DESC:FIELD OF INVENTION
The present disclosure generally relates to the field of drowsiness detection systems. More particularly, the present disclosure relates to a system and a method for detecting driver distraction or drowsiness.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
The development of mechanisms or systems for detecting driver fatigue has been the focus of much research over the past two decades. Traffic accidents caused by drowsy driving have become a serious issue affecting people's lives. Statistics indicate that approximately 10%–20% of traffic accidents involve drivers whose vigilance is diminished due to fatigue. Vehicle accidents caused by driver fatigue account for approximately 60% of fatalities.
The existing mechanism or systems use a variety of techniques, such as physiological measures (such as brain waves or heart rate) and vehicle parameters (such as speed, steering wheel movements, and lateral position). In real-world applications, these existing methods would be either infeasible or insufficient, since physiological measures involve intrusive methods, and changes in vehicle behaviour are typically dependent on vehicle type, driver experience, and driving conditions.
Further, some existing mechanism or systems monitor the driver’s behaviour, and driving pattern, and detect instances like distraction or drowsiness. While such existing mechanisms or systems are generally developed using a camera, they are quite expensive and not reliable.
As a result, it is essential to develop a mechanism that can detect driver fatigue and send an alert as soon as the driver loses adequate attention to traffic conditions.
Therefore, there is felt a need for a system and a method for detecting driver distraction or drowsiness that alleviates the aforementioned drawbacks.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide a system for detecting driver distraction or drowsiness.
Another object of the present disclosure is to provide a mechanism for keeping drivers alert.
Still another object of the present disclosure is to provide a mechanism for cost-effectiveness.
Yet another object of the present disclosure is to provide a mechanism for recognizing hand gestures.
Another object of the present disclosure is to provide a mechanism for detecting the alertness of the driver.
Still another object of the present disclosure is to provide a mechanism for operating haptic alerts.
Yet another object of the present disclosure is to provide a method for detecting driver distraction or drowsiness.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure envisages a system and a method for detecting driver distraction or drowsiness.
The system comprises a server and a controlling device.
The server is configured to communicate with a vehicle to receive vehicle feedback data over a wireless communication network.
The server includes a data repository and a server analytical module.
The data repository is configured to store a set of converting rules, a set of alert identifying rules, predefined instructions, and vehicle feedback data.
The server analytical module is configured to analyze the vehicle feedback data by means of the set of analysis rules, and transmit at least one alarm signal to the vehicle based on the analysis of the vehicle feedback data.
The controlling device is configured to communicate with the server over a wireless communication network.
The controlling device includes a microprocessor, an inputting module, a processing module, an alert generation module, and a triggering module.
The microprocessor is configured to execute the set of predefined commands to operate and execute one or more modules of the system.
The inputting module is configured to detect an analog signal in real-time by means of a plurality of sensors implemented in the proximity of a steering wheel of the vehicle.
The processing module is configured to cooperate with the inputting module to receive the analog signal and process the analog signal to convert and generate a digital signal by implementing the set of converting rules on the analog signal.
The alert generation module is configured to cooperate with the processing module to receive the generated digital signal and detect the alertness of the driver by implementing the set of alert identifying rules on the digital signal and further configured to generate at least one alarm signal based on a negative alertness of the driver detected by the set of alert identifying rules.
The triggering module is configured to cooperate with the alert generation module to receive at least one alarm signal and control a haptic motor to provide a haptic alert to the driver.
In an aspect, the controlling device includes a local analytical module configured to analyze the vehicle feedback data by implementing the set of analysis rules on the vehicle feedback data.
In an aspect, the analog signal consists of a hand movement gesture of a driver in real-time.
In an aspect, the hand gesture movement is supposed to be performed within a stipulated period.
In an aspect, at least one alarm signal is generated at uniform time intervals to detect the alertness of the driver.
In an aspect, the alertness of the driver is measured as positive feedback and negative feedback, and wherein the positive feedback indicates that the driver is alert and the negative feedback indicates that the driver is drowsy and distracted.
In an aspect, the set of alert identifying rules is a set of instructions to determine the state of the driver by generating negative feedback when the driver fails to perform the hand gesture movement or generating positive feedback when the driver performs the hand gesture movement.
In an aspect, the set of converting rules is a set of instructions to provide the analog signal proportional to the distance between the sensor face and the user's hand.
In an aspect, the haptic motor is mounted on a seat to provide a haptic alert.
In an aspect, the wireless communication network is selected from a group of networks consisting of a cellular network, wireless communication, short-range communication, long-range communication, the internet of things, and the like.
In an aspect, the plurality of sensors includes a proximity sensor.
In an aspect, the proximity sensors are mounted on a combination switch for recognizing hand gestures of the driver.
In an aspect, the driver has to gesture the driver’s hand in front of the proximity sensor mounted on the combination switch without taking his hand off the steering wheel.
In an aspect, the proximity sensor for hand gesture recognition will be activated only when an alarm signal is generated.
In an aspect, the vehicle feedback data consists of details related to the vehicle, driver’s positive feedback, driver’s negative feedback, and haptic motor data.
The present disclosure also envisages a method for detecting driver distraction or drowsiness. The method comprises the following steps:
• detecting, by an inputting module, an analog signal received from a plurality of sensors implemented in the proximity of a steering wheel of a vehicle;
• receiving, by a processing module, the analog signal from the inputting module;
• processing, by the processing module, the analog signal to convert the analog signal to a digital signal by implementing a set of converting rules on the analog signal;
• receiving, by an alert generation module, the digital signal from the processing module;
• detecting, by the alert generation module, alertness of the driver by implementing a set of alert identifying rules on the digital signals;
• generating, by the alert generation module, at least one alarm signal based on a negative alertness of the driver detected by the set of alert identifying rules;
• receiving, by a triggering module, at least one alarm signal from the alert generation module; and
• controlling, by the triggering module, a haptic motor to provide a haptic alert to the driver.
In an aspect, the analog signal consists of a hand movement gesture of a driver in real-time.
In an aspect, the method further comprises the steps:
• continuously receiving, by a server, vehicle feedback data from the plurality of sensors over a wireless communication network;
• analyzing, by a server analytical module, the vehicle feedback data by implementing a set of analysis rules on the vehicle feedback data;
• generating, by the server analytical module, at least one alarm signal based on a negative alertness of the driver detected based on the analysis of the vehicle feedback data;
• transmitting, by the server analytical module, at least one alarm signal to the triggering module to provide the haptic alert to the driver.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A system and a method for detecting driver distraction or drowsiness of the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a collision avoidance system for detecting driver distraction or drowsiness; and
Figure 2A and Figure 2B illustrate a flow chart depicting steps involved in the method for detecting driver distraction or drowsiness in accordance with an embodiment of the present disclosure.
LIST OF REFERENCE NUMERALS
100 - System
102 - Server
102a - Data Repository
102b - Server Analytical Module
104 - Controlling Device
104a - Microprocessor
104b - Inputting Module
104b -1 - Plurality of Sensors
104c - Processing Module
104d - Alert Generation Module
104e - Triggering Module
104e-1 - Haptic Motor
104f - Local Analytical Module
106 - Vehicle
108 - Wireless Communication Network
DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details, are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
When an element is referred to as being “engaged to,” "connected to," or "coupled to" another element, it may be directly engaged, connected, or coupled to the other element. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed elements.
The development of mechanism or systems for detecting driver fatigue has been the focus of much research over the past two decades. Traffic accidents caused by drowsy driving have become a serious issue affecting people's lives. Statistics indicate that approximately 10%–20% of traffic accidents involve drivers whose vigilance is diminished due to fatigue. Vehicle accidents caused by driver fatigue account for approximately 60% of fatalities.
The existing mechanism or systems use a variety of techniques, such as physiological measures (such as brain waves or heart rate) and vehicle parameters (such as speed, steering wheel movements, and lateral position). In real-world applications, these existing methods would be either infeasible or insufficient, since physiological measures involve intrusive methods, and changes in vehicle behaviour are typically dependent on vehicle type, driver experience, and driving conditions.
Further, some existing mechanisms or systems monitor the driver’s behaviour, and driving pattern, and detect instances like distraction or drowsiness. While such existing mechanisms or systems are generally developed using a camera, they are quite expensive and not reliable.
As a result, it is essential to develop a mechanism that can detect driver fatigue and send an alert as soon as the driver loses adequate attention to traffic conditions.
To address the issues of the existing systems and methods, the present disclosure envisages a system for detecting driver distraction or drowsiness (hereinafter referred to as “system 100”) and a method for detecting driver distraction or drowsiness (hereinafter referred to as “method 200”). The system 100 will now be described with reference to Figure 1 and the method 200 will be described with reference to Figure 2A and Figure 2B.
Referring to Figure 1, the system 100 comprises a server 102 and a controlling device 104.
The server 102 is configured to communicate with a vehicle 106 to receive vehicle feedback data over a wireless communication network 108.
In an aspect, the wireless communication network 108 is selected from a group of networks consisting of a cellular network, wireless communication, short-range communication, long-range communication, the internet of things, and the like.
The server 102 includes a data repository 102a and a server analytical module 102b.
The data repository 102a is configured to store a set of converting rules, a set of alert identifying rules, predefined instructions, and vehicle feedback data.
In an aspect, the data repository 102a may be a memory that can store one or more computer-readable instructions or routines, which may be fetched and executed to detect driver distraction or drowsiness. The memory may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
In an alternative aspect, the data repository 102a may be an external data storage device coupled to the system 100 directly or through one or more data servers.
The server analytical module 102b is configured to analyze the vehicle feedback data by means of the set of analysis rules, and transmit at least one alarm signal to the vehicle based on the analysis of the vehicle feedback data.
In an aspect, the vehicle feedback data consists of details related to the vehicle, driver’s positive feedback, driver’s negative feedback, and haptic motor data.
The controlling device 104 is configured to communicate with the server 102 over a wireless communication network 108.
The controlling device includes a microprocessor, an inputting module, a processing module, an alert generation module, and a triggering module.
In an aspect, the controlling device 104 includes a local analytical module 104f configured to analyze the vehicle feedback data by implementing the set of analysis rules on the vehicle feedback data.
The microprocessor 104a is configured to execute the set of predefined commands to operate and execute one or more modules of the system 100.
In an aspect, the microcontroller 104a 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 microprocessor 104a may fetch and execute computer-readable instructions stored in a memory. The functions of the microcontroller 104a may be provided through the use of dedicated hardware as well as hardware capable of executing machine-readable instructions. In other examples, the microcontroller 104a may be implemented by electronic circuitry or printed circuit board. The microcontroller 104a may be configured to execute functions of various modules of the system 100 such as the server analytical module 102b, the controlling device 104, the wireless communication network 108, the inputting module 104b, the processing module 104c, the alert generation module 104d, the triggering module 104e, and the local analytical module 104f.
The inputting module 104b is configured to detect an analog signal in real-time by means of a plurality of sensors 104a-1 implemented in the proximity of a steering wheel of the vehicle.
In an aspect, the analog signal consists of a hand movement gesture of a driver in real-time.
In an aspect, the hand gesture movement is supposed to be performed within a stipulated period.
In an aspect, the plurality of sensors 104b-1 includes a proximity sensor.
In an aspect, the proximity sensors are mounted on a combination switch for recognizing hand gestures of the driver.
In an aspect, the driver has to gesture the driver’s hand in front of the proximity sensor mounted on the combination switch without taking his hand off the steering wheel.
In an aspect, the proximity sensor for hand gesture recognition will be activated only when an alarm signal is generated.
The processing module 104c is configured to cooperate with the inputting module 104a to receive the analog signal and process the analog signal to convert and generate a digital signal by implementing the set of converting rules on the analog signal.
The alert generation module 104d is configured to cooperate with the processing module 104c to receive the generated digital signal and detect alertness of the driver by implementing the set of alert identifying rules on the digital signal.
The alert generation module 104d is further configured to generate at least one alarm signal based on a negative alertness of the driver detected by the set of alert identifying rules.
In an aspect, at least one alarm signal is generated at uniform time intervals to detect the alertness of the driver.
In an aspect, the alertness of the driver is measured as positive feedback and negative feedback, and wherein the positive feedback indicates that the driver is alert and the negative feedback indicates that the driver is drowsy and distracted.
In an aspect, the set of alert identifying rules is a set of instructions to determine the state of the driver by generating negative feedback when the driver fails to perform the hand gesture movement or generating positive feedback when the driver performs the hand gesture movement.
In an aspect, the set of converting rules is a set of instructions to provide the analog signal proportional to the distance between the sensor face and the user's hand.
The triggering module 104e is configured to cooperate with the alert generation module 104d to receive at least one alarm signal and control a haptic motor 104e-1 to provide a haptic alert to the driver.
In an aspect, the haptic motor 104e-1 is mounted on a seat to provide a haptic alert.
In an aspect, the system 100 may also include a communication interface. The communication interface may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, transceivers, storage devices, and the like. The communication interface may facilitate communication of the system 100 with various devices coupled to the system 100 or the microcontroller 104a. The communication interface may also provide a communication pathway for one or more components of the system 100 and the microcontroller 104a.
Also, the system 100 or the microcontroller 104a may include, or be coupled with, one or more transceivers to communicate with various devices coupled to the system 100 or the microcontroller 104a.
In an aspect, the system 100 provides a camera-less driver drowsiness detection mechanism for a Driver Monitoring System. The system 100 is designed to monitor the driver’s behaviour, driving pattern, and detect instances like distraction or drowsiness. While such systems are generally developed using a camera, they are quite expensive. The proposed mechanism involves a proximity sensor which is mounted on the combination switch of the vehicle. The proximity sensor in this mechanism is used for hand gesture recognition. The hand gesture movement in front of the sensor is an indication of alertness. The proposed mechanism is activated when an alarm is generated at uniform time intervals. The alarm is an indication for the driver to gesture his hand in front of the sensor without taking his hand off the steering wheel. Once the driver performs the hand gesture within the stipulated time, the sensor recognizes and sends positive feedback to the system indicating driver is alert. If a driver fails to perform the hand gesture movement, the sensor sends feedback to the system indicating the driver is drowsy and not alert. The primary benefit of this mechanism is that it is a simple cost effective system.
The following are the set of instructions used for detecting driver distraction or drowsiness:
• Analog Signal Detection: Sensors near the steering wheel detect hand movement gestures, producing an analog signal.
• Signal Processing: This analog signal is processed into a digital signal using conversion rules.
• Alertness Detection: An alert generation module applies alert identifying rules to the digital signal to determine the driver's alertness.
• Alarm Signal Generation: If the driver is detected as drowsy or distracted, an alarm signal is generated.
• Triggering Haptic Alert: This alarm signal triggers a haptic motor to provide a physical alert to the driver.
• Server Analysis: Additionally, the system sends vehicle feedback data to a server where it's analyzed for alertness, and an alarm signal can be sent back to the vehicle.
Figure 2A and Figure 2B illustrate a flow chart depicting steps involved in the method for detecting driver distraction or drowsiness in accordance with an embodiment of the present disclosure. The order in which method 200 is described is not intended to be construed as a limitation, and any number of the described method steps may be combined in any order to implement method 200, or an alternative method. Furthermore, method 200 may be implemented by processing resource or computing device(s) through any suitable hardware, non-transitory machine-readable medium/instructions, or a combination thereof. The method 200 comprises the following steps:
At step 202, the method 200 includes detecting, by an inputting module 104b, an analog signal received from a plurality of sensors 104b-1 implemented in the proximity of a steering wheel of a vehicle.
At step 204, the method 200 includes receiving, by a processing module 104c, the analog signal from the inputting module 104b.
At step 206, the method 200 includes processing, by the processing module 104c, the analog signal to convert the analog signal to a digital signal by implementing a set of converting rules on the analog signal.
At step 208, the method 200 includes receiving, by an alert generation module 104d, the digital signal from the processing module 104c.
At step 210, the method 200 includes detecting, by the alert generation module 104d, alertness of the driver by implementing a set of alert identifying rules on the digital signals.
At step 212, the method 200 includes generating, by the alert generation module 104d, at least one alarm signal based on a negative alertness of the driver detected by the set of alert identifying rules.
At step 214, the method 200 includes receiving, by a triggering module 104e, at least one alarm signal from the alert generation module 104d.
At step 216, the method 200 includes controlling, by the triggering module 104e, a haptic motor 104e-1 to provide a haptic alert to the driver.
An exemplary pseudo-code depicting the implementation of method 200 for detecting driver distraction or drowsiness.
class DrowsinessDetectionSystem:
def detect_analog_signal(self, sensors):
# Detect hand gesture as analog signal
return analog_signal

def convert_to_digital(self, analog_signal):
# Apply conversion rules to analog signal
return digital_signal

def detect_alertness(self, digital_signal):
# Apply alert identifying rules
return alertness_level

def generate_alarm_signal(self, alertness_level):
if alertness_level is negative:
return alarm_signal

def trigger_haptic_alert(self, alarm_signal, haptic_motor):
if alarm_signal:
# Activate haptic motor
return haptic_feedback

def send_data_to_server(self, vehicle_data, server):
# Send data to server
server.analyze_data(vehicle_data)

def receive_server_response(self, server):
return server.alarm_signal

# Main execution
system = DrowsinessDetectionSystem()
analog_signal = system.detect_analog_signal(sensors)
digital_signal = system.convert_to_digital(analog_signal)
alertness_level = system.detect_alertness(digital_signal)
alarm_signal = system.generate_alarm_signal(alertness_level)
haptic_feedback = system.trigger_haptic_alert(alarm_signal, haptic_motor)
vehicle_data = collect_vehicle_data()
system.send_data_to_server(vehicle_data, server)
server_alarm_signal = system.receive_server_response(server)
In an operative configuration, the system 100 comprises a server 102 is configured to communicate with a vehicle 106 to receive vehicle feedback data over a wireless communication network 108, wherein the server 102 comprises a data repository 102a and a server analytical module 102b. The data repository 102a is configured to store a set of converting rules, a set of alert identifying rules, predefined instructions, and vehicle feedback data. The server analytical module 102b is configured to analyze the vehicle feedback data by means of the set of analysis rules, and transmit at least one alarm signal to the vehicle based on the analysis of the vehicle feedback data.
The controlling device 104 is configured to communicate with the server 102 over a wireless communication network 108. The microprocessor 104a is configured to execute the set of predefined commands to operate and execute one or more modules of the system 100. The inputting module 104b is configured to detect an analog signal in real-time by means of a plurality of sensors 104b-1 implemented in the proximity of a steering wheel of the vehicle. The processing module 104c is configured to cooperate with the inputting module 104a to receive the analog signal and process the analog signal to convert and generate a digital signal by implementing the set of converting rules on the analog signal.
The alert generation module 104d is configured to cooperate with the processing module 104c to receive the generated digital signal and detect alertness of the driver by implementing the set of alert identifying rules on the digital signal and further configured to generate at least one alarm signal based on a negative alertness of the driver detected by the set of alert identifying rules. The triggering module 104e is configured to cooperate with the alert generation module 104d to receive at least one alarm signal and control a haptic motor 104e-1 to provide a haptic alert to the driver.
Advantageously, the system 100 provides for detecting driver distraction or drowsiness. The system 100 monitors the driver’s behaviour, and driving pattern, and detects instances like distraction or drowsiness. The system 100 provides the sensor recognizes and sends positive feedback to the system indicating the driver is alert. The system 100 provides the sensor that sends feedback to the system indicating the driver is drowsy and not alert.
The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope and spirit of the disclosure and appended claims. For example, due to the nature of software, functions described above can be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.
The foregoing description of the embodiments has been provided for purposes of illustration and is not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of a system and a method for detecting driver distraction or drowsiness that:
• are scalable;
• cost-effective;
• are safe;
• keep the driver alert.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation. ,CLAIMS:WE CLAIM:
1. A method (200) for detecting driver distraction or drowsiness, said method (200) comprises the following steps:
• detecting, by an inputting module (104b), an analog signal received from a plurality of sensors (104b-1) implemented in the proximity of a steering wheel of a vehicle;
• receiving, by a processing module (104c), said analog signal from said inputting module (104b);
• processing, by said processing module (104c), said analog signal to convert said analog signal to a digital signal by implementing a set of converting rules on said analog signal;
• receiving, by an alert generation module (104d), said digital signal from said processing module (104c);
• detecting, by said alert generation module (104d), alertness of the driver by implementing a set of alert identifying rules on said digital signals;
• generating, by said alert generation module (104d), at least one alarm signal based on a negative alertness of the driver detected by said set of alert identifying rules;
• receiving, by a triggering module (104e), said at least one alarm signal from said alert generation module (104d); and
• controlling, by said triggering module (104e), a haptic motor (104e-1) to provide a haptic alert to the driver.
2. The method as claimed in claim 1, wherein said analog signal consists of a hand movement gesture of a driver in real-time.
3. The method as claimed in claim 1, wherein the method further comprises:
• continuously receiving, by a server (102), vehicle feedback data from the plurality of sensors (104b-1) over a wireless communication network (108);
• analyzing, by a server analytical module (102b), said vehicle feedback data by implementing a set of analysis rules on said vehicle feedback data;
• generating, by said server analytical module (102b), at least one alarm signal based on a negative alertness of the driver detected based on the analysis of the vehicle feedback data;
• transmitting, by said server analytical module (102b), at least one alarm signal to said triggering module (104e) to provide the haptic alert to the driver.
4. A driver distraction or drowsiness detection system (100), said system (100) comprising:
• a server (102) configured to communicate with a vehicle (106) to receive vehicle feedback data over a wireless communication network (108), wherein said server (102) comprises:
i. a data repository (102a) configured to store a set of converting rules, a set of alert identifying rules, predefined instructions, and vehicle feedback data; and
ii. a server analytical module (102b) configured to analyze said vehicle feedback data by means of said set of analysis rules, and transmit at least one alarm signal to the vehicle based on the analysis of said vehicle feedback data; and
• a controlling device (104) configured to communicate with said server (102) over a wireless communication network (108), wherein said controlling device (104) includes:
i. a microprocessor (104a) configured to execute said set of predefined commands to operate and execute one or more modules of said system (100);
ii. an inputting module (104b) configured to detect an analog signal in real-time by means of a plurality of sensors (104b-1) implemented in the proximity of a steering wheel of the vehicle;
iii. a processing module (104c) configured to cooperate with said inputting module (104a) to receive said analog signal and process said analog signal to convert and generate a digital signal by implementing said set of converting rules on said analog signal;
iv. an alert generation module (104d) configured to cooperate with said processing module (104c) to receive said generated digital signal and detect alertness of the driver by implementing said set of alert identifying rules on said digital signal and further configured to generate at least one alarm signal based on a negative alertness of the driver detected by said set of alert identifying rules; and
v. a triggering module (104e) configured to cooperate with said alert generation module (104d) to receive said at least one alarm signal and control a haptic motor (104e-1) to provide a haptic alert to the driver.
5. The system as claimed in claim 4, wherein said controlling device (104) includes a local analytical module (104f) configured to analyze said vehicle feedback data by implementing said set of analysis rules on said vehicle feedback data.
6. The system as claimed in claim 4, wherein said analog signal consists of a hand movement gesture of a driver in real-time.
7. The system as claimed in claim 6, wherein said hand gesture movement is supposed to be performed within a stipulated period.
8. The system as claimed in claim 4, wherein said at least one alarm signal is generated at uniform time intervals to detect the alertness of the driver.
9. The system as claimed in claim 4, wherein said alertness of the driver is measured as positive feedback and negative feedback, and wherein said positive feedback indicates that the driver is alert and said negative feedback indicates that the driver is drowsy and distracted.
10. The system as claimed in claim 4, wherein said set of alert identifying rules is a set of instructions to determine the state of the driver by generating negative feedback when the driver fails to perform the hand gesture movement or generating positive feedback when the driver performs the hand gesture movement.
11. The system as claimed in claim 4, wherein said set of converting rules is a set of instructions to provide said analog signal proportional to the distance between the sensor face and the user's hand.
12. The system as claimed in claim 4, wherein said haptic motor (104e-1) is mounted on a seat to provide a haptic alert.
13. The system as claimed in claim 4, wherein said wireless communication network (108) is selected from a group of networks consisting of a cellular network, wireless communication, short-range communication, long-range communication, internet of things, and the like.
14. The system as claimed in claim 4, wherein said plurality of sensors (104b-1) includes a proximity sensor.
15. The system as claimed in claim 14, wherein said proximity sensors are mounted on a combination switch for recognizing hand gestures of the driver.
16. The system as claimed in claim 14, wherein the driver has to gesture the driver’s hand in front of the proximity sensor mounted on the combination switch without taking his hand off the steering wheel.
17. The system as claimed in claim 14, wherein said proximity sensor for hand gesture recognition will be activated only when an alarm signal is generated.
18. The system as claimed in claim 4, wherein said vehicle feedback data consists of details related to the vehicle, driver’s positive feedback, driver’s negative feedback, and haptic motor data.
Dated this 29th day of May, 2024

_______________________________
MOHAN RAJKUMAR DEWAN, IN/PA – 25
of R.K.DEWAN & CO.
Authorized Agent of Applicant

TO,
THE CONTROLLER OF PATENTS
THE PATENT OFFICE, AT MUMBAI