CN112487944A - Kitchen environment monitoring system and method based on image recognition - Google Patents
Kitchen environment monitoring system and method based on image recognition Download PDFInfo
- Publication number
- CN112487944A CN112487944A CN202011352907.6A CN202011352907A CN112487944A CN 112487944 A CN112487944 A CN 112487944A CN 202011352907 A CN202011352907 A CN 202011352907A CN 112487944 A CN112487944 A CN 112487944A
- Authority
- CN
- China
- Prior art keywords
- kitchen
- image
- insect pest
- monitoring
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
Abstract
The invention discloses a kitchen environment monitoring system and method based on image recognition, and relates to the technical field of image recognition. The kitchen monitoring system comprises a kitchen monitoring terminal, a monitoring center and a plurality of monitoring cameras; the kitchen monitoring terminals are respectively and electrically connected with the monitoring cameras; the kitchen monitoring terminal is in communication connection with the monitoring center; the kitchen monitoring terminal comprises a microprocessor, a storage module, an image processing module, a kitchen insect pest identification module and a wireless transmission module. The kitchen image is shot through the monitoring camera and transmitted to the image processing module, and the image processing module divides the kitchen image into a plurality of kitchen night subgraphs; the kitchen pest identification module compares the kitchen night subgraph with the pest model library to obtain a pest identification result and transmits the pest identification result to the microprocessor, and when the microprocessor judges that the pest identification result is the existence of pests, the microprocessor transmits a kitchen image and a corresponding pest identification result to the monitoring center; the efficiency of monitoring and supervision when improving unmanned in the kitchen, convenient high efficiency.
Description
Technical Field
The invention belongs to the technical field of image recognition, and particularly relates to a kitchen environment monitoring system and method based on image recognition.
Background
With the continuous improvement of the living standard of people, the requirements on the living quality are also continuously improved. More people gather food in the hotel, and the catering industry is prosperous. The working environment in the hotel kitchen is of great importance to the sanitary safety of the kitchen; when no people exist in the kitchen, hidden mice, insect pests, night cats and the like can find food, but the people are difficult to monitor at the moment, and the monitoring force in the kitchen is insufficient.
In order to improve the monitoring of the kitchen environment, the invention provides a kitchen environment monitoring system and method based on image recognition.
Disclosure of Invention
The invention aims to provide a kitchen environment monitoring system and method based on image recognition, which are used for solving the technical problems in the background technology.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention relates to a kitchen environment monitoring system based on image recognition, which comprises: the system comprises a kitchen monitoring terminal, a monitoring center and a plurality of monitoring cameras; the kitchen monitoring terminal is electrically connected with the monitoring cameras respectively; the kitchen monitoring terminal is in communication connection with the monitoring center;
the kitchen monitoring terminal comprises a microprocessor, a storage module, an image processing module, a kitchen insect pest identification module and a wireless transmission module; the microprocessor is respectively in electric signal connection with the storage module, the image processing module, the kitchen insect pest identification module, the plurality of monitoring cameras and the wireless transmission module;
the monitoring camera is arranged at the top or the side part in the kitchen and is used for shooting kitchen images and transmitting the image processing module; the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module; the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor;
and if the insect pest identification result indicates that insect pests exist, the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding insect pest identification result to the monitoring center.
As a preferred technical scheme, a pest model library is prestored in the storage module; the pest model library comprises a plurality of different types of pest characteristic models.
As a preferred technical scheme, the kitchen insect pest recognition module extracts kitchen night sub-image features to obtain current image features; the kitchen insect pest recognition module compares the current image characteristics with each insect pest characteristic model to obtain a sub-image recognition result; and the kitchen insect pest recognition module acquires an insect pest recognition result according to the sub-image recognition results.
As a preferred technical scheme, the monitoring center comprises an image collector and a feature training module; the image collector collects insect pest images of the same type as insect pest image samples of corresponding types; the characteristic training module extracts insect pest images in the insect pest image sample to obtain current insect pest characteristics; the characteristic training module is used for training current insect pest characteristics of the same type to obtain an insect pest characteristic model corresponding to the insect pest type.
As a preferred technical scheme, the monitoring center updates the pest characteristic models of various types to a pest model library in the storage module.
As a preferred technical scheme, a smoke sensor, a humidity sensor, a temperature sensor and an alarm are also arranged in the kitchen; the microprocessor is respectively connected with the smoke sensor, the humidity sensor, the temperature sensor and the alarm through electric signals;
the smoke sensor is used for detecting the smoke concentration in the kitchen and transmitting the smoke concentration to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when comparing that the smoke concentration is greater than the smoke concentration threshold;
the humidity sensor is used for detecting the humidity in the kitchen and transmitting the humidity to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison humidity is greater than the humidity threshold value;
the temperature sensor is used for detecting the temperature in the kitchen and transmitting the temperature to the microprocessor; and the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison temperature is greater than the temperature threshold value.
As a preferred technical scheme, a parameter setting module is arranged in the monitoring center; the parameter setting module is used for setting a smoke concentration threshold value, a humidity threshold value and a temperature threshold value and transmitting the smoke concentration threshold value, the humidity threshold value and the temperature threshold value to the kitchen monitoring terminal.
As a preferred technical scheme, the parameter setting module is configured to set an interval time for the monitoring camera to shoot the image and transmit the interval time to the kitchen monitoring terminal.
As a preferred technical scheme, an infrared sensor which is connected with a microprocessor through an electric signal is arranged in the kitchen and used for monitoring animals and transmitting the monitored animals to the microprocessor; if the infrared sensor detects an infrared signal, the microprocessor controls the monitoring camera to shoot a kitchen image.
The kitchen environment monitoring method based on image recognition comprises the following processes:
a00: the monitoring camera shoots a kitchen image and transmits the image processing module;
a01: the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module;
a02: the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor;
a03: judging whether the pest identification result is the existence of pests by the microprocessor; if yes, A04 is executed; if not, executing A00;
a05: the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding insect pest identification result to the monitoring center.
The invention has the following beneficial effects:
according to the invention, a monitoring camera is used for shooting a kitchen image and transmitting an image processing module, and the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to a kitchen insect pest identification module; the kitchen pest identification module compares the kitchen night subgraph with the pest model library to obtain a pest identification result and transmits the pest identification result to the microprocessor, and when the microprocessor judges that the pest identification result is the existence of pests, the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding pest identification result to the monitoring center; the efficiency of monitoring and supervision when improving unmanned in the kitchen, convenient high efficiency.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a kitchen environment monitoring system based on image recognition according to the present invention;
fig. 2 is a flowchart of a kitchen environment monitoring method based on image recognition according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the kitchen environment monitoring system based on image recognition according to the present invention includes: the system comprises a kitchen monitoring terminal, a monitoring center and a plurality of monitoring cameras; the kitchen monitoring terminals are respectively and electrically connected with the monitoring cameras; the kitchen monitoring terminal is in communication connection with the monitoring center; the kitchen monitoring terminal comprises a microprocessor, a storage module, an image processing module, a kitchen insect pest identification module and a wireless transmission module; the microprocessor is respectively in electric signal connection with the storage module, the image processing module, the kitchen insect pest identification module, the plurality of monitoring cameras and the wireless transmission module;
the monitoring camera is arranged at the top or the side part in the kitchen and is used for shooting kitchen images and transmitting the image processing module; the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module; the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor; if the pest identification result indicates that the pest exists, the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding pest identification result to the monitoring center.
Specifically, a pest model library is prestored in the storage module; the pest model library comprises a plurality of pest characteristic models of different types, and particularly, cockroaches, mice and night cats which are common in a kitchen are mainly used as corresponding classifications of the pest characteristic models; a kitchen insect pest recognition module extracts kitchen night sub-image features to obtain current image features; the kitchen insect pest recognition module compares the current image characteristics with each insect pest characteristic model to obtain a sub-image recognition result; and the kitchen pest identification module acquires pest identification results according to the sub-image identification results. In fact, the monitoring center comprises an image collector and a feature training module; the image collector collects insect pest images of the same type as insect pest image samples of corresponding types; the characteristic training module extracts insect pest images in the insect pest image sample to obtain current insect pest characteristics; the characteristic training module is used for training current insect pest characteristics of the same type to obtain insect pest characteristic models corresponding to the insect pest types, and the monitoring center is used for updating the insect pest characteristic models of the various types to an insect pest model library in the storage module.
In addition, a smoke sensor, a humidity sensor, a temperature sensor and an alarm are also arranged in the kitchen; the microprocessor is respectively connected with the smoke sensor, the humidity sensor, the temperature sensor and the alarm through electric signals; the smoke sensor is used for detecting the smoke concentration in the kitchen and transmitting the smoke concentration to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when comparing that the smoke concentration is greater than the smoke concentration threshold value;
the humidity sensor is used for detecting the humidity in the kitchen and transmitting the humidity to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison humidity is greater than the humidity threshold value; the temperature sensor is used for detecting the temperature in the kitchen and transmitting the temperature to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison temperature is greater than the temperature threshold; a parameter setting module is arranged in the monitoring center; the parameter setting module is used for setting a smoke concentration threshold value, a humidity threshold value and a temperature threshold value and transmitting the smoke concentration threshold value, the humidity threshold value and the temperature threshold value to the kitchen monitoring terminal; during the in-service use, when nobody in the kitchen, through smoke transducer, humidity transducer and temperature sensor monitoring smoke concentration, temperature and humidity in the kitchen respectively, guarantee the safety in the kitchen, improve the safety monitoring effect.
In addition, the parameter setting module is used for setting the interval time of the images shot by the monitoring camera and transmitting the interval time to the kitchen monitoring terminal; an infrared sensor which is connected with the microprocessor through electric signals is arranged in the kitchen and used for monitoring animals and transmitting the monitored animals to the microprocessor; if the infrared sensor detects an infrared signal, the microprocessor controls the monitoring camera to shoot a kitchen image; specifically, when no person is in the kitchen, the monitoring equipment is started; under the conventional condition, the microprocessor controls the monitoring camera to shoot according to the interval time; when the infrared sensor detects an infrared signal, the monitoring camera is controlled by the processor to shoot instantly, so that the system is efficient and convenient.
Referring to fig. 2, the kitchen environment monitoring method based on image recognition includes the following steps:
a00: the monitoring camera shoots a kitchen image and transmits the image processing module;
a01: the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module;
a02: the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor;
a03: judging whether the pest identification result is the existence of pests by the microprocessor; if yes, A04 is executed; if not, executing A00;
a05: the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding insect pest identification result to the monitoring center.
When the intelligent kitchen insect damage recognition system is in actual use, a kitchen image is shot through the monitoring camera and is transmitted to the image processing module, and the kitchen image is equally divided into a plurality of kitchen night subgraphs by the image processing module and is transmitted to the kitchen insect damage recognition module; the kitchen pest identification module compares the kitchen night subgraph with the pest model library to obtain a pest identification result and transmits the pest identification result to the microprocessor, and when the microprocessor judges that the pest identification result is the existence of pests, the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding pest identification result to the monitoring center; the efficiency of monitoring and supervision when improving unmanned in the kitchen, convenient high efficiency.
It should be noted that, in the above system embodiment, each included unit is only divided according to functional logic, but is not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
In addition, it is understood by those skilled in the art that all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing associated hardware, and the corresponding program may be stored in a computer-readable storage medium.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (10)
1. Kitchen environment monitoring system based on image recognition, its characterized in that includes: the system comprises a kitchen monitoring terminal, a monitoring center and a plurality of monitoring cameras; the kitchen monitoring terminal is electrically connected with the monitoring cameras respectively; the kitchen monitoring terminal is in communication connection with the monitoring center;
the kitchen monitoring terminal comprises a microprocessor, a storage module, an image processing module, a kitchen insect pest identification module and a wireless transmission module; the microprocessor is respectively in electric signal connection with the storage module, the image processing module, the kitchen insect pest identification module, the plurality of monitoring cameras and the wireless transmission module;
the monitoring camera is arranged at the top or the side part in the kitchen and is used for shooting kitchen images and transmitting the image processing module; the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module; the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor;
and if the insect pest identification result indicates that insect pests exist, the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding insect pest identification result to the monitoring center.
2. The kitchen environment monitoring system based on image recognition according to claim 1, wherein a pest model library is prestored in the storage module; the pest model library comprises a plurality of different types of pest characteristic models.
3. The kitchen environment monitoring system based on image recognition according to claim 2, wherein the kitchen pest recognition module extracts a current image feature from a kitchen night sub-image feature; the kitchen insect pest recognition module compares the current image characteristics with each insect pest characteristic model to obtain a sub-image recognition result; and the kitchen insect pest recognition module acquires an insect pest recognition result according to the sub-image recognition results.
4. The kitchen environment monitoring system based on image recognition according to claim 3, wherein the monitoring center comprises an image collector and a feature training module; the image collector collects insect pest images of the same type as insect pest image samples of corresponding types; the characteristic training module extracts insect pest images in the insect pest image sample to obtain current insect pest characteristics; the characteristic training module is used for training current insect pest characteristics of the same type to obtain an insect pest characteristic model corresponding to the insect pest type.
5. The kitchen environment monitoring system based on image recognition according to claim 4, wherein the monitoring center updates each type of pest feature model to a pest model library in a storage module.
6. The kitchen environment monitoring system based on image recognition is characterized in that a smoke sensor, a humidity sensor, a temperature sensor and an alarm are further installed in a kitchen; the microprocessor is respectively connected with the smoke sensor, the humidity sensor, the temperature sensor and the alarm through electric signals;
the smoke sensor is used for detecting the smoke concentration in the kitchen and transmitting the smoke concentration to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when comparing that the smoke concentration is greater than the smoke concentration threshold;
the humidity sensor is used for detecting the humidity in the kitchen and transmitting the humidity to the microprocessor; the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison humidity is greater than the humidity threshold value;
the temperature sensor is used for detecting the temperature in the kitchen and transmitting the temperature to the microprocessor; and the microprocessor controls the alarm to give an alarm and transmits alarm information to the monitoring center when the comparison temperature is greater than the temperature threshold value.
7. The kitchen environment monitoring system based on image recognition according to claim 6, wherein a parameter setting module is arranged in the monitoring center; the parameter setting module is used for setting a smoke concentration threshold value, a humidity threshold value and a temperature threshold value and transmitting the smoke concentration threshold value, the humidity threshold value and the temperature threshold value to the kitchen monitoring terminal.
8. The kitchen environment monitoring system based on image recognition according to claim 7, wherein the parameter setting module is used for setting the interval time for the monitoring camera to shoot the image and transmitting the interval time to the kitchen monitoring terminal.
9. The kitchen environment monitoring system based on image recognition as claimed in claim 8, wherein an infrared sensor electrically connected with a microprocessor is installed in the kitchen for monitoring animals and transmitting to the microprocessor; if the infrared sensor detects an infrared signal, the microprocessor controls the monitoring camera to shoot a kitchen image.
10. The kitchen environment monitoring method based on image recognition is characterized by comprising the following steps of:
a00: the monitoring camera shoots a kitchen image and transmits the image processing module;
a01: the image processing module equally divides the kitchen image into a plurality of kitchen night subgraphs and transmits the kitchen night subgraphs to the kitchen insect pest identification module;
a02: the kitchen insect pest recognition module compares the kitchen night subgraph with the insect pest model library to obtain insect pest recognition results and transmits the insect pest recognition results to the microprocessor;
a03: judging whether the pest identification result is the existence of pests by the microprocessor; if yes, A04 is executed; if not, executing A00;
a05: the microprocessor controls the wireless transmission module to transmit the kitchen image and the corresponding insect pest identification result to the monitoring center.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011352907.6A CN112487944A (en) | 2020-11-26 | 2020-11-26 | Kitchen environment monitoring system and method based on image recognition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011352907.6A CN112487944A (en) | 2020-11-26 | 2020-11-26 | Kitchen environment monitoring system and method based on image recognition |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112487944A true CN112487944A (en) | 2021-03-12 |
Family
ID=74935646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011352907.6A Withdrawn CN112487944A (en) | 2020-11-26 | 2020-11-26 | Kitchen environment monitoring system and method based on image recognition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112487944A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113038082A (en) * | 2021-03-24 | 2021-06-25 | 安徽超视野智能科技有限公司 | Kitchen environment monitoring equipment and method based on image recognition |
| CN114383296A (en) * | 2021-12-20 | 2022-04-22 | 青岛海尔空调器有限总公司 | Method and device for controlling air conditioner and air conditioner |
-
2020
- 2020-11-26 CN CN202011352907.6A patent/CN112487944A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113038082A (en) * | 2021-03-24 | 2021-06-25 | 安徽超视野智能科技有限公司 | Kitchen environment monitoring equipment and method based on image recognition |
| CN114383296A (en) * | 2021-12-20 | 2022-04-22 | 青岛海尔空调器有限总公司 | Method and device for controlling air conditioner and air conditioner |
| CN114383296B (en) * | 2021-12-20 | 2023-08-18 | 青岛海尔空调器有限总公司 | Method and device for controlling air conditioner and air conditioner |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112487944A (en) | Kitchen environment monitoring system and method based on image recognition | |
| KR102396172B1 (en) | System and method for managing livestock based on artificial intelligence | |
| CN109241897B (en) | Monitoring image processing method and device, gateway equipment and storage medium | |
| CN108986405B (en) | Multi-parameter control method based on Zigbee gateway | |
| CN108257343A (en) | A kind of intelligent door and window safety-protection system | |
| KR20210080226A (en) | Method for monitoring companion animal and apparatus thereof | |
| CN106327813A (en) | Intelligent voice recognition and alarm method and system thereof | |
| CN107131607A (en) | Monitoring method, device, system and air-conditioning based on air-conditioning | |
| CN111047819B (en) | Intelligent monitoring system based on remote communication | |
| CN111240223A (en) | Intelligent household control method and related product | |
| CN205281721U (en) | Intelligent monitoring system | |
| CN112036248A (en) | Intelligent fishpond management system based on scene recognition | |
| CN111491258B (en) | Object type detection method and device | |
| CN112364816A (en) | Kitchen wearing monitoring system and method based on image recognition | |
| CN115604049B (en) | Intelligent communication network system for household multifunctional monitoring | |
| CN104680688B (en) | Anti-theft alarm remote network snapshooting and monitoring device based on traffic signal controller | |
| CN116364084A (en) | Method and system for automatically detecting response delay of intelligent doorbell through sound | |
| CN112991661A (en) | Intelligent household kitchen smoke alarm system | |
| CN116740874A (en) | Intrusion detection method and related device | |
| CN115941716A (en) | Device control method, electronic device, and computer-readable storage medium | |
| CN113038082A (en) | Kitchen environment monitoring equipment and method based on image recognition | |
| CN113571091A (en) | Audio sudden change detection method and device for monitoring and household appliance | |
| KR102456010B1 (en) | Wasp detecting system and wasp detecting method | |
| CN105785887A (en) | Intelligent security and protection monitoring system | |
| CN116320321B (en) | Agricultural information transmission method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210312 |