AU2021104849A4 - A Computer implemented method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning - Google Patents
A Computer implemented method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning Download PDFInfo
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- AU2021104849A4 AU2021104849A4 AU2021104849A AU2021104849A AU2021104849A4 AU 2021104849 A4 AU2021104849 A4 AU 2021104849A4 AU 2021104849 A AU2021104849 A AU 2021104849A AU 2021104849 A AU2021104849 A AU 2021104849A AU 2021104849 A4 AU2021104849 A4 AU 2021104849A4
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- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000010801 machine learning Methods 0.000 title claims abstract description 34
- 230000005540 biological transmission Effects 0.000 claims abstract description 26
- 238000004891 communication Methods 0.000 claims abstract description 16
- 230000000246 remedial effect Effects 0.000 claims abstract description 15
- 238000010586 diagram Methods 0.000 claims abstract description 9
- 238000012360 testing method Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 241000711573 Coronaviridae Species 0.000 abstract description 23
- 208000015181 infectious disease Diseases 0.000 abstract description 14
- 238000011109 contamination Methods 0.000 abstract description 10
- 230000008520 organization Effects 0.000 abstract description 6
- 230000007480 spreading Effects 0.000 abstract description 4
- 230000002458 infectious effect Effects 0.000 description 6
- 238000001514 detection method Methods 0.000 description 5
- 239000003795 chemical substances by application Substances 0.000 description 4
- 244000052769 pathogen Species 0.000 description 4
- 208000035473 Communicable disease Diseases 0.000 description 3
- 208000001528 Coronaviridae Infections Diseases 0.000 description 3
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Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
- G08B13/19613—Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B15/00—Identifying, scaring or incapacitating burglars, thieves or intruders, e.g. by explosives
Abstract
A Computer implemented method and system for
detecting human touch using body mounted camera
to minimize covid spread using machine learning
The present invention is related to a computer implemented method and
system for detecting the touch using body mounted front facing display
camera for minimizing the spread of coronavirus/covid. In the current scenario
of covid pandemic, workplaces like hospitals, educational institutions, offices
etc. are vulnerable places for their workers as the coronavirus/covid can
survive on surface or object for many hours. The touch on said surfaces can
drastically increase the infection of coronavirus/covid. The touch identification
of said surfaces or objects can minimize the spread of coronavirus/covid and
provide a safe environment for employees or workers of an organization. The
object of the present invention is to track touches in order to analyze paths of
transmission and contamination for eliminating the spread of covid infection.
The method and system comprise front facing body mounted recording and
display devices for recording the touches on identified surfaces, objects and
persons. The information of touches is automatically analyzed and stored to
the touch database communicated through intra-body near field
communication network and personal area network. The method further
comprises generating a transmission graph from the recorded touches in the
database and analyzing the touch graph to identify the transmission paths
using machine learning algorithms and take remedial action based on the risk
associated with the identified transmission paths. In this way, a safe and
healthier environment can be provided to the employee of an organization and
risk of spreading coronavirus/covid can be minimized. The present invention is
very useful in the current scenario of coronavirus/covid pandemic.
recording the touches using the front facing body mounted display
camera (201)
periodically transmitting the recorded touches to the database of central
server through intra-body near field communication network (202)
generating the transmission graph of touches using the data stored in
the database (203)
analyzing the transmission path using machine learning model and
take remedial action accordingly (204)
Figure 2 - Flow-diagram of the method for automatically detecting human touch using body
mounted front facing camera in accordance with present invention
2
Description
recording the touches using the front facing body mounted display camera (201)
periodically transmitting the recorded touches to the database of central server through intra-body near field communication network (202)
generating the transmission graph of touches using the data stored in the database (203)
analyzing the transmission path using machine learning model and take remedial action accordingly (204)
Figure 2 - Flow-diagram of the method for automatically detecting human touch using body mounted front facing camera in accordance with present invention
A Computer implemented method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning
[0001] The present invention relates to data processing and information Technology. The field of the invention is to detect the touch on the surfaces within premises to minimize the spread of coronavirus/covid.
[0002] More particularly, this present invention is in the field of detecting human touch using body mounted camera to minimize covid spread using machine learning to provide a safe premise in this global pandemic.
[0003] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in-and-of-themselves may also be inventions.
[0004] In the current scenario of coronavirus or covid pandemic, the movement of public or social distancing plays a important role. The one way of restricting the spread of coronavirus disease is maintaining proper social distancing. Along with maintaining social distancing, it is important to track the touch within the workspace so that the user will not come under the contact of coronavirus infection due to touch. As we all know that the coronavirus is an infectious disease and it spread with the touch of infectious person or surface. Thus, this is necessary to minimize the touch on infectious surfaces or persons. Further, as we all know that this pandemic is not a matter of one or two days. The coronavirus disease will last for many years and the people need to minimize the touch so that this infection will not spread. In this global pandemic, the spread of coronavirus can be minimized by wearing mask, maintain social distancing and minimizing the touch to the infectious surface. Wearing a mask and maintaining social distancing is the responsibility of one's but identifying the touch to minimize the spread of coronavirus/covid is an essential task in this global pandemic.
[0005] In this global pandemic, people are bound to go to their workspaces or workplaces and perform their duties towards organization. There are various people works in an organization and they spent almost 9-10 working hours in their workplaces. Thus, detecting the infectious surfaces and minimizing the spread by detection of such surface is one of the most important need in this global pandemic era. But, manually identifying such surfaces in close premises or workplaces is not possible. It needs to be done with the use of technology. The identification of such infectious surfaces in the workplaces need to be automated and accordingly remedial action need to be taken.
[0006] one such way to perform this automation is by use of machine learning models. Machine learning models are one of the most advanced and current technology which is used for automation. There are various kinds of machine learning models used for providing automation or artificial intelligence which are broadly divided in two types namely supervised learning and unsupervised learning. Machine learning is a way to provide machine human like intelligence in the trained field and behaves like a human. Hence, there is a need of a method to detect the human touch within the premises or workplaces to minimize the spread of coronavirus/covid. There are various methods used in the prior art to restrict the movement of user terminals and detect the coronavirus infection in a user which are as follows:
[0007] US20130122807 Al - A method for effecting good hygiene practices to achieve highest possible safety levels in institutional environments. It is also an object of at least some embodiments of the present invention to provide an improved real-time method and system for controlling healthcare delivery processes within a clinical environment, and, preferably, to increase the efficiency and safety of common healthcare delivery processes in a clinical setting by collecting a real-time system (RTS) location and other data as well as other event data.
[0008] EP1973579 Al- A germicidal surface-covering assembly that includes at least two different donnable or drapable garments. Each garment defines at least one treated surface that is susceptible to pathogen contamination in a physical contamination event when used as intended in an environment subject to contamination (e.g., a clinical environment, a laboratory or a workplace). Each treated surface is adapted to provide a time-dependent reduction in the number of pathogens available at that treated surface after a physical contamination event, such that at least a predetermined time after a physical contamination event at a first location on a first treated surface of a first garment, a first physical contact between the first location on the first treated surface and a second location on a second treated surface of a second garment results fewer viable pathogens on the second treated surface as compared to an untreated control. Moreover, at least a predetermined time after the first physical contact, a second physical contact between the second location on the second treated surface and a third location on a third treated surface of a third garment results in fewer viable pathogens on the third treated surface as compared to an untreated control.
[0009] US2013035900 Al - A method for promoting a hygiene in an away from-home location, said method comprising conducting an initial evaluation of the away-from-home location using a test protocol to collect initial data and determine an initial level of contamination at various locations within the away-from-home location; evaluating collected data to identify specific needs and/or areas of focus within the away-from-home location; developing a plan of action to address the specific needs and/or areas of focus for the away from-home location; re-evaluating the away-from-home location after a period of time by repeating the test protocol to collect secondary data to determine the second level of contamination within the away-from-home location; evaluating the secondary data as compared to the initial data; and providing feedback to the away-from-home location by conveying a change in the level of contamination at the various locations over the period of time.
[0010] US2011094289 Al - A method and apparatus for contaminant detection of body parts, such as hands, and or their coverings, such as clean room suits or gloves, and small objects. Particularly, the method and apparatus involve collecting air samples containing aerosolized contaminate particles from the objects and analyzing the sample for presence of a contaminate. Aerosol lab-on-a-chip and/or electronic nose devices are utilized for the detection of contaminant particles.
[0011] US8525666 B2 - A method is provided for monitoring use of handwashing agents to determine compliance with hand hygiene guidelines. A handwashing agent is provided with a detectable, volatile compound, such as odours, which is then rubbed onto a subject's hands using the subject's handwashing technique. After the handwashing event, the subject's hand is then exposed to an detector (such as a badge), which includes a sensor capable of detecting the volatile compound, and an indicator that communicates detection of the volatile compound, indicating use of the handwashing agent and hand hygiene compliance.
[0012] US2011093249 Al - an integrated health care surveillance and monitoring system that provides real-time sampling, modeling, analysis, and recommended interventions. The system can be used to monitor infectious and chronic diseases. When faced with outbreak of an infectious disease agent, e.g., influenza virus, the system can identify active cases through pro-active sampling in high-risk locations, such as schools or crowded commercial areas. The system can notify appropriate entities, e.g., local, regional and national governments, when an event is detected, thereby allowing for proactive management of a possible outbreak. The system also predicts the best response for deployment of scarce resources.
[0013]Therefore, there is a need in the state of the art for a method and system for automatically detecting the touch and take remedial action accordingly to minimize the spread of coronavirus/covid. So that the probability of spreading coronavirus is reduced and there is a need for a method for detecting the covid infection at prelim stage.
[0014] Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markus groups used in the appended claims.
[0015] As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictate otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.
[0016] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context.
[0017] The use of any and all examples, or exemplary language (e.g. "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[0018] The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.
[0019] Before the present systems and methods, are described, it is to be understood that this application is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the present application. This summary is provided to introduce concepts related to systems and methods for Sybil detection in web data and the concepts are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[0020] The present invention mainly solves the technical problems existing in the prior art. In response to these problems, the present invention discloses a method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning. The objective of the invention is to minimize the spread of coronavirus by supervising the touch of user within a premise and take remedial action accordingly so that the spread of coronavirus or covid infection can be minimized. This feature help to minimize the spread of coronavirus in a office/college buildings.
[0021] The object of the present invention is to automatically detect to touch on the surface of the workplaces and take remedial action accordingly using body mounted front facing camera and machine learning models. The present invention comprises a body mounted front facing display camera which is used to record the touch of the surfaces of each and individuals within the premise and the same is also used to display the message given by proposed system to the users to minimize the spread of infection. Each and every individual of the workplace is registered to the system and attached with particular body mounted front facing camera to record the touches. Further, the said system is equipped with machine learning models. The present invention comprises a central server connecting to a database. The central server is trained using the adopted machine learning model. The central server or machine learning model on the central server is trained using the past data of touches or test cases stored in the database which help the said system to automatically detect the touch within the premise and suggest the remedial action accordingly so that the spread of coronavirus infection can be minimized.
[0022] An aspect of the present disclosure relates to a method for detecting the human touch using body mounted front facing camera to minimize the covid spread, the method comprising front facing body mounted recording and display devices for recording the touches on identified surfaces, objects and persons. The information of touches are automatically send and analyzed and stored to the touch database communicated through intra-body near field communication network and personal area network. The method further comprises generating a transmission graph from the recorded touches in the database and analyzing the touch graph to identify the transmission paths using machine learning algorithms and take remedial action based on the risk associated with the identified transmission paths. In this way, a safe and healthier environment can be provided to the employee of an organization and risk of spreading coronavirus/covid can be minimized. This feature help to minimize the spread of coronavirus in a office/college buildings.
[0023]An aspect of the present disclosure relates to a system for detecting the human touch using body mounted front facing camera to minimize the covid spread, the method comprising front facing body mounted recording and display devices for recording the touches on identified surfaces, objects and persons. The information of touches are automatically send and analyzed and stored to the touch database communicated through intra-body near field communication network and personal area network. The method further comprises generating a transmission graph from the recorded touches in the database and analyzing the touch graph to identify the transmission paths using machine learning algorithms and take remedial action based on the risk associated with the identified transmission paths. In this way, a safe and healthier environment can be provided to the employee of an organization and risk of spreading coronavirus/covid can be minimized.
[0024] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
[0025] The primary objective of the present invention is to provide a method and system for detecting the huma touch using front facing body mounted camera and machine learning technique by analyzing the transmission and contamination path so that the risk of infection can be minimized. Further, the objection of the present invention to automatically provide the remedial action accordingly based on the determined transmission paths. This feature help to minimize the spread of coronavirus in a office/college buildings.
[0026] To clarify various aspects of some example embodiments of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It is appreciated that these drawings depict only illustrated embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings.
[0027] In order that the advantages of the present invention will be easily understood, a detail description of the invention is discussed below in conjunction with the appended drawings, which, however, should not be considered to limit the scope of the invention to the accompanying drawings, in which:
[0028] Figure 1 show a block-diagram representing embodiments of the system in accordance with the present invention.
[0029] Figure 2 shows a flow-diagram of the method for detecting human touch using body mounted front facing camera and machine learning model in accordance with the present invention.
[0030] The present invention is related to a method for automatically detecting the human touch on the surface using body mounted front facing camera and machine learning model.
[0031] Figure 1 show a flow-diagram of the method for automatically detecting the human touch on the surface using body mounted front facing camera and machine learning model in accordance with the present invention.
[0032] Although the present disclosure has been described with the purpose of a method and system for automatically detecting the human touch on the surface using body mounted front facing camera and machine learning model, it should be appreciated that the same has been done merely to illustrate the invention in an exemplary manner and to highlight any other purpose or function for which explained structures or configurations could be used and is covered within the scope of the present disclosure.
[0033] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words and other forms thereof are intended to be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary systems and methods are now described. The disclosed embodiments are merely exemplary of the disclosure, which may be embodied in various forms.
[0034] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated, but is to be accorded the widest scope consistent with the principles and features described herein.
[0035] Figure 2 show the steps involved in performing the method for automatically detecting the human touch on the surface using body mounted front facing camera and machine learning model of particular area. The proposed method is composed of data processing of large database of computing devices of particular area. At step 201, the proposed method recording the touches using the front facing body mounted display camera. At step 202, periodically transmitting the recorded touches to the database of central server through intra-body near field communication network and personal area network. At step 203, generating the transmission graph of touches using the data stored in the database. At final stage of 204, analyzing the transmission path using machine learning model and take remedial action accordingly.
[0036] Figure 1 show the block diagram of the system involving detecting human touch using body mounted front facing display camera and machine learning model in accordance with the present invention. The proposed system comprises a communication network (101) used to transfer data from various body mounted front facing camera to central server and other devices. The central server (103) which is equipped with machine learning model is connected to a database (102) is used to store the data related to the touches and test cases used to train the machine learning model. The body mounted front facing camera (104) is used to record the touches on the surface or persons. The whole process is performed by central server using the process as mentioned before.
[0037] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.
[0038] Although implementations for invention have been described in a language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations for the invention.
Claims (5)
1. A computer implemented method for automatically detecting human touch using body mounted front facing display camera and machine learning models, wherein the computer implemented method is performed by a computing unit or central server for accessing system, wherein the computing unit comprises a processor, a memory, input/output device and communication unit, wherein the computer implemented method comprising steps of: recording the touches using the front facing body mounted display camera (201); periodically transmitting the recorded touches to the database of central server through intra-body near field communication network and personal area network (202); generating the transmission graph of touches using the data stored in the database (203); analyzing, by the central server (103) the collected data and determine analyzing the transmission path using machine learning model and take remedial action accordingly (204).
2. The computer implemented method as claimed in claim 1, wherein body mounted front facing display camera is used to record touch continuously and periodically transmitting the recorded touches to the central server.
3. The computer implemented method as claimed in claim 1, wherein the communication network may be but not limited to intra-body near field communication network and personal area network.
4. The computer implemented method as claimed in claim 1, transmission graph is analyzes using machine learning model on central sever trained using initial database and test cases.
5. A system for for automatically detecting human touch using body mounted front facing display camera and machine learning models, wherein the system is performed by a computing unit or central server for accessing system, wherein the computing unit comprises a processor, a memory, input/output device and communication unit, the system comprising: a communication network (101) to transmit/receive data from other embodiments of the system; database (102) to store data related to the touches, test cases and initial database related to touches; body mounted front facing camera (104) to record touches on surface or person in a workplace;
a central server (103) to analyze and process received data for determining transmission graph and performing the steps of :
recording the touches using the front facing body mounted display camera (201); periodically transmitting the recorded touches to the database of central server through intra-body near field communication network and personal area network (202); generating the transmission graph of touches using the data stored in the database (203); analyzing, by the central server (103) the collected data and determine analyzing the transmission path using machine learning model and take remedial action accordingly (204).
Databases Body (102) mounted 2021104849
front facing camera (104)
Central server (103) Communication network (101)
Figure 1: Block diagram of automatically detecting human touch in accordance with the present invention
recording the touches using the front facing body mounted display 2021104849
camera (201)
periodically transmitting the recorded touches to the database of central server through intra-body near field communication network (202)
generating the transmission graph of touches using the data stored in the database (203)
analyzing the transmission path using machine learning model and take remedial action accordingly (204)
Figure 2 – Flow-diagram of the method for automatically detecting human touch using body mounted front facing camera in accordance with present invention
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| AU2021104849A AU2021104849A4 (en) | 2021-08-03 | 2021-08-03 | A Computer implemented method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021104849A AU2021104849A4 (en) | 2021-08-03 | 2021-08-03 | A Computer implemented method and system for detecting human touch using body mounted camera to minimize covid spread using machine learning |
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| Publication Number | Publication Date |
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| AU2021104849A4 true AU2021104849A4 (en) | 2022-06-09 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115394052A (en) * | 2022-08-30 | 2022-11-25 | 重庆地质矿产研究院 | Method for obtaining geological disaster early warning key parameter prediction value based on machine learning |
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2021
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115394052A (en) * | 2022-08-30 | 2022-11-25 | 重庆地质矿产研究院 | Method for obtaining geological disaster early warning key parameter prediction value based on machine learning |
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