Internet of Things home data management method and system based on big data analysis

Abstract

The invention relates to the technical field of home equipment detection, and discloses an Internet of Things home data management method and system based on big data analysis. According to the method, the total power consumption of all smart homes in two months adjacent to the same quarter is obtained, the total power consumption difference is calculated, and the total power consumption difference is compared with a preset total power consumption difference threshold. If the total power consumption difference is smaller than or equal to the threshold, the power consumption difference is reasonable, and the system does not need intervention; and if the total power consumption difference is larger than the threshold value, it is judged that power consumption is abnormal, and the air conditioner with the maximum power consumption proportion is detected preferentially. Through the dynamic monitoring and priority response mechanism, the energy consumption management of the smart home equipment is optimized, the resource waste is avoided, the system cooperation efficiency is improved, and the core demand of smart home big data management is met.

Description

Technical Field

[0001] This invention relates to the field of home appliance testing technology, specifically to an IoT home data management method and system based on big data analysis. Background Technology

[0002] Smart home management is a modern management approach that leverages advanced technology and network interconnection to achieve a high degree of integration between various devices and systems within the home. It aims to improve the comfort and efficiency of the living environment through automated control and intelligent optimization. This system broadly covers multiple functional modules, including intelligent lighting control, precise temperature and humidity regulation, comprehensive security monitoring, remote control of home appliances, and energy consumption management, forming a collaborative intelligent ecosystem. Users can flexibly control the brightness of lights, indoor temperature, security cameras, and door lock status in their homes remotely and in real time through various interactive methods such as smartphone applications, intelligent voice assistants, or computer terminals. Simultaneously, the system can utilize various environmental sensors to achieve real-time data collection and dynamic response, thereby automatically adjusting the operating status of devices, greatly improving the convenience and intelligence of daily life. In terms of home security, the smart home system provides 24 / 7 uninterrupted real-time video monitoring, abnormal behavior detection, and instant alarm push functions, significantly enhancing the home's security capabilities.

[0003] However, it's important to note that smart home systems rely heavily on electricity, and their core components are mostly electronic devices. Prolonged continuous operation without regular maintenance and updates can lead to performance degradation, slower response times, and even malfunctions. These issues not only affect the user experience and reduce overall system efficiency but can also increase energy consumption due to reduced energy efficiency, thereby driving up household electricity costs. Furthermore, unnecessary energy waste exacerbates the environmental burden. Therefore, scientific and rational use and regular maintenance are crucial for maintaining the efficient, energy-saving, and stable operation of smart home systems. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention aims to provide an IoT home data management method and system based on big data analysis. This method can, when an unreasonable discrepancy is found in the total power consumption of all smart home devices, obtain the detection priority of each smart home device based on its power consumption percentage. Then, based on the detection priority of several operating smart homes, energy consumption data is detected one by one, yielding corresponding energy consumption detection results and maintenance reminders. This facilitates reminding users to maintain smart homes with abnormal energy consumption based on the energy consumption detection results, thereby maintaining the efficient, energy-saving, and stable operation of the smart home system. Furthermore, since energy consumption data is detected one by one for each operating smart home device, high-cost hardware with parallel data processing capabilities is not required, thus reducing the computing resources and hardware requirements for energy consumption data detection and enabling low-cost energy consumption detection and reminders.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an IoT home data management method based on big data analysis, comprising: Step 1, acquiring the total power consumption of all smart home devices in two consecutive months of the previous quarter through sensors built into the smart home devices, denoted as Total Power Consumption 1 and Total Power Consumption 2 respectively; subtracting Total Power Consumption 2 from Total Power Consumption 1 and processing the absolute value to obtain the difference in total power consumption between the two consecutive months; Step 2, setting a threshold for the total power consumption difference based on historical records, which represents the maximum reasonable difference in the total power consumption of all smart home devices in two consecutive months; if this maximum value is exceeded, it indicates that one or more smart home devices have abnormal power consumption; Step 3, ... The total power consumption difference is compared with a threshold value. Different responses are made based on the comparison results. If the total power consumption difference is less than or equal to the threshold value, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is reasonable. If the total power consumption difference is greater than the threshold value, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is unreasonable. Then, based on the power consumption ratio, the detection priority of all smart homes is obtained from largest to smallest. Step four: According to the detection priority of several smart homes in operation, the energy consumption data of several smart homes is detected one by one to obtain the energy consumption detection results and maintenance reminders of several smart homes.

[0006] In some implementations, step four specifically includes: obtaining the detection priority and detection status of several smart home devices in operation; selecting the target smart home device with the highest detection priority from among the several smart home devices with an undetected detection status; performing energy consumption data detection on the target smart home device according to the detection duration corresponding to the target smart home device, obtaining the energy consumption detection result and maintenance reminder of the target smart home device, and updating the detection status of the target smart home device to detected, and continuing to select the target smart home device with the highest detection priority from among the several smart home devices with an undetected detection status, until the energy consumption detection result and maintenance reminder of several smart home devices in operation are obtained.

[0007] In some implementations, if the target smart home is an air conditioner, the steps of detecting energy consumption data of the target smart home to obtain the energy consumption detection results and maintenance reminders include: 1. Obtaining the pressure of air before passing through the filter and the pressure of air after passing through the filter, and obtaining the pressure difference by subtracting the pressure after passing through the filter from the pressure before passing through the filter; 2. Setting a pressure difference threshold for the air after passing through the filter. When the pressure difference of the air after passing through the filter does not exceed the set pressure difference threshold, it indicates that there is little dust accumulated on the filter and the airflow is less affected; 3. Comparing the pressure difference of the air before and after passing through the filter with... By comparing the pressure difference threshold, if the pressure difference of air passing through the filter is less than or equal to the pressure difference threshold, it means that there is less dust accumulated on the filter, the filter has less resistance to airflow, and the air conditioner's filtration, purification, cooling, or heating functions are less affected. In this case, the test result for the air conditioner filter is normal, and the status quo should be maintained. If the pressure difference of air passing through the filter is greater than the pressure difference threshold, it means that there is more dust accumulated on the filter, the filter has greater resistance to airflow, and the air conditioner's filtration, purification, cooling, or heating functions are significantly affected. In this case, the test result for the air conditioner filter is abnormal, and the user is reminded to clean the filter.

[0008] In some implementations, the initial room temperature is recorded, a preset comfortable temperature that the room needs to reach and maintain is defined, and after the air conditioner is turned on, the time it takes for the air conditioner to reach the comfortable temperature is recorded as the initial time. After reaching the comfortable temperature, a preset later time is defined to maintain the comfortable temperature for a period of time. The later time and the initial time together constitute the total time. After the air conditioner has been on for the total time, it is turned off, and the total power consumption during this period is recorded as the actual total power consumption. In addition, the theoretical total power consumption of the air conditioner in a room of the same size, adjusted from the same initial temperature to the comfortable temperature and running for the same total time, is obtained. The power consumption difference is obtained by subtracting the theoretical total power consumption from the actual total power consumption, and the power consumption gap is obtained by dividing the power consumption difference by the theoretical total power consumption. At the same time, a power consumption gap threshold is set, which represents the upper limit of the power consumption gap that the user can accept. When the pressure difference of the air passing through the filter is greater than the pressure difference threshold, the power consumption gap is compared with the power consumption gap threshold, and different responses are given based on the comparison results.

[0009] In some implementations, if the power consumption difference is less than or equal to a power consumption difference threshold, it means that the power consumption difference is within an acceptable range, and in this case, the user is not reminded to clean the filter; if the power consumption difference is greater than the power consumption difference threshold, it means that the power consumption difference exceeds an acceptable range, and in this case, the user is reminded to clean the filter.

[0010] In some implementations, when the power consumption difference is greater than a power consumption difference threshold, a second threshold greater than the power consumption difference threshold is set, the power consumption difference is compared with the second threshold, and different responses are given based on the comparison results.

[0011] In some implementations, if the power consumption difference is less than the second threshold, it indicates that the power consumption difference is only slightly exceeding the user's acceptable limit, and in this case, the judgment is made again; if the power consumption difference is greater than or equal to the second threshold, it indicates that the power consumption difference is significantly exceeding the user's acceptable limit, and in this case, the reminder to the user is maintained.

[0012] In some implementations, the re-judgment process involves pre-setting an air conditioner usage cycle, obtaining the air conditioner's usage time within the previous usage cycle, dividing the usage time by the usage cycle to obtain the usage time percentage, setting a usage time percentage threshold, comparing the usage time percentage with the usage time percentage threshold, and determining different responses based on the comparison results.

[0013] In some implementations, if the percentage of usage time is less than a threshold, it indicates that the user uses the device infrequently, and in this case, the user is not notified; if the percentage of usage time is greater than or equal to the threshold, it indicates that the user uses the device frequently, and in this case, the user is notified.

[0014] This invention also provides the following technical solutions:

[0015] This invention further provides an IoT home data management system based on big data analysis, used to execute the above-described method, comprising: an acquisition module, which acquires the total power consumption of all smart home devices in two consecutive months of the previous quarter through sensors built into the smart home devices, denoted as Total Power Consumption 1 and Total Power Consumption 2 respectively; subtracting Total Power Consumption 2 from Total Power Consumption 1 and processing the absolute value to obtain the difference in total power consumption between the two consecutive months; a setting module, which sets a threshold for the total power consumption difference based on historical records, representing the maximum reasonable difference in the total power consumption of all smart home devices in two consecutive months; if this maximum value is exceeded, it indicates that one or more smart home devices have abnormal power consumption; and a comparison module. The module compares the total power consumption difference with a threshold value and takes different actions based on the comparison result. If the total power consumption difference is less than or equal to the threshold value, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is reasonable. If the total power consumption difference is greater than the threshold value, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is unreasonable. Then, based on the power consumption ratio, the detection priority of all smart homes is obtained from largest to smallest. The detection module performs energy consumption data detection on each of the smart homes in operation according to the detection priority of the smart homes in operation, and obtains the energy consumption detection results and dimensions of the smart homes.

[0016] The technical solution provided by this invention has the following advantages compared with the prior art:

[0017] Firstly, in this invention, the real-time pressure difference of air passing through the filter is compared with a set threshold to determine the corresponding treatment measures. If the pressure difference is less than or equal to the threshold, it indicates that there is little dust accumulation on the filter, air circulation is not significantly affected, and the air conditioner can still operate normally. If the pressure difference is greater than the threshold, it indicates that there is too much dust accumulation on the filter, and the air conditioner efficiency is reduced. In this case, the user needs to be reminded to clean the filter to restore the normal function and energy efficiency of the air conditioner.

[0018] Secondly, in this invention, a reasonable energy consumption difference threshold is set, so that users do not need to clean the filter frequently during the use of the air conditioner. The filter is only reminded to clean when the power consumption exceeds the acceptable range, thereby improving the convenience and intelligence of air conditioner maintenance.

[0019] Thirdly, this invention refines the judgment of power consumption differences by setting a second threshold, thus avoiding excessive interference with users. If the power consumption difference only slightly exceeds the threshold, the system will determine whether to remind the user to clean the filter based on usage frequency. This approach not only avoids frequent reminders but also more accurately reflects the user's usage habits and needs. Secondly, considering the frequency of air conditioner use, the user experience is further optimized. If the air conditioner is used infrequently, the reminder system will reduce intervention in cleaning the filter because, in this case, the decline in air conditioner performance has a smaller impact on the user; however, for air conditioners used frequently, the performance of the device and the cleanliness of the filter are particularly important, so the system will remind the user to perform maintenance. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the method steps of the present invention;

[0021] Figure 2 This is a schematic diagram of the steps in the air conditioner detection method of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It is understood that the term "a" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element can be one, while in another embodiment, the number of the element can be multiple, and the term "a" should not be understood as a limitation on the number.

[0024] The present invention provides an IoT home data management method based on big data analytics, such as... Figure 1 and Figure 2 As shown, it includes:

[0025] The first step involves using built-in sensors in the smart home system to acquire the total power consumption of all smart home devices in adjacent two months of the previous quarter, denoted as Total Power Consumption 1 and Total Power Consumption 2. The difference between Total Power Consumption 1 and Total Power Consumption 2, after absolute value processing, is obtained. A threshold for this difference is set based on historical records, representing the maximum reasonable difference in total power consumption between adjacent two months. If this maximum value is exceeded, it indicates an anomaly in power consumption of one or more smart home devices. The total power consumption difference is compared to the threshold, and different actions are taken based on the comparison results. If the total power consumption difference is less than or equal to the threshold, the difference in total power consumption between adjacent two months of the same quarter is considered reasonable. If the total power consumption difference is greater than the threshold, the difference in total power consumption between adjacent two months of the same quarter is considered unreasonable. Then, based on the power consumption percentage, all smart home devices are prioritized for detection, from highest to lowest. Based on the detection priority of several smart home devices currently in operation, energy consumption data is collected for each of these smart home devices. The detection process, which obtains energy consumption detection results and maintenance reminders for several smart home devices, specifically includes: acquiring the detection priority and detection status of several smart home devices in operation; selecting the target smart home device with the highest detection priority from those not detected; performing energy consumption data detection on the target smart home device based on its corresponding detection duration, obtaining the energy consumption detection results and maintenance reminders, and updating the detection status of the target smart home device to "detected"; continuing to select the target smart home device with the highest detection priority from those not detected, until the energy consumption detection results and maintenance reminders for several smart home devices in operation are obtained. If the target smart home device is an air conditioner, the step of performing energy consumption data detection on the target smart home device to obtain the energy consumption detection results and maintenance reminders involves obtaining the air pressure before and after passing through the filter using sensors built into the air conditioner, and using the pressure difference between the pressure before and after passing through the filter to obtain the pressure difference. The larger the pressure difference, the more dust is on the filter. This is because the filter plays a role in blocking and filtering air during air circulation. When the filter is relatively clean, air can pass through smoothly with minimal resistance, resulting in a small pressure difference. However, over time, dust, particles, and contaminants accumulate on the filter, reducing its pore size and obstructing airflow. This causes air to accumulate in front of the filter, increasing pressure, while the air behind the filter experiences relatively lower pressure due to restricted flow. Consequently, the pressure difference increases, indicating that greater force is required for the air to pass through the filter. It's worth noting that for ease of reference, the pressure difference should be a positive value. Therefore, it is calculated by subtracting the pressure of the air after passing through the filter from the pressure of the air before passing through it.This is because when air flows through a filter, the filter creates resistance to the airflow. This resistance results in a relatively higher air pressure before the filter, and as the air passes through the filter, the airflow speed decreases due to the resistance, and the pressure also decreases accordingly. Therefore, the air pressure before passing through the filter is greater than the air pressure after passing through the filter.

[0026] The second step is to set the pressure difference threshold for the air passing through the filter. The filter's function is to filter dust, pollen, and other particulate matter from the air. When the filter is clean, air can pass through relatively smoothly with a small pressure difference. Over time, impurities accumulate on the filter, gradually clogging its pores and increasing airflow resistance, thus causing the pressure difference of the air passing through the filter to gradually increase. To ensure the air conditioner operates normally and efficiently, a reasonable pressure difference threshold is set. Once the pressure difference exceeds this threshold, it indicates that a significant amount of dust has accumulated on the filter, noticeably hindering airflow. This affects the air conditioner's filtration, purification, and cooling / heating efficiency, requiring cleaning. When the pressure difference does not exceed the set threshold, it indicates that relatively little dust has accumulated on the filter, airflow is not significantly affected, the air conditioner can still maintain efficient operation, and the filtration effect remains within the normal range.

[0027] The third step, after setting the pressure difference threshold, compares the pressure difference of the air before and after passing through the filter obtained in the first step with the pressure difference threshold, and determines the appropriate action based on the comparison result. If the pressure difference of the air passing through the filter is less than or equal to the pressure difference threshold, it means that there is less dust accumulated on the filter, the filter's resistance to airflow is relatively small, and the air conditioner's filtration, purification, cooling, or heating functions are not significantly affected. In this case, the test result for the air conditioner filter is normal, and the status quo can be maintained. If the pressure difference of the air passing through the filter is greater than the pressure difference threshold, it means that there is more dust accumulated on the filter, the filter's resistance to airflow is relatively large, and the air conditioner's filtration, purification, cooling, or heating functions are significantly affected. In this case, the test result for the air conditioner filter is abnormal, and the user needs to be reminded to clean the filter.

[0028] In summary, the air conditioner testing method involves three main steps. First, the air pressure across the filter is measured using the air conditioner's built-in sensors, and the pressure difference is calculated. A larger pressure difference indicates more dust on the filter, as dust, particulate matter, and other contaminants accumulate on the filter over time, obstructing airflow and increasing the pressure difference. Second, a pressure difference threshold is set as the standard for air conditioner operation. When the filter is clean, the pressure difference is small, and airflow is smooth; however, as dust accumulates, airflow resistance increases, and the pressure difference widens. Setting a reasonable pressure difference threshold helps determine whether the filter needs cleaning. When the air pressure difference through the filter exceeds the threshold, it indicates severe dust accumulation on the filter, affecting the air conditioner's cooling, heating, and filtration effects, and cleaning is required. Finally, the real-time air pressure difference through the filter is compared with the set threshold to determine appropriate action. If the pressure difference is less than or equal to the threshold, it means that there is little dust accumulation on the filter, air circulation is not significantly affected, and the air conditioner can still operate normally. If the pressure difference is greater than the threshold, it means that there is too much dust accumulation on the filter, and the air conditioner efficiency is reduced. At this time, users need to be reminded to clean the filter to restore the normal function and energy efficiency of the air conditioner.

[0029] In addition, under the above conditions, the initial room temperature is recorded, and a preset comfortable temperature that the room needs to reach and maintain is defined. Based on this, after the air conditioner is turned on, the time it takes for the air conditioner to reach the comfortable temperature is recorded as the initial time. After reaching the comfortable temperature, a preset later time is set to maintain the comfortable temperature for a period of time. The later time and the initial time constitute the total time. After the air conditioner has been on for the total time, it is turned off, and the total electricity consumed by the air conditioner during this period is recorded as the actual total electricity consumption. Furthermore, based on the air conditioner's parameters and the manufacturer's instructions, the theoretical total electricity consumption of the air conditioner in a room of the same size, adjusted from the same initial temperature to the comfortable temperature and running for the same total time, is obtained. The electricity consumption difference is obtained by subtracting the theoretical total electricity consumption from the actual total electricity consumption, and the electricity consumption gap is obtained by dividing the electricity consumption difference by the theoretical total electricity consumption. Simultaneously, a power consumption gap threshold is set based on user acceptance. This power consumption gap threshold represents the upper limit of the power consumption gap that users can accept. Based on the above conditions, the power consumption gap is compared with the power consumption gap threshold, and different responses are derived based on the comparison results. If the difference in power consumption is less than or equal to the threshold, it means the difference is within an acceptable range. In this case, even if the pressure difference of the air before and after passing through the filter exceeds the pressure difference threshold, there is no need to remind the user to clean the filter. This is because when the power consumption difference is within an acceptable range, considering power consumption and electricity costs, this difference is acceptable to the user. Reminding the user under these acceptable conditions seems like overkill. If the difference in power consumption exceeds the threshold, it means the difference exceeds the acceptable range. In this case, if the pressure difference of the air before and after passing through the filter exceeds the pressure difference threshold, the user should be reminded to clean the filter. The reason for this is that when the pressure difference of the air before and after passing through the filter exceeds the threshold, it indicates that there is a lot of dust accumulated on the filter, which increases the resistance to airflow, affecting the filter's filtration and purification effect and the air conditioner's cooling or heating effect, thus requiring filter cleaning. However, in actual use, the filter is often easily overlooked. There are two main reasons for this. First, the filtration and purification effect of the filter is not immediately apparent to the user. The concentration of dust in the air is usually low, especially in relatively clean environments, making changes in dust levels difficult for users to perceive. Therefore, although dust gradually accumulates on the filter and affects airflow, the increase or decrease in dust has little immediate impact on perceived air quality, making this change imperceptible to users. Secondly, the filter's effect on the air conditioner's cooling or heating performance is also gradual, and users are unlikely to notice it significantly in the short term. For example, in summer, it might ideally take 20 minutes for an air conditioner to drop from 30 degrees Celsius to 20 degrees Celsius, but if the filter is dusty and the air conditioner's efficiency decreases, it might take 30 minutes. Although the cooling effect is reduced, users can still use the air conditioner without immediately experiencing noticeable discomfort.Unless the air conditioner fails to reach the preset temperature after a prolonged period (e.g., 2 hours) or only cools to 26 degrees Celsius, users are unlikely to notice a decline in its performance. Only then will users consider checking and cleaning the filter or contacting repair services. Therefore, air conditioner filter cleaning is often neglected until the problem becomes apparent. Thus, further assessment is needed to determine if the filter requires cleaning. Since users have little perception of the filtration and purification effect on room air quality, the air conditioner's cooling or heating efficiency can be used as a way to indirectly reflect the filter's cleanliness. The cooling or heating efficiency can be viewed by checking the air conditioner's actual energy consumption, especially under prolonged use, to indirectly determine its efficiency. This method, based on the difference between cooling or heating efficiency and energy consumption, indirectly assesses the filter's condition, avoiding reliance on visual perception. This is particularly effective for users who may not easily notice the impact of filter dust accumulation. By monitoring differences in power consumption, it can accurately reflect changes in air conditioner efficiency, preventing performance degradation caused by clogged filters and better controlling energy consumption to improve energy efficiency. Setting reasonable energy consumption thresholds eliminates the need for frequent filter cleaning during use; cleaning is only prompted when power consumption exceeds acceptable limits, thus improving the convenience and intelligence of air conditioner maintenance. Furthermore, early detection of performance degradation and timely intervention help extend the air conditioner's lifespan, preventing damage or increased maintenance costs due to severe dust accumulation and ensuring the air conditioner always operates at its optimal condition.

[0030] When a power consumption difference is detected to be greater than a threshold, a second threshold is set, which is greater than the first threshold and close to it (e.g., if the first threshold is 30% and the second threshold is 40%). The power consumption difference is compared to the second threshold, and different actions are taken based on the comparison result. If the power consumption difference is less than the second threshold, it means the power consumption difference is only slightly exceeding the user's acceptable limit, and a second judgment is made. If the power consumption difference is greater than or equal to the second threshold, it means the power consumption difference is significantly exceeding the user's acceptable limit, and the user is still alerted. The second judgment process involves pre-setting an air conditioner usage cycle, obtaining the air conditioner's usage time in the previous usage cycle, and dividing the usage time by the usage cycle to obtain the usage time percentage. Simultaneously, a usage time percentage threshold is set, representing the boundary between high and low user usage frequency within a usage cycle. Under this condition, the usage time percentage is compared to the usage time percentage threshold, and different actions are taken based on the comparison result. If the usage time percentage is less than the usage time percentage threshold, it means the user's usage frequency is low, and no user is alerted. If the usage time percentage is greater than or equal to the usage time percentage threshold, it means the user's usage frequency is high, and the user is alerted. In summary, the difference in power consumption previously indicated the efficiency of the air conditioner's heating or cooling capabilities. This efficiency was determined by comparing actual usage with theoretical conditions, and the power consumption difference also determined user acceptance. This is because the power consumption difference reflects the extra energy consumed compared to the ideal state. As long as the difference from the ideal state is not significant, it is acceptable to users. If the user finds this acceptable, then for an air conditioner, even if the pressure difference before and after the air passes through the filter exceeds a certain threshold, indicating a high level of dust on the filter, there is no need to remind the user to clean it. This detection and reminder method is based on user acceptance. However, besides user acceptance, the frequency of use should also be considered. Whether the filter is dusty or not, or whether the air conditioner's heating or cooling efficiency is high or low, usage frequency determines its importance to the user. If the air conditioner is used very infrequently, such as less than 5 days a month, then the air conditioner is not important to the user, and in this case, the efficiency of the air conditioner and the cleanliness of its filter are negligible. If an air conditioner is used very frequently by a user, such as being turned on for 20 days a month, then the air conditioner is very important to the user. In this case, the efficiency of the air conditioner itself and the cleanliness of its filter are things that the user needs to pay attention to.The main advantage of this method lies in its comprehensive consideration of the energy consumption differences of air conditioning equipment, user acceptance, and the frequency of air conditioner use, thus providing users with a more personalized and intelligent reminder mechanism. Firstly, by setting a second threshold to further refine the judgment of energy consumption differences, excessive interference with users can be avoided. If the energy consumption difference only slightly exceeds the threshold, the system will judge based on the usage frequency to decide whether to remind the user to clean the filter. This method not only avoids frequent reminders but also more accurately reflects the user's usage habits and needs. Secondly, considering the frequency of air conditioner use further optimizes the user experience. If the air conditioner is used infrequently, the reminder system will reduce intervention in cleaning the filter because, in this case, the decline in air conditioner performance has a smaller impact on the user; however, for air conditioners used frequently, the performance of the equipment and the cleanliness of the filter are particularly important, so the system will remind the user to perform maintenance.

[0031] The processes described above with reference to the flowcharts in the embodiments disclosed in this invention can be implemented as computer software programs. Embodiments of this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit, it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection having one or more wire segments, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless segments, wire segments, optical cables, RF, etc., or any suitable combination thereof.

[0032] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0033] Those skilled in the art should understand that the above description is only a specific embodiment of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application.

Claims

1. A method for managing IoT-based home data based on big data analytics, characterized in that: include: Step 1: Use the built-in sensors in the smart home to obtain the total power consumption of all smart home devices in two consecutive months of the previous quarter, and record them as total power consumption one and total power consumption two respectively. Subtract total power consumption two from total power consumption one and process the absolute value to obtain the difference in total power consumption between the two consecutive months. Step 2: Set a total power consumption difference threshold based on historical records. This threshold represents the maximum reasonable difference between the total power consumption of all smart home devices in two consecutive months. If this maximum value is exceeded, it indicates that there is one or more abnormal power consumption in the smart home devices. Step 3: Compare the total power consumption difference with the total power consumption difference threshold, and take different actions based on the comparison results. If the total power consumption difference is less than or equal to the total power consumption difference threshold, it means that the total power consumption difference of all smart home devices in two adjacent months of the same quarter is reasonable. If the total power consumption difference is greater than the total power consumption difference threshold, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is unreasonable. Then, based on the power consumption ratio, the detection priority of all smart homes is obtained from large to small. Step 4: Based on the detection priority of several smart home devices in operation, perform energy consumption data detection on each of the smart home devices to obtain the energy consumption detection results and maintenance reminders for the smart home devices.

2. The IoT home data management method based on big data analysis according to claim 1, characterized in that, Step four specifically includes: Obtain the detection priority and detection status of several smart home devices in operation; From a number of smart home devices that are not detected, identify the target smart home device with the highest detection priority. Based on the detection duration corresponding to the target smart home, energy consumption data is detected on the target smart home to obtain the energy consumption detection results and maintenance reminders of the target smart home. After updating the detection status of the target smart home to "detected", the system continues to select the target smart home with the highest detection priority from several smart homes with an "undetected" detection status, until the energy consumption detection results and maintenance reminders of several smart homes in operation are obtained.

3. The IoT home data management method based on big data analysis according to claim 2, characterized in that, If the target smart home device is an air conditioner, the steps for detecting the energy consumption data of the target smart home device and obtaining the energy consumption detection results and maintenance reminders include: First, obtain the pressure of the air before passing through the filter and the pressure of the air after passing through the filter, and use the pressure before passing through the filter and the pressure after passing through the filter to obtain the pressure difference; Second, set the pressure difference threshold of the air passing through the filter. When the pressure difference of the air passing through the filter does not exceed the set pressure difference threshold, it means that there is less dust accumulated on the filter and the airflow is less affected. Third, compare the pressure difference of the air before and after passing through the filter with the pressure difference threshold. If the pressure difference is less than or equal to the pressure difference threshold, it means that there is less dust accumulated on the filter, the filter has less resistance to airflow, and the air conditioner's filtration, purification, cooling, or heating functions are less affected. In this case, the test result for the air conditioner filter is normal, and the status quo should be maintained. If the pressure difference is greater than the pressure difference threshold, it means that there is more dust accumulated on the filter, the filter has greater resistance to airflow, and the air conditioner's filtration, purification, cooling, or heating functions are significantly affected. In this case, the test result for the air conditioner filter is abnormal, and the user is reminded to clean the filter.

4. The IoT home data management method based on big data analysis according to claim 3, characterized in that, Record the initial room temperature, preset the desired comfortable temperature to be reached and maintained, and record the time it takes for the air conditioner to reach the comfortable temperature after turning it on. This is recorded as the initial time. After reaching the comfortable temperature, preset a later time to maintain the comfortable temperature. The later time and the initial time together constitute the total time. After the air conditioner has been on for the total time, turn it off and record the total electricity consumed during this period. This is recorded as the actual total electricity consumption. In addition, obtain the theoretical total electricity consumption of the air conditioner in a room of the same size, from the same initial temperature to the comfortable temperature and running for the same total time. Subtract the theoretical total electricity consumption from the actual total electricity consumption to obtain the electricity consumption difference. Divide the electricity consumption difference by the theoretical total electricity consumption to obtain the electricity consumption gap. At the same time, set a power consumption gap threshold, which represents the upper limit of the electricity consumption gap that the user can accept. When the pressure difference of the air passing through the filter exceeds the pressure difference threshold, compare the power consumption gap with the power consumption gap threshold and take different actions based on the comparison results.

5. The IoT home data management method based on big data analysis according to claim 4, characterized in that, If the power consumption difference is less than or equal to the power consumption difference threshold, it means that the power consumption difference is within an acceptable range. In this case, the user is not reminded to clean the filter. If the power consumption difference is greater than the power consumption difference threshold, it means that the power consumption difference exceeds the acceptable range. In this case, the user is reminded to clean the filter.

6. The IoT home data management method based on big data analysis according to claim 5, characterized in that, When the power consumption difference exceeds the power consumption difference threshold, a second threshold greater than the power consumption difference threshold is set, and the power consumption difference is compared with the second threshold. Different responses are given based on the comparison results.

7. The IoT home data management method based on big data analysis according to claim 6, characterized in that, If the power consumption difference is less than the second threshold, it means that the power consumption difference is not far beyond the user's acceptable limit. In this case, the judgment is made again. If the power consumption difference is greater than or equal to the second threshold, it means that the power consumption difference exceeds the user's acceptable limit to a large extent. In this case, the reminder to the user will continue.

8. The IoT home data management method based on big data analysis according to claim 7, characterized in that, The second judgment process involves setting a predefined air conditioner usage cycle, obtaining the air conditioner's usage time within the previous usage cycle, dividing the usage time by the usage cycle to obtain the usage time percentage, setting a usage time percentage threshold, comparing the usage time percentage with the usage time percentage threshold, and determining different responses based on the comparison results.

9. The IoT home data management method based on big data analysis according to claim 8, characterized in that, If the percentage of time used is less than the threshold, it means the user uses the device infrequently, and in this case, no notification is given to the user. If the percentage of time used is greater than or equal to the threshold, it means the user uses the device frequently, and in this case, a notification is given to the user.

10. An IoT home data management system based on big data analytics, used to perform the method described in any one of claims 1-9, characterized in that, include: The acquisition module obtains the total power consumption of all smart home devices in two consecutive months of the previous quarter through the built-in sensors in the smart home, and records them as total power consumption one and total power consumption two respectively. The difference between the total power consumption of the two consecutive months is obtained by subtracting total power consumption two from total power consumption one and processing the absolute value. The setting module sets a threshold for the total power consumption difference based on historical records. This threshold represents the maximum reasonable difference between the total power consumption of all smart home devices in two consecutive months. If this maximum value is exceeded, it indicates that there is one or more abnormal power consumption in the smart home devices. The comparison module compares the total power consumption difference with the total power consumption difference threshold and takes different actions based on the comparison results. If the total power consumption difference is less than or equal to the total power consumption difference threshold, it means that the total power consumption difference of all smart home devices in two adjacent months of the same quarter is reasonable. If the total power consumption difference is greater than the total power consumption difference threshold, it means that the total power consumption difference of all smart homes in two adjacent months of the same quarter is unreasonable. Then, based on the power consumption ratio, the detection priority of all smart homes is obtained from large to small. The detection module performs energy consumption data detection on each of the smart home devices in operation according to their detection priority, and obtains the energy consumption detection results and maintenance information for each smart home device.

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