CN117783430B - Catering lampblack online monitoring system and method - Google Patents
Catering lampblack online monitoring system and method Download PDFInfo
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- CN117783430B CN117783430B CN202311633058.5A CN202311633058A CN117783430B CN 117783430 B CN117783430 B CN 117783430B CN 202311633058 A CN202311633058 A CN 202311633058A CN 117783430 B CN117783430 B CN 117783430B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 50
- 239000006233 lamp black Substances 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 title claims abstract description 19
- 239000000779 smoke Substances 0.000 claims abstract description 122
- 230000000007 visual effect Effects 0.000 claims abstract description 42
- 230000005856 abnormality Effects 0.000 claims abstract description 36
- 239000004071 soot Substances 0.000 claims description 26
- 238000012800 visualization Methods 0.000 claims description 26
- 238000000605 extraction Methods 0.000 claims description 25
- 230000002159 abnormal effect Effects 0.000 claims description 15
- 238000013507 mapping Methods 0.000 claims description 13
- 239000003517 fume Substances 0.000 claims description 12
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Natural products C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 1
- -1 methane hydrocarbon Chemical class 0.000 description 1
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Abstract
The invention provides a catering lampblack online monitoring system and a catering lampblack online monitoring method, wherein the system comprises the following steps: the oil smoke data acquisition module is used for acquiring oil smoke data in each catering kitchen in the city; the oil smoke abnormality monitoring module is used for monitoring oil smoke abnormality based on oil smoke data; the oil smoke abnormality alarm module is used for alarming oil smoke abnormality; the visual model generation module is used for generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city; and the visual model display module is used for displaying the visual model. According to the online monitoring system and method for the catering lampblack, the lampblack abnormality is automatically monitored, the visual model is generated and displayed for a manager to check, the manager does not need to go to a kitchen in a catering store to conduct field monitoring, convenience is improved, labor cost is reduced, and in addition, the comprehensiveness and efficiency of monitoring the catering lampblack are improved.
Description
Technical Field
The invention relates to the technical field of catering oil fume monitoring, in particular to a catering oil fume online monitoring system and method.
Background
At present, catering oil smoke pollution is one of main sources of atmospheric pollution. In order to ensure reasonable and standard-closing discharge of the catering oil smoke, the catering oil smoke is required to be monitored. Generally, the catering oil smoke monitoring requires staff to go to a kitchen of a catering store for field monitoring in the form of spot check, but in doing so, the labor cost is high, and the comprehensiveness and efficiency of the catering oil smoke monitoring are not enough. Thus, a solution is needed.
Disclosure of Invention
The invention aims at providing the catering oil smoke online monitoring system, which automatically monitors oil smoke abnormality, generates and displays a visual model for a manager to check, and the manager does not need to go to a kitchen of a catering store to monitor in the field, so that convenience is improved, labor cost is reduced, and in addition, the comprehensiveness and efficiency of catering oil smoke monitoring are improved.
The embodiment of the invention provides an online monitoring system for catering lampblack, which comprises the following components:
The oil smoke data acquisition module is used for acquiring oil smoke data in each catering kitchen in the city;
the oil smoke abnormality monitoring module is used for monitoring oil smoke abnormality based on the oil smoke data;
the oil smoke abnormality alarm module is used for alarming the oil smoke abnormality;
The visual model generation module is used for generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
and the visual model display module is used for displaying the visual model.
Preferably, the online monitoring system for catering oil smoke further comprises:
a first auxiliary module for comprising:
Counting the abnormal history of the lampblack of each catering kitchen in the city;
Updating a preset oil fume pollution management knowledge base;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies;
mapping the soot pollution management suggestion table into the visualization model;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
Preferably, the online monitoring system for catering oil smoke further comprises:
a second auxiliary module for including:
Acquiring a user portrait of a user;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model;
when the first target content and the second target content are matched, close-up display is carried out on the first target content and the second target content; otherwise, switching the second target content to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features;
Determining a second content search template corresponding to the content characteristics from a preset second content search template library;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content;
Wherein the content association condition includes:
At least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library.
Preferably, the content association condition further includes:
The absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value;
At least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content.
Preferably, the online monitoring system for catering oil smoke further comprises:
a third auxiliary module for including:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
The embodiment of the invention provides a catering oil smoke online monitoring method, which comprises the following steps:
collecting oil smoke data in each catering kitchen in a city;
Monitoring for soot anomalies based on soot data;
alarming for abnormal oil smoke;
Generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
the visualization model is displayed.
Preferably, the online monitoring method for catering oil smoke further comprises the following steps:
Counting the abnormal history of the lampblack of each catering kitchen in the city;
Updating a preset oil fume pollution management knowledge base;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies;
mapping the soot pollution management suggestion table into the visualization model;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
Preferably, the online monitoring method for catering oil smoke further comprises the following steps:
Acquiring a user portrait of a user;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model;
when the first target content and the second target content are matched, close-up display is carried out on the first target content and the second target content; otherwise, switching the second target content to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features;
Determining a second content search template corresponding to the content characteristics from a preset second content search template library;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content;
Wherein the content association condition includes:
At least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library.
Preferably, the content association condition further includes:
The absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value;
At least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content.
Preferably, the online monitoring method for catering oil smoke further comprises the following steps:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
Fig. 1 is a schematic diagram of an online monitoring system for catering oil smoke in an embodiment of the invention;
Fig. 2 is a schematic diagram of an online monitoring method for catering oil smoke in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides an online monitoring system for catering lampblack, which is shown in fig. 1 and comprises the following components:
the oil smoke data acquisition module 1 is used for acquiring oil smoke data in each catering kitchen in the city;
The lampblack abnormality monitoring module 2 is used for monitoring lampblack abnormality based on the lampblack data;
the oil smoke abnormality alarm module 3 is used for alarming the oil smoke abnormality;
the visual model generation module 4 is used for generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
and the visual model display module 5 is used for displaying the visual model.
In the above scheme, the oil smoke data includes: the concentration of oil smoke, the concentration of particulate matters, the concentration of total non-methane hydrocarbon, the state of a fan, the state of a purifier switch and the like in a catering kitchen; based on the soot data, soot anomalies are monitored, such as: a maximum threshold value of the oil smoke concentration in the kitchen can be preset, and when the oil smoke concentration in the kitchen exceeds the threshold value, abnormal oil smoke with the exceeding oil smoke concentration is output; alarming the abnormal oil smoke to remind relevant law enforcement personnel; the GIS map is a map for three-dimensionally restoring city according to the ratio of 1 to 1 based on the GIS technology; when a visual model is generated based on the oil smoke data, the oil smoke abnormality and the GIS map, the oil smoke data and the oil smoke abnormality are represented on the GIS map; and displaying the visual model for a manager to view. The system automatically monitors the abnormal oil smoke, generates and displays the visual model for a manager to check, and the manager does not need to go to a kitchen of a restaurant to monitor in the field, so that convenience is improved, labor cost is reduced, and in addition, the comprehensiveness and efficiency of monitoring the oil smoke in the restaurant are improved.
In one embodiment, the catering oil smoke on-line monitoring system further comprises:
a first auxiliary module for comprising:
counting the abnormal history of the lampblack of each catering kitchen in the city; the oil smoke abnormality history is the type, time and the like of the oil smoke abnormality in the history of the catering kitchen;
Updating a preset oil fume pollution management knowledge base; the oil smoke pollution management knowledge base has a large amount of oil smoke pollution management knowledge, and the oil smoke pollution management knowledge indicates how different oil smoke abnormality histories are used for managing catering kitchens, for example: 3 times of abnormal lampblack appears in a kitchen in a restaurant in the last month, and the lampblack pollution management knowledge indicates fine 200 yuan;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base; the oil smoke pollution management strategy is a strategy of how to manage the catering kitchen indicated by the oil smoke pollution management knowledge;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies; integrating the oil fume pollution management strategies into a table to obtain an oil fume pollution management suggestion table;
mapping the soot pollution management suggestion table into the visualization model; after mapping, the user can check and select the strategy to be executed;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
The embodiment of the invention adaptively helps a user to make a lampblack pollution management decision, and is more humanized.
In one embodiment, the catering oil smoke on-line monitoring system further comprises:
a second auxiliary module for including:
Acquiring a user portrait of a user; the user portrayal comprises: the location of the user, the responsibility of the user, etc.;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features; portrait features include the location of the user, the responsibilities of the user, etc.; the first feature extraction template is a system operation execution template for extracting the image features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library; the first content search template is a template for searching out first target content suitable for image features, for example: the portrait features are that the position of the user is the position A, and the first content searching template is a restaurant which is searched for abnormal oil smoke in 3 kilometers around the position A in the city;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model; when searching, the first target content needs to be immediately checked by a user; when the second target content meets the content association condition with the first target content, the first target content and the second target content are required to be checked together by a user;
when the first target content and the second target content are matched, close-up display is carried out on the first target content and the second target content; otherwise, switching the second target content to the first target content; when close-up display is carried out, the first target content and the second target content are put into an information display window together for independent display; when the first target content is not matched with the second target content, the user only needs to immediately check the first target content, the visual model is subjected to picture switching, and the second target content is switched to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features; the target duration may be, for example: 10 minutes; the content features include: view content type, view time, etc.;
determining a second content search template corresponding to the content characteristics from a preset second content search template library; the second content search template is a template for searching out fourth target content with proper content characteristics, for example: the content is characterized in that the content type is checked to be the oil smoke pollution management history of the restaurant B with abnormal oil smoke, and a user possibly wants to make an oil smoke pollution management decision on the restaurant B, and the second content search template is used for searching out the oil smoke pollution management history of other restaurant C belonging to the same street as the restaurant B and can be used for reference by the user;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content; when the attempt succeeds, close-up display is carried out on the fourth target content, and when the close-up display is carried out, the fourth target content is placed into an information display window for independent display;
Wherein the content association condition includes:
At least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library. The first association relationship may be: the first content type is restaurant C kitchen real-time oil smoke data, the second content type is restaurant D kitchen real-time oil smoke data, the restaurant C and the restaurant D belong to the same street, and at the moment, the first target content and the second target content can be displayed in a close-up mode at the same time, so that a user can conveniently see and manage the first target content and the second target content.
According to the embodiment of the invention, when the user views the visual model, the visual model is assisted in time, so that the management efficiency of the user is greatly improved.
In one embodiment, the content association condition further includes:
the absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value; the first content weight represents a degree of importance of the first content type [ for example: the content type is kitchen real-time oil smoke data of a restaurant, the content weight is 30, and similarly, the second content weight represents the importance degree of the second content type; the weight difference threshold may be, for example: 8, 8; when the content association condition is set, the user can not miss the content with higher importance currently viewed, and the first target content and the second target content are displayed together, so that the method is more humanized;
at least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content. The first source area is a model area for displaying first target content in the visual model, and the second source area is a model area for displaying second target content in the visual model; the second association relationship may be, for example: the user views the first source area and the second source area historically [ the user views historically, which shows that the user pays attention to the first source area, and the first target content and the second target content are displayed together, so that the method is more humanized, and the like.
In one embodiment, the catering oil smoke on-line monitoring system further comprises:
a third auxiliary module for including:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
The embodiment of the invention provides an online monitoring method for catering lampblack, which is shown in fig. 2 and comprises the following steps:
step S1: collecting oil smoke data in each catering kitchen in a city;
step S2: monitoring for soot anomalies based on soot data;
step S3: alarming for abnormal oil smoke;
Step S4: generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
step S5: the visualization model is displayed.
The online monitoring method for the catering oil smoke further comprises the following steps:
Counting the abnormal history of the lampblack of each catering kitchen in the city;
Updating a preset oil fume pollution management knowledge base;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies;
mapping the soot pollution management suggestion table into the visualization model;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
The online monitoring method for the catering oil smoke further comprises the following steps:
Acquiring a user portrait of a user;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model;
when the first target content and the second target content are matched, close-up display is carried out on the first target content and the second target content; otherwise, switching the second target content to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features;
Determining a second content search template corresponding to the content characteristics from a preset second content search template library;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content;
Wherein the content association condition includes:
At least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library.
The content association condition further includes:
The absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value;
At least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content.
The online monitoring method for the catering oil smoke further comprises the following steps:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. An on-line monitoring system for catering oil smoke, which is characterized by comprising:
The oil smoke data acquisition module is used for acquiring oil smoke data in each catering kitchen in the city;
the oil smoke abnormality monitoring module is used for monitoring oil smoke abnormality based on the oil smoke data;
the oil smoke abnormality alarm module is used for alarming the oil smoke abnormality;
The visual model generation module is used for generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
The visual model display module is used for displaying the visual model;
Further comprises:
a second auxiliary module for including:
Acquiring a user portrait of a user;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model;
when the first target content is matched with the second target content, performing close-up display on the first target content and the second target content; otherwise, switching the second target content to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features;
Determining a second content search template corresponding to the content characteristics from a preset second content search template library;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content;
Wherein the content association condition includes:
at least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library;
the content association condition further includes:
The absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value;
At least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content.
2. A catering fume on-line monitoring system according to claim 1, further comprising:
a first auxiliary module for comprising:
Counting the abnormal history of the lampblack of each catering kitchen in the city;
Updating a preset oil fume pollution management knowledge base;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies;
mapping the soot pollution management suggestion table into the visualization model;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
3. A catering fume on-line monitoring system according to claim 1, further comprising:
a third auxiliary module for including:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
4. The online monitoring method for the catering lampblack is characterized by comprising the following steps of:
collecting oil smoke data in each catering kitchen in a city;
Monitoring for soot anomalies based on soot data;
alarming for abnormal oil smoke;
Generating a visual model based on the oil smoke data, the oil smoke abnormality and a preset GIS map corresponding to the city;
Displaying the visual model;
Further comprises:
Acquiring a user portrait of a user;
Performing feature extraction on the user portrait based on a preset first feature extraction template to obtain a plurality of portrait features;
Determining a first content search template corresponding to the portrait features from a preset first content search template library;
attempting to search for first target content from within the visualization model based on the first content search template;
When the attempt is successful, determining whether a content association condition is met between the first target content and a second target content being viewed by a user in the visual model;
when the first target content is matched with the second target content, performing close-up display on the first target content and the second target content; otherwise, switching the second target content to the first target content;
Waiting for a preset target duration, and carrying out feature extraction on the first target content and third target content which is recently checked in the visual model by a user in the target duration based on a preset second feature extraction template to obtain a plurality of content features;
Determining a second content search template corresponding to the content characteristics from a preset second content search template library;
attempting to search for fourth target content from within the visualization model based on the second content search template;
when the attempt is successful, performing close-up display on the fourth target content;
Wherein the content association condition includes:
at least one first association relation is corresponding to a first content type of the first target content and a second content type of the second target content in a preset content type association library;
the content association condition further includes:
The absolute value of the weight difference between the preset first content weight corresponding to the first content type and the preset second content weight corresponding to the second content type is smaller than or equal to a preset weight difference threshold value;
At least one second association relationship is corresponding to a preset source region association library between a first source region of the first target content and a second source region of the second target content.
5. The on-line monitoring method of restaurant lampblack of claim 4, further comprising:
Counting the abnormal history of the lampblack of each catering kitchen in the city;
Updating a preset oil fume pollution management knowledge base;
Determining a plurality of oil smoke pollution management strategies based on the oil smoke abnormality history and the oil smoke pollution management knowledge base;
Generating a soot pollution management advice table based on the plurality of soot pollution management policies;
mapping the soot pollution management suggestion table into the visualization model;
Receiving a strategy to be executed input by a user based on the oil smoke pollution management suggestion table;
and executing the strategy to be executed.
6. The on-line monitoring method of restaurant lampblack of claim 4, further comprising:
When a user sets up an online meeting;
Mapping the visualization model into the online meeting.
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| CN113052436A (en) * | 2021-02-26 | 2021-06-29 | 江苏蓝创智能科技股份有限公司 | Geographical monitoring method, equipment and medium for catering oil fume |
| CN115682059A (en) * | 2021-07-23 | 2023-02-03 | 博西华电器（江苏）有限公司 | Reminding method, device and equipment for range hood, storage medium and range hood |
| CN116128697A (en) * | 2023-02-10 | 2023-05-16 | 泰华智慧产业集团股份有限公司 | Urban management case judging method and system based on catering oil fume monitoring data |
| CN117057483B (en) * | 2023-10-11 | 2024-01-26 | 北京德众国良环保科技有限公司 | Catering oil smoke prediction processing method and system based on big data |
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| CN115829807A (en) * | 2022-11-29 | 2023-03-21 | 南京景泓智能制造技术研究院有限公司 | Real-time online monitoring system for catering users |
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