Range hood analysis report generation method and device, electronic equipment and storage medium

Abstract

The invention relates to a range hood analysis report generation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring use data transmitted by a range hood; based on a preset non-compliance condition, performing non-compliance statistical processing on the use data to obtain non-compliance record information; based on a preset compliance condition, processing the non-compliance record information to obtain health prompt information; according to the non-compliance record information and the health prompt information, a use analysis report of the smoke exhaust ventilator is obtained, so that the use analysis report of the smoke exhaust ventilator is accurately generated, a user can conveniently check the use condition of the smoke exhaust ventilator in real time, personalized health suggestions are given to the user, the user is helped to know the life style of the user, and the user experience is improved. And through reasonable reminding and suggestion, the user is helped to develop healthier diet and living habits, and the negative influence of night snacks on the body is reduced, so that the reliability of analysis of non-compliant use conditions and health prompts is improved, and the accuracy of report generation is improved.

Description

Technical Field

[0001] The present application relates to the technical field of range hood data processing, and in particular to a range hood analysis report generation method, device, electronic device, and storage medium. Background Art

[0002] A range hood, also known as a range hood, is an electrical appliance used to purify the kitchen environment. As a crucial appliance in the kitchen, users' usage habits and duration of use directly reflect their dietary habits. Late-night use, in particular, is often associated with unhealthy eating habits (such as late-night snacking), potentially posing a health risk to users.

[0003] At present, range hoods can usually only provide basic air purification. The analysis process of range hood usage data is simple, the analysis of non-compliant usage and health warnings has large errors, and the accuracy of generated reports is low. Summary of the Invention

[0004] Based on this, a method, device, electronic device and storage medium for generating a range hood analysis report are provided.

[0005] In a first aspect, the present application provides a method for generating a range hood analysis report, comprising the following steps:

[0006] Obtain usage data transmitted by the range hood;

[0007] Based on the preset non-compliance conditions, the usage data is statistically processed to obtain non-compliance record information;

[0008] Based on the preset compliance conditions, non-compliant record information is processed to obtain health reminder information;

[0009] Based on the non-compliance record information and health reminder information, an analysis report on the use of the range hood is obtained.

[0010] In one embodiment, the usage data includes the acquisition time and the particle size concentration value corresponding to the acquisition time;

[0011] Based on the preset non-compliance conditions, the steps of performing non-compliance statistical processing on the usage data and obtaining non-compliance record information include:

[0012] Extract the particle size concentration value whose collection time falls within the preset time period;

[0013] When the particle size concentration value exceeds a preset concentration threshold, it is determined that the range hood is used non-compliantly during the corresponding collection time, and the particle size concentration value and the collection time are recorded as non-compliant information.

[0014] In one embodiment, when the particle size concentration value exceeds a preset concentration threshold, determining that the use of the range hood at the corresponding collection time is non-compliant, and recording the particle size concentration value and the collection time as non-compliant information includes:

[0015] When the particle size concentration values ​​of at least two consecutive collection times all exceed the preset concentration threshold, the corresponding particle size concentration values ​​are averaged to obtain the average particle size concentration value corresponding to the at least two consecutive collection times;

[0016] Based on at least two consecutive collection times, the non-compliant time period is obtained;

[0017] The particle size concentration value and non-compliant time period are recorded as non-compliant information.

[0018] In one embodiment, based on preset compliance conditions, the steps of processing non-compliant record information to obtain health reminder information include:

[0019] Perform non-compliant statistical processing on non-compliant record information within a preset period to obtain the frequency of non-compliant use and the time period of high incidence;

[0020] Based on the frequency of non-compliant use and high-incidence time periods, query the preset mapping relationship table to obtain health reminder information.

[0021] In one embodiment, the step of obtaining a range hood usage analysis report based on the non-compliance record information and the health reminder information includes:

[0022] Perform non-compliant statistical processing on the non-compliant record information of the current month to obtain the number of non-compliant uses in that month;

[0023] Obtain the number of non-compliant uses in the previous month, and compare the number of non-compliant uses in the current month with the number of non-compliant uses in the previous month to obtain non-compliant change trend information;

[0024] The steps for obtaining a range hood usage analysis report based on the non-compliance record information and health warning information include:

[0025] Obtain usage analysis reports based on non-compliance record information, health reminder information, and non-compliance change trend information.

[0026] In one embodiment, based on a preset non-compliance condition, performing non-compliance statistical processing on the usage data to obtain non-compliance record information includes:

[0027] Clean the usage data to obtain target usage data;

[0028] Based on the preset non-compliance conditions, the steps of performing non-compliance statistical processing on the usage data and obtaining non-compliance record information include:

[0029] Based on the preset non-compliance conditions, the target usage data is subjected to non-compliance statistical processing to obtain non-compliance record information.

[0030] In one embodiment, the usage analysis report includes a daily usage analysis report, a monthly usage analysis report, and a yearly usage analysis report.

[0031] In a second aspect, the present application provides a device for generating a range hood analysis report, comprising:

[0032] a data acquisition unit, configured to acquire usage data transmitted by the range hood;

[0033] A non-compliance statistics unit is used to perform non-compliance statistics processing on usage data based on preset non-compliance conditions to obtain non-compliance record information;

[0034] A prompt information acquisition unit, configured to process non-compliant record information based on preset compliance conditions to obtain health prompt information;

[0035] The report generating unit is used to obtain a usage analysis report of the range hood based on the non-compliance record information and health reminder information.

[0036] In a third aspect, the present application provides an electronic device comprising a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, a method for generating a smoke machine analysis report as described above is implemented.

[0037] In a fourth aspect, the present application provides a storage medium, which is a computer-readable storage medium used for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement any of the above-mentioned methods for generating a smoke machine analysis report.

[0038] One of the above technical solutions has the following advantages and beneficial effects:

[0039] In the above range hood analysis report generation method, the usage data transmitted by the range hood is obtained; based on the preset non-compliance conditions, the usage data is subjected to non-compliance statistical processing to obtain non-compliance record information; based on the preset compliance conditions, the non-compliance record information is processed to obtain health reminder information; based on the non-compliance record information and the health reminder information, the range hood usage analysis report is obtained, thereby accurately generating the range hood usage analysis report so that the user can view the range hood usage in real time. This application performs non-compliance statistics on the range hood usage data and generates health reminder information based on the statistical results, thereby obtaining a user usage analysis report on the range hood, thereby giving personalized health advice to the user, helping the user understand his or her own lifestyle, and through reasonable reminders and suggestions, helping the user develop healthier eating and living habits and reduce the negative impact of late-night snacks on the body, thereby improving the reliability of the analysis of non-compliant usage and health reminders and improving the accuracy of the generated report. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic diagram of an application scenario of the method for generating a range hood analysis report in an embodiment of the present application;

[0041] Figure 2 This is a schematic diagram of the first flow chart of the method for generating a range hood analysis report in an embodiment of the present application;

[0042] Figure 3 This is a first flow chart of the step of obtaining non-compliance record information in an embodiment of the present application;

[0043] Figure 4 This is a second flow chart of the step of obtaining non-compliant record information in an embodiment of the present application;

[0044] Figure 5 This is a flowchart of the steps for obtaining health reminder information in the embodiment of this application;

[0045] Figure 6 Schematic diagram of a block diagram of a device for generating a smoke detector analysis report in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention 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, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0047] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0048] Additionally, the term "plurality" shall mean two or more.

[0049] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0050] The smoke detector analysis report generation method provided in this application can be applied to Figure 1 In the application environment shown. Among them, the processing device may include a processor 102 and a memory 104, the memory 104 is connected to the processor 102, and the memory 104 is used to store usage data, non-compliance record information, health prompt information and usage analysis reports, etc. The processor 102 is used to obtain the usage data transmitted by the range hood; based on the preset non-compliance conditions, the usage data is subjected to non-compliance statistical processing to obtain non-compliance record information; based on the preset compliance conditions, the non-compliance record information is processed to obtain health prompt information; based on the non-compliance record information and the health prompt information, a usage analysis report of the range hood is obtained. The processing device also includes a display 106, the display 106 is connected to the processor 102, and the display 106 is used to display the usage analysis report. The processing device also includes a first communication module, which is connected to the processor 102. The range hood includes a sensor control module and a second communication module. The sensor control module can be used to detect kitchen air data. For example, the sensor control module can be a PM2.5 sensor module, which in turn is used to detect PM2.5 concentration data in the kitchen air and obtain range hood usage data. The sensor control module is connected to the second communication module, and the first communication module is used to connect to the second communication module. When the first communication module of the processing device establishes a connection with the second communication module of the range hood, the processing device can obtain range hood usage data. For example, the processing device can be an electronic device independent of the range hood, such as a smartphone or smart tablet. In another example, the processing device can also be a module integrated into the range hood.

[0051] In one embodiment, Figure 2 As shown, a method for generating a smoke machine analysis report is provided, which is applied to Figure 1 The following steps are taken as an example to illustrate the processor in the example:

[0052] Step S210: Acquire usage data transmitted by the range hood.

[0053] The usage data may be obtained through detection by a sensor module in the range hood. For example, the usage data may include kitchen air data, and the usage data may also include detection time data of a specific day.

[0054] For example, the processor is pre-loaded with a corresponding application (APP), and the user can operate the corresponding application. Then, the processor generates a corresponding operation request according to the user's operation, and obtains the usage data of the range hood according to the operation request.

[0055] Step S220 : Based on the preset non-compliance conditions, non-compliance statistical processing is performed on the usage data to obtain non-compliance record information.

[0056] The preset non-compliance conditions can be preset by the system; for example, the preset non-compliance conditions may include whether the PM2.5 concentration in the kitchen exceeds a preset threshold, whether the range hood is used for more than a preset time period, etc. The non-compliance record information may include information such as the number of non-compliant uses, the non-compliant use time period, and the PM2.5 concentration.

[0057] For example, users can set a non-compliance statistics time period and a non-compliance PM2.5 concentration threshold to obtain pre-set non-compliance conditions. Based on the pre-set non-compliance conditions, the processor performs non-compliance statistics on the usage data and obtains non-compliance records for the corresponding range hoods.

[0058] Step S230: Based on preset compliance conditions, the non-compliant record information is processed to obtain health reminder information.

[0059] The preset compliance conditions may be obtained according to system presets; for example, the preset compliance conditions may include the frequency of PM2.5 concentration exceeding a preset threshold, the peak time period for PM2.5 concentration exceeding the preset threshold, etc. The health reminder information may include information such as healthy usage recommendations.

[0060] For example, users can set a frequency threshold for non-compliant usage to obtain a preset compliance condition. Based on the preset compliance condition, the processor statistically processes the non-compliant record information and obtains health reminder information for users using the corresponding range hood.

[0061] Step S240: Obtain a range hood usage analysis report based on the non-compliance record information and health reminder information.

[0062] The usage analysis report may be displayed via a display, for example, the usage analysis report may be displayed via a display screen of a mobile terminal (such as a smart phone).

[0063] For example, the processor can fill the non-compliance record information and health reminder information into the preset report template based on the preset report template, and then obtain the range hood usage analysis report.

[0064] In the above-mentioned embodiment, the usage data transmitted by the range hood is obtained; based on the preset non-compliance conditions, the usage data is subjected to non-compliance statistics processing to obtain non-compliance record information; based on the preset compliance conditions, the non-compliance record information is processed to obtain health reminder information; based on the non-compliance record information and the health reminder information, the range hood usage analysis report is obtained, thereby accurately generating the range hood usage analysis report so that the user can view the range hood usage in real time. The present application performs non-compliance statistics on the usage data of the range hood and generates health reminder information based on the statistical results, thereby obtaining a user usage analysis report on the range hood, thereby giving personalized health advice to the user, helping the user understand his or her own lifestyle, and through reasonable reminders and suggestions, helping the user develop healthier eating and living habits and reduce the negative impact of late-night snacks on the body, thereby improving the reliability of the analysis of non-compliant usage and health reminders and improving the accuracy of the generated report.

[0065] In one embodiment, the usage data includes the acquisition time and the particle size concentration value corresponding to the acquisition time; Figure 3 As shown, based on the preset non-compliance conditions, the steps of performing non-compliance statistical processing on the usage data to obtain non-compliance record information include:

[0066] Step S310: extracting the particle size concentration values ​​whose collection time falls within a preset time period.

[0067] Among them, the collection time refers to the time point when the sensor module collects the particle size concentration. For example, the sensor module can collect the particle size concentration based on a preset period. The particle size concentration value (i.e., PM2.5 concentration value) is collected by the sensor module set in the range hood. The preset time period refers to the preset non-compliant time period. For example, the preset time period can be set from 22:00 to 06:00 the next day. It should be noted that the system default preset time period is from 10 pm to 6 am the next day, and users can customize the time period on the mobile terminal.

[0068] The processor can filter the usage data and extract the particle size concentration values ​​whose collection time falls within the preset time period.

[0069] Step S320 : When the particle size concentration value exceeds the preset concentration threshold, it is determined that the range hood is used in an illegal manner during the corresponding collection time, and the particle size concentration value and the collection time are recorded as illegal information.

[0070] The processor can compare the extracted particle size concentration value with the preset concentration threshold. According to the comparison result, when the particle size concentration value exceeds the preset concentration threshold, it is determined that the use of the range hood at the corresponding collection time is non-compliant, and the corresponding particle size concentration value and collection time are used as non-compliant record information, so as to accurately extract non-compliant records of usage data in the preset time period, so as to generate health reminder information, and then obtain a usage analysis report of the user's use of the range hood, thereby improving the accuracy of the generated report.

[0071] In one embodiment, Figure 4 As shown, when the particle size concentration value exceeds a preset concentration threshold, determining that the use of the range hood at the corresponding collection time is non-compliant, and recording the particle size concentration value and the collection time as non-compliant record information includes the following steps:

[0072] Step S410 : When the particle size concentration values ​​of at least two consecutive acquisition times all exceed the preset concentration threshold, average processing is performed on the corresponding particle size concentration values ​​to obtain the average particle size concentration value corresponding to the at least two consecutive acquisition times.

[0073] For example, at least two consecutive acquisition times include a first acquisition time, a second acquisition time, and a third acquisition time. The sensing module acquires a first particle size concentration value during the first acquisition time, the sensing module acquires a second particle size concentration value during the second acquisition time, and the sensing module acquires a third particle size concentration value during the third acquisition time. The first particle size concentration value, the second particle size concentration value, and the third particle size concentration value are respectively compared with a preset concentration threshold. When the first particle size concentration value, the second particle size concentration value, and the third particle size concentration value all exceed the preset concentration threshold, the first particle size concentration value, the second particle size concentration value, and the third particle size concentration value are averaged to obtain an average particle size concentration value from the first acquisition time to the third acquisition time.

[0074] Step S420: Obtain a non-compliant time period based on at least two consecutive collection times.

[0075] For example, at least two consecutive collection times include a first collection time, a second collection time, and a third collection time. If the particle size concentration values ​​collected between the first collection time and the third collection time all exceed the preset concentration threshold, then the non-compliant time period is the time period between the first collection time and the third collection time.

[0076] Step S430: The particle size concentration value and the non-compliant time period are recorded as non-compliant information.

[0077] For example, by combining the particle size concentration value and the non-compliant time period, non-compliant record information can be obtained. For example, the non-compliant record information can be date: 2025-04-01; non-compliant time period: 22:00-22:15, PM2.5 average: 300μg / m 3 .

[0078] In the above embodiment, by aggregating non-compliant records by time period, continuous non-compliant data is merged into non-compliant data of one time period, thereby simplifying the data volume of non-compliant record information.

[0079] In one embodiment, Figure 5 As shown, based on the preset compliance conditions, the steps of processing non-compliant record information and obtaining health prompt information include:

[0080] Step S510: Perform non-compliance statistics on the non-compliant record information within a preset period to obtain the non-compliant usage frequency and high-incidence time period.

[0081] The frequency of non-compliant usage may be the number of non-compliant usages in the corresponding month; the high-incidence time period refers to the time period in which non-compliant usage accounts for the highest proportion on the same day. For example, the high-incidence time period for non-compliant behavior is 22:00-02:00, accounting for 60%.

[0082] For example, the preset period may be one month. By performing statistical processing on the number of non-compliance records in the corresponding month, the frequency of non-compliant usage can be obtained; by performing statistical processing on the high-incidence time periods in the non-compliant record information in the corresponding month, the high-incidence time periods can be obtained.

[0083] Step S520: query the preset mapping relationship table based on the frequency of non-compliant use and the high-incidence time period to obtain health reminder information.

[0084] The preset mapping relationship table can be established based on historical test data. For example, user behavior can be inferred based on high-incidence time periods: when the high-incidence time period is late at night (22:00-02:00), it may be late-night cooking; if there is frequent non-compliant use at night, it may be that the diet is unhealthy. If the frequency of non-compliant use is high (such as more than 3 times per week), it will prompt to adjust lifestyle habits; if the frequency of non-compliant use is low, it will encourage to maintain good habits.

[0085] For example, recommendations are dynamically generated based on behavioral patterns: If there are many late-night non-compliance incidents, the health reminder message will be: "Try to avoid late-night cooking for snacks, choose a light diet, and maintain a healthy sleep and rest schedule." If the non-compliance is concentrated in fried foods with high PM2.5 levels, the health reminder message will be: "Reduce cooking with high oil smoke and use healthy methods such as steaming." If regularity is poor, the health reminder message will be: "Set fixed meal times and develop healthy eating habits." Furthermore, based on the frequency of non-compliant usage, if the frequency is high, the health reminder message will also include: "Your late-night cooking may affect your health, please adjust as soon as possible." If the frequency is low, the health reminder message will also include: "Your usage is mostly compliant, keep it up."

[0086] In the above embodiment, by obtaining the frequency of non-compliant usage and the high-incidence time period, and by querying the preset mapping relationship table, health prompt information is obtained, and then an analysis report on the user's use of the range hood is obtained, personalized health advice is given to the user, helping the user to understand his or her own lifestyle, and through reasonable reminders and suggestions, helping the user to develop healthier eating and living habits and reduce the negative impact of late-night snacks on the body, thereby improving the reliability of the analysis of non-compliant usage and health prompts, and improving the accuracy of the generated report.

[0087] In one embodiment, the step of obtaining a range hood usage analysis report based on the non-compliance record information and the health reminder information includes:

[0088] Perform non-compliant statistical processing on the non-compliant record information of the current month to obtain the number of non-compliant uses in the current month; obtain the number of non-compliant uses in the previous month, and compare the number of non-compliant uses in the current month with the number of non-compliant uses in the previous month to obtain non-compliant change trend information.

[0089] For example, the content of the usage analysis report may include this month's overview, time distribution, last month's non-compliance, and calculation change trends. For example, this month's overview can be: total usage days (such as 30 days); total number of non-compliant uses (such as 15 times); number of non-compliant usage days (dates with at least one non-compliance, such as 10 days). The time periods can be: high-incidence time periods for non-compliant behaviors (such as "22:00-02:00 accounts for 60%"). Last month's non-compliance can be: query the number of non-compliances last month (such as 20 times last month). The calculation change trend can be: better, the number of non-compliances this month has decreased (such as 15 < 20); worse, the number of non-compliances this month has increased; no change, the number is the same. Exemplary, the content of the usage analysis report is: "The number of non-compliances this month is 15 times, a decrease of 25% compared to 20 times last month. The situation has improved and will continue to be maintained."

[0090] It should be noted that usage analysis reports are generated at 23:59 on the last day of each month or at midnight on the first day of the following month. Usage analysis reports can be saved in JSON format and stored in a database or cloud storage for easy querying.

[0091] In one embodiment, the step of obtaining a range hood usage analysis report based on the non-compliance record information and the health reminder information includes:

[0092] Obtain usage analysis reports based on non-compliance record information, health reminder information, and non-compliance change trend information.

[0093] An example of an output report using the analysis report is: Number of non-compliant operations in April: 5 times, compared with last month: worse (3 times last month); the health reminder information is: You have used the range hood more frequently at night this month, which may be caused by late-night snacks. It is recommended to reduce nighttime cooking, maintain a healthy diet, and avoid staying up late.

[0094] Among them, by merging non-compliant record information, health reminder information and non-compliant change trend information, a usage analysis report is obtained, which enables personalized health advice to users, helps users understand their own lifestyles, improves the reliability of non-compliant usage and health reminder analysis, and improves the accuracy of report generation.

[0095] In one embodiment, based on a preset non-compliance condition, performing non-compliance statistical processing on the usage data to obtain non-compliance record information includes:

[0096] The usage data is cleaned and processed to obtain target usage data.

[0097] For example, usage data is filtered to remove invalid data (e.g., missing or abnormal particle size concentration values). Another example is deduplication of usage data by device ID and timestamp to prevent duplicate records, thereby improving the reliability of analysis of non-compliant usage and health alerts, and enhancing the accuracy of generated reports.

[0098] In one embodiment, based on a preset non-compliance condition, the steps of performing non-compliance statistical processing on the usage data to obtain non-compliance record information include:

[0099] Based on the preset non-compliance conditions, the target usage data is subjected to non-compliance statistical processing to obtain non-compliance record information.

[0100] For example, target usage data may include particle size concentration values, corresponding timestamps (accurate to the minute), and the range hood's on / off status. Data is stored in a database (such as MySQL or MongoDB). Non-compliance records include the device ID (to distinguish users), timestamp, particle size concentration value, and on / off status. It should be noted that non-compliance records are stored by date partition, facilitating daily and monthly queries.

[0101] In one embodiment, the usage analysis report includes a daily usage analysis report, a monthly usage analysis report, and a yearly usage analysis report.

[0102] For example, based on the method of the above embodiment, the usage data of a specific day is processed to obtain a daily usage analysis report; similarly, based on the method of the above embodiment, the usage data of the corresponding month is processed to obtain a monthly usage analysis report; based on the method of the above embodiment, the usage data of the corresponding year is processed to obtain an annual usage analysis report.

[0103] The processor can view the corresponding usage analysis report through switching requests, thereby improving the diversity of usage analysis report generation and making it easier for users to view range hood usage analysis at different times.

[0104] In one example, when a usage analysis report is generated, a notification is pushed through the app: "Your range hood usage report for April 2025 has been generated. Come and check it out." It should be noted that if no range hood usage data is available, an empty report is generated with the message "No usage record this month. Maintain good habits." If usage data is incomplete, the missing dates are marked and a partial report is generated.

[0105] It should be understood that although Figures 2 to 5 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figures 2 to 5 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0106] In one embodiment, Figure 6 As shown, the present application provides a device for generating a range hood analysis report, comprising:

[0107] The data acquisition unit 610 is used to acquire usage data transmitted by the range hood.

[0108] The non-compliance statistics unit 620 is used to perform non-compliance statistics processing on the usage data based on preset non-compliance conditions to obtain non-compliance record information.

[0109] The prompt information acquisition unit 630 is used to process the non-compliant record information based on preset compliance conditions to obtain health prompt information.

[0110] The report generating unit 640 is used to obtain a usage analysis report of the range hood based on the non-compliance record information and the health reminder information.

[0111] The specific limitations of the smoke machine analysis report generation device can be found in the limitations of the smoke machine analysis report generation method described above and will not be further elaborated here. Each module in the aforementioned smoke machine analysis report generation device can be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of the processor in the smoke machine analysis report generation system in hardware form, or stored in the memory of the smoke machine analysis report generation system in software form, allowing the processor to call and execute the corresponding operations of each module.

[0112] In one embodiment, an electronic device is also provided, comprising a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, a method for generating a smoke machine analysis report as described above is realized.

[0113] The electronic device may be a mobile terminal, such as a smart phone, a smart tablet or a smart computer. The electronic device may also be integrated into the range hood.

[0114] The electronic device is connected to the range hood, and the processor obtains the usage data transmitted by the range hood; based on the preset non-compliance conditions, the usage data is subjected to non-compliance statistics processing to obtain non-compliance record information; based on the preset compliance conditions, the non-compliance record information is processed to obtain health reminder information; based on the non-compliance record information and the health reminder information, a range hood usage analysis report is obtained, thereby accurately generating a range hood usage analysis report so that the user can view the range hood usage in real time. This application performs non-compliance statistics on the range hood usage data, and generates health reminder information based on the statistical results, thereby obtaining a user usage analysis report on the range hood, thereby giving personalized health advice to the user, helping the user understand his or her own lifestyle, and through reasonable reminders and suggestions, helping the user develop healthier eating and living habits, and reducing the negative impact of late-night snacks on the body, thereby improving the reliability of the analysis of non-compliant usage and health reminders, and improving the accuracy of the generated report.

[0115] In one embodiment, a storage medium is also provided. The storage medium is a computer-readable storage medium used for computer-readable storage. The storage medium stores one or more programs. The one or more programs can be executed by one or more processors to implement any of the above-mentioned methods for generating a smoke machine analysis report.

[0116] For example, when the computer program is executed by a processor, the following steps of the method for generating a smoke machine analysis report are implemented:

[0117] Obtain usage data transmitted by the range hood; perform non-compliance statistical processing on the usage data based on preset non-compliance conditions to obtain non-compliance record information; process the non-compliance record information based on preset compliance conditions to obtain health prompt information; obtain a usage analysis report of the range hood based on the non-compliance record information and the health prompt information.

[0118] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned division operation methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0119] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for generating a range hood analysis report, characterized in that: The following steps are involved: Obtain usage data transmitted by the range hood; Based on the preset non-compliance conditions, performing non-compliance statistical processing on the usage data to obtain non-compliance record information; Based on the preset compliance conditions, non-compliant record information is processed to obtain health reminder information; A usage analysis report of the range hood is obtained based on the non-compliance record information and the health reminder information.

2. The method for generating a range hood analysis report according to claim 1, characterized in that: The usage data includes the collection time and the particle size concentration value corresponding to the collection time; The step of performing non-compliance statistical processing on the usage data based on the preset non-compliance condition to obtain non-compliance record information includes: Extracting the particle size concentration value when the acquisition time falls within a preset time period; When the particle size concentration value exceeds a preset concentration threshold, it is determined that the range hood is used non-compliantly during the corresponding collection time, and the particle size concentration value and the collection time are used as the non-compliant record information.

3. The method for generating a range hood analysis report according to claim 2, characterized in that: The step of determining that the use of the range hood at the corresponding collection time is non-compliant when the particle size concentration value exceeds a preset concentration threshold, and using the particle size concentration value and the collection time as the non-compliant record information includes: When the particle size concentration values ​​at at least two consecutive acquisition times all exceed a preset concentration threshold, averaging the corresponding particle size concentration values ​​to obtain an average particle size concentration value corresponding to the at least two consecutive acquisition times; Obtaining a non-compliant time period according to the at least two consecutive collection times; The particle size concentration value and the non-compliance time period are used as the non-compliance record information.

4. The method for generating a range hood analysis report according to claim 1, wherein: The step of processing the non-compliant record information based on the preset compliance conditions to obtain health prompt information includes: Perform non-compliant statistical processing on non-compliant record information within a preset period to obtain the frequency of non-compliant use and the time period of high incidence; According to the frequency of non-compliant use and the high-incidence time period, a preset mapping relationship table is queried to obtain the health reminder information.

5. The method for generating a range hood analysis report according to claim 1, characterized in that: The step of obtaining a range hood usage analysis report based on the non-compliance record information and the health reminder information includes: Perform non-compliant statistical processing on the non-compliant record information of the current month to obtain the number of non-compliant uses in that month; Obtain the number of non-compliant uses in the previous month, and compare the number of non-compliant uses in the current month with the number of non-compliant uses in the previous month to obtain non-compliant change trend information; The step of obtaining a range hood usage analysis report based on the non-compliance record information and the health reminder information includes: The usage analysis report is obtained based on the non-compliance record information, the health reminder information and the non-compliance change trend information.

6. The method for generating a range hood analysis report according to any one of claims 1 to 5, characterized in that: The step of performing non-compliance statistical processing on the usage data based on the preset non-compliance conditions to obtain non-compliance record information includes: Cleaning the usage data to obtain target usage data; The step of performing non-compliance statistical processing on the usage data based on the preset non-compliance condition to obtain non-compliance record information includes: Based on the preset non-compliance conditions, non-compliance statistical processing is performed on the target usage data to obtain the non-compliance record information.

7. The method for generating a range hood analysis report according to claim 6, characterized in that: The usage analysis report includes a daily usage analysis report, a monthly usage analysis report and an annual usage analysis report.

8. A device for generating a smoke machine analysis report, characterized in that: include: a data acquisition unit, configured to acquire usage data transmitted by the range hood; a non-compliance statistics unit, configured to perform non-compliance statistics processing on the usage data based on preset non-compliance conditions to obtain non-compliance record information; A prompt information acquisition unit, configured to process non-compliant record information based on preset compliance conditions to obtain health prompt information; A report generating unit is used to obtain a usage analysis report of the range hood based on the non-compliance record information and the health reminder information.

9. An electronic device, characterized in that: It includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, a method for generating a smoke machine analysis report as described in any one of claims 1 to 7 is realized.

10. A storage medium, which is a computer-readable storage medium and is used for computer-readable storage, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method for generating a range hood analysis report according to any one of claims 1 to 7.

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