Description:TECHNICAL FIELD
The present subject matter is generally related to image processing and more particularly, but not exclusively, to a method and a system for detecting fugitive emissions from equipment in industrial plants in real-time using image processing techniques.

BACKGROUND
In industries, processes like solid material transfer, discharge, mixing and the like, inevitably generates dust. Effective handling of dust from these processes is a big challenge these days due to stringent environment norms. Fugitive emissions from one or more equipments from an industrial plant are unintended discharge of gas, smoke, dust and the like to the atmosphere which may adversely affect health of the surrounding people through direct (inhale) or indirect contact (water and soil). Normally de-dusting machinery is put in place to prevent this dust/emission from escaping to the environment. Monitoring the efficiency of these mechanisms is of utmost importance to remain compliant to the environmental laws and ensure prevention of dust/emission discharge to atmosphere.

The existing mechanisms implement several contact and proximity sensors for real time detection of the fugitive emission from the equipments in the industries. These sensors are very useful for very localized application but if the area to be monitored is huge, then multiple sensors may be required which increases the cost drastically. Also, often location of sensor fixing is also very challenging due to altitude, presence of vapour, gases and corroding fumes. Further, maintenance of the sensors and replacement of malfunctioned sensors is a difficult task.

The present disclosure is directed to overcome one or more limitations stated above or any other limitation associated with the conventional arts

The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY

In one non-limiting embodiment of the disclosure, a method for detecting fugitive emission from an equipment in real-time is disclosed. The method comprises receiving, by a control unit, plurality of images of the equipment from an image capturing device. Thereafter, the method comprises determining difference in intensity among the plurality of images by considering plurality of pixel in each image of the plurality of images. Once the difference in intensity is determined, the method comprises detecting in real-time fugitive emissions from the equipment when the difference in intensity is greater than a threshold value.

In an embodiment of the disclosure, the threshold value is identified based on general eruption volume of the fugitive emissions in historic images of the equipment.

In an embodiment of the disclosure, the method comprises detecting abnormal health status of the equipment upon detection of the fugitive emissions from the equipment.

In an embodiment of the disclosure, the method comprises providing notification to one or more personnel for performing corrective measures of the equipment upon detecting the fugitive emissions from the equipment.

In an embodiment of the disclosure, the plurality of images for which the difference in intensity is determined are of successive images.

In an embodiment of the disclosure, at each pixel location in each of the plurality of images the difference in intensity is determined.

In an embodiment of the disclosure, the method comprises performing image thresholding technique to determine the difference in the intensity in the plurality of images.
In another non-limiting embodiment of the disclosure, a system for detecting fugitive emission from an equipment in real-time is disclosed. The system comprises an image capturing device and a control unit. The image capturing device is configured at field of view of the equipment for capturing plurality of images of the equipment. The control unit receives the plurality of images of the equipment from the image capturing device and determines difference in intensity among the plurality of images by considering plurality of pixel in each image of the plurality of images. Thereafter, the control unit detects fugitive emissions from the equipment when the difference in intensity is greater than a threshold value.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which:

Fig.1 shows an exemplary environment for detecting fugitive emissions from equipment in real-time in accordance with some embodiments of the present disclosure;

Fig.2 shows a block diagram of a control unit in accordance with some embodiments of the present disclosure;

Fig.3a shows an exemplary illustration of vessels/equipment of an industry in accordance with some embodiments of the present disclosure;

Fig.3b shows an exemplary illustration of fugitive emission from vessels/equipments in accordance with some embodiments of the present disclosure;

Fig.3c shows a user interface for selecting date and time for viewing details of historic eruption of one or more vessels in accordance with some embodiments of the present disclosure;

Fig.4 shows a flowchart illustrating a method for detecting fugitive emissions from equipment in real-time in accordance with some embodiments of the present disclosure; and

Fig.5 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure.

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown.

DETAILED DESCRIPTION
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the specific forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.
The terms “comprises”, “comprising”, “includes”, “including” or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device, or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.
The present disclosure relates to a method and system for detecting fugitive emissions from equipment in real-time. The system comprises an image capturing device and a control unit. The image capturing device may be placed at field of view of an equipment. As an example, the equipment may be a vessel in an industry such as a steel plant. The image capturing device may capture images or videos of the equipment and provide the images or frames to the control unit. The control unit may compare successive images for determining difference in intensity by considering plurality of pixel in each of the successive images. In some embodiments, at each pixel location in the successive images, the difference in intensity is determined. Once the difference in intensity is determined, the control unit may detect fugitive emissions from the equipment when the difference in intensity is greater than a threshold value. The threshold value may be identified based on general eruption volume of the fugitive emissions in historic images of the equipment. When the fugitive emissions are detected from the equipment, the control unit may detect abnormal health status of the equipment and also provide notification to one or more personnel for performing corrective measures of the equipment. In this manner, the present disclosure provides real-time detection of fugitive emissions from the equipment using image processing techniques to identify equipment failure and to perform corrective measures quickly.

Fig.1 shows an exemplary environment for detecting fugitive emissions from equipment in real-time in accordance with some embodiments of the present disclosure.

The environment 100 may include an equipment 101, an image capturing device 103, a control unit 105 and a database 107. As an example, the equipment 101 may be a vessel in an industry such as a steel plant. The image capturing device 103 may be a camera placed near field of view of the equipment 101. As an example, an industrial machine vision camera along with compatible leans may be selected based on field of view and distance of the equipment 101. The image capturing device 103 may capture images or videos of the equipment 101 and transmit the images or the videos to the control unit 105. The control unit 105 processes the images or frames in the video to detect plumes of dust or fugitive emission from the equipment 101. In some embodiments, the control unit 105 may implement one or more filters for preprocessing each frame or the image to remove noises. The control unit 105 may compare the successive images received from the image capturing unit to determine difference in intensity. In some embodiments, the control unit 105 may implement thresholding technique to determine the difference in the intensity in the successive images. At each pixel location in the successive frames or the images, the control unit 105 may determine difference in intensity. Once the difference in intensity is determined, the control unit 105 may compare the intensity with a threshold value stored in the database 107 associated with the control unit 105. The threshold value may be identified based on general eruption volume of the fugitive emissions in historic images of the equipment 101. When the difference in intensity is greater than the threshold value, the control unit 105 may detect the fugitive emissions from the equipment 101. Once the fugitive emissions are detected, the control unit 105 may detect abnormal health status of the equipment 101 and provide notifications 109 to one or more personnel for performing corrective measures of the equipment 101. The fugitive emissions from the equipment 101 is associated with health status of the equipment 101. In one embodiment the control unit 105 may provide the notifications 109 when the difference in intensity is greater than the threshold.
Fig.2 shows a block diagram of a control unit 105 accordance with some embodiments of the present disclosure.
In some implementations, the control unit 105 may include I/O Interface 201, a processor 203and a memory. The I/O Interface 201 may be configured to receive the images from the image capturing device 103 and to provide one or more notifications 109. The processor 203may be configured to receive the image and process the image for detecting fugitive emissions from the equipment 101. The control unit 105 may include data and modules. As an example, the data is stored in a memory 205 configured in the control unit 105 as shown in the Fig.2. In one embodiment, the data may include image data 207, threshold data 209, health status data 211 and other data 215. In the illustrated Fig.2, modules are described herein in detail.

In some embodiments, the data may be stored in the memory 205 in form of various data structures. Additionally, the data can be organized using data models, such as relational or hierarchical data models. The other data 215 may store data, including temporary data and temporary files, generated by the modules for performing the various functions of the control unit 105
In some embodiments, the data stored in the memory 205 may be processed by the modules of the control unit 105. The modules may be stored within the memory. In an example, the modules communicatively coupled to the processor 203 configured in the control unit 105, may also be present outside the memory 205 as shown in Fig.2 and implemented as hardware. As used herein, the term modules may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory 205 that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
In some embodiments, the modules may include, for example, a receiving module 217, intensity determination module 219, fugitive emission detection module 221, health status detection module 223, notification module 225 and other modules 227. The other modules 227 may be used to perform various miscellaneous functionalities of the control unit 105. It will be appreciated that such aforementioned modules may be represented as a single module or a combination of different modules.
In some embodiments, the other modules 227 may be used to perform various miscellaneous functionalities of the control unit 105. It will be appreciated that such modules may be represented as a single module or a combination of different modules. Furthermore, a person of ordinary skill in the art will appreciate that in an implementation, the one or more modules may be stored in the memory, without limiting the scope of the disclosure. The said modules when configured with the functionality defined in the present disclosure will result in a novel hardware.

In some embodiments, the receiving module 217 may be configured to receive plurality of images or image frames of the equipment 101 from an image capturing device 103. The Image capturing device 103 may be placed near field of view (FOV) of the equipment 101 to capture images or video of the equipment 101. In one embodiment the image or the video is captured in periodic intervals. The captured images or the frames may be provided to the control unit 105 for further processing to detect fugitive emissions from the equipment 101. The images or the frames may be stored as image data 207.
In some embodiments, the intensity determination module 219 may be configured to determine difference in intensity among the plurality of images. The intensity determination module 219 may pre-process the received images to remove noise. The intensity determination module 219 may consider successive images and may generate three accumulator difference images such as A, A+ and A- as shown below wherein in these images difference in intensity at each pixel location is identified. As an example, the image I= f(x,y,t) may represent the image at a time instant t and (x, y) may represent coordinate of the pixels.

A(x,y) = {¦(A_(t-1) (x,y)+1; if |f(x,y,t)-f(x,y,t-1)| > d @A_(t-1) (x,y) ;if not )¦ ……… (1)
A^+ (x,y)= {¦(?A^+?_(t-1) (x,y)+1; if (f(x,y,t)-f(x,y,t-1)) > d @?A^+?_(t-1) (x,y) ; if not )¦………. (2)
A^- (x,y)= {¦(?A^-?_(t-1) (x,y)+1; if (f(x,y,t)-f(x,y,t-1)) < -d @?A^-?_(t-1) (x,y) ;if not )¦ ………. (3)

Wherein:
A (x,y) is the accumulator image based on absolute difference between successive frames
A+ (x,y) is the accumulator image based on positive difference between successive frames
A- (x,y) is the cccumulator image based on negative difference between successive frames

The successive images may be compared with a threshold value such as d. The d indicates change in intensity at a pixel location in the successive images. The intensity determination module 219 may identify eruption or fugitive emission from the equipment 101 if there are any changes in the accumulator images over a predefined time window such as t, t-1. In an embodiment, the intensity determination module 219 may identify the pixel location at which the difference in intensity is determined using an image segmentation technique such as for example thresholding technique. The thresholding can be mathematically expressed as given below.
Q^G (Final)={¦(1; if Q(i,j) > T @0; if Q(i,j)< T)¦

Wherein: QG is any of the accumulator images (A, A+, A-) and T is the threshold limit for pixels in the accumulator images. The threshold value may be identified based on general eruption volume of the fugitive emissions in historic images of the equipment 101. The threshold value may be stored as threshold data 209.

As an example, the received images may be treated as a two-dimensional array. Consider a number of images I1, I2, I3.
I_1= [¦(125&214&65@98&255&200@170&100&189)]
I_2= [¦(100&135&217@75&85&198@200&165&90)]
I_3= [¦(137&100&200@50&125&160@184&170&150)]
In an embodiment, if we need to track the difference between respective elements of two successive arrays then the accumulator array Ia is defined as: if the difference between successive elements between two arrays is more than a certain threshold value and then the corresponding value in accumulator array is incremented by one. Let Ia be the accumulator array which is initialized with zeros for all elements. Considering difference between I1 and I2,
I_a= [¦(1&1&0@1&1&0@0&0&1)]
Again, if we consider difference between I2 and I3 and increment/decrement the accumulator, I_a= [¦(1&2&1@2&1&1@1&0&1)].
In this manner, we can have values in accumulator change as more images come in. When the accumulator values reach certain threshold, conclusions can be made. Now the accumulator can be based on absolute difference, or positive difference or negative difference such as A, A+ and A-.

In some embodiments, the fugitive emission detection module 221 may compare the difference in intensity with the threshold value T. If the difference in intensity is greater than T, then the fugitive emission detection module 221 may detect fugitive emission from the equipment 101. If the difference in intensity is less than T, then the fugitive emission detection module 221 may detect absence of fugitive emission from the equipment 101. In one embodiment a predefined number of images or a video for a predefined time may be used to determine the fugitive emission.

In some embodiments, the health status detection module 223 may detect the health of the equipment 101 to be normal when there is absence of fugitive emissions from the equipment 101. However, the health status detection module 223 may detect abnormal status of the equipment 101 upon detecting fugitive emissions from the equipment 101. The health status information may be stored as health status data 211.

In some embodiments, the notification module 225 may be configured to send notifications 109 to one or more personnel associated with the equipment 101 upon detecting fugitive emissions from the equipment 101. Upon receiving the notification 109, the one or more personnel may perform corrective measures on the equipment 101.

Fig.3a shows an exemplary illustration of vessels of a steel plant in accordance with some embodiments of the present disclosure. Fig.3a shows three vessels or equipment 101s namely, vessel 1, vessel 2 and vessel 3 of a steel plant. The Table 1 below shows current process status of each of the vessels in the steel plant.

Vessel ID Status Oxygen % Vent Open Skirting gap ORE North ORE South
Vessel 1 No operation
Vessel 2 Blow Start 90.37 60 651 0 0
Vessel 3 Blow Start 30.91 72 273 0 0

Table 1

Fig.3b shows an exemplary illustration of fugitive emission from vessels in accordance with some embodiments of the present disclosure. As shown in Fig.3b fugitive emission is detected from vessel 2. Therefore, the current status of each of the vessels is as shown in below Table 2.

Eruption Start Time Eruption End Time Vessel ID Status Oxygen Vent Open Skirting gap ORE North ORE South
Vessel 1 No operation
26/11/2019- 2:38:24 PM 26/11/2019- 2:39:09 PM Vessel 2 Blow Start 90.37 60 651 0 0
Vessel 3 No operation

Table 2
The Table 2 indicates that there is a fugitive emission detected from vessel 2 and Table 2 also indicates start time and end time of the fugitive eruption.

Fig.3c shows a user interface 301 for selecting date and time for viewing details of historic eruption of one or more vessels in accordance with some embodiments of the present disclosure. As shown in Fig.3c, the user may select any specific date and time to view the historic eruptions of one or more vessels in the steel plant. As an example, there may be three vessels namely, vessel 1, vessel 2 and vessel 3 and the user may select the date as “26/11/2019 and time as “3:48:38 PM”. The user interface 301 may show a display area/vessel area for displaying the vessels of the steel plant and also show table indicating process status of each of the vessels. The black and white image on the right is the result of applying image processing algorithm. Black portions are where there is no dust. White portions are where dust presence is detected with intensity above a certain threshold.

Fig.4 shows a flowchart illustrating a method for detecting fugitive emissions from an equipment 101 in accordance with some embodiments of the present disclosure.

As illustrated in Fig.4, the method 400 includes one or more blocks illustrating a method for detecting fugitive emissions from an equipment 101. The method 400 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform specific functions or implement specific abstract data types.

The order in which the method 400 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the spirit and scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

At block 401, the method may include receiving plurality of images of the equipment 101 from the image capturing device 103. The image capturing device 103 may capture images or videos of the equipment 101 and transmit the images or the videos to the control unit 105.
At block 403, the method may include determining difference in intensity among the plurality of images by considering plurality of pixel in each image of the plurality of images. The control unit 105 may compare the successive images received from the image capturing unit to determine difference in intensity. In an embodiment, the control unit 105 may implement thresholding technique to determine the difference in the intensity in the successive images. At each pixel location in the successive frames or the images, the control unit 105 may determine difference in intensity.
At block 405, the method may include detecting fugitive emissions from the equipment 101. Once the difference in intensity is determined, the control unit 105 may compare the intensity with a threshold value. The threshold value may be identified based on general eruption volume of the fugitive emissions in historic images of the equipment 101. When the difference in intensity is greater than the threshold value, the control unit 105 may detect the fugitive emissions from the equipment 101.

In some embodiments, once the fugitive emissions are detected, the control unit 105 may detect abnormal health status of the equipment 101 and provide notifications 109 to one or more personnel for performing corrective measures of the equipment 101. The fugitive emissions from the equipment 101 is associated with health status of the equipment 101.
Computer System

Fig.5 illustrates a block diagram of an exemplary computer system 500 for implementing embodiments consistent with the present disclosure. In an embodiment, the computer system 500 may be a control unit 105, which is used for detecting fugitive emissions from an equipment 101. The computer system 500 may include a central processing unit (“CPU” or “processor”) 502. The processor 502 may comprise at least one data processor for executing program components for executing user or system-generated business processes. The processor 502 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.
The processor 502 may be disposed in communication with one or more input/output (I/O) devices (511 and 512) via I/O interface 501. The I/O interface 501 may employ communication protocols/methods such as, without limitation, audio, analog, digital, stereo, IEEE-1394, serial bus, Universal Serial Bus (USB), infrared, PS/2, BNC, coaxial, component, composite, Digital Visual Interface (DVI), high-definition multimedia interface (HDMI), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System For Mobile Communications (GSM), Long-Term Evolution (LTE) or the like), etc. Using the I/O interface 501, the computer system 500 may communicate with one or more I/O devices 511 and 512. The computer system 500 may receive an image for processing from an image capturing device 103.
In some embodiments, the processor 502 may be disposed in communication with a communication network 509 via a network interface 503. The network interface 503 may communicate with the communication network 509. The network interface 503 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), Transmission Control Protocol/Internet Protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc.
The communication network 509 can be implemented as one of the several types of networks, such as intranet or Local Area Network (LAN) and such within the organization. The communication network 509 may either be a dedicated network or a shared network, which represents an association of several types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the communication network 509 may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.
In some embodiments, the processor 502 may be disposed in communication with a memory 505 (e.g., RAM 513, ROM 514, etc. as shown in Fig. 5) via a storage interface 504. The storage interface 504 may connect to memory 505 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as Serial Advanced Technology Attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fiber channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.
The memory 505 may store a collection of program or database components, including, without limitation, user /application 506, an operating system 507, a web browser 508, mail client 515, mail server 516, web server 517 and the like. In some embodiments, computer system 500 may store user /application data 506, such as the data, variables, records, etc. as described in this invention. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as OracleR or SybaseR.
The operating system 507 may facilitate resource management and operation of the computer system 500. Examples of operating systems include, without limitation, APPLE MACINTOSHR OS X, UNIXR, UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTIONTM (BSD), FREEBSDTM, NETBSDTM, OPENBSDTM, etc.), LINUX DISTRIBUTIONSTM (E.G., RED HATTM, UBUNTUTM, KUBUNTUTM, etc.), IBMTM OS/2, MICROSOFTTM WINDOWSTM (XPTM, VISTATM/7/8, 10 etc.), APPLER IOSTM, GOOGLER ANDROIDTM, BLACKBERRYR OS, or the like. A user interface may facilitate display, execution, interaction, manipulation, or operation of program components through textual or graphical facilities. For example, user interfaces may provide computer interaction interface elements on a display system operatively connected to the computer system 500, such as cursors, icons, check boxes, menus, windows, widgets, etc. Graphical User Interfaces (GUIs) may be employed, including, without limitation, APPLE MACINTOSHR operating systems, IBMTM OS/2, MICROSOFTTM WINDOWSTM (XPTM, VISTATM/7/8, 10 etc.), UnixR X-Windows, web interface libraries (e.g., AJAXTM, DHTMLTM, ADOBE® FLASHTM, JAVASCRIPTTM, JAVATM, etc.), or the like.

Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present invention. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, nonvolatile memory, hard drives, Compact Disc (CD) ROMs, Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media.
In an embodiment, the present disclosure provides a method and system for detecting fugitive emissions from equipment in real-time.

In an embodiment, the present disclosure implements image-based system for detecting fugitive emissions from an equipment and hence capable of covering large area as well as capable of accessing inaccessible locations for detection.

In an embodiment, the present disclosure implements image-based system rather than implementing sensors for detection of fugitive emissions and hence the method of present disclosure is cost efficient, maintenance free and safe.

In an embodiment, the present disclosure detects fugitive emission from the equipment which is associated with health status of the equipment and hence provides a mechanism for performing corrective measure quickly.
The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.

The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise. The enumerated listing of items does not imply that any or all the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

When a single device or article is described herein, it will be clear that more than one device/article (whether they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether they cooperate), it will be clear that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral Numerals:
Reference Number Description
100 Environment
101 Equipment
103 Image capturing device
105 Control unit
107 Database
109 Notification
201 I/O Interface
203 Processor
205 Memory
207 Image data
209 Threshold data
211 Health status data
215 Other data
217 Receiving module
219 Intensity determination module
221 Fugitive emission detection module
223 Health status detection module
225 Notification module
227 Other modules
301 User Interface
500 Exemplary computer system
501 I/O Interface of the exemplary computer system
502 Processor of the exemplary computer system
503 Network interface
504 Storage interface
505 Memory of the exemplary computer system
506 User /Application
507 Operating system
508 Web browser
509 Communication network
511 Input devices
512 Output devices
513 RAM
514 ROM
515 Mail Client
516 Mail Server
517 Web Server

Claims:We claim:
1. A method for detecting fugitive emissions from equipment 101 in real-time, the method comprising:
receiving, by a control unit 105, plurality of images of the equipment 101 from an image capturing device 103;
determining, by the control unit 105, difference in intensity among the plurality of images by considering plurality of pixel in each image of the plurality of images; and
detecting in real-time, by the control unit 105, fugitive emissions from the equipment 101 when the difference in intensity is greater than a threshold value.
2. The method as claimed in claim 1, wherein the threshold value is identified based on general eruption volume of the fugitive emissions in historic images of the equipment 101.

3. The method as claimed in claim 1 further comprises detecting abnormal health status of the equipment 101 upon detection of the fugitive emissions from the equipment 101.

4. The method as claimed in claim 1 comprises providing notification 109 to one or more personnel for performing corrective measures of the equipment 101 upon detecting the fugitive emissions from the equipment 101.

5. The method as claimed in claim 1, wherein the plurality of images for which the difference in intensity is determined are of successive images.

6. The method as claimed in claim 1, wherein at each pixel location in each of the plurality of images the difference in intensity is determined.

7. The method as claimed in claim 1 performs image thresholding technique to determine the difference in the intensity in the plurality of images.

8. A system for detecting fugitive emissions from equipment 101 in real-time, the system comprising:
an image capturing device 103 configured at field of view of the equipment 101 for capturing plurality of images of the equipment 101;
a control unit 105 configured to:
receive the plurality of images of the equipment 101 from the Image capturing device 103;
determine difference in intensity among the plurality of images by considering plurality of pixel in each image of the plurality of images; and
detect fugitive emissions from the equipment 101 when the difference in intensity is greater than a threshold value.
9. The system as claimed in claim 8, wherein the control unit 105 identifies the threshold value based on general eruption volume of the fugitive emissions in historic images of the equipment 101.

10. The system as claimed in claim 8, wherein the control unit 105 detects abnormal health status of the equipment 101 upon detection of the fugitive emissions from the equipment 101.

11. The system as claimed in claim 8, wherein the control unit 105 provides notification 109 to one or more personnel for performing corrective measures of the equipment 101 upon detecting the fugitive emissions from the equipment 101.

12. The system as claimed in claim 8, wherein the plurality of images for which the control unit 105 determines difference in intensity are successive images.

13. The system as claimed in claim 8, wherein the control unit 105 implements image thresholding technique to determine the difference in intensity in the plurality of images.

14. The system as claimed in claim 8, wherein the control unit 105 determines the difference in intensity at each pixel location in each of the plurality of images.