CN111191565A - Food safety supervision system and method - Google Patents
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- 235000013305 food Nutrition 0.000 title claims abstract description 48
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- 230000002159 abnormal effect Effects 0.000 claims abstract description 4
- 230000007613 environmental effect Effects 0.000 claims description 13
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Abstract
The invention provides a food safety supervision system, comprising: the video acquisition device is used for acquiring image information of a food manufacturing place and sending the image information to the background analysis device; the background analysis device is used for identifying the image information by using a preset image identification algorithm, generating early warning information when the abnormal characteristics are identified, and sending the early warning information to the early warning sending device; and the early warning sending device is used for sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule. The invention also discloses a food safety supervision system and a method. The technical scheme of the invention can effectively improve the supervision range of the supervision department, enhance the fairness and traceability of the judgment and reduce the cost of the supervision department.
Description
Technical Field
The invention relates to the field of food safety, in particular to a food safety supervision system and a food safety supervision method.
Background
With the development of socioeconomic level, the society has a higher and higher attention to food safety problems. With the exposure of some food safety problem time, the improvement of the standard degree of the food production process and the sanitation and tidiness degree of the production environment become the working key points of food safety supervision departments. At present, the known method for monitoring the food making process and environment mainly comprises manual irregular sampling inspection and camera installation, and two modes of real-time monitoring and disclosing the food making process in a mode of 'bright kitchen and bright kitchen'.
The manual irregular spot inspection method is used for carrying out irregular on-site inspection on restaurants, dining halls and the like in a district, and evaluating whether workers in the place wear uniforms or not, whether kitchen personnel wear masks or not, whether kitchen environments are tidy or not and the like or not through contents observed by supervision personnel of the on-site inspection. And (4) performing rectification evaluation on units which do not meet the standard, and performing measures such as fine, shutdown and rectification seriously.
The supervision mode of the bright kitchen range means that standardized video acquisition equipment is installed in each place, real-time videos of the food making process are collected to a supervision department through network signal transmission, and a specially-assigned person supervises by watching the videos. If the non-compliant behavior is found, the video can be used as law enforcement evidence. And the part of conditional places also disclose real-time videos to the public and report and monitor through social strength.
The two methods have the problems of low efficiency and overlarge cost. According to the manual irregular spot inspection method, the supervision personnel need to go to the spot inspection manually and check the inspection content item by item according to the standard, so that not only is the labor cost high, but also the irregular behaviors in daily operation are difficult to find. The time cost for the supervision personnel to go can be saved by disclosing the cooking process image data, but the nonstandard problem can be found only by long-time observation through the display equipment, and the feasibility is too low only by using a small number of supervision personnel to supervise several organizations simultaneously. The supervision is carried out through public power, firstly, the mechanism is required to be put into display equipment such as a screen and a projection, secondly, the public supervision enthusiasm is difficult to continue, and finally, the public lacks professional supervision knowledge and hardly achieves the supervision effect.
The traditional food production process supervision mode can only judge whether the specification is standard or not by checking specific relevant requirements by a supervisor no matter on-site inspection or supervision by real-time video. The supervisor needs to know the specification requirements in detail and pay for the difference between the actual specification and the actual specification due to the kernel removal of manpower and material resources. Illegal operation and environmental hygiene non-compliance in non-working time or non-inspection time are difficult to identify.
1. The number of the current supervisors is greatly different from the number of units needing to be supervised, and the number of the supervisors is insufficient;
2. the existing supervision method excessively depends on human resources, and whether the video is used or not needs to be manually judged to reach the standard or not;
3. the effective supervision time is too short, and supervision obligations can be fulfilled only when supervisors are on duty;
4. because the problem supervision depends on manual inspection, the problem can not be found and solved in time when appearing;
5. whether the standard is standardized or not depends on the professional ability of a supervisor, and different judgment scales are different due to different understandings of different people on the standard
Disclosure of Invention
In order to overcome the technical defects, the invention provides a food safety supervision system and a food safety supervision method, which can effectively improve the supervision range of a supervision department, enhance the fairness and traceability of judgment and reduce the cost of the supervision department.
In order to solve the problems, the invention is realized according to the following technical scheme:
a food safety supervision system comprising:
the video acquisition device is used for acquiring image information of a food manufacturing place and sending the image information to the background analysis device;
the background analysis device is used for identifying the image information by using a preset image identification algorithm, generating early warning information when the abnormal characteristics are identified, and sending the early warning information to the early warning sending device;
and the early warning sending device is used for sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule.
Further, the method also comprises the following steps:
and the information storage device is used for storing the image information and the early warning information.
Further, the method also comprises the following steps:
and the external retrieval device is used for retrieving the image information and the early warning information stored in the information storage device.
Further, the background analysis device identifies the image information by using a preset image identification algorithm, and generates the early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics.
Further, the early warning information includes image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source device and a non-standard judgment result.
Further, the video capture device includes:
the camera is used for collecting the image information;
the compression equipment is used for compressing the image information;
and the router is used for sending the image information to the background analysis device.
Furthermore, the level of the early warning information comprises a plurality of important levels, and corresponding processing personnel is set for the early warning information of each important level in the preset sending rule.
The invention also correspondingly discloses a food safety supervision method, which comprises the following steps:
s1, collecting image information of a food manufacturing place;
s2, identifying the image information by using a preset image identification algorithm, and generating early warning information when the non-standard characteristics are identified;
and S3, sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule.
Further, the step S3 is specifically:
identifying the image information by using a preset image identification algorithm, and generating the early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics; the early warning information comprises image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source equipment and a non-standard judgment result.
Furthermore, the level of the early warning information comprises a plurality of important levels, and corresponding processing personnel is set for the early warning information of each important level in the preset sending rule.
Compared with the prior art, the invention has the beneficial effects that:
the invention discloses a food safety supervision system and a method, which can effectively improve the supervision range of supervision departments, enhance the justness and traceability of the judgment and reduce the cost of the supervision departments compared with the traditional method for manually judging the non-compliant behaviors and the non-compliant sanitation by judging the non-compliant behaviors or the environment of collected video data by using an image recognition algorithm.
Drawings
Fig. 1 is a schematic block diagram of a food safety supervision system according to embodiment 1 of the present invention.
Fig. 2 is a schematic diagram of another implementation architecture of the food safety supervision system according to embodiment 1 of the present invention.
Fig. 3 is a schematic step diagram of a food safety supervision method according to embodiment 2 of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1
As shown in fig. 1, the present invention discloses a food safety supervision system, comprising:
the video acquisition device 1 is used for acquiring image information of a food manufacturing place and sending the image information to the background analysis device 2;
the background analysis device 2 is used for identifying the image information by using a preset image identification algorithm, generating early warning information when the abnormal characteristics are identified, and sending the early warning information to the early warning sending device 3; specifically, the background analysis device 2 adopts a GPU analysis platform, and carries a trained video analysis algorithm to analyze the analysis result and generate an early warning platform for early warning such as in-station mails, short messages, or mails
And the early warning sending device 3 is used for sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule. Specifically, the warning sending device 3 sends warning information such as an internal message, a short message, a mail and the like to related personnel, such as a food making responsible person and a supervisory person, according to the warning information.
And the information storage device 4 is used for storing the image information and the early warning information.
And the external retrieval device 5 is used for retrieving the image information and the early warning information stored in the information storage device.
A practical implementation system of the food safety supervision system is shown in fig. 2.
Specifically, the background analysis device identifies the image information by using a preset image identification algorithm, and generates early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics.
Specifically, the early warning information includes image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source device, and the non-standard determination result. Specifically, the levels of the early warning information include a plurality of important levels, and corresponding processing personnel are set for the early warning information of each important level in the preset sending rule.
Specifically, the video acquisition device 1 is a video data acquisition module with definition not lower than 1080P and a night acquisition function, and the video data acquisition module needs to be connected with an analysis platform carrying a video analysis algorithm, so that the acquired video data can be transmitted to the analysis platform with low delay. Specifically, the video capture device 1 includes:
the camera 11 is used for collecting image information;
a compression device 12 for compressing image information;
and the router 13 is used for sending the image information to the background analysis device.
According to the food safety supervision system disclosed by the embodiment, the collected video data is judged to be in an unconventional behavior or environment by using the image recognition algorithm, and compared with the traditional method for manually judging the unconventional behavior and the unconventional sanitation, the food safety supervision system disclosed by the embodiment can effectively improve the supervision range of a supervision department, enhance the fairness and traceability of the judgment, and reduce the cost of the supervision department.
Example 2
As shown in fig. 3, the present embodiment discloses a food safety supervision method, which includes the following steps:
s1, collecting image information of a food manufacturing place;
s2, identifying the image information by using a preset image identification algorithm, and generating early warning information when the unnormalized features are identified;
and S3, sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule.
Specifically, step S3 specifically includes:
identifying the image information by using a preset image identification algorithm, and generating early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics; the early warning information comprises image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source equipment and a non-standard judgment result.
Specifically, the levels of the early warning information include a plurality of important levels, and corresponding processing personnel are set for the early warning information of each important level in the preset sending rule.
The food safety supervision method disclosed in the present embodiment is explained in conjunction with a specific operation flow, which is as follows:
the method comprises the following steps: installing and starting video acquisition equipment;
step two: connecting the acquisition equipment with the analysis platform to ensure that the acquired video data can be transmitted to the analysis platform in real time;
step three: starting an analysis platform carrying a video analysis algorithm;
step four: judging non-compliance behaviors and non-compliance environments by the analysis platform;
step five: storing video screenshot data of non-compliant behaviors or non-compliant environments;
step six: generating early warning information according to the source equipment ip, screenshot data and judgment results contained in the video data;
step seven: sending the early warning information to an early warning platform;
step eight: the early warning platform sends early warning information such as internal information, short messages, mails and the like to related personnel, such as food making responsible persons and supervisory personnel according to the early warning information.
According to the food safety supervision method disclosed by the embodiment, an AI algorithm is added to the conventional method for manually judging the non-compliant behaviors and the non-compliant sanitation through video data to judge the non-compliant behaviors and the non-compliant sanitation, so that the supervision range of a supervision department is improved, the fairness and the traceability of the judgment are enhanced, and the cost of the supervision department is reduced.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-viewable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
While the preferred embodiments of the present invention have been illustrated and described in detail, it should be understood that modifications and variations can be effected by one skilled in the art in light of the above teachings without undue experimentation. Therefore, any technical solutions that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the prior art according to the present inventive concept should be within the scope of protection defined by the present claims.
Claims (10)
1. A food safety supervision system, comprising:
the video acquisition device is used for acquiring image information of a food manufacturing place and sending the image information to the background analysis device;
the background analysis device is used for identifying the image information by using a preset image identification algorithm, generating early warning information when the abnormal characteristics are identified, and sending the early warning information to the early warning sending device;
and the early warning sending device is used for sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule.
2. The food safety regulatory system of claim 1, wherein: further comprising:
and the information storage device is used for storing the image information and the early warning information.
3. The food safety regulatory system of claim 2, wherein: further comprising:
and the external retrieval device is used for retrieving the image information and the early warning information stored in the information storage device.
4. The food safety regulatory system of claim 1, wherein: the background analysis device identifies the image information by using a preset image identification algorithm, and generates the early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics.
5. The food safety supervision system according to claim 4, wherein: the early warning information comprises image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source equipment and a non-standard judgment result.
6. The food safety regulatory system of claim 1, wherein: the video capture device includes:
the camera is used for collecting the image information;
the compression equipment is used for compressing the image information;
and the router is used for sending the image information to the background analysis device.
7. The food safety regulatory system of claim 2, wherein: the levels of the early warning information comprise a plurality of important levels, and corresponding processing personnel are set for the early warning information of each important level in the preset sending rule.
8. A food safety supervision method is characterized in that: the method comprises the following steps:
s1, collecting image information of a food manufacturing place;
s2, identifying the image information by using a preset image identification algorithm, and generating early warning information when the non-standard characteristics are identified;
and S3, sending the early warning information to the mobile terminal of the corresponding processing personnel according to a preset sending rule.
9. The food safety regulation method of claim 8, wherein: the step S3 specifically includes:
identifying the image information by using a preset image identification algorithm, and generating the early warning information when identifying the non-standard environmental characteristics and/or the non-standard behavior characteristics; the early warning information comprises image screenshot data of the non-standard environmental characteristics and/or the non-standard behavior characteristics, the IP of the source equipment and a non-standard judgment result.
10. The food safety regulation method of claim 8, wherein: the levels of the early warning information comprise a plurality of important levels, and corresponding processing personnel are set for the early warning information of each important level in the preset sending rule.
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| CN201911365432.1A CN111191565A (en) | 2019-12-26 | 2019-12-26 | Food safety supervision system and method |
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Cited By (1)
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| CN113610688A (en) * | 2021-06-25 | 2021-11-05 | 格讯科技(深圳)有限公司 | Food safety supervision method based on big data analysis and storage medium |
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Application publication date: 20200522 |