110) is in the motionless state; and
detecting the fall of the vehicle (110) upon the determination that the IMU value of the vehicle (110) exceeds the predefined IMU threshold.

2. The method (800) as claimed in claim 1, wherein determining the at least one of the motionless state or the motion state of the vehicle (110) based on the estimated vehicle speed comprises:
creating a moving array corresponding to each of IMU value, the motor encoder value, and the throttle value, wherein the moving array indicates one or more values associated with each of the IMU value, the motor encoder value, and the throttle value at each of the predefined time duration;
determining that the vehicle (110) is in the motionless state if a plurality of the one or more values in the moving array is less than a predefined speed threshold; and
determining that the vehicle (110) is in the motion state if the plurality of the one or more values in the moving array exceeds the predefined speed threshold.

3. The method (800) as claimed in claim 1, comprising:
controlling operations associated with the at least one of, at least one illumination device (210) and a vehicle motor (116), upon detecting the fall of the vehicle (110), wherein the operations indicate initiating an illumination pattern of the at least one illumination device (210) and disabling the vehicle motor (116); and
transmitting a notification to at least one of a user device or a Human Machine Interface (HMI) of the vehicle (110) upon detecting the fall.

4. The method (800) as claimed in claim 3, comprising:
reverting the operations associated with the one or more of the at least one illumination device (210) and the vehicle motor (116) in response to receiving a user-input indicating instructions to override the operations.

5. The method (800) as claimed in claim 1, wherein estimating the vehicle speed comprises:
receiving the IMU value including a linear acceleration value of the vehicle and an orientation value of the vehicle from the at least one IMU (202);
receiving the motor encoder value indicating a rotation of the vehicle motor (116) and the throttle value indicating a power value applied to the vehicle (110);
computing a change in velocity of the vehicle (110) based on correlating the linear acceleration value and the orientation value over time with the motor encoder value and the throttle value; and
estimating the vehicle speed based on computing the change in velocity of the vehicle (110).

6. The method (800) as claimed in claim 5, wherein the at least one IMU (202) comprises an accelerometer (202a) configured to estimate the linear acceleration value of the vehicle indicating a rate of change of velocity along a straight line, and a gyroscope (202b) configured to estimate angular position, thereby determining the orientation value of the vehicle indicating the rate of change of angular position of the vehicle with respect to time.

7. The method (800) as claimed in claim 6, wherein the at least one IMU is installed within a proximity to a center of gravity of the vehicle (110).

8. The method (800) as claimed in claim 1, wherein calibrating the at least one IMU (202) comprises:
receiving the IMU value while the vehicle (110) has a pitch angle and a roll angle of zero degrees to align a world reference frame with the vehicle reference frame;
determining an orientation of the at least one IMU (202) relative to the world reference frame based on the IMU value; and
calibrating the at least one IMU based on the determined orientation, such that the calibration enables accurate measurement of the vehicle’s motion and orientation.

9. The method (800) as claimed in claim 1, wherein determining the IMU value of the vehicle exceeding the predefined IMU threshold comprises:
creating an IMU moving array corresponding to each of a linear acceleration and an orientation value of the vehicle (110) based on the IMU value, wherein the IMU moving array indicates one or more values associated with each of the linear acceleration and the orientation value respectively for a predefined time duration; and
determining that the IMU value of the vehicle (110) exceeds the predefined IMU threshold in response to computing that a plurality of the one or more values in the IMU moving array exceeds the predefined IMU threshold.

10. A system for detecting a fall of a vehicle, the system (128) comprising:
a memory (304);
at least one processor (302) in communication with the memory (304), wherein the at least one processor (302) is configured to:
calibrate at least one Inertial Measurement Unit (IMU) (202) installed in the vehicle (110) based on a vehicle frame of reference to compute a motion and an orientation of the vehicle relative to axes of the vehicle (110);
estimate a vehicle speed based on correlation of an IMU value received from the at least one IMU (202), a motor encoder value received from a motor encoder sensor (204), and a throttle value received from a throttle sensor (206);
determine at least one of a motionless state or a motion state of the vehicle (110) based on the estimated vehicle speed;
determine the IMU value of the vehicle (110) exceeding a predefined IMU threshold in response to the determination that the vehicle is in the motionless state; and
detect the fall of the vehicle (110) upon the determination that the IMU value of the vehicle exceeds the predefined IMU threshold.

11. The system (128) as claimed in claim 10, wherein to determine the at least one of the motionless state or the motion state of the vehicle (110) based on the estimated vehicle speed the at least one processor (302) is configured to:
create a moving array corresponding to each of IMU value, the motor encoder value, and the throttle value, wherein the moving array indicates one or more values associated with each of the IMU value, the motor encoder value, and the throttle value at each of the predefined time duration;
determining that the vehicle is in the motionless state if a plurality of the one or more values in the moving array is less than a predefined speed threshold; and
determining that the vehicle is in the motion state if the plurality of the one or more values in the moving array exceeds the predefined speed threshold.

12. The system (128) as claimed in claim 10, wherein the at least one processor (302) is configured to:
control operations associated with the at least one of, at least one illumination device (210) and a vehicle motor (116), upon detecting the fall of the vehicle (110), wherein the operations indicate initiating an illumination pattern of the at least one illumination device (210) and disabling the vehicle motor (116); and
transmit a notification to at least one of a user device or a Human Machine Interface (HMI) of the vehicle (110) upon detecting the fall.

13. The system (128) as claimed in claim 12, wherein the at least one processor (302) is configured to:
revert the operations associated with the one or more of the at least one illumination device (210) and the vehicle motor (116) in response to receiving a user-input indicating instructions to override the operations.

14. The system (128) as claimed in claim 10, wherein to estimate the vehicle speed, the at least one processor (302) is configured to:
receive the IMU value including a linear acceleration value of the vehicle and an orientation value of the vehicle (110) from the at least one IMU (202);
receive the motor encoder value indicating a rotation of the vehicle motor (116) and the throttle value indicating a power value applied to the vehicle (110);
compute a change in velocity of the vehicle (110) based on correlating the linear acceleration value and the orientation value over time with the motor encoder value and the throttle value; and
estimate the vehicle speed based on computing the change in velocity of the vehicle (110).

15. The system (128) as claimed in claim 14, wherein the at least one IMU (202) comprises an accelerometer (202a) configured to estimate the linear acceleration value of the vehicle indicating a rate of change of velocity along a straight line, and a gyroscope (202b) configured to estimate angular position, thereby determining the orientation value of the vehicle (110) indicating the rate of change of angular position of the vehicle with respect to time.

16. The system (128) as claimed in claim 15, wherein the at least one IMU (202) is installed within a proximity to a center of gravity of the vehicle (110).

17. The system (128) as claimed in claim 10, wherein to calibrate the at least one IMU, the at least one processor (302) is configured to:
receive the IMU value while the vehicle has a pitch angle and the roll angle of zero degrees to align a world reference frame with the vehicle reference frame;
determine an orientation of the at least one IMU (202) relative to the world reference frame based on the IMU value; and
calibrate the at least one IMU based on the determined orientation, such that the calibration enables accurate measurement of the vehicle’s motion and orientation.

18. The system (128) as claimed in claim 10, wherein to determine the IMU value of the vehicle (110) exceeding the predefined IMU threshold, the at least one processor (302) configured to:
create an IMU moving array corresponding to each of a linear acceleration and an orientation value of the vehicle (110) based on the IMU value, wherein the IMU moving array indicates one or more values associated with each of the linear acceleration and the orientation value respectively for a predefined time duration; and
determine that the IMU value of the vehicle (110) exceeds the predefined IMU threshold in response to computing that a plurality of the one or more values in the IMU moving array exceeds the predefined IMU threshold.