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C.A.(COMM.IPD-PAT) 3/2021 AUDERTEC SOLUTIONS LLP ..... Appellant
Through: Ms. Priya Adlakha, Mr. Bindra Rana, Ms. Rima Majumdar, Mr. Dhruv Mathur and Mr. Swaraj Singh Raghuwanshi, Advs.
Through: Mr. Harish Vaidyanathan Shankar, CGSC, Mr. Srish Kumar Mishra, Mr. Sagar Mehlawat and Mr. Alexander Mathai Paikaday, Advs.
JUDGMENT
1. The appellant submitted Application No. 202011011938 dated 19 March 2020 for grant of a patent in respect of an invention titled “a method and system for detecting road anomalies” (hereinafter “the subject patent”). The application stands rejected by the Controller of Patents and Designs (“the Controller”) vide order dated 8 January 2021 passed under Section 15 of the Patents Act, 1970. The appellant is in appeal against the said order.
2. The impugned order rejects the application on the ground that Signing Date:13.03.2024 22:46 the claim in the application suffers from want of inventive step vis-avis prior art D-2. Though the First Examination Report (FER) dated 15 June 2020 cites four prior art documents D-1 to D-4 as disclosing all the features of the claims in the subject patent, the notice of personal hearing, issued consequent to the reply filed by the appellant to the FER, restricted the allegation of lack of inventive step to comparison of the subject patent with the prior art D-1 to D-3 and the final impugned order holds the subject patent to be lacking an inventive step only vis-a-vis the prior art D-2.
3. I may note that this position was accepted by both sides and arguments were also advanced before me, on the aspect of obviousness and inventive subject in the subject patent vis-a-vis the prior art D-2.
4. The Court is only required, therefore, to examine whether the subject patent is lacking an inventive step vis-a-vis D-2; in other words, whether the distinguishing features of the subject patent would be obvious to a person skilled in the art from the disclosures contained in D-2 and, therefore, whether the impugned order is correct in rejecting the appellant’s application on the ground of lack of inventive step.
5. For this, one has to appreciate the essential features of the suit patent, which are claimed, by the appellant, to be inventive.
6. The complete specifications of the suit patent read thus: Signing FORM 2 THE PATENTS ACT, 1970 (39 of 1970) & THE PATENTS RULES, 2003 COMPLETE SPECIFICATION (See section 10 and rule 13)
1. TITLE OF THE INVENTION A METHOD AND SYSTEM FOR DETECTING ROAD ANOMALIES
2. APPLICANT a) AUDERTEC SOLUTIONS LLP; b) Indian; c) SCO 315-316, First Floor, Himalaya Marg, Sector 35B, Chandigarh – 160036, India
3. PREAMBLE TO THE DESCRIPTION The following specification particularly describes the invention and the manner in which it is to be performed.
FIELD OF THE INVENTION [001] The present invention relates to transportation management information system. More particularly, it relates to a system and method to maintain the heavily travelled roadways.
BACKGROUND OF THE INVENTION [002] In the recent years, with exponential increase in traffic on the roads, there is lot of pressure on continuous upkeep and maintenance of the road networks across the cities. Road authorities are losing the continuous battle for upkeep of the road because of frequent weather change, improper drainage, improper or inadequate repair work, improper design of the road, frequent cutting of the roads for laying cables and conduits, heavy traffic or heavy vehicles plying on the roads which are not designed to handle such loads. As a result, road imperfections develop continuously and need to be managed before they become dangerous. Signing [003] Road anomaly may be defined as misalignment in the road surface due to any cut or crack in the road due to cable laying or any pothole due to improper water drainage or some 20 bump or uneven level due to manhole cover which leads to sudden braking or turning of the vehicle as soon as driver tries to negotiate the anomaly or sometimes if the driver is not able to negotiate then it leads sudden jerk in the vehicle. [004] In both the above situations either vehicle damage could happen, or accident can occur due to sudden application of brakes or turning of the vehicle. In some cases, skidding of the vehicle because of sudden braking or turning over has led to fatalities. Hence, it becomes utmost important to continuously monitor the road surface condition for anomaly and make sure that the road condition should not become worse to cause accident or unfit for driving. Also, the roads can be maintained better if the anomalies are detected and fixed in the early stages due to less cost of preventive maintenance as compared to rehabilitation or upgrading or reconstruction of the roads. [005] Further, USA patent US9863928 B[1] discloses a road condition detection system for identifying and monitoring road conditions, and for communicating information regarding road conditions to various users. The road condition detection system is provided for capturing data indicative of road conditions and analyzing the captured data to locate and identify various road conditions (e.g., road hazards, such as potholes, or weather conditions, such as ice). In various embodiments, the road condition detection system includes a road condition sensor array configured for being attached to a vehicle and for capturing road condition data. The captured data may be transmitted and assessed by a server configured for identifying potential road hazards or other road conditions based on the road condition data captured by the sensor array. The prior art discloses a system based on laser and vibration sensors. The system however, does not detect the severity of the road condition. [006] Another USA patent US20180068495A[1] discloses a method of detecting and identifying road surface defects is provided. Motion and position information is received from a plurality of vehicles. A profile is retrieved for a particular vehicle from a database of vehicle profiles by using an identifier of the particular vehicle. One or more criteria are identified for detecting a particular type of road surface defect based on the retrieved profile of the particular vehicle. Upon determining that the received motion and position data satisfies the identified criteria, a Signing detection of a road surface defect of the particular type and a location associated with the detected road surface defect based on the received position information is reported. The prior art discloses method of detecting the road conditions using motion sensors and accelerometer. The method disclosed in prior art is cost intensive as multiple vehicle types and their sensor data has to be correlated based on their weight, tyre size, dimensions etc. [007] Nowadays, various methods and systems are available based on the technologies related to sensors and laser. These methods and systems have limitations due to vibration-based sensors and high costing of laser scanning. Also, the laser sensor is not efficient in wet weather and narrow roads. Due to these limitations there is a need of cost effective method and system for detecting the road anomalies.
OBJECTIVE OF THE INVENTION [008] The primary objective of the present invention is to provide a method and system to give prior warning to the subscribed driver or user for upcoming road issues. [009] Another objective of the present invention is to provide a cost-effective method and system for better surveillance of road condition. [0010] Yet another objective of the present invention is to automate the measurement of road condition. [0011] Yet another objective of present invention is to provide safe driving assistance to its subscribed users. [0012] Another objective of the present invention is to provide a proactive system and a method to report road anomalies regularly. [0013] Yet another objective of the present invention is to provide a method and for periodic tracking of the road conditions which may help in accessing the quality of re-carpeting or patch work done.
SUMMARY OF INVENTION [0014] The present invention proposes a system for tracking the road anomalies through a dashcam mounted on plurality of vehicles. The method and system maps and identifies the road anomalies by analyzing the video of road conditions and classify Signing the road anomalies by earmarking the road anomalies into potholes, bumps, cracks, etc. and rating them into yellow, amber and red colors based on certain parameters like dimensions of anomalies, type of anomaly, type of road on which anomaly has happened(highway, main city road, colony road, service road, etc.), GPS co-ordinates, date time stamp when the anomaly has been reported, changes if any since first time the anomaly has been reported, area to which the location belongs (sector, area, wards, zones, sub-district, tehsil/taluka, etc.).
BRIEF DESCRIPTION OF THE DRAWINGS [0015] A complete understanding of the present invention may be obtained by reference to the accompanying drawings, when taken in conjunction with the detailed description thereof and in which: [0016] Figure 1 illustrates the layout of various components of the system for detecting the road anomalies. [0017] Figures 2(a) and 2(b) illustrates the functioning of data capturing unit for detecting road anomalies. [0018] Figures 3(a), 3(b), 3(c) and 3(d) illustrate the process of classification of road anomalies and mapping of road anomalies on to a web mapping service application. [0019] Figures 4, 5 and 6 illustrates the process of publishing of road anomalies to users.
DETAILED DESCRIPTION OF THE INVENTION [0020] The following presents a simplified description of the invention in order to provide a basic understanding of some aspects of the invention. This description is not an extensive overview of the present invention. It is not intended to identify the key/critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present some concept of the invention in a simplified form. [0021] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the invention. In addition, descriptions of wellknown functions and constructions are omitted for clarity and Signing [0022] Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments. [0023] The terms and words used in the following description and claims are not limited to the bibliographical meanings, but, are merely used to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention. [0024] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. [0025] It should be emphasized that the term “comprises/comprising” when used in this specification is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof. The equations used in the specification are only for computation purpose. [0026] In accordance with the present invention, Fig. 1 shows system for detecting road anomalies. The various components of the system for detecting road anomalies are, data capturing unit (100), data recording unit (200), data processing unit (300), data mapping unit (400) and data publishing unit (500): -Data Capturing and Data Recording Unit (100 and 200) may comprise a High Definition dash board camera mounted on top of a vehicle, which is driven at a speed of 20-30 km/hour at a pre-decided route set by the user. The dashboard camera may be mounted on front or back of the vehicle, pointing towards the road surface to capture video of the road surface. As the vehicle moves, the camera continuously records the road conditions through its lenses, covering a 130degree view. The cameras provide a high definition view of the road surface and simultaneously the GPS data is recorded by the GPS data recording unit (200). Once the survey is done by the camera, the camera Signing footage and GPS log files (.GPX) are downloaded to a central computer to compute the same. – Data Processing Unit (300) may comprise of the central system to process the raw videos and identify and classify the road anomalies based on training dataset of the road anomalies. This process also helps in classifying the severity of the road anomaly data and notifying the road authorities and subscribed drivers in case of potential issues. This process also gets the input of the GPS data like the deceleration in speed at a particular spot or patch of the road. – Data Mapping and Publishing Unit (400 and 500) may comprise the geographical mapping of road anomalies, creation of anomalies database and its updation based on road survey conducted, plotting of the road anomalies on any available web mapping service based on the route selected by the drivers along with the name of the roads featuring distress spots and suggesting alternate route with their anomalies information. Further, the report generates a map plotting the exact spots of road distress with color coding based on severity of road anomalies on the web map and create a heat map to show the concentration of road anomalies in the area or zone. This helps both the road authorities to take necessary actions on preventive maintenance and the subscribed drivers take the conscious decision on choosing the appropriate route. [0027] Fig. 2(a) and 2(b) illustrate the functioning of data capturing unit (100) for detecting the road anomalies. The data capturing unit (100) comprises a dashboard camera (Dashcam), a Global Positioning System (GPS) and a storage device. The Dashcam is a video camera with high definition 1080p, 130 degree viewing angle covering all lanes of the road, Wide Dynamic range (WDR) function which adjusts according to the ambient light, built in G-sensor for image stabilization in case of shock or jerk. The Dash cam may be but not limited to, Akaso dash cam C330. Dashcam records the videos of the roads to analyses the road anomalies. [0028] In an embodiment, the dashboard camera and GPS may be combined. [0029] Further, Dashboard camera may pair with a communication device through available network to transfer data Signing to the mobile application. Afterwards, the data from mobile application can be transferred to central server through any network. Alternatively, the data may be physically transferred to central server via storage device such as Secure Digital (SD) card. [0030] The GPS data recording unit (200) or a GPS logger is a device which is used to capture the GPS co-ordinates and create a stream of it so that once the whole route is recorded the data can be used to trace the vehicle’s path on the map, the date time stamp and the speed at which the vehicle has traversed the route. The GPS logger may comprise of GPS receiver, a processing and storage unit. In an exemplary embodiment, U-blox[7] GPS Receiver, a Raspberry PI model 4 B and 16 GB SD card for recording the stream of GPS co-ordinates are used. The data recorded from GPS logger is stored as.GPX file. With every track being recorded as a.GPX file it is easy to play it in GPX player software which plays the recorded location position along with date time stamp and the speed. The captured.GPX files can be uploaded from Raspberry PI to central server through SSH protocol in a secure manner for processing at the central server. The GPS logger will help create a trace of the route travelled by the vehicle used for road survey. The GPS co-ordinates of potholes and patches are identified and mapped to identify the accurate position of road issues. [0031] Further, the data capturing unit (100) installed on plurality of vehicles to capture the video and GPS data. Vehicles may be but not limited to, any utility vehicle deployed by municipal committees, personal cars, or commercial vehicles such as trucks, buses etc. but preferably plying during the less traffic time in the morning when shadows are less prevalent. [0032] Fig. 3(a), 3(b), 3(c) and 3(d) illustrate the process of classification of road anomalies and mapping of road anomalies on to a web mapping service application. [0033] As shown in Figure 3(a), the central server is a high end desktop machine which process the data captured by data capturing unit (100). In an exemplary embodiment, a desktop machine with Intel i[7] processor, Nvidia GPU, atleast 16-32 GB RAM, 512 SSD is used. The central server runs an Artificial Intelligence based algorithm to identify the road anomaly based on the trained dataset of road anomalies. Training data set categorize anomalies in different categories such as potholes, cracks, scrapped road, bumps, misalignments of manhole covers and frames. Further, the server classify the quality of roads as fair, bad or worse and determine the right speed to cross over the Signing anomalies based on recent driver experience. It also determines the alternate travel path for users to avoid travelling over a road having anomalies. [0034] Further, as shown in figure 3(b) and 3(c), the video is processed through the data processing unit (300) to detect the road anomalies. After processing the video, image frames are recorded having bounding box corresponding to the detected anomalies along with date and time stamp. A bounding box is an imaginary box to demarcate the objects from their surroundings. In digital image processing, the bounding box is merely the coordinates of the rectangular border that fully encloses a digital image when it is placed over a page, a canvas, a screen or other similar bidimensional background. Based on the dimensions of the anomalies and the data of deceleration on location of the road anomaly, the road anomaly is classified into fair (yellow), bad (amber) or worse (red). If there are multiple road anomalies in the particular stretch of the road the whole patch may be marked as bad or worse. [0035] The data mapping unit (400) classifies and labels the road condition by creating a map of road including road anomalies and provide the average deceleration in speed to negotiate the road anomaly. While the driver sees the different routes on the map for reaching the destination the driver may also choose to select the route which has less road anomalies. [0036] In accordance with the present invention the method for detecting road anomalies is discussed herein: Step 1: Installation of the dashboard camera and GPS logger in the vehicle; Step 2: Starting the dashboard camera and GPS logger simultaneously when the vehicle starts surveying the road; Step 3: Dashboard camera will record the road condition and GPS logger will start capturing the distance covered, time taken and speed at each point and creates GPS log file (.GPX file). Step 4: The data captured through dashboard camera and GPS logger is stored in separate local storage device. Signing Step 5: The Data stored in the local storage device is transferred to data processing unit (300). Step 6: The video is processed through the data processing unit (300) to detect the road anomalies and create a bounding box and capture the image frame along date and time stamp. Step 7: The data timestamp of image obtained from the (.GPX file) with road anomaly is compared with the corresponding time stamp through GPS logger and the GPS co-ordinates of the road anomalies based on corresponding GPS time stamp are determined. Step 8: The road anomaly is further geotagged as red or amber or yellow to bring to the attention of the user about the condition and severity of the anomaly on web mapping application using the GPS coordinates which will show up as pin on map. Step 9: The said user can click on the pin to see the actual image of the road anomaly with the date time stamp. User will be able to see the severity of the anomaly and average speed for the patch based on drivers travelling at off peak hours. Step10: There might be a date time stamp based and area wise heat map created to segregate the different areas where there are more anomalies as compared to other areas. [0037] Step 1 to 5 facilitate the data capturing of required data. Step 6-7 is related to the process of detecting of road anomalies. Step 8 is based on mapping of road anomalies on the web mapping service application. Steps 9-10 are facilitating the publishing of road anomalies to be detected by the users. [0038] In accordance with the present invention the said process for classification of the road anomaly and determining its severity and accordingly determining the speed of vehicle on the same road is discussed herein: The severity of the road anomaly is classified based on correlation of the video of the road labelled through data mapping system, exact geotagging of the location and average decelaration of speed during off peak traffic on the same spot. Signing Tagging of road anomalies in different color scheme like red or amber or yellow to bring to the attention of the road authorities about the severity of the anomaly, so that the prioritizing and planning of repair work by authorities can be carried out. Historical analysis of the deceleration of the speed through the same location where the anomaly is detected. Informing the user in advance about the severity of the road anomaly and the average speed for that patch of road. [0039] The process of classification of the road anomaly and determining its severity and the amount of deceleration of speed from the average speed on the same road is a continuous and iterative process which will keep on geotagging the new spots or changing the colors and removing the geotags if the road is resurfaced or patch work done. [0040] In accordance with the present invention FIG. 4, 5 and 6 illustrate the process of publishing of road anomalies to users. a) Process for visualization of the road conditions based on specific area includes: Collecting and processing the data of road anomalies for a particular area for a period of every 10-15 days to show the variation in data over a period of time. Geographically color code the sub areas within area based on number of anomalies and their severity. b) Process for identifying the route, automatic downloading of the road anomalies data for the route and providing the suggestions if the road quality is really worse consists the following: User switches on the web mapping service application and selects the destination and presses start. System identifies the current location and the destination location and selects the best route. Signing System downloads the road anomalies data for the route from the current database of road anomalies and shows it visually to the subscribed driver on web mapping service application. The driver is given warning of the upcoming road anomaly based on its severity and subscribed driver’s speed (only on mobile application). The system also tells about the average speed at which driver should cross the particular patch of road based on past few days’ data for off peak traffic. c) Process of warning the driver (only on mobile application) in case the upcoming road anomaly is severe or driver is at higher speed as compared to average speed in off peak hour includes: Subscribed user’s speed is calculated based on GPS logger installed and route is detected. The route currently being undertaken is compared against road anomaly’s database and the average speed for past few days for off peak hour. Driver is given audio warning if the driver’s speed is much higher for approaching anomaly. [0041] The method of publishing the information about upcoming road anomalies may give visual and audio alert to subscribed user in case the driver is at higher speed then prescribed speed for the respective patch. [0042] In accordance with the present invention the advantages offered by the present invention are: Enabling easy survey of roads for locating distress spots, requiring minimal human involvement. Leveraging technology to efficiently cover a large area within the monitoring framework within less time. Leveraging technology to capture any other incident along the streets like dumping of construction waste, spilling of waste, collection of water, etc. Signing Enabling report generation that details out the nearexact location of the potholes and other distress spots on the scanned roads, thus making it convenient for the city authorities to identify the locations as well as assess the distress severity, and accordingly take prompt action. The present invention uses a dashcam a specialized camera having wide angle of 130 degree, G sensor for image stabilization for capturing road conditions and subsequent video analysis through AI algorithm for detecting and classifying the road conditions and correlating with the data on deceleration in speed from multitude of vehicles at the same spot on the road irrespective of traffic condition and other adverse conditions for further classifying the road conditions. The present invention does all the processing centrally and focuses on analysis of pothole and road surface anomalies. [0043] While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. We Claim:
1) A method for detecting road anomalies, comprising: - installation of the dashboard camera and GPS logger in the vehicle; - starting the dashboard camera and GPS logger simultaneously when the vehicle starts surveying the road; - recording the road condition through the dash board camera and capturing the GPS co-ordinates through GPS logger and create GPS log file (.GPX file); - storing the data captured through dashboard camera and GPS logger in separate local storage devices Signing - transferring the video and GPS data captured by data capturing unit (100) to the data processing unit (the central server)(300); - processing the video captured from the data capturing unit (100) to identify the road anomaly by matching with trained data set of road anomalies by the server; - creating a bounding box around the detected road anomaly; - capturing an image frame along with date time stamp for corresponding bounding box; - segregating the detected road anomalies and classifying the severity of road anomalies; - determining the GPS coordinates of road anomaly by matching the date time stamp data of anomaly detected with corresponding date time stamp data received from the GPS log file (.GPX file); - determining the suitable speed to cross an upcoming road anomaly based on data captured for past few days; and - mapping of road anomaly on a web mapping service application using GPS coordinates along with information of speed and severity of road anomaly.
2) The method as claimed in claim 1, wherein detected road anomalies can be potholes, bumps or cracks or any other road pavement (surface) misalignment.
3) The method as claimed in claim 1, wherein said method classifies the severity of road anomalies based on different parameters including dimensions of anomalies, type of anomaly, type of road on which anomaly is detected.
4) The method as claimed in claim 1, wherein said method earmark the severity of road anomalies by different colors.
5) The method as claimed in claim 1, wherein the said method notifies user for safe speed through visual and audio alert message.
6) A system for detecting road anomalies, comprising: Signing -the data capturing unit (100) installed on the vehicle to capture the video and GPS data; -the data recording unit (200) to store the data acquired by data capturing unit (100); -the processing unit (300) having a server configured to process the data received from the data capturing unit (100); -data mapping unit (400) to mark the location of detected anomalies on the web mapping service application; and -data publishing unit (500) to notify the information regarding suitable speed and severity of road anomaly to the user;
7) The system for detecting road anomalies as claimed in claim 6, wherein the data capturing unit (100) includes at least one dashboard camera, at least one GPS logger and at least one storage device.
8) The system for detecting road anomalies as claimed in claim 6, wherein the GPS logger includes a GPS receiver, a single board computer processing unit, and a power source. Dated this 19th day of March, 2020 Sd./- RANA, Vikrant (PA-248) of S. S. Rana & Co. Attorney of the Applicant AUDERTEC SOLUTIONS LLP”
7. One may simplify the features of the subject patent as they emerged from the complete specifications reproduced (supra), thus:
(i) The subject patent is intended to detect road anomalies.
The expression “road anomalies” is a compendious term covering any defect in road surface, owing to any cut and crack in the road, pothole, bump or uneven level, which would require a driver driving on the road, to suddenly brake or turn the Signing vehicle or if he does not do so, to a sudden jerk in the vehicle. As this can result in accident, mapping of road anomalies is necessary, both for notifying the concerned authorities, who can rectify the roads as well as to inform subscribed drivers of such anomalies, so that they can negotiate the vehicle appropriately or choose roads, which are more easily negotiable.
8. Five objectives of the claimed inventions are identified, viz. (a) Providing a method and system to give prior warning to a subscribed driver or user of upcoming road issues, (b) providing a cost effective method and system for better surveillance of road condition, (c) automating measurements of road condition,
(d) providing safe driving assistance to subscribed users, (e) providing a proactive system and a method to report road anomalies regularly and (f) providing a method for periodic tracking of road conditions.
9. The method claimed in the subject patent, when adopted, fulfils two purposes. Firstly, it analyzes the video of the road so as to map the conditions of the road. Secondly, it classifies road anomalies by earmarking them on the basis of the type of anomaly and rating the anomaly as yellow, amber or red, based on pre-determined parameters. Thirdly, the complete specifications are accompanied by drawings, designated as figures 1, 2(a), 2(b), 3(a), 3(b), 3(c), 3(d), 4, 5 and 6. These drawings, followed four steps: Signing (a) Detection of the anomalies by a Data Capturing Unit, (b) Classification of the anomalies,
(c) Mapping of the anomalies,
(d) Publication of the data to users
I may note, here, that when one peruses Claims 1 to 8 in the suit patent – already reproduced (supra) – it is clear that fourth step noted hereinabove, i.e. publication of the data to users is not part of the claims in the subject patent.
10. The claimed invention is divided in complete specifications, into: (a) Data Capturing and Data Recording Unit, (b) Data Processing Unit and
(c) Data Mapping and Publishing Unit.
11. The Data Capturing and Data Recording Unit comprises the following features: (a) The unit has:
(i) a camera,
(ii) a Global Positioning System (GPS) and
(iii) a storage device.
(i) a WDR function which adjusts to ambient light
(ii) a G – sensor for image stabilisation in the case of
(iii) The camera is a high definition dashboard camera mounted atop the vehicle at the front or the rear. It points towards the surface of the road. It has a 130 degree viewing lens. It can be mounted at a multitude of the vehicles.
12. The vehicle is to be driven at a speed of 20 to 30 kilometre per hour at a pre-decided route set by the user. As the vehicle moves, the camera records a video of the entire road surface, including any anomaly in the road covering of 130 degree view.
13. The GPS data of the road is simultaneously recorded on the GPS recording unit.
14. The GPS Data Recording Unit – (hereinafter the GPS DRU) – alternatively called the GPS logger - consists of a GPS receiver and a processing/storing unit.
15. The GPS DRU captures the GPS coordinates of the road and creates a stream so that it is possible to trace the path of the vehicle, the date time stamp and the speed of the vehicle.
16. The data is stored as a.GPX file, which can easily be played using GPX player software which, when played, would identify the position of the vehicle, date and time stamp and the speed. Signing
17. Thus, the GPS DRU identifies anomalies and maps them so that accurate locations are identified.
18. The camera footage and the GPS log files (in.GPX format) are downloaded to a central computer.
19. Alternatively, the camera may be paired with a mobile through a mobile application, and the mobile can send the data to the central server. Again, alternatively, the video recording recorded by the camera can be physically transferred to the central server through a Secure Digital (SD) Card.
20. The Data Process Unit consists of a central server, which is a desktop machine that processes the data captured by the camera and the GPS DRU and mapped by the GPS DRU.
21. The central server identifies road anomalies based on a dataset. The trained dataset classifies the anomalies into various categories such as potholes, cracks, scrapped road, bumps, misalignments of manhole covers, and the like.
22. The central server thereafter classifies the road, based on the nature of anomalies contained therein as fair (yellow), bad (amber) or worse (red) and, thereby, identifies the quality of road by colour coding.
23. Based on this data, the central server determines the speed at Signing which the anomaly is to be negotiated, based on recent driving experience and also suggests alternate travel path which could be adopted.
24. The data mapping and publishing unit does the following function: (a) It geographically maps the road anomaly. (b) It creates an anomalies database which is updated from time to time based on surveys.
(c) It plots the road anomalies on a web mapping service, depending on the route selected by the user.
(d) The road anomalies thus plotted identified the name of the road as well as colour coded distress spots on the road. (e) It suggests alternative routes which can be adopted.
25. As such, the data mapping and publishing unit creates a heat map which identifies concentration of road anomalies on various roads. This serves two functions. It helps authorities to repair the roads and correct the anomalies and also helps subscribed drivers to negotiate the anomalies and select alternate routes.
26. Thus, the entire method claimed in the subject patent involves (a) Classification of the road anomaly, by co-relating the video of the road labelled through the data mapping system, Signing exact geo tagging of the anomaly and average deceleration of speed while negotiating the anomaly. (b) Tagging of the road anomalies in colour coded fashion so as to inform the authorities about the severities of the anomalies and enable them to prioritize and plan repair work.
(c) Conducting historical analysis of the deceleration through the location where the anomaly is detected and
(d) Informing subscribed users in advance of the existence and severity of road anomalies.
27. The specifications clarified that the aforesaid process is continuous and iterative so that that new spots are continuously geotagged, anomalies specific colours are changed from time to time and, if the road is re-surfaced or patch work is done, geo-tags are removed.
28. Thus, the process for visualization of road conditions based on specific area includes (a) collection and processing of road anomalies data for a particular area for a particular period of 10-15 days so that periodical variation in road anomalies can be noted and (b) geographical colour coding of the sub-areas within the area based on number and severity of anomalies.
29. Para 0040 of the complete specifications also refers to the process of communication of the road anomalies to the subscriber drivers/users. The user is required to switch on the web mapping service application, select the destination to which he intends to Signing travel and press ‘Start’. When he does so, the system identifies his existing location, destination location and selects the best route[1].
30. From the database of road anomalies, the system downloads the road anomaly data for the road that the driver has selected and shows it to the driver on the web mapping service application. The driver is thus warned of the upcoming road anomaly based on severity and the speed of the driver. The driver is also provided suggestion of the average speed at which the anomaly should be negotiated. Prior Art D-2
31. The complete specifications of the prior art D-2, sans the drawings, may be reproduced thus: (57) ABSTRACT The present invention is directede to a road condition detection system for identifying and monitoring road conditions, and for communicating information regarding road conditions to various users. The road condition detection system is provided for capturing data indicative of road conditions and analyzing the captured data to locate and identify varius road conditions (e.g., road hazards, such as potholes, or weather conditions, such as ice). In various embodiments, the road condition detection system includes a road condition sensor array configured for being attached to a vehicle and for capturing road condition data. The captured data may be transmitted and assessed by a server configured for identifying potential road hazards or other road conditions based on the road condition data captured by the sensor array. “ROAD CONDITION DETECTION SYSTEM CROSS-REFERENCE TO RELATED APPLICATIONS This, it may be noted, is similar to the GPS system frequently used by drivers. Signing This application claims the benefit of U.S. Provisional Application No. 61/803,777, filed Mar. 20, 2013, the entirety of which is hereby incorporated by reference.
BACKGROUND OF THE INVENTION Field of the Invention Various embodiments of the present invention described herein generally relate to a road condition detection system for detecting and monitoring road conditions. Description of Related Art Various road conditions may make a road difficult to navigate or increase the risk of damage to a vehicle driving on the road. Some of these conditions include road imperfections (e.g., potholes, bumps, and cracks), weather conditions (e.g., wet or icy roads), low visibility (e.g., due to street lights being out), or debris in the road (e.g., tree limbs, gravel, and car accident debris). If one of these conditions is present on a given road, it would be advantageous for drivers to be notified so they may avoid a particular road hazard or hazardous road condition. Additionally, it would be advantageous for appropriate agencies, such as the local Department of Transportation, to be notified so that hazardous conditions can be addressed and the public may be apprised of current road conditions. Several media outlets exist that inform drivers of road conditions, such as local news stations, local radio stations, and online traffic sites. Similarly, government agencies (e.g., Department of Transportation) have systems that enable drivers to report roadway conditions to the appropriate personnel. However, the above-described media outlets and agencies often depend on people manually reporting road conditions. For example, if a driver sees a hazardous condition on a given road, the driver may call the Department of Transportation and describe the condition and its location (e.g., a pothole or patch of ice). In order to address the road condition, the Department of Transportation may first send a crew to locate the condition, which may be difficult to do depending on the description given by the driver. Furthermore, information regarding the road condition may become inaccurate through the chain of communication (e.g., where one DOT employee describes the condition inaccurately to another responsible for a repair or inspection). In addition, the crew may also need to inspect the identified road condition to determine what must be done to address it. At some later point in time, a separate Signing crew may be sent to address the condition. This process is often imprecise and inefficient, thereby resulting in lingering hazardous road conditions posing a continuing threat to drivers and vehicles. Accordingly, there is an ongoing need in the art for systems and methods for more efficiently identifying and reporting road conditions.
BRIEF SUMMARY OF THE INVENTION Various embodiments of the present invention are directed to a system for detecting and monitoring road conditions. According to various embodiments, the system comprises one or more memory storage areas and one or more processors in communication with the one or more memory storage areas. The processors are, collectively, configured to: receive road condition data captured by one or more road condition detection systems provided on one or more vehicles, wherein the road condition data is indicative of one or more road condition attributes of one or more road surfaces traveled by the one or more vehicles; identify, based on the received road condition data, one or more road hazards existing on the one or more road surfaces, the one or more road hazards each comprising an identified road condition that is at least potentially hazardous to a vehicle traversing the road surface; determine, based on the received road condition data, the location of the identified one or more road hazards; and store data indicative of the identified one or more road hazards and their respective locations in the one or more memory storage areas. Various embodiments of the present invention also include a system for detecting road conditions including at least one road condition sensor array configured for being mounted to a vehicle, the road condition sensor array comprising one or more sensing devices configured capturing road condition data indicative of one or more road condition attributes of one or more road surfaces traveled by the vehicle; at least one processor configured for controlling the operation of the at least one road condition sensor array; and one or more memory storage areas configured for storing the road condition data captured by the road condition sensor array.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S) Reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein: FIG. 1 is a schematic block diagram of a road condition Signing detection system according to one embodiment of the present invention; FIG. 2 is a schematic block diagram of road condition sensor array adapted for use on a vehicle according to one embodiment of the present invention; and FIG. 3 is a flow diagram of steps executed by a road condition detection system according to one embodiment of the present invention; and FIG, 4 is a flow diagram of steps executed by a central server according to another embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION The present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the inventions are shown. Indeed, these inventions may be embodied in many is different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout. Overview The present invention relates to systems and methods for identifying and monitoring road conditions, and for communicating information regarding road conditions to various users. According to various embodiments, a road condition detection system is provided for capturing data indicative of road conditions and analyzing the captured data to locate and identify various road conditions (e.g., road hazards, such as potholes, or weather conditions, such as ice). In various embodiments, the road condition detection system comprises a road condition sensor array configured for being attached to a vehicle and for capturing road condition data, an onboard computer for analyzing the road condition data in real time and transmitting information regarding road conditions to remotes users of the system, and a central data analysis server configured for conducting post processing analysis of the data collected by the road condition sensor array to determine additional information about various road conditions. In various embodiments, the road condition sensor array is configured to sense and record information about a given road as the vehicle travels along the road. For example, the road condition sensor array may include an optical camera, a vibration sensor, a road surface scanner, and various other devices configured to Signing capture road condition data indicative of various road condition attributes, such as a road's surface profile, imperfections, illumination level, reflectivity, and/or other conditions. The road condition sensor array may also include, or may be in communication with, a geo-location device, allowing the system to geo-code the location of road condition data indicative of these attributes. According to various embodiments, a plurality of vehicles in a fleet (e.g., a fleet of delivery vehicles) may each be equipped with a road condition sensor array, thereby capturing road condition data for various roads over a wide area at various times. In various embodiments, the road condition data collected by the road condition sensor array may be processed and stored (in whole or in part) by an onboard vehicle computer. In addition, the data capturing operations of the road condition sensor array may be controlled by the onboard computer, which may dictate when the road condition sensor array captures road condition data and the frequency with which it does so. In addition, the onboard computer may include various telematics devices and sensors monitoring dynamic attributes of the vehicle, or may be in communication with a separate telematics devices or sensors provided on the vehicle. As described in greater detail below, the road condition data captured by the road condition sensor array may be analyzed by the onboard computer in order to identify various road conditions based on the road condition data (e.g., bumps, potholes, debris, wet or icy conditions, etc.). Information advising users of these various conditions may then be transmitted from the onboard computer to one or more users devices in real time over a network. In addition, the road condition data may be analyzed further by the central server to identify additional road conditions (e.g., more detailed information regarding cracks and potholes, visibility conditions, weather conditions, etc.). In addition, the central data analysis server may be configured to create data applied to maps indicating various road conditions (e.g., layers applied to digital maps), calculate a road condition index for individual roads or areas, and compare changes in road conditions for particular roads or locations. The analyses performed by the central server may be useful, for example, in identifying and communicating road conditions to drivers and for evaluation of road repairs and maintenance. Road Condition Detection System FIG. 1 shows a road condition detection system 100, according to Signing one embodiment. In the illustrated embodiment, the road condition detection system 100 generally comprises a road condition sensor array 120 mounted on a vehicle 110, an onboard computer 130, and a central data analysis server (herein "central server") 170. As discussed in greater detail below, the onboard computer 130 is configured to communicate with the road condition sensor array 120 in order to control the capture and storage of road condition data. The onboard computer 130 is further configured to s communicate with the central server 170 via a communication network 150 in order to transmit road condition data to the server 170 for analysis. Additionally, the central server 170 and onboard computer 130 may be configured to communicate with one or more user devices 180 (e.g., a mobile phone, tablet computer, digital information acquisition device, or the like) to provide updated road condition data to a user. The components of the illustrated embodiment are discussed in more detail below. Road Condition Sensor Array FIG. 2 shows a road condition sensor array 120 mounted on a vehicle 110 according to one embodiment. In the illustrated embodiment, the road condition sensor array 120 generally comprises a front sensing unit 121a housed within a detachable front mounting housing 122a, and a rear sensing unit 121b housed within a detachable rear mounting housing 122b. According to various embodiments, the front sensing unit 121a comprises various road image detection devices, including an optical camera, a vibration sensor, and a road surface scanner. As the vehicle 110 drives along a road 5, the road condition sensor array's sensing unit 121a captures road condition data relating to the conditions of the road 5. For example, the captured road condition data may include video data, surface profile data, illumination level data, vibration data, and other data generated by other devices in the sensing unit 121a. As described in greater detail below, the sensing unit's devices are in communication with the vehicle's onboard computer 130, which may be configured to control the operation of the sensing unit 121a and store captured road condition data. In various embodiments, the sensing unit 121a includes an optical camera configured to capture video and/or still images of the road surface and detect the illumination level of the road 5. For example, in one embodiment, the optical camera may be configured to capture video of the road surface continuously as the vehicle 110 travels. In such embodiments, the onboard computer 130 may continuously store video data generated by the optical camera and may be configured to buffer and transmit data to a user device 180. Signing According to various embodiments, the optical camera may also be configured to receive light from the road through an aperture in the camera housing, which may vary in size to control the amount of light reaching the optical sensor. The optical sensor is configured to detect the intensity of the light received through the aperture resulting in illumination level data corresponding to the illumination level of the road 5 at a given point. Accordingly, if the vehicle 110 is traveling at night along a lighted road and passes by an area where street lights are out, the illumination level data will indicate a reduction in luminous intensity. Similarly, the illumination level data may indicate poor illumination in tunnels, under bridges, or in covered areas (e.g., parking lots). In this way the optical camera is able to capture illumination level data indicative of a particular road's varying illumination levels along the distance traveled by the vehicle 110. In various embodiments, the optical camera may be further configured to detect the reflectivity of the surface of the road 5. This may be accomplished, for example, by the camera emitting light (e.g., via a flash bulb or LED bulb) and detecting the level of light reflected by the road surface. As such, the optical camera is able to capture reflectivity data indicative of the surface reflectivity of the road 5 at any given point. Accordingly, if a road surface is wet (e.g., due to rain or an oil leak) or coated with another hazardous substance, the reflectivity data will indicate a comparative increase in the reflectivity of the road surface. Likewise, where the road is dry, the reflectivity data will indicate a comparative decrease in the reflectivity of the road surface. In this way. the optical camera is also able to capture reflectivity data indicative of a particular road’s varying reflectivity along the distance traveled by the vehicle 110. As will be appreciated from the description herein, the optical camera may be configured to capture video data, illumination level data, and reflectivity data, or two or more cameras may be provided, each being configured to capture illumination level data or reflectivity data. In addition, a lens may be disposed within the camera housing aperture and a shutter and/or lens cover may cover the lens when the camera is not actively recording illumination level data or reflectivity data. In this way, the shutter and/or lens cover may protect the lens from damage such as being scratched or cracked. In other embodiments, the illumination level data and reflectivity data may be captured via other suitable devices. such as laser sensors or the like. In addition to the optical camera, the sensing unit 121a may Signing include a road surface scanner may comprise a laser or electromagnetic sensor disposed within a scanner housing. As the vehicle travels along the road 5, the sensor is configured to scan the surface of the road 5 and capture surface profile data indicative of the road’s surface profile. Accordingly, if the vehicle 110 travels over a pothole, the captured surface profile data will indicate a depression in the road surface. Likewise. if the vehicle 110 travels over piece of debris or other object on the surface of the road 5, the captured surface profile data will indicate a protrusion on the road surface. In this way. the road surface scanner is able to capture surface profile data indicative of a particular road’s full surface profile along the distance traveled by the vehicle 110. As noted above, the sensing unit 121a also includes a vibration sensor configured to capture vibration data indicative of the magnitude and frequency of vibration of the vehicle 110 as it travels along the road. For example, in one embodiment, the vibration sensor is configured to detect vibrations in the vehicle’s chassis (e.g., vibrations transmitted from the road surface through the wheels and suspension to the chassis). Accordingly, if the vehicle 110 travels over a pot hole, the vibration data captured by the vibration sensor will indicate a sharp change in vibration magnitude or frequency. Additionally, if the vehicle 110 is traveling a smooth road. the vibration data will indicate a lowmagnitude, consistent vehicle vibration, while a rough road will result in inconsistent vibration data corresponding to various bumps and imperfections in the road surface. In this way, the vibration sensor is also able to capture vibration data indicative of the smoothness of a particular road along the distance traveled by the vehicle 110. According to various embodiments, the sensing unit 121a may further comprise an infrared camera, a noise detecting device, and/or other road condition detecting devices. For example, the infrared camera may be used for capturing infrared data indicative of hot spots on the road surface while the noise detecting device may be used for capturing noise data indicative of loud noises associated with a vehicle traveling over a pot hole or other debris. Indeed, as will be appreciated from the description herein, the sensing unit 121a may include any road condition detecting device capable of detecting useful data indicative of one or more road conditions. Additionally, in some embodiments, the various cameras and/or sensors of the road condition sensor array 120 may have zoom capabilities in order to capture road condition data with at varying degrees of granularity. As shown in FIG. 2, the various devices of the sensing unit Signing 121¢ are secured within a mounting housing 122a. In the illustrated embodiment, the mounting housing 122a is mounted to the front bumper of vehicle 110 and faces the road surface directly in front of the vehicle 110 (e.g. as indicated by the dashed lines in FIG. 2). In certain embodiments, the mounting housing 122 includes a quick release mechanism configured to engage a mating member on the vehicle’s front bumper. This allows the sensing unit 121a to be easily removed from vehicle 110 and easily mounted on another vehicle. Moreover, as will be appreciated from the description herein, the vehicle 110 may include a plurality of mating members positioned at various locations on the vehicle 110 (e.g., front bumper, rear bumper, centrally underneath vehicle, side of vehicle frame, etc.) such that the one or more road condition sensor arrays 120 can be secured at various locations on the vehicle 110. In the illustrated embodiment, the road condition sensing array 120 also includes a rear sensing unit 121b secured within a rear mounting housing 122b. According to various embodiments, the rear sensing unit 121b may comprise the same, or one or more of, the various sensors and detection devices provided in the front sensing unit 121a. In addition, the rear mounting housing 122b may be substantially the same as, or similar to, the front mounting housing 122a. As will be appreciated from FIG. 2, the provision of both front and rear sensing units 121a, 122b enables the road condition sensing array 120 to capture additional road condition data to verify various road conditions. Indeed, in certain embodiments, the rear sensing unit 121b may be configured to capture road condition data to confirm road conditions indicated by the road condition data captured by the front sensing unit 121a. In various other embodiments, the sensing units 121a, 121b and mounting housings 122a, 122b may be provided at any suitable location on the vehicle 110 depending on its configuration and intended use. In addition, according to various embodiments, less or additional sensing units may be provided as needed. For example, in certain embodiments. only a single front or rear sensing unit may be provided. In other embodiments, additional sensing units may be placed on lateral sides of the vehicle. Onboard Computer & Communications Network According to various embodiments, the road condition sensor array’s sensing units 121a, 121b may be controlled by the vehicle’s onboard computer 130. In various embodiments, the onboard computer 130 comprises at least one processor, a locationdetermining device or sensor (e.g., a GPS sensor), a real-time clock, J-Bus protocol architecture, an electronic control module Signing (ECM), a port for receiving data from vehicle sensors located on the vehicle 110, a communication port for receiving instruction data, a radio frequency identification (RFID) tag, a power source, a data radio for communication with a WWAN, a WLAN and/or a WPAN, a programmable logic controller (PLC), and one or more memory storage devices. The memory storage devices may include volatile memory and/or non-volatile memory, which can be embedded and/or may be removable. For example, the non-volatile memory may be embedded or removable multimedia memory cards (“MMCs”), secure digital (“SD”) memory cards. Memory Sticks, EEPROM, flash memory, hard disk, or the like. The memory storage device may also include DRAM and NVRAM memory modules. In other embodiments, various components of the onboard computer 130 (e.g., the RFID tag, the location sensor, and the PLC) may be located in the vehicle 110, external from the onboard computer 130. The onboard computer’s location sensor may be, for example, a GPS-based sensor compatible with a low Earth orbit (LEO) satellite system, medium Earth orbit satellite system, or a Department of Defense (DOD) satellite system. Alternatively, triangulation may be used in connection with various cellular towers positioned at various locations throughout a geographic area in order to determine the location of the vehicle 110. The location sensor may be used to receive position, time, and speed data. In addition, the location sensor may be configured to detect when its vehicle 110 has entered or exited a GPS-defined geographic area (e.g., a geo-fenced area). As will be appreciated from the description herein, more than one location sensor may be utilized, and other similar techniques may likewise be used to collect geolocation information associated with the vehicle 110. In addition, various embodiments of the onboard computer 130 may include multiple processors configured for carrying out the various processes described herein. As will be appreciated from the description herein, the onboard computer 130 may not include certain of the components described above, and may include any other suitable components in addition to, or in place of, those described above. As an example, the onboard computer 130 may include various types of communications components (e.g., to support new or improved communications techniques). In the illustrated embodiment, the onboard computer 130 is generally configured to communicate with the road condition sensor array’s sensing units 121a, 121b in order to (i) control when the sensing units 121a, 122b capture road condition data, (ii) store the road condition data captured by the sensing units 121a, 122b, Signing and (iii) transmit the stored road condition data to the central server 170 and/or the user device 180. For example, in one embodiment, the onboard computer 130 causes the sensing units 121a, 122b to capture road condition data continuously as the vehicle 110 travels. In other embodiments, the onboard computer 130 causes the sensing units 121a, 122b to capture road condition data at given time intervals when the vehicle 110 is on (e.g., such that all of the sensing unit’s sensors capture data every second, every 2 seconds, or every 5 seconds). In other embodiments, the onboard computer 130 causes the sensing units 121a, 122b to capture road condition data at given distance intervals as the vehicle 110 travels down road 5 (e.g., such that all of the sensing unit’s sensors capture data every 5 feet, every 10 feet, or every 50 feet traveled). In further embodiments, the onboard computer 130 causes the sensing units 121a, 122b to start or stop capturing road condition data when the vehicle 110 changes direction, goes over a bump, or accelerates. In addition, the onboard computer 130 may be configured to monitor signals received from the sensing units 121a, 122b and capture data only when certain predefined parameters are met (e.g., illumination intensity below a predefined valued or a road surface profile deviating more than a certain amount from a predefined base profile). Moreover, the onboard computer 130 may be configured to trigger data capture by one or more specific devices in the sensing units 121a, 122b according to the criteria above. Indeed. as will be appreciated from the description herein, the onboard computer 130 may be programmed to trigger data capture by the sensing units 121a, 122b according to any desirable parameters. As noted above, the onboard computer 130 includes a location-determining device or sensor, such as a GPS sensor, and a real-time clock. Accordingly, in various embodiments, the onboard computer 130 may be configured to associate and store location and/or date and time information—e.g., as indicated by the location sensor and clock—with the road condition data collected by the road condition sensor array 120. By associating location and date and time information with the road condition data captured by the road condition sensor array 120, the physical and temporal location of a road hazard indicated by the road condition data may be determined (e.g., by the central server 170 as explained below). In various embodiments, the road condition data captured by the road condition sensor array 120 may be stored in the onboard computer 130 (e.g. in the computer’s memory storage devices). For example, in certain embodiments, the onboard computer 130 is configured to store road condition data collected by the road condition sensor array 120 continuously as it is captured. In other embodiments, the onboard computer 130 is Signing configured to store road condition data collected by the road condition sensor array 120 only if the onboard computer 130 detects a deviation in the road condition data that may indicate the presence of a road hazard (e.g., a change in vibration frequency or road surface profile). In yet another embodiment, the onboard computer 130 is configured to store only road condition data captured within a particular geo-fenced area. As described in greater detail below, the road condition data captured by the road condition sensor array 120 and stored by the onboard computer 130 is transmitted to the central server 170 via a communications network 150. According to various embodiments of the present invention, the communications network 150 may be capable of supporting communication in accordance with any one or more of a number of second-generation (2G), 2.5G and/or third-generation (3G) mobile communication protocols or the like. More particularly, the network 150 may be capable of supporting communication in accordance with 2G wireless communication protocols IS-136 (TDMA), GSM, and IS- 95 (CDMA). Also, for example, the network 150 may be capable of supporting communication in accordance with 2.5G wireless communication protocols GPRS, Enhanced Data GSM Environment (EDGE), or the like. In addition, for example, the network 150 can be capable of supporting communication in accordance with 3G wireless communication protocols such as Universal Mobile Telephone System (UMTS) network employing Wideband Code Division Multiple Access (WCDMA) radio access technology. Some narrow-band AMPS (NAMPS), as well as TACS, network(s) may also benefit from embodiments of the present invention, as should dual or higher mode mobile stations (e.g., digital/ analog or TDMA/CDMA/analog phones). As yet another example, the network 150 may support communication in accordance with techniques such as, for example, radio frequency (RF), Bluetooth™, infrared (IrDA), or any of a number of different wireless networking techniques, including Wireless LAN (WLAN) techniques. In certain embodiments, the onboard computer 130 may be configured to transmit stored road condition data whenever it is able to establish a successful connection with the central server 170 via a WLAN component of the network 150 (e.g., when the vehicle 110 returns to a hub broadcasting a wireless networking signal). In addition, the onboard computer 130 may be further configured to immediately transmit (e.g. via 3G cellular network) captured road condition data meeting predefined “alert” parameters (e.g., road condition data clearly indicating a road hazard, such as a pothole or debris). In such embodiments, the onboard computer 130 (and/or Signing central server 170) may be further configured to transmit the alertstatus road condition data to the Department of Transportation, local media outlets, or other online road condition services in order to provide real-time status updates for various roads. Central Server According to various embodiments, the road condition data captured by the road condition sensor array 120 and stored by the onboard computer 130 may be subsequently transmitted over the network 150 to the central server 170 for post processing. As will be appreciated from the description herein, the central server 170 includes various devices for performing one or more functions in accordance with embodiments of the present invention, including those more particularly shown and described herein. However, various embodiments of the central server 170 may include alternative devices for performing one or more like functions without departing from the spirit and scope of the present invention. In various embodiments, the central server 170 includes a processor that communicates with other elements within the central server 170 via a system interface or bus. In some embodiments, the central server 170 includes a display device/input device for receiving and displaying data. This display device/input device may be, for example, a keyboard or pointing device that is used in combination with a monitor. In certain embodiments, the central server 170 may not include a display device/input device and may be alternatively accessed by a separate computing device (e.g., a networked workstation) having a display device and input device. The central server 170 further includes memory, which preferably includes both read only memory (ROM) and random access memory (RAM). The server's ROM is used to store a basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within the central server
170. In addition, the central server 170 includes at least one storage device—such as a hard disk drive, a floppy disk drive, a CD Rom drive, or optical disk drive—for storing information on various computer-readable media, such as a hard disk, a removable magnetic disk, or a CD-ROM disk. As will be appreciated by one of ordinary skill in the art, each of these storage devices is connected to the system bus by an appropriate interface. The storage devices and their associated computer-readable media provide nonvolatile storage for a personal computer. It is important to note that the computer-readable media described above could be replaced by any other type of computer-readable media known in the art. A number of program modules may be stored by the Signing various storage devices and within RAM. Such program modules include an operating system and/or a plurality of program modules (e.g., one or more modules configured for analyzing road condition data). According to various embodiments, the modules control certain aspects of the operation of the central server 170 with the assistance of the processor and operating system. Also located within the central server 170 is a network interface for interfacing and communicating with other elements of a computer network. It will be appreciated by one of ordinary skill in the art that one or more of the central server 170 components may be located geographically remotely from other central server 170 components. Furthermore, one or more of the components may be combined, and additional components performing functions described herein may be included in the central server 170. While the foregoing describes a single processor, as one of ordinary skill in the art will recognize, the central server 170 may comprise multiple processors operating in conjunction with one another to perform the functionality described herein. In addition to the memory, the processor can also be connected to at least one interface or other means for displaying, transmitting and/or receiving data, content or the like. In this regard, the interface(s) can include at least one communication interface or other means for transmitting and/or receiving data, content or the like, as well as at least one user interface that can include a display and/or a user input interface. The user input interface, in turn, can comprise any of a number of devices allowing the entity to receive data from a user, such as a keypad, a touch display, a mouse, a joystick or other input device. While reference is made to a central “server” 170, as one of ordinary skill in the art will recognize, embodiments of the present invention are not limited to a client-server architecture. The system of embodiments of the present invention is further not limited to a single server, or similar network entity or mainframe computer system. Other similar architectures including one or more network entities operating in conjunction with one another to provide the functionality described herein may likewise be used without departing from the spirit and scope of embodiments of the present invention. For example, a mesh network of two or more personal computers (PCs), or similar electronic devices, collaborating with one another to provide the functionality described herein in association with the central server 170 may likewise be used without departing from the spirit and scope of embodiments of the present invention. In the illustrated embodiment, the central server 170 is configured to receive road condition data from the onboard computer 130 via network 150. For example, in certain s embodiments, the central server 170 may receive a substantially Signing real-time data feed via network 150. In other embodiments, the central server 170 may receive road condition data downloaded from the onboard computer 130 when the vehicle 110 is in range of a WLAN. Processing of Road Condition Data FIG. 3 illustrates steps executed by the road condition detection system 100 to analyze captured road condition data according to one embodiment. As shown in FIG. 3, the process begins at step 302 where road condition data captured by the road condition sensor array 120 is transmitted to the onboard computer 130 via a road sensor input interface. Next, at step 204, the onboard computer 130 performs continuous storage and buffering of the road condition data received from the sensor array 120. Simultaneously, in step 306, the onboard computer 130 analyzes the vibration data present in the road condition data. At step 308, the onboard computer determines whether a bump has been indicated by the vibration data. For example, where the vehicle travels over a pothole or piece of debris, the vibration data captured by the sensor array’s vibration sensor (e.g., an accelerometer) will indicate a sharp change in vibration. If a bump is detected, the onboard computer moves to step 310 where it marks the road condition data corresponding to the detected bump and freezes the data buffer (e.g., saving and marking the previous one minute of data). Next, at step 312, the onboard computer 130 determines whether real time transmission of road condition information is enabled. If real time transmission is enabled, the onboard computer 130 moves to step 314 where it immediately transmits road condition data captured around the impact of the detected bump. For example, in one embodiment, the onboard computer 130 may immediately transfer the relevant road condition data to the central server 170 for processing and transmission to various user devices
180. In other embodiments, the onboard computer 130 may be configured to be configured to immediately transmit the relevant road condition data directly to a user device 180. In yet another embodiment, the onboard computer 130 may be configured to immediately generate and transmit road condition information indicative of the detected bump and/or any related road conditions to the user device 180. In this way, hazardous conditions may be transmitted in real-time wirelessly to users for immediate updates regarding road conditions. Turning now to step 316, the onboard computer 130 is further configured to perform an end-of-day upload of all captured road condition data. For example, as noted above, in one embodiment the onboard computer 130 may be configured to transmit all captured road condition data to the central server 170 Signing at the end of work day when a WLAN 2 connection can be established with the central server. Next, at step 318, post processing of the captured road condition data is performed by the central server 170. In certain embodiments, this may include reformatting the data and associating the captured road condition data with GPS coordinates and time stamp data to provide context to the captured road condition data. Next, at step 320, the central server next performs signature recognition analyses of the road condition data to determine further information regarding road conditions. These analyses are described in greater detail below in regard to the exemplary method shown in FIG. 4. Finally, at step 322, the central server 170 generates finalized reports and contents for distribution to various user devices 180. The reports and content may include, but are not limited to, map data for display on existing digital maps indicating one or more road conditions (e.g., on Google Maps), reports on the conditions of roads in certain areas, text messages alerting users to various road hazards, and the like. In certain embodiments, a report may be generated where a user may use a viewer to fast forward through video data to locations where hazardous road conditions have been identified. Referring back to step 320 in greater detail, various embodiments of the central server 170 are generally configured for analyzing road condition data received from the onboard computer 130 to identify hazardous road conditions indicated by signatures in the data. In various embodiments, the central server 170 includes a pattern recognition module for processing the road condition data. As described in greater detail below, the pattern recognition module is generally configured for sensing deviations in the road condition data which may indicate various specific road conditions or road hazards. FIG. 4 illustrates steps executed by the pattern recognition module according to one embodiment. Beginning at step 190, the pattern recognition module identifies and retrieves target road condition data. For example, in certain embodiments, a user may request that the central server 170 analyze data for a particular area (e.g.. a geo-fenced area such as a county, city, highway, neighborhood, or the like) received during a particular time period (e.g., within the past week). In this case, the pattern recognition module would review the road condition data it has received from the onboard computer 130 and identify road condition data captured at locations within the user-specified area during the userspecified time period. As will be appreciated from the description herein, the pattern recognition module may be configured to retrieve target data relating to any set of user parameters. Next, at step 200, the pattern recognition module analyzes. the video data (e.g., the video or image data captured by the Signing sensing unit’s optical camera) present in the retrieved road condition data to identify potential road imperfections. For example, as the vehicle 110 travels along the road 5 in FIG. 2, the video data will show relatively consistent images of the road surface. However, where potholes, cracks, debris, or other imperfections are present, the pattern recognition module will identify these deviations in the image signature and associate them with road imperfections. If the pattern recognition module detect imperfections in the road’s surface based on the video data, the module moves to step 201 where the associated data is stored (e.g., in the server’s memory storage areas). In addition, at step 201, the pattern recognition module will determine the location and time of the captured data associated with the road imperfection and associate this location/time data with the stored video data for use in generating images of road imperfections. Next, at step 202, the pattern recognition module analyzes the surface profile data (e.g., data captured by the sensing unit’s road surface scanner) present in the retrieved target road condition data to identify potential road imperfections. For example, as the vehicle 110 travels along the road 5 in FIG. 2, the surface profile data will indicate a relatively consistent road profile (e.g., a consistent detected distance from the scanner to the road surface). However, where the vehicle 110 travels over a pothole or piece of debris in the road, the surface profile data will deviate significantly and indicate an abnormal surface profile. Accordingly, the pattern recognition module is configured to identify deviations or abnormalities in the surface profile data. In addition, the pattern recognition module may be configured to compare the surface profile data in the target data with historical surface profile data to identify changes in the road surface profile over a period of time (e.g., by comparing earlier surface profile measurements captured at a particular location with the most recent surface profile measurement for the particular location to identify surface profile deviations or abnormalities). As shown in FIG. 4, if the pattern recognition module does not detect imperfections in the road’s surface profile based on the surface profile data, the module moves to step 204. However, if the pattern recognition module does detect imperfections in the road’s surface profile, the module moves to step 203 where the associated data is stored (e.g., in the server’s memory storage areas). In addition, at step 203, the pattern recognition module will determine the location and time of the captured data associated with the road imperfection and associate this location/time data with the stored surface profile data for use in generating graphical representations of road imperfections. Signing Next, at step 204, the pattern recognition module analyzes the vibration data (e.g., data captured by the sensing unit’s vibration sensor) present in the retrieved target road condition data to identify potential road imperfections. For example, as a vehicle 110 travels along the road 5 in FIG. 2, the vibration data will indicate relatively consistent road profile (e.g., a consistent vibration frequency detected as the vehicle 110 moves). However. where the vehicle 110 travels over a pothole or piece of debris in the road, the vibration data will deviate significantly and indicate an abnormal surface profile (e.g., a sharp change in vibration frequency or magnitude). Accordingly, the pattern recognition module is configured to identify deviations or abnormalities in the vibration data. not detect imperfections in the road's surface profile based on the vibration data, the module moves to step 206. However, if the pattern recognition module does detect imperfections in the road's surface profile, the module moves to step 205 where the associated data is stored (e.g., in the server's memory storage areas), In addition, at step 205, the pattern recognition module will again determine the location and time of the captured data associated with the road imperfection and associate this location/time data with the stored vibration data for use in generating graphical representations of road imperfections. Next, at step 206, the pattern recognition module analyzes the illumination level data (e.g., data captured by the sensing unit's optical camera) present in the retrieved target road condition data to identify potential low illumination sections of road. For example, as a vehicle 110 travels along the road 5 in FIG. 2, the illumination level data will indicate relatively consistent illumination (e.g., either a consistent day- light luminous intensity or, during the night, a consistent artificial light luminous intensity). However, where the vehicle 110 travels on a portion of road where a street light is out - or that is otherwise poorly lit - the illumination level data will deviate significantly and indicate an abnormal illumination level (e.g., a sharp change in illumination intensity). Accordingly, the pattern recognition module is configured to identify deviations or abnormalities in the illumination level data. In addition, the pattern recognition module may be configured to compare the illumination level data in the target data with historical illumination level data to identify changes in illumination levels over a period of time (e.g., by comparing earlier illumination level measurements captured at a particular location at a particular time of day with the most recent illumination level measurement for the particular location at the particular time of day to identify Signing illumination level deviations or abnormalities). not detect low illumination levels based on the illumination level data, the module moves to step 208. However, if the pattern recognition module does detect low illumination levels, the module moves to step 207 where the associated data is stored (e.g., in the server's memory storage areas). In addition, at step 207, the pattern recognition module will again determine the location and time of the captured data associated with the low illumination levels an associate this location/time data with the stored illumination level data for use in generating graphical representations road imperfections. Next, at step 208, the pattern recognition module generates a graphical representation of various road condition indicated by the target road condition data. For example, in one embodiment, the graphical representation may comprise an interactive road map showing the location of potential road imperfections (e.g., potholes or debris) and low illumination areas (e.g., where a street or tunnel light is out). In this way, a user is able to view road conditions existing within the parameters set for the target data (e.g., hazards within a particular area and/or time period). In addition, the interactive road map may be configured to automatically match before and after images and/or data regarding particular condition so the user is provided with comparative information about the current and prior state of the condition. For example, in one embodiment, a user may select a particular road hazard on the map and the pattern recognition module will retrieve the most recent image of the hazard (e.g., an image of a pothole captured by the optical camera) and next most recent image of the hazard (e.g., an earlier image of the same location before pot hole was formed). As will be appreciated from the description herein, various embodiments of the pattern recognition module may be configured to analyze additional road condition data to identify other road conditions. For example, as noted above, the sensing unit 121 may be configured to capture reflectivity data indicative of the reflection coefficient of a road surface. As such, the pattern recognition module may be configured to analyze any captured reflectivity data and identify data indicating an abnormal reflectivity (e.g., where the road is wet or icy). Additionally, the pattern recognition module may be configured to similarly analyze infrared data (e.g. to identify iced roads) and noise data (e.g., to identify debris or road imperfections). Furthermore, the pattern recognition module may be configured to show conditions indicated by this additional data on any generated graphical Signing representations, such as the interactive map noted above. The pattern recognition system may also be configured to identify additional conditions indicated by the road condition data. For example, in certain embodiments, the illumination level data and reflectivity data may be used to indicate weather conditions in a particular area (e.g., sunny, cloudy, raining, etc.). In addition, the condition of painted lines on roads (e.g., lane markers) may be evaluated based on captured video data, reflectivity data, or the like (e.g., to determine whether painted lines are weathered and need to be repainted). In various embodiments, the pattern recognition module may also be configured to use the hazards or conditions to calculate a road condition index representing a relative hazard level for a particular road or area. For example, in certain embodiments, the road condition index may be calculated using a predetermined function of the number of identified hazards occurring over a given length of road and/or the illumination level over a given length of road. In further embodiments, the predetermined function for calculating the road condition index may take into account the severity of the identified hazards. For example, in various embodiments, a deep pot hole indicated by surface profile data may be weighted more heavily in the road condition index calculation than a light bump indicated by the vibration data. In certain embodiments, the sensor array may also be configured to direct certain optical cameras towards road signs or mile markers and captures images indicating where other associated road condition data is being captured. Use of Road Condition Sensor Arrays in Vehicle Fleet According to various embodiments, the road condition detection system 100 may be adapted for use with a fleet of vehicles in order to provide comprehensive road condition updates. The vehicle fleet may be, for example, that of a freight or mail carrier (e.g., the United States Postal Service or United Parcel Service, Inc.), a public transportation provider (e.g., city buses and/or taxis), or one or more rental car agencies. In such embodiments, road condition sensor arrays 120 are provided on numerous vehicles in the fleet and configured to transmit captured road condition data to the central server 170. In this way, road condition data indicative of all roads on which the equipped vehicles travel can be collected and analyzed by the central server 170 (e.g., using the methods described above). By providing roads condition sensor arrays on one or more large vehicle fleets, road condition data may be captured and analyzed to indicate road conditions over a wide area. Signing In embodiments where the central server 170 receives large amounts of road condition data from road condition sensor arrays 120 in a vehicle fleet, the server’s pattern recognition module may be configured to repeat steps 202-208 for all received road condition data in order to continuously identify potential road hazards. In various embodiments, information about identified road conditions may be communicated to the Department of Transportation, local media outlets, online road condition services, directly to user devices 180, and/or stored by server 170. In addition, the pattern recognition module may be further configured to continuously update the above-described interactive map (e.g., by periodic updates in accordance with the transmission of road condition data from the onboard computers 130 to the server 170 and by immediate “alert” updates in the scenarios noted above). This updated, global interactive road map may also include calculated road condition indexes. In various embodiments, the global interactive map may be made accessible via a website or other remote application such that it can be accessed via the network 150 and viewed one a remote personal computer, smart phone, or other device. In this way, the interactive map can be accessed and viewed by drivers, government agencies, and others interested in updates on the status of potential road hazards. In further embodiments, the central server 170 may be configured for indicating potential road hazards on other map-based systems, such as Google Maps, Bing Maps, or Apple Maps. As noted above, the road condition information provided in this way may be used to plan road repairs, salting, other road maintenance, as well as to provide status updates for commuters in order to avoid traffic and potential vehicle damage.
CONCLUSION As will be appreciated from the description herein, the components and operation of the road condition detection system 100 may be modified according to various embodiments. For example, various sensing devices may be employed in the road condition sensor array’s sensing unit 121 to capture a variety of road condition data. In addition, the central server 170 may be configured accordingly to identify various hazards and other conditions based on the captured road condition data using various methods or algorithms. Moreover, according to various embodiments, the road condition data may be processed as described herein by the central server 170, the onboard computer 130, any other suitable computing device, or some combination thereof. Indeed, many modifications and other embodiments of the Signing inventions set forth herein will come to mind to one skilled in the art to which these inventions pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the inventions are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation. That which is claimed:
1. A system for detecting and monitoring road conditions, the system comprising: one or more memory storage areas comprising historical illumination data associated with particular locations on one or more road surfaces and associated with particular times of day; and one or more processors in communication with the one or more memory storage areas; wherein the one or more processors are, collectively, configured to: monitor road condition data captured by one or more road condition detection systems provided on a vehicle, the one or more road condition detection systems comprising: a vibration sensor configured to capture vibration data indicative of the magnitude and frequency of vibration of the vehicle; an optical camera comprising an aperture configured to receive light from the one or more road surfaces traveled by the vehicle: an optical sensor configured to capture illumination data associated with an intensity of the light received through the aperture; a location determining device configured 1o determine the location of the vehicle on the one or more road surfaces; Signing a real-time clock configured to indicate a time of day: capture, for storage in the one or more memory storage areas, road condition data from the one or more road condition detection systems, wherein the captured road condition data is indicative of one or more road condition attributes of the one or more road surfaces traveled by the vehicle, the road condition data comprising: vibration data from the vibration sensor; and illumination data from the optical sensor; associate location data from the location determining device and time of day data from the real-time clock with the road condition data captured by the vibration sensor and the optical sensor; retrieve the historical illumination data from the one or more memory storage areas; compare the captured illumination data with the historical illumination data corresponding to the locations and the times of day of the captured illumination data; identify one or more deviations between the captured illumination data and the historical illumination data; store data indicative of the identified one or more deviations between the captured illumination data and the historical illumination data and their respective locations in the one or more memory storage areas; identify a change in magnitude or frequency of the captured vibration data that is indicative of one or more potholes existing along the one or more road surfaces; determine, based on the captured vibration data, a severity of the identified one or more potholes; determine, based on the captured vibration data, the location of the identified one or more potholes; store data indicative of the identified one or more potholes and their respective locations in the one or more memory storage areas; and determine, based at least in part on the determined severity Signing of the identified one or more potholes, the determined location of the identified one or more potholes, and deviations between the captured illumination data and the historical illumination data, a road condition index value for a road surface, wherein the road condition index value is indicative of the quantity of the identified one or more road potholes along the road surface, the severity of each of the identified one or more potholes along the road surface, and the illumination level along the road surface.
2. The system of claim 1, wherein the one or more processors are configured to determine the location of the identified one or more potholes by temporally associating the location data with road condition attributes indicated in the captured road condition data.
3. The system of claim 1, wherein the captured road condition data comprises reflectivity data indicative of light reflectivity levels along the one or more road surfaces.
4. The system of claim 1, wherein the captured road condition data comprises video data comprising a video recording of the one or more road surfaces; and wherein the one or more processors each are configured to identify deviations in the continuity of the video recording indicative of one or more potholes along the one or more road surfaces.
5. The system of claim 1, wherein the one or more processors are further configured to generate a geographical map display indicating the location of one or more of the identified one or more potholes.
6. The system of claim 1, wherein the one or more processors are further configured to transmit the data indicative of the identified one or more potholes to one or more remote user devices; and wherein the one or more processors are further configured to generate an alert to be transmitted to the one or more remote user devices upon identifying one or more potholes.
7. The system of claim 1, wherein the optical camera is configured for capturing road condition data comprising one or more of: Signing reflectivity data indicative of light reflectivity levels along the one or more road surfaces; and video data comprising a video recording of the one or more road surfaces.
8. The system of claim 1, wherein the one or more road condition detection systems further comprise a road surface scanner configured for capturing surface profile data indicative of the surface profile of the one or more road surfaces.
9. The system of claim 1, wherein the one or more road condition detection systems comprise a front sensing unit configured for being mounted to a front portion of the vehicle and a rear sensing unit configured for being mounted to a rear portion of the vehicle aft of the front sensing unit.
10. The system of claim 9, wherein one or more sensing devices of the rear sensing unit are configured to capture road condition data corresponding to the road condition data captured by the front sensing unit to confirm the accuracy of the road condition data captured by the front sensing unit.
11. The system of claim 1, wherein the one or more processors are configured for transmitting the captured road condition data to a remote server.
12. The system of claim 1, wherein the one or more processors are further configured to identify a change in magnitude or frequency of the vibration data that is indicative of a protrusion from the road surface.
32. Mr. Rana, learned Counsel for the appellant, points out the following features of distinction, between the invention in the suit patent and D-2: S.No. Feature of the suit patent Feature of the prior art D-2
4 Works on the basis of AI Works on the basis of pattern Signing based pattern matching vis-àvis pre-existing data. matching using an on board computer on the basis of vibrations, which transmits existing road conditions to central server. Makes no reference to AI. Matching is rule based, not with reference to a trained data set.
5 Characterizes the type and severity of anomaly. Does not disclose characterization of the type and severity of anomaly.
6 Central server directly receives data from the sensing unit. Data from the sensing unit is processed by the onboard computer which then sends it to the central server.
7 No such feature. Road anomalies are classified according to severity level which is colour coded by an AI program in the central server.
33. While the subject matter of D-2 is also a system mounted on the vehicle to track road anomalies, Mr. Rana submits that the above features are unique to the subject patent and cannot be said to be either anticipated or obvious from D-2. A person skilled in the art would not, he submits, be able to arrive at the invention in the subject patent from the teachings in the suit patent without hindsight knowledge. Mr. Rana submits that, in assessing whether the later patent would be obvious or anticipated from the earlier patent, the Court is required, as per the judgment of the Division Bench of this Court in F. Hoffmann La Roche Ltd v. Cipla Ltd[2], to
(i) identify a person ordinarily skilled in the art,
(ii) identify the inventive concept embodied in the patent,
(iii) impute, to the normally skilled but unimaginative ordinary person skilled in the art what was common general knowledge in the art at the priority date,
(iv) identify the differences between the matter cited and the alleged invention and ascertain whether the differences are merely workshop improvements or actually involve inventive steps,
(v) determine whether the differences would be obvious to a person skilled in the art without having to adopt a hindsight approach. Viewed thus, Mr. Rana submits that it cannot be said that the subject patent has no inventive step vis-à-vis D-2. Analysis
34. When one reads the complete specifications in D-2 vis-à-vis the principal features of the subject patent which are claimed to be inventive, the conclusion is inevitable that all the said features are already expressly envisioned in the complete specifications in D-2. For ready reference, and at the cost of repetition, the following extracts from the complete specifications in D-2 may be noted: (i) “According to various embodiments, a road condition detection system is provided for capturing data indicative of road conditions and analysing the captured data to locate and identify various road conditions (e.g., road hazards, such as potholes, or weather conditions, such as ice). In various Signing embodiments, the road condition detection system comprises a road condition sensor array configured for being attached to a vehicle and for capturing road condition data, an onboard computer for analysing the road condition data in real time and transmitting information regarding road conditions to remote users of the system, and a central data analysis server configured for conducting post processing analysis of the data collected by the road condition sensor array to determine additional information about various road conditions.” (ii) “In various embodiments, the road sensor array is configured to sense and record information about a given road as the vehicle travels along the road. For example, the road condition sensor array may include an optical camera, a vibration sensor, a road surface scanner, and various other devices configured to capture road condition data indicative of various road condition attributes…” (iii) “The road condition sensor array may also include, or may be in communication with, a geo-location device, allowing the system to geo-code the location of road condition data indicative of these attributes.” (iv) “As described in greater detail below, the road condition data captured by the road condition sensor array may be analysed by the onboard computer in order to identify various road conditions based on the road condition data… In addition, Signing the road condition data may be analysed further by the Central server to identify additional road conditions. … In addition, the central data analysis server may be configured to create data applied to maps indicating various road conditions (e.g. layers applied to digital maps), calculate a road condition index for individual roads or areas, and compare changes in road conditions for particular roads or locations. The analysis performed by the Central server may be useful, for example, in identifying and communicating road conditions to drivers and for evaluation of road repairs and maintenance.” (v) “Fig. 1 shows a road condition detection system, according to one embodiment. In the illustrated embodiment, the road condition detection system generally comprises a road condition sensor array mounted on the vehicle, an on-board computer, and the central data analysis server (herein “central server”). As discussed in greater detail below, the on-board computer is configured to communicate with the road condition sensor array in order to control the capture and storage of road condition data. The on board computer is further configured to communicate with the central server via a communication network in order to transmit road condition data to the server for analysis. Additionally, the central server and on-board computer may be configured to communicate with one or more user devices (e.g., a mobile phone, tablet computer, digital information acquisition device, or the like) to provide updated road condition data to the user.” Signing (vi) “Fig. 2 shows a road condition sensor array mounted on the vehicle according to one embodiment. … According to various embodiments, the front sensing unit comprises various road to make detection devices, including an optical camera, a vibration sensor and a road surface scanner. As the vehicle drives along a road, the road condition sensor arrays sensing unit captures road condition data relating to the conditions of the road. For example, the captured road condition data may0020include video data, surface profile data, illumination level data, vibration data, and other data generated by other devices in the sensing unit.” (vii) “… For example, in one embodiment, the optical camera may be configured to capture video of the road surface continuously as the vehicle travels. In such embodiments, the on-board computer may continuously store video data generated by the optical camera and may be configured to buffer and transmit data to a user device.” (viii) “In various other embodiments, the sensing units and mounting housings may be provided at any suitable location on the vehicle depending on its configuration and intended use.” (ix) “In the illustrated embodiment, the on-board computer is generally configured to communicate with the road condition sensor arrays sensing units in order to (i) control when the Signing sensing units capture road condition data, (ii) store the road condition data captured by the sensing units, and (iii) transmit the stored road condition data to the central server and/or the user device. For example, in one embodiment, the on-board computer courses the sensing units to capture road condition data continuously as the vehicle travels.” (x) “In various embodiments, the road condition data captured by the road condition sensor array may be stored in the on-board computer (e.g., in the computer’s memory storage devices). For example, in certain embodiments, the on-board computer is configured to store road condition data collected by the road condition sensor array continuously as it is captured. In other embodiments, the on-board computer is configured to store road condition data collected by the road condition sensor array only if the on-board computer detects a deviation in the road condition data that may indicate the presence of a road hazard…”
35. So comprehensive, indeed, are the complete specifications of the D-2 patent that reference to further extracts therefrom is hardly necessary. A reading of the complete specifications indicates that the D-2 patent has envisioned a system for detecting road anomalies which is largely similar to that envisioned by the subject patent. The principle of a camera capturing road anomalies, which may be an audio or video camera, and which may capture anomalies in the road as the vehicle travels; the principle of the system being mounted on Signing one vehicle, vis-à-vis a multitude of vehicles; the transmission of the data captured by the camera/sensor array to the on-board computer; the diverse possibilities of the data being stored on real-time basis, vis- à-vis the data being stored on a backup platform so as to have access to historical data regarding the road; geo-profiling of the road, road conditions, and the network of roads; transmission of the data to a central server which would, either on real-time basis or on the basis of historical data, chart the anomalies in various roads; and final transmission of the data to the users so as to provide information regarding road anomalies and take remedial steps where necessary, are all fully and completely contemplated, captured and visualised by the D-2 patent. The possibility of various embodiments, in which the specifics of the various features of the system for tracking road anomalies may vary, and the specific varied features are all envisaged by the D-2 patent.
36. The aspect of obviousness, vis-à-vis prior art, has, unlike the trade mark regime, to be assessed from the point of view of a person skilled in the art who is possessed of common general knowledge as it exists on the priority date of the prior art, but who is not expected to exercise any imaginative faculties. The authority, or the Court, assessing the aspect of validity of the later patent in view of the teachings contained in the earlier patent, has to reasonably assess whether a person skilled in the art would, or would not, be able to arrive at the later patent from the teachings in the complete specifications of the earlier patent. Absolute identity of the specifications in the two patents is not what is required. What is Signing needed is sufficiency of guidance or teaching in the specifications of the earlier patent which, when coupled with the object sought to be achieved by the later patent, would arm a person skilled in the art, possessed of ordinary general knowledge as it existed on the priority date of the earlier patent, to arrive at the later patent. While trademark infringement is examined from the point of view of a person of average intelligence and imperfect recollection, the person, from whose point of view the aspect of patent infringement is to be examined, or from whose point of view the aspect of obviousness of the later patent from the earlier patent is to be assessed, is a person who is neither of average intelligence nor suffers from any imperfection in recollection. He is a person who is skilled in the art and is, therefore, vis-à-vis the art concerned, possessed of the necessary intelligence and skill as is expected of a person dealing in such matters.
37. The impugned order of the Assistant Controller has extracted certain observations from Order 250/2012 dated 2 November 2012 passed by the IPAB, which read: “Once the very subject-matter of the invention has been disclosed by the prior art… the person skilled in the art is assumed to be willing to make trial and error experiments to get it to work…” (The person) is not a person of exceptional skill and; knowledge… He must, however, be prepared to display a reasonable degree of skill and common knowledge of the art in making trials…” On the aspect of obviousness, the following observations of the IPAB had been relied upon by the Assistant Controller: “When there is a design need or market pressure to solve a the problem and (there they) are a finite number of identified, Signing predictable solutions, a person of ordinary skill in the art has as good reason to pursue the known options within his or her technical grasp. If this leads to the anticipated success, it is likely the product not of innovation but of ordinary skill and common sense…” To my mind, these observations correctly encapsulate the principle of obviousness, and the indicia of an inventive step, vis-à-vis prior art, as a requirement of a valid patent.
38. Given the weight and amplitude of the teachings in the complete specifications of the D-2 patent, I find no reason to differ with the decision of the Assistant Controller, insofar as it holds that the subject patent is invalid on the ground of obviousness and lack of inventive step, when compared with the prior art D-2. Conclusion
39. For all the aforesaid reasons, the appeal fails and is dismissed.