Description:FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
The Patent Rules, 2003
COMPLETE SPECIFICATION
(See sections 10 & rule 13)
1. TITLE OF THE INVENTION
A MULTI-FUNCTIONAL INTELLIGENT ROAD ASSET MONITORING AND ASSESSMENT SYSTEM AND METHOD WITH INTEGRATED INTERNET OF THINGS (IoT)
2. APPLICANT (S)
NAME NATIONALITY ADDRESS
DIVYASAMPARK IHUB ROORKEE FOR DEVICES MATERIALS AND TECHNOLOGY FOUNDATION IN Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India.
3. PREAMBLE TO THE DESCRIPTION
COMPLETE SPECIFICATION

The following specification particularly describes the invention and the manner in which it is to be performed.

FIELD OF INVENTION:
[001] The present invention relates to the field of system for roadway monitoring and maintenance. The present invention in particular relates to a multi-functional intelligent road asset monitoring and assessment system and method with integrated Internet of Things (IoT).
DESCRIPTION OF THE RELATED ART:
[002] Highway assets refer to highway infrastructure assets formed through construction and are an important part of the total assets of the national economy.
[003] With the development of the economy, my country's transportation infrastructure construction has steadily improved, and the total mileage of the national comprehensive transportation network has exceeded 6 million kilometers.
[004] For such a huge transportation network, how to carry out scientific and effective management to ensure the normal operation of highway infrastructure, thereby extending the service life of highway infrastructure, promoting rural development and revitalization, and reducing the maintenance cost of highway infrastructure is a technical problem that needs to be solved urgently.
[005] Publication No. IN202011011938 relates to a method and system for detecting road anomalies is disclosed which determines the road anomalies by analyzing the video of the road taken through the data capturing unit mounted on vehicles. The data capturing unit is configured to capture the video of the entire road through a wide angle and G Sensor based camera and corresponding GPS coordinates through a GPS logger. The data captured is stored in local memory and later transferred to the processing unit. The Al-based central server is configured to identify various road conditions based on different parameters. The method and system classify the quality of roads as good, bad, or worse and determine the right speed to cross the road anomaly based on recent driver experience. The system is configured to provide key insights about the road condition to the road authorities as well as the subscribed drivers and insurance companies.
[006] Publication No. IN202021056584 relates to an AI-based rapid road condition monitoring system, said system comprising at least one data acquisition unit consisting of at least one portable LiDAR sensor configured to acquire three-dimensional information about the road surface, at least one scanning mechanism deployed on a vehicle based on a rotating polygonal mirror approach configured to acquire high-density data about the road surface conditions along length and width of the road surface and enable point cloud formation in a linear form wherein the system comprises an embedded high-performance computing (HPC) based processing unit integration with the data acquisition unit for rapid acquisition and real-time processing of data and a deep learning-based model integrated with the system for detecting road conditions in real-time.
[007] Publication No. US2024247944 relates to various systems and methods are presented regarding assisting an autonomous vehicle (AV) navigating a road when the road includes one or more road conditions that may be deleterious to the mechanical structure of the AV, operation of the AV, and suchlike. The deleterious road conditions can include a pothole, road debris, a speed bump, etc. Operation of a vehicle driving ahead of the AV can be monitored. The other vehicle may cause a pothole to be occluded from view by sensors onboard the AV, hence by monitoring operation of the other vehicle, e.g., maneuvering around/driving through a pothole, the AV can assess a size/location of the pothole and determine an action such as maneuver, slow down, change lanes, etc. The pothole location can be reported by the AV to enable other drivers and AVs to be aware of the pothole.
[008] Patent No. US11481991 relates to system and methods for automated incident identification and reporting while operating a vehicle on the road using a device. The device identifies incidents using artificial intelligence neural networks trained to detect, classify, segment, and/or extract other information pertaining to objects of interest representing incidents. Additionally, a system and method for further storing, transmitting, processing, organizing and accessing the information graphically with respect to incident type, location, date and time during operation.
[009] Existing technologies in this domain typically focus on specific aspects of road condition assessment, such as pothole detection or traffic sign monitoring, often relying on standalone systems that lack real-time processing capabilities and do not perform edge analysis. For instance, some systems rely on post-processing video footage or use resource-heavy technologies like LiDAR, making them less efficient for diverse road monitoring scenarios and requiring centralized computing power. These solutions are often limited in their scope, focusing on either road surface anomalies or specific conditions, without considering the broader road infrastructure or integrating multiple data sources in real time.
[010] Additionally, many existing systems are designed for dedicated vehicles, making them impractical for widespread deployment or continuous monitoring. They also lack the flexibility to incorporate additional infrastructure elements such as trees, wildlife crossings, or other roadside assets, which are crucial for comprehensive road safety and urban planning. As a result, these systems are unable to provide holistic and timely insights during active surveys.
[011] To address these limitations, the present invention offers a multi-functional intelligent road asset monitoring and assessment system, which integrates Internet of Things (IoT) capabilities with a real-time, edge-based processing framework. This system incorporates multiple sensors (cameras, accelerometers, gyroscopes, and GPS) to detect a wide range of road and infrastructure anomalies while providing real-time alerts and data transmission. The modular design also allows for customization and expansion, making it more adaptable and efficient for road asset monitoring compared to existing technologies.
OBJECTS OF THE INVENTION:
[012] The principal object of the present invention is to provide a multi-functional intelligent road asset monitoring and assessment system and method with integrated Internet of Things (IoT).
[013] Another object of the present invention is to provide a comprehensive, timely, and efficient solution for road condition monitoring.
[014] Yet another object of the present invention is to instant data processing and alerts directly from the edge device, reducing response times significantly compared to systems with centralized processing.
[015] Still another object of the present invention is to provide a cost effective and modular system that allows customization to specific needs and various vehicle types, increasing adaptability.
[016] Yet another object of the present invention is to provide an intelligent road asset monitoring and assessment system which detects diverse road anomalies and hazards, improving overall road safety.
SUMMARY OF THE INVENTION:
[017] The present invention relates to a multi-functional intelligent road asset monitoring and assessment system and method with integrated Internet of Things (IoT). The system integrates multiple data sources like cameras, sensors, and GPS for thorough road condition analyses. It is a modular system that allows customization to specific needs and various vehicle types, increasing adaptability.
[018] The system operates seamlessly without disrupting the vehicle's primary functions, enabling dynamic and continuous monitoring of road conditions. It leverages a sophisticated array of multiple camera types alongside diverse sensors such as accelerometers, gyroscopes, and ignition sensors. This robust setup allows it to detect a wide array of conditions, from potholes and cracks to faded markings, broken crash barriers, deteriorated guardrails and more.
[019] Furthermore, the present system edge computing framework facilitates immediate on-device data processing, significantly reducing latency and enhancing system responsiveness. This capability is complemented by cloud-based data analysis, which enables deeper analytical insights and historical data tracking, thereby boosting the system’s predictive maintenance capabilities. The comprehensive sensor integration and image processing technology in the present system not only enables the detection of road anomalies but also facilitates the identification of stray or wild animals and the monitoring of roadside trees. This capability ensures that the present system can comprehensively manage and respond to a variety of scenarios that affect road safety.
[020] The invention includes edge computing with real-time, multi-modal road condition monitoring capabilities, which significantly advances beyond the capabilities of traditional monitoring systems. Unlike existing technologies that often rely on manual data interpretation or suffer from processing delays, the invention processes data instantaneously on the edge device. This capability allows for immediate identification of and response to various road conditions directly from the device, eliminating the need for back-end server reliance.
BREIF DESCRIPTION OF THE INVENTION
[021] It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered for limiting of its scope, for the invention may admit to other equally effective embodiments.
[022] FIG. 1 shows the overall system architecture, according to the present invention.
[023] FIG. 2A shows the camera selection interface of the device.
[024] FIG. 2B compliments FIG. 2A by showing the specific types of cameras used, including Infrared, Stereo, Standard RGB, and Night Vision cameras, and how they can be selected based on the operational mode set in FIG. 2A.
[025] FIG. 3 shows the GPS module's connectivity options.
[026] FIG. 4 shows the various display options available for the device.
[027] FIG. 5 shows the power setup for the device.
[028] FIG. 6 shows the Alarm/Speaker/Indicator System.
[029] FIG. 7 shows the integration of various sensors.
[030] FIG. 8 shows the internet connectivity options for the device.
[031] FIG. 9 shows the JSON data structure used in the communication from the device to the server/API.
[032] FIG. 10 shows the data visualization capabilities accessible via the cloud and server infrastructure.
DETAILED DESCRIPTION OF THE INVENTION:
[033] The present invention provides a system and method for continuous, real-time monitoring of road conditions, enabling immediate detection of and response to various road anomalies but not limited to potholes, cracks, and faded road markings. It automates the update process of a database with detailed information on detected anomalies, complete with timestamps and GPS locations. The system includes a hybrid power system, utilizing vehicle power efficiently to ensure continuous operation without frequent battery replacements or charges. It gives authorities and other relevant parties access to the road condition database, supporting better planning and decision-making for road maintenance and safety initiatives.
[034] The present invention reduces the need for manual surveys and frequent maintenance checks, thereby lowering costs associated with road maintenance and labor. Additionally, unlike current survey vehicles which are costly, our device is significantly more affordable, offering a cost-effective alternative for comprehensive road monitoring. It ensures timely maintenance and swift response to road anomalies, helping to extend the lifespan of road infrastructure.
[035] The integration of IoT, image processing, and edge computing technologies makes this invention a robust solution for real-time road monitoring, capable of delivering detailed, actionable insights to road maintenance teams and authorities, thereby improving road safety and infrastructure management.
[036] FIG. 1 illustrates the complete architecture of the road condition detection system 1, which comprises a controller 100. The figure illustrates how these components interact with the GSM/WiFi module, which then connects to the API, Cloud, and Server infrastructure for data processing and storage. The controller 100 acts as the central processing unit, coordinating inputs and outputs from various integrated components essential for the system's operation. These components include a camera 200, for capturing real-time visual data of the roads, a GPS module 300, that provides precise geolocation data, and a screen display 400, which serves as the user interface for data visualization and system monitoring.
[037] The system also incorporates a power setup 500 that manages power distribution to ensure continuous operation, and an alarm/speaker 600 which alerts operators or drivers to real-time road conditions or system statuses. Additionally, various sensors 700, such as accelerometers and gyroscopes, are connected to the controller 100 to gather comprehensive data on road conditions. Connectivity with external networks is facilitated by a GSM or WiFi module 800, enabling the system to communicate with cloud servers.
[038] Data collected from these components is processed by the controller 100, formatted in JSON 900, and transmitted via an API to cloud servers 1000 where further analysis and storage take place. This structured setup allows the system to effectively monitor and analyze road conditions, supporting dynamic responses to road anomalies and enhancing overall road safety and infrastructure management. The integrated approach of these components ensures that the system operates efficiently, maintaining high accuracy and responsiveness essential for modern road condition monitoring applications.
[039] Further classification and detailed descriptions of each system component and their specific functionalities, such as the various cameras, modes of selection for detection surveys, connections for different types of GPS, display options, vehicle power options, the functioning of alarm/speaker and indicators, sensors, WiFi/GSM connectivity, the format of JSON data, and data representation, will be comprehensively outlined in subsequent figures. These sections will delve into the technical specifics and the operational intricacies of the components, providing a thorough insight into the sophisticated technology and innovative applications of the invention.
[040] FIG. 2A illustrates the adaptable camera 200 selection and mode operation system 2, a crucial component in customizing the road condition detection system to meet a variety of monitoring requirements. A range of operational modes 210 that can be dynamically configured before the commencement of a survey, tailored to evolving needs and insights derived from trained models. This adaptability allows the system to effectively customize its functionality for different road conditions and monitoring scenarios, including but not limited to signboards (2201) and potholes (2202) as referenced in system 220.
[041] The system offers various operational modes, labeled from Mode0 (2101) to Mode3 (2104), tailored to monitor different road conditions effectively. These modes are capable of detecting a diverse array of road and environmental anomalies including potholes, signboards, speed breakers, cracks, foot over bridges, faded road markings, blurred crosswalks, guard rails, and environmental elements like trees and wildlife. The flexibility of mode selection ensures that monitoring can be customized to current needs and optimized based on the latest insights from continuously updated and trained models, enhancing the system's overall efficacy in real-time road condition assessment.
[042] FIG. 2B illustrates the Camera 200 selection, detailed in 21 in section 230, similarly showcases flexibility. The system includes multiple camera options such as Camera0 (2001) to Camera3 (2004), each capable of being utilized across various modes. The selection of cameras—ranging from infrared cameras (2301) for low-light conditions, stereo cameras (2302) for depth sensing, Standard RGB Cameras (2303) for general use, to night vision cameras (2304) for night-time monitoring—is not rigidly prescribed. Instead, any camera type may be chosen based on its suitability for the specific conditions and tasks at hand, as recommended by the analysis capabilities of the system's models.
[043] FIG. 3 depicts system 3 for GPS module 300 connectivity configurations within the road condition detection system. This figure illustrates the available communication methods that can be used to connect the GPS module 300 to the controller 100, as outlined in section 310. The system supports two primary types of communication interfaces: UART/Serial Communication 3101 and I2C Communication 3102. These options provide flexibility in how the GPS module 300 interfaces with the controller 100, allowing for a tailored setup based on specific system requirements or constraints.
[044] The GPS module 300 can be connected to the controller 100 through a USB port using USB 320, enabling easy and flexible integration. Alternatively, the GPS module 300 may be directly connected to specified pins within the controller 100, providing a more fixed and potentially robust connection for environments that demand higher reliability and resistance to physical disruptions.
[045] Section 330 outlines the power supply 3301 and options available for the GPS module 300, ensuring flexible and reliable operation within the road condition detection system. Power may be supplied either through a 5-12V external battery or directly from the vehicle's power system 33011. This is particularly advantageous for systems integrated into vehicle operations that demand a stable and dependable power source. As well, the GPS module 300 can draw power 3301 directly from the controller 100, referred to as power from the device 33012. This integrated power setup reduces the complexity of external wiring and connections, simplifying installation and maintenance while enhancing system reliability.
[046] This configuration ensures that the GPS module 300 is properly powered and connected, allowing it to reliably perform its function of providing geographic location data to the system. The choice of power source and communication method can be adapted based on the installation environment and specific operational needs, enhancing the system’s overall adaptability and efficiency in real-time road condition monitoring.
[047] FIG. 4 details system 4, which presents the available display 400, options for the road condition detection system, emphasizing adaptability to suit diverse operational requirements and user preferences. The system features an external display 4001, typically used for temporary setups such as during system configuration, troubleshooting, or maintenance. This option is particularly valuable for intricate troubleshooting processes where a larger screen can provide a clearer view of the system's diagnostics and detailed feedback.
[048] The system also includes a vehicle-installed display 4002, which is permanently integrated within a vehicle, strategically placed for easy accessibility and constant visibility. This display is crucial for offering real-time feedback and system status updates to the vehicle operator, facilitating prompt reactions to detected road conditions or system notifications.
[049] Furthermore, the inbuilt display 4003, is an integral part of the device, providing a compact and seamless user interface. It blends effortlessly with the device's architecture, enhancing the overall aesthetic and functional coherence.
[050] All display options mentioned—external, vehicle-installed, and inbuilt—may feature touchscreen capabilities, underscoring the system's commitment to accessibility and ease of use. This universality in touchscreen functionality across all display types significantly enhances user interaction, allowing intuitive control and efficient navigation through the system’s features. Operators can easily adjust settings, respond to alerts, and navigate through data with simple touch gestures. This flexibility ensures that regardless of the chosen display type, the user experience remains consistent and highly responsive, facilitating effective management of the road condition detection system.
[051] Power configurations for these displays mirror the adaptable setups used for other system components. Displays can draw power 330, through 320 from the controller 100, directly from the device, or through dedicated connections to specified pins on the controller. This flexible power arrangement ensures that the displays are not only versatile in their application but also in their installation and power requirements, making the system adaptable to a wide range of operational environments.
[052] FIG. 5 illustrates system 5, which details the power supply configuration for the device, designed to ensure reliable and continuous operation of the controller 100 and other connected components. This system provides diverse power supply options tailored to different operational environments to enhance system reliability.
[053] The primary power supply to the controller 100 is delivered directly via path 501 from section 500, ensuring stable and uninterrupted power flow. Additionally, the system is equipped with a UPS module integrated with a battery (510), serving as a vital backup power source. This module is essential for maintaining system operations during power interruptions or when primary power sources are temporarily unavailable.
[054] Section 500 details the primary power input options for the system. The vehicle battery (5001) supplies power directly from the vehicle’s own battery, providing a robust and dependable energy source particularly suitable for systems integrated into vehicle operations. Alternatively, power can be sourced from the vehicle's general power supply system (5002), which may include regulated outputs designed to accommodate additional electronic devices.
[055] The Battery and UPS Module (510) within system 5 plays a crucial dual role. It functions not only as a charging unit but also as a direct power source to the device via path 502. This arrangement ensures that the device can continuously operate by drawing power directly from the main power inputs in section 500. If the power from section 500 proves insufficient or becomes completely unavailable, the device automatically switches to draw power from the Battery and UPS Module (510). This seamless transition maintains system operation without interruption. Additionally, when the vehicle is operational and the power supply from section 500 is stable and sufficient, the UPS module recharges. This keeps the battery fully charged and ready to provide backup power whenever necessary, ensuring that the system remains operational and effective even in fluctuating power conditions.
[056] This configuration provides flexibility in sourcing and managing power, enhancing the resilience of the system to remain operational under various conditions, whether stationary or mobile. The integration of a UPS is particularly beneficial, as it ensures that critical data is preserved and system functionality is sustained during power disruptions, making this setup ideal for deployment in environments where consistent power supply may be a challenge.
[057] FIG. 6 details the components of system 6, which includes the alarm, speaker, and various indicators, all integral to the functionality of the road condition detection system. This system is not only pivotal for monitoring road conditions but also serves multiple roles, enhancing its utility in various operational contexts.
[058] The speaker (610) is primarily utilized to alert vehicle operators about imminent road hazards detected through the system's sensors or from data processed from the cloud (6000). Beyond its use in regular road surveys, the speaker system can actively function to warn drivers of upcoming potholes or other dangerous road conditions in advance, thereby playing a crucial role in enhancing road safety.
[059] Additionally, the warning indicator (620) provides visual alerts for various system states, including warnings about critical system errors or potential issues such as overheating of the device. This ensures that operators are immediately aware of any conditions that might impact the system’s performance. The battery power indicator (630) displays the current power status of the system’s battery, ensuring that there is always enough power to sustain the system's operations, particularly during extended use in the field. The network connectivity indicator (6403) not only signifies the status of the network connection but also actively blinks to indicate data transmission to the server or cloud 6000. This blinking feature is crucial for operators to know when data is being sent, ensuring continuous and secure data flow, which is essential for real-time monitoring and response.
[060] FIG. 7 showcases system 7, illustrating the integration of various sensors connected to the controller 100. This setup includes an accelerometer 710, gyroscope 720, and ignition sensor 730, each playing a vital role in the overall functionality of the road condition detection system. These sensors are instrumental in capturing precise and dynamic data related to the vehicle's movement and operational status, thereby enhancing the system's responsiveness and reliability.
[061] The accelerometer (710) in the system serves a critical role in monitoring vibrations within the vehicle. By measuring variations in acceleration, this sensor can detect subtle and abrupt changes in the vehicle's movement that typically occur when encountering uneven road surfaces, such as potholes, cracks, and other irregularities. This capability is crucial for assessing the condition of the road and the impact of these conditions on vehicle stability and passenger comfort.
[062] Adjacent to the accelerometer is the gyroscope (720), which complements the accelerometer by measuring the vehicle's rotational motion around its axis. This sensor is essential for detecting changes in orientation and tilt, providing a more comprehensive picture of the vehicle's dynamics during maneuvers. This information helps in assessing the road conditions that might cause such tilts and turns, offering valuable insights into potential road hazards.
[063] The ignition sensor (730) monitors the vehicle's ignition status, providing critical information about the vehicle’s operational state. This sensor ensures that the system is active only when the vehicle is running, which helps in conserving power and focusing monitoring efforts during active vehicle use. It also triggers system startup and shutdown sequences, aligning the road condition detection system’s operation with the vehicle’s use.
[064] Together, these sensors (700) supply the controller (100) with a detailed dataset for real-time analysis of the vehicle's interactions with the road. This data, along with precise location details, is transmitted to a cloud server for further analysis, complementing the anomalies detected by the cameras. This comprehensive monitoring and in-depth analysis of road conditions enhance road safety and efficiency, ensuring the system remains an essential tool in advanced vehicle safety and infrastructure management.
[065] FIG. 8 illustrates system 8, detailing the network connectivity options within the road condition detection system, which are essential for interfacing with servers and facilitating data transmission. This system supports versatile connectivity solutions to ensure reliable communication with cloud-based servers for data analysis and storage.
[066] The system offers two main connectivity options: an inbuilt WiFi/GSM module (801) and a detachable USB dongle (802). The inbuilt WiFi/GSM module is integrated directly into the controller, featuring an external antenna (804) that protrudes from the device to enhance signal reception and transmission quality. This setup provides a permanent and robust network connection, ideal for continuous operation and environments where a fixed connectivity solution is preferable.
[067] Alternatively, the system can utilize a WiFi/GSM dongle (802), which connects to the device via a USB port (803). This dongle option allows for easy installation and replacement, providing flexibility in network connectivity. It is particularly useful in scenarios where network requirements may change, such as switching between different network providers or upgrading to newer technology without altering the core hardware of the device.
[068] These connectivity options ensure that the system can maintain consistent communication with the server, transmitting real-time data for immediate analysis. This capability is crucial for the timely detection and response to road anomalies, enhancing the overall safety and efficiency of road travel. The choice between a fixed inbuilt module and a flexible dongle-based solution gives users the ability to tailor the network setup according to specific needs and operational conditions.
[069] FIG. 9 showcases system 9, which outlines the structured JSON (JavaScript Object Notation) format used to encapsulate and transmit data regarding various road assets and conditions detected by the system. This format is designed to be machine-readable and is optimized for efficient processing and integration with cloud-based systems. The JSON structure includes several key fields that capture comprehensive details about each detected item, whether it's road anomalies, guard rails, railings, signboards, or other relevant road deteriorating assets. The "Device Number" ("deviceno") identifies the specific device capturing the data, essential for managing inputs from multiple sources. The "Type" ("type") field describes the type of object detected, such as "pothole," "guard rail," "railing," "signboard," etc., helping in sorting and prioritizing the data for further analysis. The "Detail" ("detail") field provides initial descriptions of the detected items, which could include basic identifications for anomalies or conditions like "blur," "bent," or "faded" for signboards; these descriptions may be updated with more detailed information following further data processing. The "Timestamp" ("timestamp") logs the exact time when the detection occurred, critical for real-time monitoring and historical data analysis. The "Location" ("location") includes geographic coordinates (latitude and longitude) where the detection was made, crucial for pinpointing issues on a map and planning maintenance or inspection routes. The "Image" ("image") contains a base64 encoded image of the detected item, providing a visual reference that can be used for verification and further analysis. Data can be transmitted in real-time as detections are made to allow for immediate actions, although this might influence system performance due to the continuous data transfer. Alternatively, data may be stored in the device's internal memory and transmitted in batches at predetermined intervals or upon survey completion, reducing network load and optimizing data handling. This JSON data structure not only ensures comprehensive documentation of each detected condition but also facilitates extensive scalability, supporting seamless integration with APIs that push the data to cloud servers, where advanced analytics can be performed. This structured approach ensures that the road condition detection system operates effectively, delivering crucial data for improved road safety and efficient infrastructure management.
[070] FIG. 10 illustrates system 10, detailing the process of fetching, analyzing, and visualizing road condition data from cloud servers (1020) and server systems (1030) via APIs (1010). This system enables comprehensive data analysis, pivotal for crafting targeted action plans based on the gathered information. Data is presented in three primary formats to accommodate different analytical needs and user preferences: Table View (1002), Detailed View (1003), and Map View (1004). Table View (1002) provides a structured presentation of data, allowing users to quickly scan and compare multiple entries at once, ideal for identifying trends or anomalies over large datasets. Detailed View (1003) offers an in-depth analysis of specific incidents or conditions. Map View (1004) integrates geographical data, displaying road conditions and incidents directly on a map interface, which assists in spatial analysis and planning maintenance or emergency response actions based on geographic insights.
[071] Additionally, this system filters data based on parameters such as device number, location, date, and time, tailoring the output to meet the specific requirements of clients or authorities. This filtered data is then available on the data dashboard, customized to display information relevant to particular areas or concerns, enhancing the usability and application of the collected data for effective road management and safety strategies.
[072] The system is engineered to operate fully automatically, activating when the vehicle starts and shutting down upon vehicle cessation. During operation, it conducts surveys and transmits data to a server without manual input, aligning seamlessly with the vehicle's use. This automation ensures efficient power use and data relevance, streamlining road condition monitoring for enhanced maintenance strategies.
[073] In an aspect, the present invention provides a system for detecting animals on highways and integrating this data into wildlife crossing planning, contributing to ecological conservation and reducing vehicle-animal collisions.
[074] In another aspect, the present invention provides a system for monitoring roadside trees, supporting urban and environmental planning by preserving natural habitats. This system systematically collects data on tree populations along roadways, aiding informed decision-making in infrastructure development and ecological conservation.
[075] Numerous modifications and adaptations of the system of the present invention will be apparent to those skilled in the art, and thus it is intended by the appended claims to cover all such modifications and adaptations which fall within the true spirit and scope of this invention.
, Claims:WE CLAIM:
1. A multi-functional intelligent road asset monitoring and assessment system (1) and method with integrated Internet of Things (IoT) comprises-
a) controller 100 as the central processing unit, coordinating inputs and outputs from various integrated components characterized in that camera 200, for capturing real-time visual data of the roads, a GPS module 300, that provides precise geolocation data, and a screen display 400, which serves as the user interface for data visualization and system monitoring.
b) a power setup 500 to manage power distribution to ensure continuous operation.
c) an alarm/speaker 600 which alerts operators or drivers to real-time road conditions or system statuses.
d) sensors 700, characterized in that an accelerometer 710, gyroscope 720, and ignition sensor 730, wherein accelerometer (710) monitors vibrations within the vehicle and detects subtle and abrupt changes in the vehicle's movement due to uneven road surfaces, ; gyroscope (720), measures the vehicle's rotational motion around its axis and ignition sensor (730) monitors the vehicle's ignition status, providing critical information about the vehicle’s operational state and triggers system startup and shutdown sequences, aligning the road condition detection system’s operation with the vehicle’s us wherein these sensors (700) supply the controller (100) with a detailed dataset for real-time analysis of the vehicle's interactions with the road.
e) GSM or WiFi module 800, enables system to communicate with cloud servers and to connect with external networks.
2. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the camera 200 selection and mode operation system 2, meets a variety of monitoring requirements wherein a range of operational modes 210 are dynamically configured
3. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the system includes Camera0 (2001) to Camera3 (2004), being utilized across various modes; Infrared Cameras (2301) for low-light conditions, Stereo Cameras (2302) for depth sensing, Standard RGB Cameras (2303) for general use, to Night Vision Cameras (2304) for night-time monitoring.
4. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the GPS module 300 is connected to the controller 100 through a USB port using USB 320,
5. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the GPS module 300 may be directly connected to specified pins within the controller 100.
6. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the system features an external display 4001, for temporary setups.
7. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the system also includes a vehicle-installed display 4002, which is permanently integrated within a vehicle, placed for easy accessibility and constant visibility.
8. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the inbuilt display 4003, is an integral part of the device, providing a compact and seamless user interface.
9. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the system employs edge computing for initial data capture and processing, selectively transmitting only relevant data pertaining to identified road condition categories to a server.
10. The multi-functional intelligent road asset monitoring and assessment system as claimed in claim 1, wherein the process of fetching, analyzing, and visualizing road condition data from cloud servers (1020) and server systems (1030) via APIs (1010) enabling comprehensive data analysis, pivotal for crafting targeted action plans based on the gathered information and data is presented in three primary formats to accommodate different analytical needs and user preferences of table view (1002), detailed view (1003), and map view (1004) table view (1002) provides a structured presentation of data, allowing users to quickly scan and compare multiple entries at once, ideal for identifying trends or anomalies over large datasets.