Description:Field of the Invention
The proposed invention describes the pathole detection using artificial intelligence to better assist motorists in decision-making on the roadways and transportation safety.
Objective of this Invention
The primary objective of propounding the idea of pathole detection is to provide a better solution that it is an essential part of maintaining roads and ensuring safe driving conditions. The development of the pathole detection is to provide better assist to the motorists in decision-making on the roadways and other types of roads. It is a difficult undertaking that necessitates the accurate identification and monitoring of traffic conditions in real time. With advance in computer vision, Iot, and AI, video feeds from distributed cameras can be evaluated with deep learning models to inspect road condition with AI.
Background of the Invention
Roads are the essential means of transportation for a country to provide commutation facilities nationwide. Road infrastructure enables opportunities to connect people and transport goods to enhance business opportunities, access to jobs, economic growth, and health care invention across the country. As first -rated roads contribute to the country’s GDP, the calamitous, infrastructure of roads can become fatal for passenger’s safety and vehicles’ condition. The roads are usually made up of asphalt pavement and are prone to different structural damages with the passage of time. For instance, US9524597B2 can identify the invention for vehicle-to-third-party communications that includes a vehicle personality module customized to build a vehicle personality and a communications invention that uses the formed vehicle personality instead of a user's profile for one or more communications. The one or more communications are associated with one or more of an identifier and an icon indicating the vehicle personality, with the identification and/or icon being sent with at least one communication and seen by the recipient.Similarly, US10073462B2 discloses the invention provides an autonomous vehicle capable of driving autonomously across a path of heavy traffic and delivering objects or persons, even on difficult conditions, while assuring vehicle safety and general road safety. At least one variable pitch camera is included in the driverless vehicle for producing images that will be used for computer vision to control the autonomous vehicle. The invention makes it possible to change the pitch of the variable pitch camera as the autonomous vehicle moves in order to maximize camera image clarity and/or resolution. The photos can be used to discern lanes, detect pedestrians, rebuild an area in three dimensions (3D), and/or detect potholes. The invention uses at least one image from the variable pitch camera to regulate the movement and/or trajectory of the autonomous vehicle.
EP3560783B1also relates to a invention that the present invention relates to a technical field of a road surface condition estimation apparatus and a road surface condition estimation method each of which is configured to estimate a condition of a road surface. discloses a method of estimating a condition of a road surface by frequency-analyzing a wheel speed signal to thereby calculate a vibration gain, calculating a resonance gain correction coefficient corresponding to a difference between a reference pressure and an inner pressure of a tire, calculating a corrected vibration gain on the basis of the vibration gain and the resonance gain correction coefficient, and comparing the corrected vibration gain with a threshold value.US11282391B2 similarly deals with the method may include acquiring an image of a vehicle's environment; selecting a set of pixels located within a region of interest that is located at an upper part of the image; calculating an illumination condition indicator based on values of the set of pixels; and selecting a selected machine learning process, out of a machine learning processes, based on the illumination condition indicator.US11029685B2 relates to receiving sensed information related to driving sessions of multiple vehicles by a computerized invention; applying a machine learning process on the sensed information to detect fallen cargo and classify the fallen cargo to fallen cargo classes; estimating, from the sensed information, an impact of at least some of the fallen cargo classes on the behaviour of at least some of the multiple vehicles and determining.
US10480939B2A disclosed mobile pavement surface scanning invention is designed for detecting pavement distress. In one embodiment, the invention comprises one or more light sources mounted on a mobile vehicle to illuminate the pavement, along with one or more stereoscopic image-capturing devices mounted on the vehicle for capturing sequential images of the illuminated pavement surface. Additionally, a plurality of positioning sensors is mounted on the mobile vehicle, which are adapted to encode the vehicle's movement and provide a synchronization signal for the sequential images captured by the stereoscopic image-capturing devices. The invention also includes one or more computer processors, which are adapted to synchronize the intensity image pairs captured by each camera in the stereoscopic image-capturing devices. The processors perform a 3D reconstruction of the pavement from the intensity image pairs using stereoscopic principles, generate a depth image, and produce an intensity image pair from the 3D reconstruction. Subsequently, the processors process at least one of the depth image and the intensity image using one or more distress detection modules to identify a type of pavement distress.US11435751B2 deals with a vehicle may incorporate an on-board data processing invention that receives sensor data gathered by the vehicle's different sensors. The on-board data processing invention can interpret acquired sensor data to identify prospective vehicle stops while a vehicle moves along a route. The on-board data processing invention can then identify the geographical coordinates of the potential vehicle stop location, use artificial intelligence to classify the vehicle's situation at the potential stop, and determine whether the stop was caused by a road obstacle, such as a speed bump, a gutter, an unmarked crosswalk, or any other obstacle that is not at an intersection.If the stop was caused by a road impediment, the on-board data processing invention can generate virtual stop or yield line data matching to the specified geographic coordinates and send this data to a server for processing via a network.Similarly, US9866782B2 refers network connectivity is used to share important visual and other sensory information between vehicles, as well as to convey relevant information offered by network services to generate a more complete picture of the vehicle's surroundings. The enhanced view is displayed to the vehicle's occupants in order to improve the driving experience and/or allow the occupants to take appropriate action (e.g., avoid obstructions, identify traffic delays, etc.). In one example, the enhanced view includes information that is not visible to the naked eye and/or cannot currently be sensed by the vehicle's sensors (e.g., due to a partially or completely blocked view, low visibility conditions, hardware capabilities of the vehicle's sensors, sensor position, etc.).The integration of AI in pathole detection addresses these challenges by automating the process, significantly improving efficiency and accuracy. The use of a mobile pavement surface scanning invention with AI-driven algorithms allows for real-time analysis of pavement conditions without the need for human intervention.
Summary of the Invention
Pothole detection using AI involves the deployment of cameras on vehicles to capture real-time images or video frames of the road. A trained convolution neural network (CNN) processes these frames to identify potholes. Theinvention estimates the distance of detected potholes from the vehicle and displays the information on a screen within the driver's line of sight, indicating the presence of potholes up to a range of 10 to 20 meters. The main components are the camera for detection and a front-facing display for providing immediate information to the driver. This camera captures continuous images or video frames of the road as the vehicle moves. The collected data is then processed by a trained neural network , typically a convolution neural network (CNN), which has been trained on a diverse dataset to recognize potholes accurately. The output of the invention, indicating the presence and location of potholes, is displayed on a screen conveniently positioned in front of the driver. This display acts as a direct interface to convey information about potholes within a specified range, typically up to 10 to 20 meters ahead. The goal is to ensure that the driver receives prompt and accurate alerts regarding road conditions, allowing for proactive responses to potential hazards.

Brief Description of Drawings
The invention will be described in detail with reference to the exemplary embodiments shown in the figures wherein:
Figure-1: Flowgorithm representing process for detecting and estimating depth of pathole.
Figure-2: Diagrammatic representation for RoadView Display Invention.

Detailed Description of the Invention
AI-powered pothole detection is an innovative solution designed to enhance traffic safety using artificial intelligence in automobiles. This invention consists of two primary components: an advanced camera and an interactive screen. The camera technology in this system is a robust component designed to capture high-quality, real-time visual data for effective pothole detection. The RGB camera provides high-resolution imaging for detailed color representation, making it suitable for general-purpose computer vision applications. It is available in various factors, including small and compact designs that can be easily integrated into vehicles. Moreover, it works well under a wide range of lighting conditions, ensuring reliable performance day or night. The depth camera, on the other hand, provides depth information for each pixel, which is crucial for distance estimation and assessing the proximity of road anomalies. It can operate in various lighting conditions, including low-light environments, enhancing its utility in different scenarios. The depth camera is designed for depth perception, enabling the creation of a 3D map of the environment, which helps in accurately identifying and measuring potholes. Precise calibration and alignment of the camera are essential to ensure accurate distance estimations and reliable detection. Calibration processes account for factors such as the vehicle’s speed, position, and orientation, maintaining the accuracy of the system’s output. Calibration processes are tailored to the specific vehicle to maintain the accuracy of the system’s output, including adjusting the camera's positioning and alignment to ensure optimal performance.
The display technology serves as the primary interface between the AI system and the driver, providing real-time, clear, and actionable information to enhance driver awareness and contribute to road safety. The display features include Liquid Crystal Display (LCD), which is backlit by a white LED or other light sources, offering high resolution and color accuracy. It is commonly used in automotive applications due to its reliability and cost-effectiveness and ensures that the driver receives clear and accurate information, even in varying lighting conditions. Organic Light Emitting Diode (OLED) technology, featuring self-emissive pixels for individual control, enables true blacks and high contrast ratios. It is thinner and lighter than traditional LCDs, which helps in reducing the overall weight of the display system. Known for its vibrant colors and wide viewing angles, OLED ensures that the information is clearly visible from different perspectives. Thin-Film Transistor Liquid Crystal Display (TFT-LCD) technology utilizes thin-film transistor technology for enhanced image quality and faster response times. It offers a balance between performance and cost, making it a popular choice for automotive displays. TFT-LCD technology is known for its durability and consistent performance, even under demanding conditions.
Both the camera and display technologies are seamlessly integrated into the vehicle's existing systems. The AI-powered system processes data in real time, providing immediate feedback and alerts to the driver. The interactive screen is designed to be user-friendly, allowing drivers to easily interpret and act upon the information provided. By accurately detecting and displaying potholes, the system helps drivers avoid potential hazards, contributing to overall road safety. The data collected by the system can also be used for road maintenance planning, identifying areas that need repair. The system acts as an additional layer of assistance, helping drivers navigate challenging road conditions with greater confidence.The robustness of the camera technology lies in its high-resolution imaging and depth perception capabilities. High-resolution imaging is crucial for detailed color representation, making it suitable for general-purpose computer vision applications. This feature ensures that the camera can accurately capture the visual data required for effective pothole detection. The compact design of the RGB camera allows for easy integration into vehicles, without compromising on the quality of the visual data captured. The ability of the camera to operate under a wide range of lighting conditions ensures that the system can function reliably, regardless of the time of day or weather conditions.The depth camera provides depth information for each pixel, which is essential for distance estimation and assessing the proximity of road anomalies. This capability is crucial for accurate pothole detection, as it allows the system to create a 3D map of the environment. The depth camera can operate in various lighting conditions, including low-light environments, making it versatile and effective in different scenarios. The ability to create a 3D map of the environment helps in accurately identifying and measuring potholes, ensuring that the system can provide reliable and actionable information to the driver.
Precise calibration and alignment of the camera are essential to ensure accurate distance estimations and reliable detection. Calibration processes are implemented to account for factors such as the vehicle’s speed, position, and orientation. This ensures that the system can maintain the accuracy of its output, regardless of the vehicle’s movements. Calibration processes are tailored to the specific vehicle, including adjusting the camera's positioning and alignment to ensure optimal performance. This ensures that the system can provide reliable and accurate information to the driver, enhancing overall road safety.The display technology serves as the primary interface between the AI system and the driver, providing real-time, clear, and actionable information. The use of Liquid Crystal Display (LCD) technology ensures that the driver receives clear and accurate information, even in varying lighting conditions. The backlit display offers high resolution and color accuracy, making it suitable for automotive applications. The reliability and cost-effectiveness of LCD technology make it a popular choice for automotive displays.Organic Light Emitting Diode (OLED) technology features self-emissive pixels for individual control, enabling true blacks and high contrast ratios. OLED displays are thinner and lighter than traditional LCDs, reducing the overall weight of the display system. Known for their vibrant colors and wide viewing angles, OLED displays ensure that the information is clearly visible from different perspectives. This makes OLED technology a suitable choice for automotive displays, enhancing the overall user experience.Thin-Film Transistor Liquid Crystal Display (TFT-LCD) technology utilizes thin-film transistor technology for improved image quality and faster response times. The balance between performance and cost makes TFT-LCD technology a popular choice for automotive displays. TFT-LCD displays are known for their durability and consistent performance, even under demanding conditions. This ensures that the display can provide reliable and actionable information to the driver, enhancing overall road safety.
Both the camera and display technologies are seamlessly integrated into the vehicle's existing systems. The AI-powered system processes data in real time, providing immediate feedback and alerts to the driver. This ensures that the driver can receive and act upon the information provided by the system, enhancing overall road safety. The interactive screen is designed to be user-friendly, allowing drivers to easily interpret and act upon the information provided. This ensures that the system can provide reliable and actionable information to the driver, enhancing overall road safety.By accurately detecting and displaying potholes, the AI-powered system helps drivers avoid potential hazards, contributing to overall road safety. The data collected by the system can also be used for road maintenance planning, identifying areas that need repair. This ensures that road maintenance can be carried out efficiently, enhancing overall road safety. The system acts as an additional layer of assistance, helping drivers navigate challenging road conditions with greater confidence.The robustness of the camera technology lies in its high-resolution imaging and depth perception capabilities. High-resolution imaging is crucial for detailed color representation, making it suitable for general-purpose computer vision applications. This feature ensures that the camera can accurately capture the visual data required for effective pothole detection. The compact design of the RGB camera allows for easy integration into vehicles, without compromising on the quality of the visual data captured. The ability of the camera to operate under a wide range of lighting conditions ensures that the system can function reliably, regardless of the time of day or weather conditions.The depth camera provides depth information for each pixel, which is essential for distance estimation and assessing the proximity of road anomalies. This capability is crucial for accurate pothole detection, as it allows the system to create a 3D map of the environment. The depth camera can operate in various lighting conditions, including low-light environments, making it versatile and effective in different scenarios. The ability to create a 3D map of the environment helps in accurately identifying and measuring potholes, ensuring that the system can provide reliable and actionable information to the driver.
Precise calibration and alignment of the camera are essential to ensure accurate distance estimations and reliable detection. Calibration processes are implemented to account for factors such as the vehicle’s speed, position, and orientation. This ensures that the system can maintain the accuracy of its output, regardless of the vehicle’s movements. Calibration processes are tailored to the specific vehicle, including adjusting the camera's positioning and alignment to ensure optimal performance. This ensures that the system can provide reliable and accurate information to the driver, enhancing overall road safety.The display technology serves as the primary interface between the AI system and the driver, providing real-time, clear, and actionable information. The use of Liquid Crystal Display (LCD) technology ensures that the driver receives clear and accurate information, even in varying lighting conditions. The backlit display offers high resolution and color accuracy, making it suitable for automotive applications. The reliability and cost-effectiveness of LCD technology make it a popular choice for automotive displays.Organic Light Emitting Diode (OLED) technology features self-emissive pixels for individual control, enabling true blacks and high contrast ratios. OLED displays are thinner and lighter than traditional LCDs, reducing the overall weight of the display system. Known for their vibrant colors and wide viewing angles, OLED displays ensure that the information is clearly visible from different perspectives. This makes OLED technology a suitable choice for automotive displays, enhancing the overalluser experience.
Advantages of the proposed model,
Enhanced Road Safety which is providing real-time alerts about potholes directly to the driver, the invention contributes to enhanced road safety. Drivers are promptly informed of potential hazards, allowing them to take preventive actions and navigate road conditions more safely.Early Warning Invention acts as an early warning invention, alerting drivers to potholes up to 10 to 20 meters ahead. This advanced warning allows drivers to react promptly, reducing the likelihood of vehicle damage and improving overall road safety. Reduced Vehicle Maintenance Costs-By alerting drivers to the presence of potholes, the invention helps reduce wear and tear on vehicles. Drivers can avoid potholes or adjust their driving behaviour, leading to lower maintenance costs associated with suspension and tire damage. Minimized Impact on Infrastructure is proactively addressing potholes can contribute to minimizing the impact on road infrastructure. Early detection allows for timely repairs and maintenance, helping to extend the lifespan of roads and reduce overall infrastructure maintenance costs.Improved Driver Awareness which is displayed in cars provides a visual representation of detected potholes, including their location and estimated distance. This enhances driver awareness and ensures that critical information is easily accessible within the driver's line of sight. Customizable Alert’s the invention may include customizable settings for alerts, allowing drivers to tailor the invention to their preferences. This flexibility enhances user experience and ensures that the invention accommodates individual driving habits and preferences. Contribution to Smart Transportation-the proposed model aligns with the concept of smart transportation by leveraging AI for real-time monitoring and data-driven decision-making. This contributes to the development of intelligent inventions that enhance the overall efficiency and safety of transportation networks.
6 claims and 2 figures. , Claims:The scope of the invention is defined by the following claims:

Claims:
1. Ai-powered pathole detection—navigating the future comprising,
a) A RGB camera and front’s side display.
b) The system uses object detection and estimate the depth of pathole upto 10 to 20 meters.
c) The system follows the Real-time alerts as it ensuring timely awarness.
d) The system receives warnings about patholes up to 10 to 20 meters ahead which allows to react proactively for a safe navigation.
2. According to claim 1, easy and clear to understand display showing detected pathole especially on hill side road.
3. As per claim 1, reduces maintenance costs, avoiding potential vehicle damage associated with patholes.
4. According to claim 1, empowers drivers with proactive information to navigate roads safely and avoid potential hazards.
5. As per claim 1, adapts to various conditions, ensuring reliable performance in different environments.
6. According to claim 1, deep learning algorithms more frequently can detect patholes and estimate the depth of it.