POTHOLE DETECTION SYSTEM

Abstract

ABSTRACT The present invention discloses pothole detection system that overcomes the limitations of prior art by combining multi-sensor fusion, AI-driven analysis, real-time crowd-sourced data, and edge computing. The system utilizes various sensors to collect comprehensive road condition data, which is then processed by AI algorithms for accurate pothole identification and assessment. Real-time data from connected vehicles further enhances the system's accuracy and responsiveness. By leveraging edge computing, the system enables real-time alerts and potential integration with vehicle control systems for improved safety. Predictive modeling capabilities allow for proactive maintenance by anticipating pothole formation. This comprehensive approach results in a more accurate, timely, scalable, and proactive pothole detection system, contributing to enhanced road safety and efficient infrastructure management.

Specification

Description:POTHOLE DETECTION SYSTEM

Field of Invention
The present invention relates to the pothole detection. More particularly, a multi-sensor fusion and AI-driven system for real-time pothole detection and road condition assessment.

Background of the Invention
Potholes are a major safety hazard on roads. They can cause damage to vehicles, lead to accidents, and even injure or kill people. Traditional methods of pothole detection, such as manual inspection and visual surveys, are time-consuming and labor-intensive. They can also be inaccurate, especially in large or remote areas. There are certain prior arts that discusses about pothole detection.
Ryu, S. K., Kim, T., & Kim, Y. R. (2015). Image-Based Pothole Detection System for ITS Service and Road Management System. Mathematical Problems in Engineering, 2015(1), 968361.
Kim, T., & Ryu, S. K. (2014). Review and analysis of pothole detection methods. Journal of Emerging Trends in Computing and Information Sciences, 5(8), 603-608.
Wang, H. W., Chen, C. H., Cheng, D. Y., Lin, C. H., & Lo, C. C. (2015). A Real-Time Pothole Detection Approach for Intelligent Transportation System. Mathematical Problems in Engineering, 2015(1), 869627.
Kang, B. H., & Choi, S. I. (2017, July). Pothole detection system using 2D LiDAR and camera. In 2017 ninth international conference on ubiquitous and future networks (ICUFN) (pp. 744-746). IEEE.
Rode, S. S., Vijay, S., Goyal, P., Kulkarni, P., & Arya, K. (2009, February). Pothole detection and warning system: infrastructure support and system design. In 2009 International Conference on electronic computer technology (pp. 286-290). IEEE.
US9626763B1 - Pothole detection;
KR20200007165A - Pot-hole detection system using vision sensor mounted on unmanned air vehicle, and method for the same;
DE102014214729A1 - Pothole detection in the vehicle;
The primary issue in prior art pothole detection patents and applications is their limited ability to provide accurate, real-time, scalable solutions. Many existing systems face challenges:
• Inaccurate detection: Reliance on single sensor types or limited data analysis can lead to false positives and negatives, hindering effective road maintenance. • Delayed response: Post-processing data or reliance on manual reporting can cause delays in identifying and addressing potholes, increasing drivers' risks.
• Limited coverage: Some solutions focus on specific areas or individual vehicles, making it challenging to monitor large road networks efficiently.
• Lack of predictive capability: Most prior-art systems focus on reactive detection rather than proactively predicting pothole formation to enable preventative maintenance.
The current technologies and products in the market offer solutions to the pothole detection problem but are limited in accuracy, real-time capability, scalability, and proactive prediction.
The present invention addresses the drawbacks and deficiencies of existing pothole detection solutions by employing a multi-faceted approach.

Objectives of the Invention
The prime objective of the present invention is to provide a pothole detection system that has multi-sensor fusion and AI-driven system for real-time pothole detection and road condition assessment.
Another object of this invention is to provide the pothole detection system where multi-sensor fusion overcomes the limitations of single-sensor systems by combining data from various sources, improving accuracy and reliability in diverse conditions.
Another objective of the present invention is to provide the pothole detection system where the AI-driven analysis further enhances detection by learning from vast datasets and adapting to changing road conditions.
Another objective of the present invention is to provide the pothole detection system where the Real-time crowd-sourced data integration offers a dynamic and up-to-date picture of road conditions, enabling faster response to emerging potholes.
Another objective of the present invention is to provide the pothole detection system where the Edge computing and 5G connectivity facilitate rapid data processing and decision making, allowing for real-time alerts and potentially even proactive vehicle control adjustments.
Another objective of the present invention is to provide the pothole detection system where the predictive models leveraging historical and environmental data offer the potential for preventative maintenance, reducing the occurrence of potholes altogether.
Yet another object of this invention is to provide the pothole detection system that is more accurate, timely, scalable, and proactive, ultimately improving road safety and maintenance efficiency.
These and other objects of the present invention will be apparent from the drawings and descriptions herein. Every object of the invention is attained by at least one embodiment of the present invention.

Summary of the Invention
In one aspect of the present invention provides a pothole detection system that addresses the limitations of existing solutions by combining multi-sensor fusion, AI-driven analysis, real-time crowdsourced data, and edge computing.

In one of the aspects, in the present invention, the system utilizes data from various sensors and GPS to comprehensively understand road conditions, the AI algorithms process this data to identify and assess potholes, even in challenging environments, accurately, Real-time data from connected vehicles further enhances the system's accuracy and responsiveness; by leveraging edge computing and 5G connectivity, the system enables real-time pothole detection and alerts, allowing for immediate action by drivers and road maintenance authorities.

In one of the aspects, the present invention incorporates predictive modeling capabilities, analyzing historical data and environmental factors to anticipate pothole formation and facilitate proactive maintenance, this results in a more accurate, reliable, scalable, and proactive pothole detection system, ultimately improving road safety and efficiency.

Brief Description of Drawings
The drawings described herein are for illustrative purposes only of selected embodiments and not all possible implementations, and are not intended to limit the scope of the present disclosure. Further objectives and advantages of this invention will be more apparent from the ensuing description when read in conjunction with the accompanying drawing and wherein:
Figure 1 illustrates the flow diagram according to an embodiment of the present invention.
Figure 2 illustrates the working diagram according to an embodiment of the present invention.


DETAIL DESCRIPTION OF INVENTION
Unless the context requires otherwise, throughout the specification which follow, the word "comprise" and variations thereof, such as, "comprises" and "comprising" are to be construed in an open, inclusive sense that is as "including, but not limited to".
In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. It should also be noted that the term "or" is generally employed in its sense including "and/or" unless the content clearly dictates otherwise.
The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
The headings and abstract of the invention provided herein are for convenience only and do not interpret the scope or meaning of the embodiments. Reference will now be made in detail to the exemplary embodiments of the present invention.
The present invention discloses a pothole detection system that incorporates predictive modeling capabilities, analyzing historical data and environmental factors to anticipate pothole formation and facilitate proactive maintenance.
In describing the preferred embodiment of the present invention, reference will be made herein to like numerals refer to like features of the invention.
According to preferred embodiment of the invention, referring to Figure 1, the pothole detection system comprises the steps of: Data Collection Components, Processing and Analysis Components, Pothole Detection and Assessment, Integration and Mapping, Predictive Modeling, Proactive Maintenance, and Vehicle Control Systems.
According to another embodiment of the invention, in the pothole detection system:
• the Data Collection Components comprises of vehicle sensors such as cameras (images from cameras), LiDAR (3D Point Clouds), accelerometers (acceleration measurements), and GPS (GPS coordinates); and roadside sensors such as cameras, LiDAR.
• The processing and analysis components comprise of edge computing unit and AI algorithms for analysis.
• Pothole detection and assessment performs pothole identification & assessment.
• Integration and Mapping comprises of crowd-sourced data integration and dynamic map of road conditions.
• Predictive Modeling comprises of predictive model such as historical data, weather patterns, traffic flow.
• Proactive Maintenance includes proactive maintenance system;
• And Vehicle Control Systems comprises of automatic adjustments to suspension and autonomous avoidance maneuvers.
According to another embodiment of the invention, referring to Figure 2, the pothole detection system works in the following manner:
• the pothole detection system collects data from multiple sensors mounted on vehicles or roadside infrastructure;
• this data, which might include images from cameras, 3D points clouds from LiDAR, acceleration measurements, and GPS coordinates, is then processed in real time using an edge computing unit equipped with specialized AI algorithms;
• these algorithms analyse the sensor data to identify and assess potholes, distinguishing them from other road features like cracks or manhole covers;
• Simultaneously, the system integrates crowdsourced data from different connected vehicles, creating a dynamic map of road conditions
• From the road conditions, the pothole identification and assessment are performed; or the pothole identification and assessment is performed directly through AI algorithm;
• The pothole detection system utilizes predictive models to anticipate pothole formation based on historical data, weather patterns, and traffic flow; this allows for proactive maintenance, potentially preventing potholes from forming in the first place;
• vehicle control system performs the automatic adjustments to suspension or even autonomous avoidance manoeuvres when a pothole is detected.
According to another embodiment of the invention, the pothole detection system involves a combination of these features, leveraging multi-sensor fusion, AI-driven analysis, real-time crowd-sourced data, edge computing, and predictive modeling to achieve the highest accuracy, responsiveness, and proactivity level. The specific implementation might vary depending on the available infrastructure and target applications, but the core principles of the invention remain consistent across different embodiments.
According to another embodiment of the invention, the pothole detection system is having industrial use/application in the smart city infrastructure management.

According to another embodiment of the invention, the pothole detection system is having following advantages over prior arts:
• Multi-Sensor Fusion: The system uniquely combines data from various sensors (cameras, LiDAR, accelerometers, GPS, etc.) to create a comprehensive and accurate understanding of road conditions. It overcomes the limitations of single-sensor systems, which are prone to inaccuracies and false detections.
• AI-Driven Analysis: The utilization of advanced AI algorithms, including machine learning and predictive modeling, allows for real-time pothole detection, assessment, and even prediction of pothole formation, exceeding the capabilities of traditional image processing or rule-based systems.
• Real-Time Crowd-Sourced Data Integration: The seamless incorporation of data from connected vehicles provides a dynamic and up-to-date picture of road conditions, surpassing static or delayed information from manual inspections or limited user reporting.
• Edge Computing and 5G Connectivity: The system enables real-time decision-making and alerts by processing data and running AI algorithms directly on vehicles or roadside units, overcoming cloud-based solutions' latency and bandwidth limitations.
• Potential Integration with Vehicle Control Systems: Connecting the pothole detection system with vehicle suspension or autonomous driving systems offers a unique safety and comfort enhancement beyond mere detection and reporting.
• Predictive Pothole Detection: Predicting pothole formation using historical data, weather patterns, and traffic flow represents a proactive approach to road maintenance, distinguishing the present system from reactive detection systems.

Although a preferred embodiment of the invention has been illustrated and described, it will at once be apparent to those skilled in the art that the invention includes advantages and features over and beyond the specific illustrated construction. Accordingly it is intended that the scope of the invention be limited solely by the scope of the hereinafter appended claims, and not by the foregoing specification, when interpreted in light of the relevant prior art.
, Claims:We Claim;
1. A pothole detection system comprises the steps of: data collection components, processing and analysis components, pothole detection and assessment, integration and mapping, predictive modeling, proactive maintenance, and vehicle control systems wherein the system incorporates predictive modeling capabilities, analysing historical data and environmental factors to anticipate pothole formation and facilitate proactive maintenance, and vehicle control systems.
2. The pothole detection system as claimed in claim 1, wherein
• the data collection components comprise of vehicle sensors and roadside sensors.
• the processing and analysis components are the edge computing unit and ai algorithms for analysis;
• the pothole detection and assessment perform pothole identification & assessment;
• the integration and mapping comprise of crowd-sourced data integration and dynamic map of road conditions;
• the predictive modeling comprises of predictive model;
• the proactive maintenance includes proactive maintenance system;
• and the vehicle control systems comprises of automatic adjustments to suspension and autonomous avoidance maneuvers.
3. The pothole detection system as claimed in claim 1, wherein the system works in the following manner:
• the system collects data from multiple sensors mounted on vehicles or roadside infrastructure;
• this data, which might include images from cameras, 3D points clouds from LiDAR, acceleration measurements, and GPS coordinates, is then processed in real time using an edge computing unit equipped with specialized AI algorithms;
• these algorithms analyse the sensor data to identify and assess potholes, distinguishing them from other road features like cracks or manhole covers;
• Simultaneously, the system integrates crowdsourced data from different connected vehicles, creating a dynamic map of road conditions;
• From the road conditions, the pothole identification and assessment are performed; or it is performed directly through AI algorithm;
• The system then utilizes predictive models to anticipate pothole formation based on historical data, weather patterns, and traffic flow; this allows for proactive maintenance, potentially preventing potholes from forming in the first place;
• The vehicle control system performs the automatic adjustments to suspension or even autonomous avoidance manoeuvres when a pothole is detected.

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