Intelligent kitchen safety monitoring method and device based on cloud platform

Abstract

The invention relates to the technical field of data analysis, in particular to an intelligent kitchen safety monitoring method and device based on a cloud platform, and the device comprises a data collection module, a data analysis module, a data transmission module and a safety control module. According to the invention, the preset safety coefficient of the family member is set, the behavior analysis value of the family member is calculated according to the equipment data and the behavior data collected by the monitoring point, the behavior analysis value is transmitted to the cloud platform, the standard analysis value is calculated based on the behavior analysis value, and the behavior analysis value is compared with the standard analysis value. Determining a security constraint threshold value of the family member in combination with the line risk value; when the family member enters the kitchen to operate the online equipment, the behavior analysis value of the family member is compared with the safety constraint threshold value, and an alarm is given or the circuit is controlled to be disconnected according to the comparison result, so that the purpose of protecting the personal safety of the family member in advance is achieved, the safety of the family member in the kitchen is automatically monitored, and the management effect of kitchen safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to an intelligent kitchen safety monitoring method and device based on a cloud platform. Background Art

[0002] Kitchen safety is an important aspect of family safety. The kitchen integrates a large number of high-power electrical appliances. When users use them improperly or accidents occur due to the appliances themselves, it will cause serious harm to users and families. Therefore, it is necessary to monitor kitchen safety and control electrical equipment.

[0003] In the prior art, such as the patent document entitled Kitchen Safety Management Method, Device, Storage Medium and Electronic Device with publication number CN111221256B, a management method is disclosed, which helps to reduce the occurrence of electrical accidents and greatly reduce the safety risks of children alone at home by incorporating kitchen equipment and doors into the home Internet of Things system for overall control; but the above patent document has the following defects: the management method is to lock the kitchen area, that is, to lock kitchen-related equipment for special groups of people and at special times, and to avoid kitchen safety risks by preventing special groups from entering the kitchen or using equipment. It is impossible to autonomously supervise the safety of the kitchen, that is, when it is not in the kitchen safety mode and is using electrical appliances in the kitchen, when special circumstances occur, it is impossible to control the locking of the electrical appliances or give relevant alarms, which has considerable limitations. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose an intelligent kitchen safety monitoring method and device based on a cloud platform.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: an intelligent kitchen safety monitoring method and device based on a cloud platform, comprising the following steps:

[0006] S1. Enter the image information of family members and the preset safety factor;

[0007] S2. Obtain image information of the person entering the kitchen, identify the image and extract image features, and bind the image features with family members;

[0008] S3, obtaining the online equipment information used in the kitchen and adding monitoring points to the online equipment;

[0009] S4. Collect usage information of different online devices and behavior information of family members through monitoring points, integrate and calculate the usage information and behavior information, and obtain usage behavior analysis values ​​of family members;

[0010] S5. Obtain the line power of the line where the online device is located, calculate the line risk value according to the line power, modify the text analysis value according to the line risk value, and obtain the safety constraint threshold of the family members;

[0011] S6. Monitor and control the usage behavior of family members when using equipment in the kitchen based on safety constraint thresholds.

[0012] As a further solution of the present invention, the method for adding monitoring points to online equipment is:

[0013] Determine the device model of the online device according to the online device information, obtain the high-definition image corresponding to the device model and use it as the target image, obtain a panoramic image of the kitchen, use image processing technology to determine the location information of the target image in the panoramic image, mark it as the target area, and use the target area as the monitoring point of the online equipment.

[0014] As a further solution of the present invention, the usage information includes the number of devices online at the same time, the duration of online at the same time, and the monitoring duration; the behavior information includes the total control duration, the personal control duration, and the number of effective control persons;

[0015] The method of collecting usage behavior information is:

[0016] SS01. Obtain the device status of online devices. When any online device is in working state, determine whether there are other online devices in working state at the same time. If there are other online devices, calculate the number of online devices in working state at the same time and use it as the number of simultaneous online devices. And count the simultaneous online duration based on the current number of simultaneous online devices. If there are no other online devices, do not perform any operation.

[0017] SS02. When any online device is in working state, the kitchen is determined to be in monitoring mode. When no online device is in working state, the kitchen is determined to be in safety mode regardless of whether there are family members in the kitchen. The total time the kitchen is in monitoring mode is obtained and used as the monitoring duration. When the kitchen is in monitoring mode, it is determined whether there are family members in the kitchen. If so, it is determined to be in control mode, and the total time in control mode is counted and used as the total control duration. The total time of different family members entering the kitchen is counted separately and used as the individual control duration.

[0018] Analyze the personal control time of family members. If the personal control time is not less than the effective time threshold, it is marked as effective control time; if the personal control time is less than the effective time threshold, it is marked as invalid control time; mark the family members corresponding to the effective control time as effective control members, count the total number of effective control members and use it as the effective control number;

[0019] SS03, value calculation formula through behavior analysis The behavior analysis value FXi of family members is calculated; E is the preset safety factor, TZ is the number of devices online at the same time, TC is the simultaneous online time, Tj is the monitoring time, Tk is the total control time, YK is the number of effective control persons, Tgi is the personal control time; i is the family member number, i∈[1,n], and n is the total number of family members.

[0020] As a further solution of the present invention, in the monitoring mode, the online devices connected to the same line and the line power P are simultaneously obtained, the online devices in working state are marked as target devices, the minimum power in the power range of the target devices is marked as the lower limit power, and the maximum power in the power range of the target devices is marked as the upper limit power;

[0021] The lower power limit and upper power limit of the target device are accumulated to obtain the minimum power A and the maximum power B respectively. A standard power range [A, B] is established based on the minimum power A and the maximum power B. A risk assessment model is generated based on whether the line power P belongs to the standard power range [A, B].

[0022] The expression of the risk assessment model is:

[0023] XZj is the line risk value; j is the line number, j∈[1,m], and m is the total number of online devices.

[0024] As a further solution of the present invention, a method for obtaining the safety constraint threshold of family members is as follows:

[0025] Process the line risk value XZj and the behavior analysis value FXi of the family member. If there is no line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as a valid analysis value; if there is a line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as an invalid analysis value, and the valid analysis value is transmitted to the cloud platform;

[0026] Based on the cloud platform, several valid analysis values ​​are accumulated and averaged to obtain an average analysis value, which is used as a standard constraint threshold to supervise family members according to the standard analysis threshold;

[0027] If the behavior analysis value is not greater than the standard constraint threshold, determine whether the current line risk value is equal to 1; if the line risk value is 1, use the standard constraint threshold as the user's safety constraint threshold; if the line risk value is -1, use the behavior analysis value of the family member as the safety constraint threshold;

[0028] If the behavior analysis value is greater than the standard constraint threshold, determine whether the current line risk value is equal to -1; if the line risk value is -1, use the standard constraint threshold as the user's safety constraint threshold; if the line risk value is 1, the behavior analysis value of the family member is upgraded to obtain a modified behavior analysis value, and use the modified behavior analysis value as the safety constraint threshold of the family member.

[0029] As a further solution of the present invention, the method for supervising the use behavior of family members is:

[0030] If the behavior analysis value of a family member is greater than the corresponding safety constraint threshold, an alarm will be issued and the risk values ​​of all lines in the kitchen will be monitored. If the line risk value is -1, the corresponding line will be prompted and the circuit will be disconnected.

[0031] As a further solution of the present invention, a preset safety factor is used to control the user's behavior analysis value, and different family members can set different preset safety factors.

[0032] In addition, the present invention also discloses an intelligent kitchen safety monitoring device based on a cloud platform, including a data acquisition module, a data analysis module, a data transmission module and a safety control module;

[0033] The data acquisition module includes several cameras, several smart wifi sockets and a central control screen. Several cameras are set up in the kitchen to obtain a panoramic image of the kitchen and perform face recognition; several smart wifi sockets are used to collect the power of the lines where online devices are located, and control the connection of the lines to achieve access or disconnection; the central control screen is used to set the preset safety factor of family members;

[0034] A data analysis module, used to implement steps S2 to S6;

[0035] A data transmission module, used to transmit the calculated behavior analysis value to the cloud platform, and receive the safety constraint thresholds set by the cloud platform for family members;

[0036] Security control module; used to monitor the user's behavior analysis value, and judge the behavior analysis value based on the security constraint threshold, and control the online devices and family members according to the judgment results.

[0037] Compared with the existing technology, the advantages of the present invention are: the present invention sets preset safety factors for family members, calculates behavior analysis values ​​of family members based on equipment data and behavior data collected at monitoring points, transmits the behavior analysis values ​​to the cloud platform, and obtains standard analysis values ​​based on the behavior analysis values, compares the behavior analysis values ​​with the standard analysis values, and determines the safety constraint threshold of family members in combination with line risk values; when family members enter the kitchen to operate online equipment, their behavior analysis values ​​are compared with the safety constraint thresholds, and an alarm is issued or the line is controlled to be disconnected based on the comparison results, so as to achieve the purpose of protecting the personal safety of family members in advance, realize autonomous monitoring of the safety of family members in the kitchen, and improve the management effect of kitchen safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a module structure diagram of the present invention.

[0039] Figure 2 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0041] Example 1: Reference Figure 1 , an intelligent kitchen safety monitoring device based on a cloud platform, including a data acquisition module, a data analysis module, a data transmission module and a safety control module;

[0042] The data acquisition module includes several cameras, several smart wifi sockets and a central control screen. Several cameras are set in the kitchen to obtain a panoramic image of the kitchen and perform face recognition; several smart wifi sockets are used to collect the power of the lines where online devices are located, and control the connection of the lines to achieve access or disconnection. One smart wifi socket corresponds to and controls one line; the central control screen is used to set the preset safety factor of family members; face recognition and smart wifi sockets are both existing technologies and will not be repeated here;

[0043] A data analysis module, used to implement steps S2 to S6;

[0044] A data transmission module, used to transmit the calculated behavior analysis value to the cloud platform, and receive the safety constraint thresholds set by the cloud platform for family members;

[0045] Security control module; used to monitor the user's behavior analysis value, and judge the behavior analysis value based on the security constraint threshold, and control the online devices and family members according to the judgment results.

[0046] Example 2: Reference Figure 2 , an intelligent kitchen safety monitoring method based on a cloud platform, comprising the following steps:

[0047] S1. Enter the image information and preset safety factor of the family members; the preset safety factor is used to control the behavior analysis value of the user, and different family members can set different preset safety factors; for example, the preset safety factor can be 1 to 10, the preset safety factor of a child who is unable to take care of himself can be set to 10, and the preset safety factor of an adult who is proficient in operating kitchen online equipment can be set to 1;

[0048] S2. Obtain image information of the person entering the kitchen, identify the image and extract image features, and bind the image features to the family members; it should be noted that the image information referred to here specifically refers to the face image;

[0049] S3, obtaining the online equipment information used in the kitchen and adding monitoring points to the online equipment;

[0050] The method to add monitoring points to online equipment is:

[0051] Determine the device model of the online device according to the online device information, obtain the high-definition image corresponding to the device model and use it as the target image, obtain a panoramic image of the kitchen, use image processing technology to determine the location information of the target image in the panoramic image, mark it as the target area, and use the target area as the monitoring point of the online device;

[0052] S4. Use information of different online devices and behavior information of family members are collected through monitoring points, and the use information and behavior information are integrated and calculated to obtain the use behavior analysis value of family members; the use information includes the number of devices online at the same time, the time online at the same time, and the monitoring time; the behavior information includes the total control time, the personal control time, and the number of effective control persons;

[0053] The method of collecting usage behavior information is:

[0054] SS01. Obtain the device status of the online device. When any online device is in working state, determine whether there are other online devices in working state at the same time; if there are other online devices, calculate the number of online devices in working state at the same time and use it as the number of simultaneous online devices, and count the simultaneous online time based on the current number of simultaneous online devices; if there are no other online devices, do not operate; the device status of the online device can be determined by obtaining the color of the indicator light of the online device and judging it according to the color of the indicator light. Specifically, it can be realized by spectral analysis technology. Spectral analysis technology is a prior art and will not be described here.

[0055] SS02. When any online device is in working state, the kitchen is determined to be in monitoring mode. When no online device is in working state, the kitchen is determined to be in safety mode regardless of whether there are family members in the kitchen. The total time the kitchen is in monitoring mode is obtained and used as the monitoring duration. When the kitchen is in monitoring mode, it is determined whether there are family members in the kitchen. If so, it is determined to be in control mode, and the total time in control mode is counted and used as the total control duration. The total time of different family members entering the kitchen is counted separately and used as the individual control duration.

[0056] The personal control time of family members is analyzed. If the personal control time is not less than the effective time threshold, it is marked as effective control time; if the personal control time is less than the effective time threshold, it is marked as invalid control time; the family members corresponding to the effective control time are marked as effective control members, and the total number of effective control members is counted and used as the number of effective control members; the effective time threshold can be calculated by the formula Y=Tj÷X, where Y is the effective time threshold, Tj is the monitoring time in minutes, and X is the ratio coefficient; the ratio coefficient X can be set to 10; for example, if the monitoring time Tj is 100 minutes, the effective time threshold is 100÷10=10 minutes;

[0057] SS03, value calculation formula through behavior analysis The behavior analysis value FXi of the family member is calculated; E is the preset safety factor, TZ is the number of devices online at the same time, TC is the time spent online at the same time, Tk is the total time spent on control, YK is the number of effective control persons, and Tgi is the personal control time; i is the family member number, i∈[1, n], and n is the total number of family members; the units of the time spent online at the same time TC, the total time spent on control TK, and the personal control time Tgi are all in minutes; it should be noted that if the personal control time of a family member does not exist, it will be set to 1 minute;

[0058] In the monitoring mode, the online devices connected to the same line and the line power P are obtained at the same time, the online devices in working state are marked as target devices, the minimum power in the power range of the target devices is marked as the lower limit power, and the maximum power in the power range of the target devices is marked as the upper limit power;

[0059] The lower power limit and upper power limit of the target device are accumulated to obtain the minimum power A and the maximum power B respectively. A standard power range [A, B] is established based on the minimum power A and the maximum power B. A risk assessment model is generated based on whether the line power P belongs to the standard power range [A, B].

[0060] The expression of the risk assessment model is:

[0061] XZj is the line risk value; j is the line number, j∈[1,m], m is the total number of online devices;

[0062] S5. Obtain the line power of the line where the online device is located, calculate the line risk value according to the line power, modify the text analysis value according to the line risk value, and obtain the safety constraint threshold of the family members;

[0063] The method to obtain the safety constraint threshold of family members is:

[0064] Process the line risk value XZj and the behavior analysis value FXi of the family member. If there is no line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as a valid analysis value; if there is a line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as an invalid analysis value, and the valid analysis value is transmitted to the cloud platform;

[0065] Based on the cloud platform, several valid analysis values ​​are accumulated and averaged to obtain an average analysis value, which is used as a standard constraint threshold to supervise family members according to the standard analysis threshold;

[0066] If the behavior analysis value is not greater than the standard constraint threshold, determine whether the current line risk value is equal to 1; if the line risk value is 1, use the standard constraint threshold as the user's safety constraint threshold; if the line risk value is -1, use the behavior analysis value of the family member as the safety constraint threshold;

[0067] If the behavior analysis value is greater than the standard constraint threshold, determine whether the current line risk value is equal to -1; if the line risk value is -1, use the standard constraint threshold as the user's safety constraint threshold; if the line risk value is 1, increase the behavior analysis value of the family member to obtain a modified behavior analysis value, and use the modified behavior analysis value as the safety constraint threshold of the family member;

[0068] S6. Monitor and control the use of equipment by family members in the kitchen according to the safety constraint threshold;

[0069] Methods for supervising the use of family members are:

[0070] If the behavior analysis value of a family member is greater than the corresponding safety constraint threshold, an alarm will be issued and the risk values ​​of all lines in the kitchen will be monitored. If the line risk value is -1, the corresponding line will be prompted and disconnected;

[0071] By setting preset safety factors for family members, and calculating the behavior analysis values ​​of family members based on the equipment data and behavior data collected at the monitoring points, the behavior analysis values ​​are transmitted to the cloud platform, and the standard analysis values ​​are calculated based on the behavior analysis values. The behavior analysis values ​​are compared with the standard analysis values, and combined with the line risk values, the safety constraint thresholds of family members are determined; when family members enter the kitchen to operate online equipment, their behavior analysis values ​​are compared with the safety constraint thresholds, and alarms are issued or line disconnections are controlled based on the comparison results, so as to achieve the purpose of protecting the personal safety of family members in advance, realize autonomous monitoring of the safety of family members in the kitchen, and improve the management effect of kitchen safety.

[0072] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent kitchen safety monitoring method based on a cloud platform, characterized in that: The following steps are involved: S1. Enter the image information of family members and the preset safety factor; S2. Obtain image information of the person entering the kitchen, identify the image and extract image features, and bind the image features with family members; S3, obtaining the online equipment information used in the kitchen and adding monitoring points to the online equipment; S4. Collect usage information of different online devices and behavior information of family members through monitoring points, integrate and calculate the usage information and behavior information, and obtain usage behavior analysis values ​​of family members; S5. Obtain the line power of the line where the online device is located, calculate the line risk value according to the line power, modify the text analysis value according to the line risk value, and obtain the safety constraint threshold of the family members; S6. Monitor and control the usage behavior of family members when using equipment in the kitchen based on safety constraint thresholds.

2. According to claim 1, a cloud platform-based intelligent kitchen safety monitoring method is characterized in that: The method to add monitoring points to online equipment is: Determine the device model of the online device according to the online device information, obtain the high-definition image corresponding to the device model and use it as the target image, obtain a panoramic image of the kitchen, use image processing technology to determine the location information of the target image in the panoramic image, mark it as the target area, and use the target area as the monitoring point of the online equipment.

3. The intelligent kitchen safety monitoring method based on a cloud platform according to claim 1 is characterized in that: Usage information includes the number of devices online at the same time, the duration of online at the same time, and the monitoring duration; behavior information includes the total control duration, the individual control duration, and the number of effective control persons; The method of collecting usage behavior information is: SS01. Obtain the device status of online devices. When any online device is in working state, determine whether there are other online devices in working state at the same time. If there are other online devices, calculate the number of online devices in working state at the same time and use it as the number of simultaneous online devices. And count the simultaneous online duration based on the current number of simultaneous online devices. If there are no other online devices, do not perform any operation. SS02: When any online device is in working state, the kitchen is judged to be in monitoring mode; when no online device is in working state, the kitchen is judged to be in safety mode regardless of whether there are family members in the kitchen; Get the total time the kitchen is in monitoring mode and use it as the monitoring duration; Determine whether there are family members in the kitchen when in monitoring mode. If so, determine that it is in control mode, and count the total time in control mode as the total control time; Count the total time different family members spend in the kitchen and use it as personal control time; Analyze the personal control time of family members. If the personal control time is not less than the effective time threshold, it is marked as effective control time; if the personal control time is less than the effective time threshold, it is marked as invalid control time; mark the family members corresponding to the effective control time as effective control members, count the total number of effective control members and use it as the effective control number; SS03, value calculation formula through behavior analysis The behavior analysis value FXi of family members is calculated; E is the preset safety factor, TZ is the number of devices online at the same time, TC is the time spent online at the same time, Tj is the monitoring time, Tk is the total control time, YK is the number of effective controlled persons, and Tgi is the personal control time; i is the family member number, i∈[1,n], and n is the total number of family members.

4. The intelligent kitchen safety monitoring method based on a cloud platform according to claim 3 is characterized in that: In the monitoring mode, the online devices connected to the same line and the line power P are obtained at the same time, the online devices in working state are marked as target devices, the minimum power in the power range of the target devices is marked as the lower limit power, and the maximum power in the power range of the target devices is marked as the upper limit power; The lower power limit and upper power limit of the target device are accumulated to obtain the minimum power A and the maximum power B respectively. A standard power range [A, B] is established based on the minimum power A and the maximum power B. A risk assessment model is generated based on whether the line power P belongs to the standard power range [A, B]. The expression of the risk assessment model is: XZj is the line risk value; j is the line number, j∈[1,m], and m is the total number of online devices.

5. The intelligent kitchen safety monitoring method based on a cloud platform according to claim 4 is characterized in that: The method to obtain the safety constraint threshold of family members is: Process the line risk value XZj and the behavior analysis value FXi of the family member. If there is no line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as a valid analysis value; if there is a line risk value XZj equal to -1, the behavior analysis value FXi of the family member is marked as an invalid analysis value, and the valid analysis value is transmitted to the cloud platform; Based on the cloud platform, several valid analysis values ​​are accumulated and averaged to obtain an average analysis value, which is used as a standard constraint threshold to supervise family members according to the standard analysis threshold; If the behavior analysis value is not greater than the standard constraint threshold, determine whether the current line risk value is equal to 1; if the line risk value is 1, use the standard constraint threshold as the user's safety constraint threshold; if the line risk value is -1, use the behavior analysis value of the family member as the safety constraint threshold; If the behavior analysis value is greater than the standard constraint threshold, determine whether the current line risk value is equal to -1; if the line risk value is -1, use the standard constraint threshold as the user's safety constraint threshold; If the line risk value is 1, the behavior analysis value of the family member is upgraded to obtain a modified behavior analysis value, and the modified behavior analysis value is used as the safety constraint threshold of the family member.

6. The intelligent kitchen safety monitoring method based on a cloud platform according to claim 5 is characterized in that: Methods for supervising the use of family members are: If the behavior analysis value of a family member is greater than the corresponding safety constraint threshold, an alarm will be issued and the risk values ​​of all lines in the kitchen will be monitored. If the line risk value is -1, the corresponding line will be prompted and the circuit will be disconnected.

7. The intelligent kitchen safety monitoring method based on a cloud platform according to claim 6 is characterized in that: The preset safety factor is used to control the user's behavior analysis value. Different family members can set different preset safety factors.

8. An intelligent kitchen safety monitoring device based on a cloud platform, applying the intelligent kitchen safety monitoring method based on a cloud platform as described in claim 7, characterized in that: It includes data acquisition module, data analysis module, data transmission module and safety control module; The data acquisition module includes several cameras, several smart wifi sockets and a central control screen. Several cameras are set up in the kitchen to obtain a panoramic image of the kitchen and perform face recognition; several smart wifi sockets are used to collect the power of the lines where online devices are located, and control the connection of the lines to achieve access or disconnection; the central control screen is used to set the preset safety factor of family members; A data analysis module, used to implement steps S2 to S6; A data transmission module, used to transmit the calculated behavior analysis value to the cloud platform, and receive the safety constraint thresholds set by the cloud platform for family members; Safety control module; It is used to monitor the user's behavior analysis value, judge the behavior analysis value based on the security constraint threshold, and manage the online devices and family members according to the judgment results.

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