Audertec Solutions Llp vs. Controller General Of Patents, Designs And Trade Marks & Anr.

$~(Original)
* IN THE HIGH COURT OF DELHI AT NEW DELHI
+ 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.
Versus
CONTROLLER GENERAL OF PATENTS,
DESIGNS AND TRADE MARKS & ANR. ..... Respondents
Through: Mr. Harish Vaidyanathan
Shankar, CGSC, Mr. Srish Kumar Mishra,
Mr. Sagar Mehlawat and Mr. Alexander
Mathai Paikaday, Advs.
CORAM:
HON'BLE MR. JUSTICE C. HARI SHANKAR
J U D G M E N T
% 01.03.2024
C.A.(COMM.IPD-PAT) 3/2021
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
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the claim in the application suffers from want of inventive step vis-a-
vis 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:
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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.
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[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 due to sudden application of brakes
occur
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 B1 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 US20180068495A1 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
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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
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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 well-
known functions and constructions are omitted for clarity and
conciseness
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[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 130-
degree 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
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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 name of the roads featuring distress spots and
the
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
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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-blox7 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 i7 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
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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 bi-
dimensional 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.
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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.
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 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 re-
surfaced 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.
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 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.
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 Enabling report generation that details out the near-
exact 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
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- 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:
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-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.
th
Dated this 19 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
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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:
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(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.
(b) The camera has
(i) a WDR function which adjusts to ambient light
(ii) a G – sensor for image stabilisation in the case of
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jerk.
(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.
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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
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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,
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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 geo-
tagged, 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
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travel and press ‘Start’. When he does so, the system identifies his
1
existing location, destination location and selects the best route .
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
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1
This, it may be noted , is similar to the GPS system frequently used by drivers.
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BACKGROUND OF THE INVENTION
Field of the Invention

Description of Related Art

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BRIEF SUMMARY OF THE INVENTION

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
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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
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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
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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 121 a housed within a detachable
front mounting housing 122 a, and a rear sensing unit 121 b housed
within a detachable rear mounting housing 122 b. According to
various embodiments, the front sensing unit 121 a 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
121 a 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
121 a. 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 121 a and store captured road condition data.
In various embodiments, the sensing unit 121 a 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 .
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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 11 0 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 121 a may
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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 121 a 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 low-
magnitude, 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 121 a
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 121 a 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
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121 ¢ are secured within a mounting housing 122 a. In the illustrated
embodiment, the mounting housing 122 a 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 121 a 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 121 b secured within a
rear mounting housing 122 b. According to various embodiments,
the rear sensing unit 121 b may comprise the same, or one or more
of, the various sensors and detection devices provided in the front
sensing unit 121 a. In addition, the rear mounting housing 122 b
may be substantially the same as, or similar to, the front mounting
housing 122 a. As will be appreciated from FIG. 2 , the provision of
both front and rear sensing units 121 a, 122 b 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 121 b may be configured to
capture road condition data to confirm road conditions indicated by
the road condition data captured by the front sensing unit 121 a.
In various other embodiments, the sensing units 121 a, 121 b
and mounting housings 122 a, 122 b 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 121 a, 121 b may be controlled by the
vehicle’s onboard computer 130 . In various embodiments, the
onboard computer 130 comprises at least one processor, a location-
determining device or sensor (e.g., a GPS sensor), a real-time
clock, J-Bus protocol architecture, an electronic control module
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(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 geo-
location 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 121 a, 121 b in order to (i) control when
the sensing units 121 a, 122 b capture road condition data, (ii) store
the road condition data captured by the sensing units 121 a , 122 b ,
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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 121 a, 122 b to
capture road condition data continuously as the vehicle 110 travels.
In other embodiments, the onboard computer 130 causes the
sensing units 121 a , 122 b 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 121 a, 122 b 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 121 a, 122 b 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
121 a, 122 b 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 121 a, 122 b 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 121 a, 122 b 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
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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
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central server 170 ) may be further configured to transmit the alert-
status 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
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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
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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
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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 user-
specified 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
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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.
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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.
As shown in FIG. 4, if the pattern recognition module does
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
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illumination level deviations or abnormalities).
As shown in FIG. 4 , if the pattern recognition module does
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
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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.
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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
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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;
and
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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
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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:

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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
2
La Roche Ltd v. Cipla Ltd , to
(i) identify a person ordinarily skilled in the art,
(ii) identify the inventive concept embodied in the patent,
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2
2015 SCC OnLine Del 13619
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(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
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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,
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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.”
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(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
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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
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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
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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,
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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.
C.HARI SHANKAR, J
MARCH 1, 2024
rb/dsn
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