Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a vehicle safety and maintenance system and particularly to an Artificial Intelligence (AI) driven pre-ride safety and maintenance system for two-wheelers.
Description of Related Art
[002] Two-wheelers are one of the most widely used modes of transportation globally, particularly in urban and densely populated regions. Their affordability, fuel efficiency, and ease of maneuverability make them a preferred choice for millions of riders. However, two-wheeler safety and maintenance have long been areas of concern, with numerous studies and reports indicating that improper maintenance and neglected safety checks contribute to a significant number of accidents and vehicle breakdowns.
[003] Traditionally, two-wheeler maintenance and pre-ride safety inspections have relied on manual checks performed by riders. Various safety guidelines, such as the T-CLOCS (Tires, Controls, Lights, Oil, Chassis, Stands) checklist, have been promoted to encourage riders to inspect their vehicles before every ride. However, adherence to such protocols remains inconsistent due to a lack of awareness, urgency, or technical knowledge.
[004] Several technological advancements have attempted to address different aspects of two-wheeler safety and maintenance. Tire Pressure Monitoring Systems (TPMS) provide real-time alerts regarding tire pressure but do not assess tire wear or degradation. Some motorcycles feature side stand sensors that prevent ignition if the stand is extended, but these are not universally available across all models. Mobile applications help riders track fuel consumption and maintenance schedules, but they rely on manual data entry, making them prone to inaccuracy and human oversight.
[005] Helmet compliance remains another critical safety factor, with regulations in many regions mandating helmet use. Some high-end motorcycles incorporate Bluetooth-based helmet detection systems, but these are not standard across all vehicles. Moreover, such systems typically function as reminders rather than enforcement mechanisms.
[006] In addition to safety concerns, long-term vehicle maintenance is also crucial. Riders often overlook issues such as oil quality degradation, battery health, and potential fuel or oil leaks, especially when a vehicle remains inactive for extended periods. Traditional servicing methods are often mileage-based rather than condition-based, leading to either premature servicing or unexpected failures due to delayed maintenance.
[007] While existing solutions address specific aspects of two-wheeler safety and maintenance, they operate independently and require riders to manage multiple systems manually. There remains a need for a comprehensive, automated approach that enhances safety compliance, ensures pre-ride readiness, and optimizes maintenance through real-time monitoring and predictive analysis.
[008] There is thus a need for an improved and advanced an Artificial Intelligence (AI) driven pre-ride safety and maintenance system for two-wheelers that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[009] Embodiments in accordance with the present invention provide an Artificial Intelligence (AI) driven pre-ride safety and maintenance system for two-wheelers. The system comprises an integrated detection unit configured to gather sensor data. The sensor data is selected from a real-time tire air pressure and temperature, a position of a side stand, a helmet compliance, a fuel and engine oil leak, or a combination thereof. The system further comprises a storage unit configured to store the sensor data gathered by the integrated detection unit. The system further comprises a microcontroller communicatively connected to the integrated detection unit. The microcontroller is configured to analyze the sensor data using an Artificial Intelligence (AI) engine for determining pre-ride safety conditions, predictive vehicle maintenance status, a risk assessment, or a combination thereof; trigger an ignition control unit to prevent ignition of a vehicle when the pre-ride safety conditions deviate from a safe limit; and display real-time safety warnings and maintenance alerts on a dashboard display unit.
[0010] Embodiments in accordance with the present invention further provide a method for carrying out pre-ride safety and maintenance for two-wheelers. The method comprising steps of: gathering a sensor data from an integrated detection unit; storing the gathered sensor data in a storage unit; analyzing the sensor data using an artificial intelligence (AI) engine for determining pre-ride safety conditions, predictive vehicle maintenance status, a risk assessment, or a combination thereof; triggering an ignition control unit to prevent ignition of a vehicle when pre-ride safety conditions deviate from a safe limit; and displaying real-time safety warnings and maintenance alerts on a dashboard display unit.
[0011] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide an Artificial Intelligence (AI) driven pre-ride safety and maintenance system for two-wheelers.
[0012] Next, embodiments of the present application may provide a pre-ride safety and maintenance system that carries out comprehensive and automated pre-ride safety checks.
[0013] Next, embodiments of the present application may provide a pre-ride safety and maintenance system that features AI-driven predictive maintenance.
[0014] Next, embodiments of the present application may provide a pre-ride safety and maintenance system that collaborates with IoT-enabled remote monitoring and alerts.
[0015] These and other advantages will be apparent from the present application of the embodiments described herein.
[0016] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0018] FIG. 1 illustrates a block diagram of an Artificial Intelligence (AI) driven pre-ride safety and maintenance system for two-wheelers, according to an embodiment of the present invention; and
[0019] FIG. 2 depicts a flowchart of a method for carrying out pre-ride safety and maintenance for two-wheelers, according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a block diagram of an Artificial Intelligence (AI) driven pre-ride safety and maintenance system 100 (hereinafter referred to as the system 100) for two-wheelers, according to an embodiment of the present invention. The system 100 may be adapted to assess a vehicle health. The system 100 may be adapted to conduct pre-ride safety checks. The pre-ride safety checks may be, but not limited to, a fuel level, a tire pressure, and so forth. Embodiments of the present invention are intended to include or otherwise cover any pre-ride safety checks, including known, related art, and/or later developed technologies. The system 100 may further be adapted to alert a rider in case of bad vehicle health or failed pre-ride safety checks.
[0025] The system 100 may comprise an integrated detection unit 102, a storage unit 104, a microcontroller 106, an Artificial Intelligence (AI) engine 108, an ignition control unit 110, a dashboard display unit 112, and an Internet of Things (IoT) enabled computing device 114.
[0026] In an embodiment of the present invention, the integrated detection unit 102 may be adapted to gather sensor data. The sensor data may be a real-time tire air pressure and temperature, a position of a side stand, a helmet compliance, a fuel and engine oil leaks, and so forth. Embodiments of the present invention are intended to include or otherwise cover any sensor data, including known, related art, and/or later developed technologies.
[0027] The integrated detection unit 102 may comprise tire pressure sensors, a magnetic sensor, a helmet compliance unit, a fuel detection unit, a temperature sensor, a viscosity sensor, and so forth. Embodiments of the present invention are intended to include or otherwise cover any sensor, including known, related art, and/or later developed technologies.
[0028] The integrated detection unit 102 may verify the helmet compliance by data interpolation from Radio Frequency Identifier (RFID), a Bluetooth, a Near Field Communication (NFC), and so forth. Embodiments of the present invention are intended to include or otherwise cover any means for data interpolation, including known, related art, and/or later developed technologies.
[0029] In an embodiment of the present invention, the storage unit 104 may be adapted to store the sensor data gathered by the integrated detection unit 102. The storage unit 104 may be, but not limited to, a hard drive, a flash drive, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the sensor data gathered by the integrated detection unit 102, including known, related art, and/or later developed technologies.
[0030] In an embodiment of the present invention, the microcontroller 106 may be communicatively connected to the integrated detection unit 102. The microcontroller 106 may be configured to analyze the sensor data using the Artificial Intelligence (AI) engine 108 for determining pre-ride safety conditions, predictive vehicle maintenance status, a risk assessment, and so forth. The microcontroller 106 may be configured to trigger the ignition control unit 110 to prevent an ignition of the vehicle when the pre-ride safety conditions deviate from a safe limit. The microcontroller 106 may be configured to trigger the ignition control unit 110 to prevent the ignition of the vehicle when the side stand is detected in an extended position unless the integrated detection unit 102 engine confirms helmet compliance.
[0031] In an exemplary scenario, the microcontroller 106 may be configured to allow the ignition of the vehicle only when the pre-ride safety conditions meet the safe limits. In other words, the ignition of the vehicle may be conducted when the tire air pressure and temperature are in an operatable range, the side-stand is in a contracted position, the rider is wearing the helmet, and there is no fuel and engine oil leak. Voiding any of the above listed safety conditions will prevent ignition of the vehicle. Thus, ensuring rider safety.
[0032] The microcontroller 106 may be configured to execute a vehicle inactivity check after a predefined period of non-usage, assessing a battery charge, a tire pressure, an engine oil condition, a fuel evaporation, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the checks, including known, related art, and/or later developed technologies.
[0033] The microcontroller 106 may be configured to transmit diagnostic reports and predictive maintenance schedules to the computing device for real-time access. The microcontroller 106 may be configured to enable the dashboard display unit 112 to display real-time safety warnings and maintenance alerts. The microcontroller 106 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the microcontroller 106, including known, related art, and/or later developed technologies.
[0034] The Artificial Intelligence (AI) engine 108 may be configured to process the sensor data stored in the storage unit 104 to predict tire wear. The Artificial Intelligence (AI) engine 108 may be configured to compare a real-time engine oil viscosity and temperature data with a benchmark data. The Artificial Intelligence (AI) engine 108 may be configured to execute computing techniques such as, but not limited to, a node processing, a neural network, or a combination thereof. Embodiments of the present invention are intended to include or otherwise cover any computing techniques, including known, related art, and/or later developed technologies.
[0035] In an embodiment of the present invention, the dashboard display unit 112 may be installed in a visual proximity of the rider. The dashboard display unit 112 may be adapted to display the real-time safety warnings and maintenance alerts. The dashboard display unit 112 may be adapted to display a notification relating to the predicted tire wear. The dashboard display unit 112 may be adapted to display a notification relating to a requirement for an oil change. The dashboard display unit 112 may be, but not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the dashboard display unit 112, including known, related art, and/or later developed technologies.
[0036] In an embodiment of the present invention, the Internet of Things (IoT) enabled computing device 114 may be an electronic device used by the rider. The Internet of Things (IoT) enabled computing device 114 may be configured to diagnostic reports and predictive maintenance schedules relating to the vehicle. The Internet of Things (IoT) enabled computing device 114 may be, but not limited to, a mobile phone, a smartphone, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the Internet of Things (IoT) enabled computing device 114, including known, related art, and/or later developed technologies.
[0037] FIG. 2 depicts a flowchart of a method 200 for carrying out the pre-ride safety and maintenance for the two-wheelers using the system 100, according to an embodiment of the present invention.
[0038] At step 202, the system 100 may gather the sensor data from the integrated detection unit 102.
[0039] At step 204, the system 100 may store the gathered sensor data in the storage unit 104.
[0040] At step 206, the system 100 may analyze the sensor data using the Artificial Intelligence (AI) engine 108 for determining the pre-ride safety conditions, the predictive vehicle maintenance status, the risk assessment, and so forth.
[0041] At step 208, the system 100 may check for a deviation of the pre-ride safety conditions deviate from the safe limit. If the pre-ride safety conditions deviate from the safe limit, then the method 200 may proceed to a step 210. Else, the method 200 may revert to the step 202.
[0042] At step 210, the system 100 may trigger the ignition control unit 110 to prevent the ignition of the vehicle.
[0043] At step 212, the system 100 may display the real-time safety warnings and maintenance alerts on the dashboard display unit 112.
[0044] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0045] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An Artificial Intelligence (AI) driven pre-ride safety and maintenance system (100) for two-wheelers, the system (100) comprising:
an integrated detection unit (102) configured to gather sensor data, wherein the sensor data is selected from a real-time tire air pressure and temperature, a position of a side stand, a helmet compliance, a fuel and engine oil leaks, or a combination thereof:
a storage unit (104) adapted to store the sensor data gathered by the integrated detection unit (102); and
a microcontroller (106) communicatively connected to the integrated detection unit (102), characterized in that the microcontroller (106) is configured to:
analyze the sensor data using an Artificial Intelligence (AI) engine (108) for determining pre-ride safety conditions, predictive vehicle maintenance status, a risk assessment, or a combination thereof;
trigger an ignition control unit (110) to prevent ignition of a vehicle when the pre-ride safety conditions deviate from a safe limit; and
display real-time safety warnings and maintenance alerts on a dashboard display unit (112).
2. The system (100) as claimed in claim 1, wherein the integrated detection unit (102) comprises tire pressure sensors, a magnetic sensor, a helmet compliance unit, a fuel detection unit, a temperature sensor, a viscosity sensor, or a combination thereof.
3. The system (100) as claimed in claim 1, wherein the integrated detection unit (102) is configured to verify the helmet compliance by data interpolation from Radio Frequency Identifier (RFID), a Bluetooth, a Near Field Communication (NFC), or a combination thereof.
4. The system (100) as claimed in claim 1, comprising an Internet of Things (IoT) enabled computing device (114) configured to receive the pre-ride safety conditions, the predictive vehicle maintenance status, the risk assessment, or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the microcontroller (106) is configured to prevent ignition if the side stand is detected in an extended position and unless the integrated detection unit (102) engine confirms helmet compliance.
6. The system (100) as claimed in claim 1, wherein the microcontroller (106) is configured to analyze fuel and oil leakage data, preventing ignition if leakage exceeds a predefined safety threshold.
7. The system (100) as claimed in claim 1, wherein the microcontroller (106) is configured to execute a vehicle inactivity check after a predefined period of non-usage, assessing a battery charge, a tire pressure, an engine oil condition, a fuel evaporation, or a combination thereof.
8. The system (100) as claimed in claim 1, wherein the Artificial Intelligence (AI) engine (108) is configured to process the sensor data stored in the storage unit (104) to predict tire wear and notify the rider via the dashboard display unit (112).
9. The system (100) as claimed in claim 1, wherein the microcontroller (106) is configured to transmit diagnostic reports and predictive maintenance schedules to the computing device for real-time access.
10. A method (200) for carrying out pre-ride safety and maintenance for two-wheelers, the method (200) is characterized by steps of:
gathering a sensor data from an integrated detection unit (102);
storing the gathered sensor data in a storage unit (104);
analyzing the sensor data using an Artificial Intelligence (AI) engine (108) for determining pre-ride safety conditions, predictive vehicle maintenance status, a risk assessment, or a combination thereof;
triggering an ignition control unit (110) to prevent ignition of a vehicle when pre-ride safety conditions deviate from a safe limit; and
displaying real-time safety warnings and maintenance alerts on a dashboard display unit (112).
Date: March 04, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant