CN113128896B - Intelligent workshop management system and method based on Internet of things - Google Patents
Intelligent workshop management system and method based on Internet of things Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
- G06F3/013—Eye tracking input arrangements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V40/20—Movements or behaviour, e.g. gesture recognition
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V40/40—Spoof detection, e.g. liveness detection
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/30—Individual registration on entry or exit not involving the use of a pass
- G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
- G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention relates to the technical field of workshop management, in particular to an intelligent workshop management system and method based on the Internet of things. The option generation module generates options according to daily reports of the user, and the options are displayed on a screen; the identity verification module is used for acquiring the real-time motion trail of the pupil of the user when the user selects the answer, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user; the mental state detection module is used for acquiring pupil information of the user and detecting the mental state of the user according to the pupil information of the user; the entrance guard opening and closing control module controls the opening and closing of the entrance guard system. The system can strengthen the identity authentication of the user who needs to enter the workshop and detect the mental state of the user, thereby ensuring the safe operation of the workshop.
Description
Technical Field
The invention relates to the technical field of workshop management, in particular to an intelligent workshop management system and method based on the Internet of things.
Background
In the existing production, how to ensure the safe operation of workshops, especially prevent irrelevant personnel from entering workshops, is an important point in the production process. In the prior art, the technical means adopted for the method are usually marking marks by scribing to prompt that irrelevant personnel do not enter a workshop, but a plurality of people can break into the workshop, so that the prior art adopts an access control system to verify the identity information of the person who wants to enter the workshop by setting passwords, face recognition and other modes, the passwords are easy to leak, the face recognition system has a large loophole, the identity of the person entering the workshop is still difficult to confirm by the control modes, and the irrelevant personnel still can easily think of breaking into the workshop.
In particular to a chemical workshop, the danger of articles in the workshop is high, and strict management and control are more needed for personnel entering the workshop. Moreover, personnel working in such workshops need to be careful in ensuring operation, otherwise a small error may lead to a significant risk. Therefore, for personnel entering the workshop, not only is the identity of the personnel required to be more strictly authenticated, but also the mental state of the personnel is required to be detected, so that the safe operation of the workshop is ensured.
Disclosure of Invention
The intelligent workshop management system based on the Internet of things can strengthen identity authentication of a user who needs to enter a workshop and detect the mental state of the user, so that safe operation of the workshop is ensured.
The basic scheme provided by the invention is as follows:
the intelligent workshop management system and method based on the Internet of things comprise a daily report acquisition module, a storage module, an identity recognition module, a daily report acquisition module, an option generation module, an identity verification module, a mental state detection module and an access control module:
the daily report acquisition module is used for: the daily newspaper collecting device is used for collecting daily newspaper of each user in a workshop;
the storage module: the system is used for storing the identity information of each user in the workshop;
the identity recognition module is as follows: the system is used for identifying the identity of the user according to the identity information of each user in the storage module;
the daily report acquisition module is used for: the method comprises the steps of acquiring daily reports of a user according to the identity of the user;
the option generation module: the method comprises the steps of generating options according to daily reports of a user, wherein the options are displayed on a screen;
the identity verification module: when the user selects the answer, acquiring a real-time motion trail of the pupil of the user, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user;
the mental state detection module: the pupil information detection device is used for acquiring pupil information of a user and detecting the mental state of the user according to the pupil information of the user;
the entrance guard opening and closing control module is used for: the authentication module is used for authenticating that the user is himself, and controlling the access control system to be opened when the mental state of the user reaches a neutral mental state threshold value; and the identity verification module verifies that the user is not the person, or the access control system is controlled to be closed when the mental state of the user does not reach the threshold value of the neutral mental state.
The principle and the advantages of the invention are as follows: the daily news of each user in the workshop is different due to different daily working contents, daily news of the user is different, therefore, the probability that irrelevant personnel know the daily news of the user is low, compared with the mode of setting a password in an access control system in the prior art, the daily news of each user is different in the scheme, the daily news of each user is well known to the user, the user can submit records to inquire about the daily news content and the working contents when the daily news is unclear, the scheme can generate options for the corresponding user according to the daily news of different users, the safety is higher, the identity authentication of the user is more rigorous and reliable, and if the user is the user, the user cannot recall the daily news of the user, and the current state is also indicated to be bad. In addition, the pupil in the answer selection process of the user is obtained in real time, and irrelevant people are prevented from masquerading as staff in a workshop by using static photos of the user. In addition, the staff in the workshop, especially the staff in the chemical industry class workshop, need to guarantee good mental state, otherwise easily appear the mistake in the course of the work to lead to serious result, so this scheme detects the mental state of user on the basis of strengthening the authentication to the user, ensures that the user is staff in the workshop and mental state can guarantee the safe going on of work.
Further, the identity information comprises a fingerprint, and the identity recognition module comprises a fingerprint acquisition module, a fingerprint comparison module and an identity confirmation module:
the fingerprint acquisition module is as follows: the fingerprint acquisition device is used for acquiring fingerprints of a user;
the fingerprint comparison module: the fingerprint acquisition module is used for comparing the acquired fingerprints of the users with the fingerprints of the users in the storage module respectively to generate the coincidence degree;
the identity confirmation module: and when the contact ratio is higher than the contact ratio threshold value, confirming the identity of the user.
The beneficial effects are that: the fingerprint is unique and permanent, the identity of the user is identified by the fingerprint, the fingerprint is safe, and the fingerprint identification is more convenient than the coded lock, and the user can touch the coded lock.
Further, the identity verification module comprises an answer judging module, an option position generating module, a pupil tracking module, a track comparing module and a verification result generating module:
the answer determination module: the method comprises the steps of determining the accuracy of answers selected by a user;
the option position generation module: for generating a position of the option on the screen;
the pupil tracking module: the real-time motion trail of the pupil is used for tracking when the user selects an answer;
the track comparison module: the real-time motion trail of the pupil of the user is compared with the position of the option on the screen, and the residence time of the pupil of the user at the position of the option is generated;
the verification result generation module: when the answer selected by the user reaches the accuracy threshold and the residence time reaches the time threshold, generating a verification result of the user as the user; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user.
The beneficial effects are that: the user selects the answer and needs to see the options, the position of the options on the screen is generated through the option position generating module, the real-time movement track of the pupils when the user selects the answer is tracked through the pupil tracking module, and the track comparison module compares the real-time movement track of the pupils of the user with the position of the options on the screen, so that whether the user has the option to answer can be judged, thereby preventing irrelevant staff from masquerading staff by utilizing the dynamic images of staff in workshops, ensuring that the staff himself is answering, and more rigorous and reliable identity authentication of the user can be ensured by adopting the scheme.
Further, the identity information also includes facial features of the user when the eyes are open and facial features of the user when the eyes are closed.
The beneficial effects are that: the identity of the user is identified through various identity information, so that the accuracy of the identity identification is improved.
Further, an intelligent workshop management method based on the Internet of things is characterized in that: the method comprises the following steps:
s1: collecting daily reports of all users in a workshop;
s2: storing identity information of each user in a workshop;
s3: identifying the identity of the user according to the stored identity information of each user;
s4: acquiring daily reports of the user according to the identity of the user;
s5: generating options according to daily reports of the user, wherein the options are displayed on a screen;
s6: when the user selects an answer, acquiring a real-time motion trail of the pupil of the user, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user;
s7: acquiring pupil information of a user, and detecting the mental state of the user according to the pupil information of the user;
s8: verifying that the user is himself, and controlling the access control system to be opened when the mental state of the user reaches a neutral mental state threshold value; and (3) when the user is verified to be not the person or the mental state of the user does not reach the threshold value of the neutral mental state, controlling the access control system to be closed.
The beneficial effects are that: the daily news of each user in the workshop is different due to different daily working contents, daily news of the user is different, therefore, the probability that irrelevant personnel know the daily news of the user is low, compared with the mode of setting a password in an access control system in the prior art, the daily news of each user is different in the scheme, the daily news of each user is well known to the user, the user can submit records to inquire about the daily news content and the working contents when the daily news is unclear, the scheme can generate options for the corresponding user according to the daily news of different users, the safety is higher, the identity authentication of the user is more rigorous and reliable, and if the user is the user, the user cannot recall the daily news of the user, and the current state is also indicated to be bad. In addition, the pupil in the answer selection process of the user is obtained in real time, and irrelevant people are prevented from masquerading as staff in a workshop by using static photos of the user. In addition, the staff in the workshop, especially the staff in the chemical industry class workshop, need to guarantee good mental state, otherwise easily appear the mistake in the course of the work to lead to serious result, so this scheme detects the mental state of user on the basis of strengthening the authentication to the user, ensures that the user is staff in the workshop and mental state can guarantee the safe going on of work.
Further, the identity information includes a fingerprint, and the S3 includes:
s301: collecting fingerprints of users;
s302: comparing the collected fingerprints of the users with stored fingerprints of the users respectively to generate the coincidence degree;
s303: and when the overlap ratio is higher than the overlap ratio threshold value, confirming the identity of the user.
The beneficial effects are that: the fingerprint is unique and permanent, the identity of the user is identified by the fingerprint, the fingerprint is safe, and the fingerprint identification is more convenient than the coded lock, and the user can touch the coded lock.
Further, the S6 includes:
s601: judging the accuracy of the answer selected by the user;
s602: generating the position of the option on the screen;
s603: tracking the real-time motion trail of the pupil when the user selects the answer;
s604: comparing the real-time motion trail of the pupil of the user with the position of the option on the screen to generate the residence time of the pupil of the user at the position of the option;
s605: when the answer selected by the user reaches the accuracy threshold and the residence time reaches the time threshold, generating a verification result of the user as the user; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user.
The beneficial effects are that: the user needs to watch the options when selecting the answers, and the real-time movement track of the pupils of the user is compared with the positions of the options on the screen, so that whether the user has the options to answer can be judged, thereby preventing irrelevant personnel from masquerading staff by using dynamic images of staff in workshops, ensuring that the staff himself is answering, and the scheme can ensure that the identity authentication of the user is more rigorous and reliable.
Further, the identity information also includes facial features of the user when the eyes are open and facial features of the user when the eyes are closed.
The beneficial effects are that: the identity of the user is identified through various identity information, so that the accuracy of the identity identification is improved.
Drawings
Fig. 1 is a logic block diagram of an intelligent workshop management system based on the internet of things according to an embodiment of the invention.
Fig. 2 is a flowchart of an intelligent workshop management method based on the internet of things according to an embodiment of the invention.
Detailed Description
The following is a further detailed description of the embodiments:
example 1 is substantially as shown in figure 1:
the intelligent workshop management system based on the Internet of things comprises a daily report acquisition module, a storage module, an identity recognition module, a daily report acquisition module, an option generation module, an identity verification module, a mental state detection module and an access control module. The daily newspaper collecting module is used for collecting daily newspaper of each user in the workshop; the storage module is used for storing identity information of each user in the workshop, in this embodiment, the identity information is a fingerprint, and in other embodiments of the application, the identity information can also be a facial feature of the user when the eyes of the user are open and a facial feature of the user when the eyes of the user are closed.
The identity recognition module is used for recognizing the identity of the user according to the identity information of each user in the storage module. The identity recognition module comprises a fingerprint acquisition module, a fingerprint comparison module and an identity confirmation module. The fingerprint acquisition module is used for acquiring the fingerprint of the user; the fingerprint comparison module is used for respectively comparing the collected fingerprints of the users with the fingerprints of all the users in the storage module to generate the coincidence ratio; and the identity confirmation module is used for confirming the identity of the user when the coincidence degree is higher than the coincidence degree threshold value. In this embodiment, the contact ratio includes 0% -100% and the contact ratio threshold is 90%.
And the daily report acquisition module acquires the daily report of the user according to the identity of the user identified by the identity identification module. In this embodiment, a daily report of the last working day of the user is obtained. The option generation module generates options according to a daily report of the last working day of the user, wherein the options are displayed on a screen, and the contents of the daily report comprise working contents, working plans and working summaries.
In this embodiment, the option generating module generates three topics, which are the topics of the work content, the work plan and the work summary in the daily report of the last working day of the user. The specific generation mode is as follows: and extracting one keyword from the work plan, randomly generating three keywords, and respectively taking the three keywords as four options of the selection questions for a user to select the work plan of the last work day, so that the user can be reminded of work which needs to be carried out today while carrying out identity confirmation of the user. The manner of generating the questions related to the work content and the work summary is the same as the manner of generating the questions related to the work plan, and is not described in detail herein.
The identity verification module is used for acquiring the real-time motion trail of the pupil of the user when the user selects the answer, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user. The identity verification module comprises an answer judging module, an option position generating module, a pupil tracking module, a track comparison module and a verification result generating module.
The answer judging module is used for judging the accuracy of the answer selected by the user; the option position generating module is used for generating the positions of options on the screen, wherein in the embodiment, the options occupy one quarter of the area of the screen, and the positions of the options on the screen are respectively an upper left corner, a lower left corner, an upper right corner and a lower right corner; the pupil tracking module is used for tracking the real-time motion trail of the pupil when the user selects the answer; the track comparison module is used for comparing the real-time motion track of the pupil of the user with the position of the option on the screen, and generating the residence time of the pupil of the user at the position of the option; the verification result generation module is used for generating a verification result of the user as the user when the answer selected by the user reaches the correct rate threshold and the residence time reaches the time threshold; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user. In this embodiment, the accuracy threshold is 2/3 and the time threshold is 5 seconds.
The mental state detection module is used for acquiring pupil information of the user and detecting the mental state of the user according to the pupil information of the user. In this embodiment, the pupil information is the area of the eyelid covering the pupil and the blink frequency, and the mental state detection module uses the area of the eyelid covering the pupil and the blink frequency of the user as the input of the input layer and uses the mental state of the user as the output of the output layer in an artificial intelligence manner.
Specifically, firstly, a three-layer BP neural network model is constructed, wherein the three-layer BP neural network model comprises an input layer, a hidden layer and an output layer, in the embodiment, the input layer is provided with 2 nodes, the output of the output layer is provided with 1 node, in the embodiment, the mental state of the output user is from 0 to 10, and the threshold value of the neutral mental state of the user is 6; for hidden layers, the present embodiment uses the following formula to determine the number of hidden layer nodes:where l is the number of nodes in the hidden layer, n is the number of nodes in the input layer, m is the number of nodes in the output layer, a is a number between 1 and 10, and in this embodiment is taken as 6, so that the hidden layer has 8 nodes in total. BP neural networks typically employ Sigmoid micromanipulations and linear functions as the excitation functions of the network. The present embodiment selects the sigmoid tangent function tan sig as the excitation function of the hidden layer neurons. The predictive model selects an S-shaped logarithmic function tan sig as the excitation function of the neurons of the output layer.
The entrance guard opening and closing control module is used for verifying that the user is himself by the identity verification module, and controlling the entrance guard system to be opened when the mental state of the user reaches a neutral mental state threshold value; and the identity verification module verifies that the user is not the person, or the access control system is controlled to be closed when the mental state of the user does not reach the threshold value of the neutral mental state.
Example 2 is substantially as shown in figure 2:
the intelligent workshop management method based on the Internet of things comprises the following steps of:
s1: collecting daily reports of all users in a workshop;
s2: storing identity information of each user in a workshop; in this embodiment, the identity information is a fingerprint, and in other embodiments of the present application, the identity information may also be a facial feature when the user opens his/her eyes and a facial feature when the user closes his/her eyes.
S3: identifying the identity of the user according to the stored identity information of each user;
s4: acquiring daily reports of the user according to the identity of the user;
s5: generating options according to daily reports of the user, wherein the options are displayed on a screen;
s6: when the user selects an answer, acquiring a real-time motion trail of the pupil of the user, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user;
s7: acquiring pupil information of a user, and detecting the mental state of the user according to the pupil information of the user; in this embodiment, the pupil information is the area of the eyelid covering the pupil and the blink frequency;
s8: verifying that the user is himself, and controlling the access control system to be opened when the mental state of the user reaches a neutral mental state threshold value; and (3) when the user is verified to be not the person or the mental state of the user does not reach the threshold value of the neutral mental state, controlling the access control system to be closed.
Wherein S3 includes S301: collecting fingerprints of users;
s302: comparing the collected fingerprints of the users with stored fingerprints of the users respectively to generate the coincidence degree; in this embodiment, the overlap ratio includes 0% -100%;
s303: when the overlap ratio is higher than the overlap ratio threshold value, confirming the identity of the user; in this embodiment, the overlap ratio threshold is 90%.
Specifically, S4 obtains the daily report of the user according to the identified identity of the user. In this embodiment, a daily report of a last working day of the user is obtained, and options are generated according to the daily report of the last working day of the user, wherein the options are displayed on a screen, and the contents of the daily report include working contents, working plans and working summaries.
In this embodiment, three topics are generated in total, and are the topics of the working content, working plan and working summary in the daily report of the last working day of the user. The specific generation mode is as follows: and extracting one keyword from the work plan, randomly generating three keywords, and respectively taking the three keywords as four options of the selection questions for a user to select the work plan of the last work day, so that the user can be reminded of work which needs to be carried out today while carrying out identity confirmation of the user. The manner of generating the questions related to the work content and the work summary is the same as the manner of generating the questions related to the work plan, and is not described in detail herein.
Wherein S6 includes:
s601: judging the accuracy of the answer selected by the user;
s602: generating the position of the option on the screen; in this embodiment, the options occupy a quarter of the screen, and the positions of the options on the screen are respectively an upper left corner, a lower left corner, an upper right corner and a lower right corner;
s603: tracking the real-time motion trail of the pupil when the user selects the answer;
s604: comparing the real-time motion trail of the pupil of the user with the position of the option on the screen to generate the residence time of the pupil of the user at the position of the option;
s605: when the answer selected by the user reaches the accuracy threshold and the residence time reaches the time threshold, generating a verification result of the user as the user; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user. In this embodiment, the accuracy threshold is 2/3 and the time threshold is 5 seconds.
In this embodiment, S7 uses the area of the user' S eyelid covering the pupil and the blink frequency as input to the input layer and the mental state of the user as output to the output layer by means of artificial intelligence. Specifically, firstly, a three-layer BP neural network model is constructed, wherein the three-layer BP neural network model comprises an input layer, a hidden layer and an output layer, in the embodiment, the input layer is provided with 2 nodes, the output of the output layer is provided with 1 node, in the embodiment, the mental state of the output user is from 0 to 10, and the threshold value of the neutral mental state of the user is 6; for hidden layers, the present embodiment uses the following formula to determine the number of hidden layer nodes:where l is the number of nodes in the hidden layer, n is the number of nodes in the input layer, m is the number of nodes in the output layer, a is a number between 1 and 10, and in this embodiment is taken as 6, so that the hidden layer has 8 nodes in total. BP neural networks typically employ Sigmoid micromanipulations and linear functions as the excitation functions of the network. The present embodiment selects the sigmoid tangent function tan sig as the excitation function of the hidden layer neurons. The predictive model selects an S-shaped logarithmic function tan sig as the excitation function of the neurons of the output layer.
The foregoing is merely exemplary of the present invention, and the specific structures and features well known in the art are not described in any way herein, so that those skilled in the art will be able to ascertain all prior art in the field, and will not be able to ascertain any prior art to which this invention pertains, without the general knowledge of the skilled person in the field, before the application date or the priority date, to practice the present invention, with the ability of these skilled persons to perfect and practice this invention, with the help of the teachings of this application, with some typical known structures or methods not being the obstacle to the practice of this application by those skilled in the art. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (8)
1. Intelligent workshop management system based on Internet of things, and is characterized in that: the intelligent daily newspaper acquisition system comprises a daily newspaper acquisition module, a storage module, an identity recognition module, a daily newspaper acquisition module, an option generation module, an identity verification module, a mental state detection module and an access control module:
the daily report acquisition module is used for: the daily newspaper collecting device is used for collecting daily newspaper of each user in the workshop, wherein the daily newspaper of each user in the workshop is different due to different daily working contents, and the daily newspaper of the users is different;
the storage module: the system is used for storing the identity information of each user in the workshop;
the identity recognition module is as follows: the system is used for identifying the identity of the user according to the identity information of each user in the storage module;
the daily report acquisition module is used for: the method comprises the steps of acquiring daily reports of a user according to the identity of the user;
the option generation module: the method comprises the steps of generating options according to daily reports of a user, wherein the options are displayed on a screen;
the identity verification module: when the user selects the answer, acquiring a real-time motion trail of the pupil of the user, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user;
the mental state detection module: the pupil information detection device is used for acquiring pupil information of a user and detecting the mental state of the user according to the pupil information of the user;
the entrance guard opening and closing control module is used for: the authentication module is used for authenticating that the user is himself, and controlling the access control system to be opened when the mental state of the user reaches a neutral mental state threshold value; and the identity verification module verifies that the user is not the person, or the access control system is controlled to be closed when the mental state of the user does not reach the threshold value of the neutral mental state.
2. The intelligent workshop management system based on the internet of things according to claim 1, wherein: the identity information comprises fingerprints, and the identity recognition module comprises a fingerprint acquisition module, a fingerprint comparison module and an identity confirmation module:
the fingerprint acquisition module is as follows: the fingerprint acquisition device is used for acquiring fingerprints of a user;
the fingerprint comparison module: the fingerprint acquisition module is used for comparing the acquired fingerprints of the users with the fingerprints of the users in the storage module respectively to generate the coincidence degree;
the identity confirmation module: and when the contact ratio is higher than the contact ratio threshold value, confirming the identity of the user.
3. The intelligent workshop management system based on the internet of things according to claim 1, wherein: the identity verification module comprises an answer judgment module, an option position generation module, a pupil tracking module, a track comparison module and a verification result generation module:
the answer determination module: the method comprises the steps of determining the accuracy of answers selected by a user;
the option position generation module: for generating a position of the option on the screen;
the pupil tracking module: the real-time motion trail of the pupil is used for tracking when the user selects an answer;
the track comparison module: the real-time motion trail of the pupil of the user is compared with the position of the option on the screen, and the residence time of the pupil of the user at the position of the option is generated;
the verification result generation module: when the answer selected by the user reaches the accuracy threshold and the residence time reaches the time threshold, generating a verification result of the user as the user; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user.
4. The intelligent workshop management system based on the internet of things according to claim 1, wherein: the identity information also includes facial features of the user when the eyes are open and facial features of the user when the eyes are closed.
5. The intelligent workshop management method based on the Internet of things is characterized by comprising the following steps of: the method comprises the following steps:
s1: collecting daily reports of all users in a workshop;
s2: storing identity information of each user in a workshop;
s3: identifying the identity of the user according to the stored identity information of each user;
s4: acquiring daily reports of the user according to the identity of the user;
s5: generating options according to daily reports of the user, wherein the options are displayed on a screen;
s6: when the user selects an answer, acquiring a real-time motion trail of the pupil of the user, and verifying the identity of the user according to the real-time motion trail of the pupil of the user and the answer selected by the user;
s7: acquiring pupil information of a user, and detecting the mental state of the user according to the pupil information of the user;
s8: verifying that the user is himself, and controlling the access control system to be opened when the mental state of the user reaches a neutral mental state threshold value; and (3) when the user is verified to be not the person or the mental state of the user does not reach the threshold value of the neutral mental state, controlling the access control system to be closed.
6. The intelligent workshop management method based on the internet of things according to claim 5, wherein: the identity information includes a fingerprint, and the S3 includes:
s301: collecting fingerprints of users;
s302: comparing the collected fingerprints of the users with stored fingerprints of the users respectively to generate the coincidence degree;
s303: and when the overlap ratio is higher than the overlap ratio threshold value, confirming the identity of the user.
7. The intelligent workshop management method based on the internet of things according to claim 5, wherein: the step S6 comprises the following steps:
s601: judging the accuracy of the answer selected by the user;
s602: generating the position of the option on the screen;
s603: tracking the real-time motion trail of the pupil when the user selects the answer;
s604: comparing the real-time motion trail of the pupil of the user with the position of the option on the screen to generate the residence time of the pupil of the user at the position of the option;
s605: when the answer selected by the user reaches the accuracy threshold and the residence time reaches the time threshold, generating a verification result of the user as the user; and when the answer selected by the user does not reach the correct rate threshold or the residence time does not reach the time threshold, generating a verification result that the user is not the user.
8. The intelligent workshop management method based on the internet of things according to claim 5, wherein: the identity information also includes facial features of the user when the eyes are open and facial features of the user when the eyes are closed.
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