Wireless smart home system

Abstract

The invention discloses a wireless smart home system, and relates to the technical field of smart home, and the system comprises the steps: firstly, classifying each smart device according to the use condition of each smart device, and selecting the operation mode and adjustment power of each smart device according to the type of each functional device and historical regulation record data during the peak period of power utilization; during energy-saving adjustment, operation of the intelligent devices is monitored, operation conditions of the intelligent devices are analyzed, and targeted adjustment and control are performed on different types of electric appliances, so that the energy-saving adjustment and control effect of the electric appliances is improved, normal operation of the electric appliances is guaranteed, it is ensured that the adjustment effect meets basic requirements, the intelligent level of smart home is improved, and the energy-saving adjustment and control effect of the electric appliances is improved. And the high-quality and high-level living requirements of the user on the smart home are met, the experience feeling of the user on the smart home is improved, and high efficiency and energy conservation of the electric appliance are effectively realized.

Description

Technical Field

[0001] The present invention relates to the technical field of smart home, and in particular to a wireless smart home system. Background Art

[0002] With the development of wireless communication technology, a stable, efficient and convenient communication method has been provided for the interconnection between smart home devices, allowing devices to break free from the constraints of wired connections, achieve flexible layout and remote control, and at the same time provide users with a convenient, comfortable and energy-saving home life experience.

[0003] Existing technologies such as the invention patent disclosed in the application with the publication number CN118131640A, the energy-saving method and system of smart home appliances based on the Internet of Things technology, match the user's habitual indoor environmental parameters, and compare the historical actual indoor environmental parameters to determine the indoor energy-saving standard environmental data, and then compare the collected indoor environmental sensor detection data with the corresponding energy-saving standard environmental data to obtain the difference of each parameter, and then determine the adjustment level and energy-saving control parameters of each parameter based on the difference of each parameter, and finally send each energy-saving control parameter to the energy-saving controller, which can realize efficient and intelligent energy-saving control of home appliances. While performing automatic energy-saving control of home appliances, the present invention fully considers the user's living habits, which can optimize energy utilization and save electricity bills on the one hand, and ensure the user's home comfort on the other hand, while achieving the purpose of energy saving, it improves the user's quality of life.

[0004] The above scheme has at least the following deficiencies: 1. Different electrical appliances have different usage frequencies. In order to ensure the normal use of electrical appliances during peak hours of electricity consumption, the regulation of electrical appliances with different usage frequencies is also different. However, the above scheme lacks classification according to the frequency of use of electrical appliances, and then targeted regulation of different types of electrical appliances, thereby reducing the effect of energy-saving regulation of electrical appliances. At the same time, it cannot guarantee the normal operation of electrical appliances, and cannot improve the user experience of smart homes.

[0005] 2. When electrical appliances are energy-saving and regulated, it is necessary to ensure that their operating effects meet basic requirements. However, the above scheme does not confirm the adjustment scheme of the electrical appliances based on relevant data of the electrical appliances in their historical operation process, thus failing to ensure that the adjustment effects meet basic requirements, failing to improve the intelligence level of smart homes, and failing to meet users' high-quality and high-level living needs for smart homes, thereby reducing users' experience of smart homes and failing to effectively achieve efficient energy saving of electrical appliances. Summary of the invention

[0006] In view of the above-mentioned technical deficiencies, an object of the present invention is to provide a wireless smart home system.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a wireless smart home system, including: a power consumption monitoring module, which is used to monitor the comprehensive power consumption data of the house, judge the power consumption status of the house in the current period, and execute the energy-saving control module if the power consumption status is at a peak state.

[0008] The energy-saving control module is used to monitor the operating data of each smart device in the current period, obtain the historical operating data of each smart device, and regulate the power consumption data of each smart device in the current period.

[0009] The operation monitoring module is used to adjust the power consumption data of each smart device, monitor the operation of each smart device again, and analyze the operating status of each smart device.

[0010] The execution module is used to provide corresponding feedback according to the operating status of each smart device.

[0011] The beneficial effects of the present invention are as follows: the present application provides a wireless smart home system, which first classifies each smart device according to its usage. During peak power consumption, the operating mode and power adjustment of each smart device are selected according to the type of each functional device and the recorded data of historical regulation. During energy-saving regulation, the operation of each smart device is monitored and the operating status of each smart device is analyzed. By performing targeted regulation on different types of electrical appliances, the effect of energy-saving regulation of electrical appliances is improved, while the normal operation of electrical appliances is guaranteed, ensuring that the regulation effect meets basic needs, thereby improving the intelligence level of smart homes, meeting users' high-quality and high-level life needs for smart homes, increasing users' experience of smart homes, and effectively achieving efficient energy saving of electrical appliances. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0013] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] See also Figure 1 As shown, a wireless smart home system includes: a power consumption monitoring module, an energy-saving control module, an operation monitoring module and an execution module.

[0016] The electricity consumption monitoring module is used to monitor the comprehensive electricity consumption data of the house and determine the electricity consumption status of the house in the current period. If the electricity consumption status is at a peak, the energy-saving control module is executed.

[0017] The comprehensive electricity consumption data includes the total electricity consumption in the current period and the total electricity consumption in the historical period. The wireless smart home system is connected to the electricity meter in the house to obtain the comprehensive electricity consumption data of the house.

[0018] In a specific embodiment, the process of determining the power consumption status of the house in the current period is as follows: the total power consumption of the current period and the total power consumption of the historical period are obtained from the comprehensive power consumption data of the house, which are recorded as W1 and W2 respectively. Substitute them into the power consumption status analysis model, and output the power consumption status analysis result of the house in the current period.

[0019] The power usage status analysis result includes values ​​of 1 and 0. When the power usage status analysis result is 1, it indicates that the power usage status is in a peak state, otherwise it indicates that the power usage status is in a non-peak state.

[0020] The expression of the power consumption status analysis model is: Where α represents the power consumption status analysis result of the house in the current period, W and ΔW are the preset total power consumption threshold and total power consumption difference threshold respectively.

[0021] It should be noted that the total power consumption threshold and the total power consumption difference threshold are critical values ​​for judging whether the total power consumption and the growth of total power consumption are too large, respectively. They are set by system engineers and can also be customized by users through the system.

[0022] When the total power consumption is too large or increases suddenly, the current in the circuit will increase accordingly. If it exceeds the rated current carrying capacity of the wires and sockets, the wires will overheat, and the insulation layer of the wires will age faster or even melt due to overheating, causing a short circuit. When a short circuit occurs, the current will instantly become extremely large, generating a large amount of heat, which may directly damage the electrical equipment connected to it; at the same time, the impact of high current will damage various electrical equipment and shorten their service life. Therefore, the total power consumption and the total power consumption difference are used to judge that the power consumption state is at a peak state.

[0023] The energy-saving control module is used to monitor the operating data of each smart device in the current period, obtain the historical operating data of each smart device, and regulate the power consumption data of each smart device in the current period.

[0024] Among them, each smart device includes various electrical appliances, such as lamps, air conditioners, refrigerators, and air purifiers, etc. The operation data of each smart device is operation-related data when each smart device is running, such as power, voltage, current, and operating temperature, etc.

[0025] Each smart device is equipped with a number of sensors, including but not limited to power sensors, voltage sensors, current sensors and temperature sensors. These sensors transmit the collected data to the wireless smart home system through wireless communication.

[0026] The historical operation data of each smart device includes not only the operation data in each historical period, but also the operation time and startup times of each smart device in each historical period. The historical operation data of each smart device is stored in the historical storage space of the wireless smart home system.

[0027] In a specific embodiment, the power consumption data of each smart device in the current time period is regulated, and the specific process is as follows: the operating time, startup times and power of each smart device in each historical time period are obtained from the historical operating data of each smart device, and then each smart device is classified into necessary equipment, high-frequency equipment and low-frequency equipment.

[0028] Preferably, the smart devices are classified as follows: when the running time of a smart device in each historical period is the same as the duration of each historical period, the smart device is classified as a necessary device; otherwise, the running time and the number of startups of the smart device in each historical period are recorded as YT t and YC t, where t represents the number of each historical period, t is a positive integer, and is substituted into the usage evaluation model to output the usage evaluation result of the smart device. The usage evaluation result contains values ​​of 1 and 0. When the evaluation result is 1, the smart device is classified as a high-frequency device, and when the evaluation result is 0, the smart device is classified as a low-frequency device, thereby completing the classification of each smart device.

[0029] The expression used to evaluate the model is:

[0030] In the formula, δ represents the usage evaluation result of the smart device, YT and YC are the preset operation time threshold and startup number threshold, r represents the number of historical time periods, ε1 and ε2 are the set operation time proportional coefficient and startup number proportional coefficient, respectively.

[0031] It should be noted that the operation time, startup times and usage evaluation results of each smart device in each historical period are extracted from the wireless smart home system, and the Pearson correlation coefficient between the operation time and startup times and the usage evaluation results of the smart device is calculated using the Pearson correlation coefficient calculation method, which are recorded as a1 and a2 respectively.

[0032] The setting process of the operation time threshold and the startup number threshold is the same as the setting process of the total power consumption threshold and the total power consumption difference threshold, which will not be repeated here.

[0033] Obtain the operating modes, reference power and historical operating records of each operating mode corresponding to each necessary device, monitor the effect data of each necessary device in the current period, and then adjust the operating mode of each necessary device.

[0034] It should be noted that the effect data of necessary equipment is a data set on the degree to which the necessary equipment achieves the expected function or goal. It can intuitively reflect the actual working conditions of the equipment. For example, if the necessary equipment is a refrigerator, the effect data is the temperature inside the refrigerator. If the necessary equipment is an air conditioner, the effect data is the indoor temperature.

[0035] Preferably, the specific process of adjusting the operating mode of each necessary device is as follows: using the operating data of each smart device in the current time period, obtaining the operating mode and actual power corresponding to each necessary device in the current time period, and at the same time obtaining the preset effect data corresponding to each necessary device from the home control center, comparing the effect data of each necessary device in the current time period with the preset effect data to obtain the effect data difference of each necessary device, and obtaining the operating time, actual operating power, effect data difference and effect stability value of each historical operation of each operating mode from the historical operation records of each necessary device.

[0036] It should be noted that the preset effect data is the effect data threshold set by the user through the wireless smart home system. Assuming that the necessary equipment is an air conditioner and the temperature set by the user is 24°C, the preset effect data is 24°C.

[0037] The historical operation records of each necessary device are stored in the wireless smart home system.

[0038] Compare the effect data difference of each necessary device with the effect data difference of each historical operation of each operation mode, select each historical operation with the same effect data difference as each reference operation, and obtain each reference operation of each necessary device corresponding to each operation mode.

[0039] The operating time, actual operating power and effect stability value of each reference operation of each necessary equipment in each operating mode are extracted, and the operating effect index corresponding to each operating mode of each necessary equipment is calculated using the reference power corresponding to each operating mode of each necessary equipment.

[0040] Optionally, the calculation process of the operation effect index corresponding to each operation mode in each necessary device is as follows: the operation time, actual operation power, and effect stability value of each reference operation in each operation mode corresponding to each necessary device are recorded as T byz , P byz and ST byz , where b represents the number of each necessary device, y represents the number of each operating mode, z represents the number of each reference operation, b, y and z are all positive integers; the reference power corresponding to each necessary device and each operating mode is denoted as P′ by .

[0041] Using the calculation formula:

[0042] Get the operation effect index corresponding to the yth operation mode in the bth necessary equipment Where v represents the number of reference runs, W bmin represents the minimum power consumption per unit time of the bth necessary equipment, T by Indicates the total running time corresponding to the yth running mode in the bth necessary device, ST bmax It represents the maximum effective stability value of the b-th necessary equipment, γ1 and γ2 are the proportional coefficient of the set unit time power loss and the proportional coefficient of the effective stability value respectively.

[0043] The minimum power consumption per unit time and the maximum effect stability value of each necessary device are obtained from the historical operation records of each necessary device. The setting method of γ1 and γ2 is the same as that of ε1 and ε2, so they are not repeated here.

[0044] Compare the actual power corresponding to each necessary device in the current time period with the reference power corresponding to each operating mode, and select the operating modes with reference power less than the actual power as the optional operating modes; then sort the optional operating modes corresponding to each necessary device in descending order according to the operating effect index; if the first-ranked optional operating mode of a certain necessary device is different from the operating mode of the current time period, the first-ranked optional operating mode is used as the adjusted operating mode; if the first-ranked optional operating mode of a certain necessary device is the same as the operating mode of the current time period, the second-ranked optional operating mode is used as the adjusted operating mode, and then the operating mode of each necessary device is adjusted to the adjusted operating mode.

[0045] It should be noted that when there is no operating mode in which the reference power is less than the actual power, the operating mode is not adjusted.

[0046] In the above, different necessary equipment has different operation modes. For example, assuming that the necessary equipment is a refrigerator, its operation modes include a refrigeration mode and an energy-saving mode.

[0047] The associated data of each high-frequency device in the current period is obtained, and the power of each high-frequency device is adjusted according to the operating data of each intelligent device in the current period.

[0048] Among them, the associated data of each high-frequency device is the relevant data for triggering the startup of each high-frequency device. For example, assuming that the high-frequency device is an air conditioner, a temperature sensor is provided on the air conditioner to collect the indoor temperature and transmit it to the wireless smart home system through wireless communication; when the indoor temperature reaches the startup temperature threshold set by the user, the air conditioner switch is automatically started, and the indoor temperature is the associated data.

[0049] In a specific embodiment, the power of each high-frequency device is adjusted, and the specific process is as follows: each monitoring moment is arranged in the current time period according to a preset time interval, and the associated data corresponding to each high-frequency device at each monitoring moment is collected, thereby calculating the associated data characteristic value corresponding to each high-frequency device.

[0050] Optionally, the correlation value GV corresponding to each high-frequency device at each monitoring moment kj , substitute into the calculation formula Get the associated data eigenvalue GL of the kth high-frequency device k ′, where o represents the number of monitoring moments, j represents the number of each monitoring moment, and both j and o are positive integers.

[0051] The associated data characteristic values, actual power and effect stability values ​​corresponding to each historical operation of each high-frequency device are obtained from the home control center, and the associated data characteristic values ​​and effect stability values ​​of each high-frequency device at each actual power are counted, and then the control priority value of each high-frequency device corresponding to each actual power is calculated.

[0052] Preferably, the calculation process of the control priority value of each high-frequency device corresponding to each actual power is as follows: each associated data characteristic value and each effect stability value of each high-frequency device at each actual power are respectively recorded as GL kma and ST kmd , where k represents the number of each high-frequency device, m represents the number corresponding to each actual power, a represents the number of each associated data characteristic value, d represents the number of each effect stability value, and k, m, a and d are all positive integers.

[0053] Using the operating data of each intelligent device in the current period, the actual power of each high-frequency device in the current period is obtained, which is recorded as P k , and the actual power of each high-frequency device is recorded as P km , the associated data feature value corresponding to each high-frequency device is recorded as GL k ′.

[0054] According to the calculation formula:

[0055] Get the control priority value φ of the kth high-frequency device corresponding to the mth actual power km , where e represents the natural constant, u represents the number of associated data eigenvalues, h represents the number of effect stability values, ΔGL k represents the minimum correlation data eigenvalue difference of the kth high-frequency device, ST kmax Indicates the maximum effective stability value of the kth high-frequency device.

[0056] The actual power with the largest control priority value among the high-frequency devices is selected as the adjusted power, and then the power of each high-frequency device is adjusted to the adjusted power.

[0057] Obtain the number of startups, startup times, and usage duration of each low-frequency device in each historical period, analyze the necessity of starting each low-frequency device, shut down each low-frequency device with low startup necessity, and adjust the power of each low-frequency device with high startup necessity.

[0058] In a specific embodiment, the necessity of starting each low-frequency device is analyzed, and the specific analysis process is as follows: the number of times each low-frequency device is started, the time of each start, and the duration of each start in each historical period are obtained from the home control center.

[0059] Compare each historical period with the current period, and take each historical period whose start time and end time are the same as the start time and end time of the current period as the target period.

[0060] According to the number of startups of each low-frequency device in each historical period and the duration of each startup, the total number of startups and the total duration of use of each low-frequency device in the target period are counted, which is recorded as Qf and QT f , where f represents the serial number of each low-frequency device, and f is a positive integer; at the same time, the total number of historical startup times and the total historical usage time of each low-frequency device are counted, recorded as Q′ f and QT f ′.

[0061] According to the analysis formula Obtain the startup necessity results of each low-frequency device θ f , where ω is the set necessity coefficient threshold.

[0062] It should be noted that the setting process of the necessity coefficient threshold is the same as the setting process of the total power consumption threshold and the total power consumption difference threshold, and will not be repeated here.

[0063] The startup necessity result includes values ​​of 1 and 0. When the startup necessity result is 1, it indicates that the startup necessity is high. When the startup necessity result is 0, it indicates that the startup necessity is low.

[0064] In the above, the power adjustment method of each low-frequency device with a higher necessity to start is the same as the power adjustment method of each high-frequency device. Therefore, according to the analysis method of the adjustment power of each high-frequency device, the adjustment power of each low-frequency device with a higher necessity to start is analyzed and adjusted accordingly.

[0065] The operation monitoring module is used to adjust the power consumption data of each smart device, monitor the operation of each smart device again, and analyze the operating status of each smart device.

[0066] In a specific embodiment, the specific process of analyzing the operating status of each intelligent device is as follows: after the operating mode of each necessary device is adjusted, each collection time is set, and then the actual power and effect data corresponding to each necessary device at each collection time are collected, and the operating status of each necessary device is calculated.

[0067] Obtain the reference power of each necessary device corresponding to the adjusted operating mode from the wireless smart home system, denoted as P1 b The actual power and effect data of each necessary device at each collection time are recorded as P2 bi and S2 bi , i represents the number of each collection moment, and i is a positive integer.

[0068] Using the calculation formula Get the effect stability value ST corresponding to the bth necessary equipment b , n represents the number of acquisition moments.

[0069] It should be noted that the effect stability value corresponding to each necessary device is stored in the wireless smart home system.

[0070] Reuse analysis formula Get the operating status analysis result ψ corresponding to the bth necessary equipment b , where ξ is the set operating state coefficient threshold and e is a natural constant.

[0071] The setting process of ξ is the same as the setting process of the total power consumption threshold and the total power consumption difference threshold, which will not be repeated here.

[0072] When b =1, it indicates that the operation status of the bth necessary equipment is good. b =0, it indicates that the operating status of the bth necessary equipment is poor.

[0073] After the power adjustment of each high-frequency device is completed, each collection time point is set, and then the power and effect data of each high-frequency device at each collection time point are collected, and the operating status of each high-frequency device is calculated.

[0074] When the low-frequency devices with a high startup necessity start to start, they are recorded as target devices, and the detection time is set. The actual power and effect data of each target device at each detection time are obtained, and the operating status of each target device is calculated.

[0075] It should be noted that the operation status of each high-frequency device and the operation status of each target device are calculated in the same process as the operation status of each necessary device. The operation status of each high-frequency device and the operation status of each target device are calculated according to the calculation process of the operation status of each necessary device.

[0076] The execution module is used to provide corresponding feedback according to the operating status of each smart device.

[0077] In the above, when a necessary device, a high-frequency device or a target device is in a poor operating state, a poor state prompt is sent to the user.

[0078] The embodiment of the present invention first classifies each smart device according to the usage of each smart device. During the peak period of electricity consumption, the operation mode and power adjustment of each smart device are selected according to the type of each functional device and the recorded data of historical regulation. During energy-saving regulation, the operation of each smart device is monitored and the operation status of each smart device is analyzed. By performing targeted regulation on different types of electrical appliances, the effect of energy-saving regulation of electrical appliances is improved, while the normal operation of electrical appliances is guaranteed, ensuring that the regulation effect meets basic needs, thereby improving the intelligence level of smart homes, meeting users' high-quality and high-level life needs for smart homes, increasing users' experience of smart homes, and effectively achieving efficient energy saving of electrical appliances.

[0079] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. A wireless smart home system, characterized in that: include: The power consumption monitoring module is used to monitor the comprehensive power consumption data of the house and determine the power consumption status of the house in the current period. If the power consumption status is at a peak, the energy-saving control module is executed; The energy-saving control module is used to monitor the operation data of each smart device in the current period, obtain the historical operation data of each smart device, and regulate the power consumption data of each smart device in the current period; The operation monitoring module is used to monitor the operation of each smart device again after adjusting the power consumption data of each smart device, and analyze the operation status of each smart device; The execution module is used to provide corresponding feedback according to the operating status of each smart device.

2. A wireless smart home system according to claim 1, characterized in that: The process of determining the power consumption status of the house in the current period is as follows: Obtain the total electricity consumption of the current period and the total electricity consumption of the historical period from the comprehensive electricity consumption data of the house, and record them as W1 and W2 respectively. Substitute them into the electricity consumption status analysis model, and output the electricity consumption status analysis results of the house in the current period; The power consumption status analysis result includes values ​​of 1 and 0. When the power consumption status analysis result is 1, it indicates that the power consumption status is in a peak state, otherwise it indicates that the power consumption status is in a non-peak state; The expression of the power consumption status analysis model is: Where α represents the power consumption status analysis result of the house in the current period, W and ΔW are the preset total power consumption threshold and total power consumption difference threshold respectively.

3. A wireless smart home system according to claim 1, characterized in that: The specific process of regulating the power consumption data of each smart device in the current period is as follows: The operation time, start-up times and power of each smart device in each historical period are obtained from the historical operation data of each smart device, and then each smart device is classified into necessary devices, high-frequency devices and low-frequency devices; Obtain each operating mode, reference power and historical operating record corresponding to each necessary device, monitor the effect data of each necessary device in the current period, and then adjust the operating mode of each necessary device; Obtain the associated data of each high-frequency device in the current period, and adjust the power of each high-frequency device according to the operating data of each smart device in the current period; Obtain the number of startups, startup times, and usage duration of each low-frequency device in each historical period, analyze the necessity of starting each low-frequency device, shut down each low-frequency device with low startup necessity, and adjust the power of each low-frequency device with high startup necessity.

4. A wireless smart home system according to claim 3, characterized in that: The specific process of classifying each smart device is as follows: If the running time of a smart device in each historical period is the same as the duration of each historical period, the smart device is classified as a necessary device; otherwise, the running time and the number of startups of the smart device in each historical period are recorded as YT t and YC t , where t represents the number of each historical period, t is a positive integer, and is substituted into the usage evaluation model to output the usage evaluation result of the smart device. The usage evaluation result contains values ​​of 1 and 0. When the evaluation result is 1, the smart device is classified as a high-frequency device, and when the evaluation result is 0, the smart device is classified as a low-frequency device, thereby completing the classification of each smart device; The expression used to evaluate the model is: In the formula, δ represents the usage evaluation result of the smart device, YT and YC are the preset operation time threshold and startup number threshold, r represents the number of historical time periods, ε1 and ε2 are the set operation time proportional coefficient and startup number proportional coefficient, respectively.

5. A wireless smart home system according to claim 3, characterized in that: The specific process of adjusting the operation mode of each necessary device is as follows: Using the operation data of each smart device in the current period, the operation mode and actual power corresponding to each necessary device in the current period are obtained, and at the same time, the preset effect data corresponding to each necessary device is obtained from the home control center, and the effect data of each necessary device in the current period is compared with the preset effect data to obtain the effect data difference of each necessary device, and the operation time, actual operation power, effect data difference and effect stability value of each historical operation of each operation mode are obtained from the historical operation records of each necessary device; Compare the effect data difference of each necessary device with the effect data difference of each historical operation of each operation mode, select each historical operation with the same effect data difference as each reference operation, and obtain each reference operation of each necessary device corresponding to each operation mode; Extract the operation time, actual operation power, and effect stability value of each reference operation of each necessary device in each operation mode, and use the reference power corresponding to each operation mode of each necessary device to calculate the operation effect index corresponding to each operation mode of each necessary device; Compare the actual power corresponding to each necessary device in the current time period with the reference power corresponding to each operating mode, and select the operating modes with reference power less than the actual power as the optional operating modes; then sort the optional operating modes corresponding to each necessary device in descending order according to the operating effect index; if the first-ranked optional operating mode of a certain necessary device is different from the operating mode of the current time period, the first-ranked optional operating mode is used as the adjusted operating mode; if the first-ranked optional operating mode of a certain necessary device is the same as the operating mode of the current time period, the second-ranked optional operating mode is used as the adjusted operating mode, and then the operating mode of each necessary device is adjusted to the adjusted operating mode.

6. A wireless smart home system according to claim 5, characterized in that: The calculation process of the operation effect index corresponding to each operation mode in each necessary device is as follows: The operation time, actual operation power and effect stability value of each reference operation of each necessary equipment in each operation mode are recorded as T byz , P byz and ST byz , where b represents the number of each necessary device, y represents the number of each operating mode, z represents the number of each reference operation, b, y and z are all positive integers; the reference power corresponding to each necessary device and each operating mode is denoted as P′ by ; Using the calculation formula: Get the operation effect index corresponding to the yth operation mode in the bth necessary equipment Where v represents the number of reference runs, W bmin represents the minimum power consumption per unit time of the bth necessary equipment, T by Indicates the total running time corresponding to the yth running mode in the bth necessary device, ST bmax It represents the maximum effective stability value of the b-th necessary equipment, γ1 and γ2 are the proportional coefficient of the set unit time power loss and the proportional coefficient of the effective stability value respectively.

7. A wireless smart home system according to claim 3, characterized in that: The specific process of adjusting the power of each high-frequency device is as follows: Arrange each monitoring moment in the current period according to the preset time interval, collect the associated data corresponding to each high-frequency device at each monitoring moment, and thereby calculate the associated data feature value corresponding to each high-frequency device; Obtain the associated data characteristic values, actual power and effect stability values ​​corresponding to each historical operation of each high-frequency device from the home control center, thereby counting the associated data characteristic values ​​and effect stability values ​​of each high-frequency device at each actual power, and then calculating the control priority value of each high-frequency device corresponding to each actual power; The actual power with the largest control priority value among the high-frequency devices is selected as the adjusted power, and then the power of each high-frequency device is adjusted to the adjusted power.

8. A wireless smart home system according to claim 7, characterized in that: The calculation process of the control priority value of each high-frequency device corresponding to each actual power is as follows: The characteristic values ​​of the associated data and the stability values ​​of the effects of each high-frequency device at each actual power are respectively recorded as GL kma and ST kmd , where k represents the number of each high-frequency device, m represents the number corresponding to each actual power, a represents the number of each associated data characteristic value, d represents the number of each effect stability value, and k, m, a and d are all positive integers; Using the operating data of each intelligent device in the current period, the actual power of each high-frequency device in the current period is obtained, which is recorded as P k , and the actual power of each high-frequency device is recorded as P km , the associated data feature value corresponding to each high-frequency device is recorded as GL′ k ; According to the calculation formula: Get the control priority value φ of the kth high-frequency device corresponding to the mth actual power km , where e represents the natural constant, u represents the number of associated data eigenvalues, h represents the number of effect stability values, ΔGL k represents the minimum correlation data eigenvalue difference of the kth high-frequency device, ST kmax Indicates the maximum effective stability value of the kth high-frequency device.

9. A wireless smart home system according to claim 3, characterized in that: The necessity of starting each low-frequency device is analyzed, and the specific analysis process is as follows: Obtaining the number of startups, the startup time, and the usage duration of each startup of each low-frequency device in each historical period from the home control center; Compare each historical period with the current period, and take each historical period whose start time and end time are the same as the start time and end time of the current period as each target period; According to the number of startups of each low-frequency device in each historical period and the duration of each startup, the total number of startups and the total duration of use of each low-frequency device in the target period are counted, which is recorded as Q f and QT f , where f represents the serial number of each low-frequency device, and f is a positive integer; at the same time, the total number of historical startup times and the total historical usage time of each low-frequency device are counted, recorded as Q′ f and QT′ f ; According to the analysis formula Obtain the startup necessity results of each low-frequency device θ f , where ω is the set necessity coefficient threshold; The startup necessity result includes values ​​of 1 and 0. When the startup necessity result is 1, it indicates that the startup necessity is high. When the startup necessity result is 0, it indicates that the startup necessity is low.

10. A wireless smart home system according to claim 3, characterized in that: The specific process of analyzing the operating status of each smart device is as follows: After the operation mode of each necessary device is adjusted, each collection time is set, and then the actual power and effect data corresponding to each necessary device at each collection time are collected to calculate the operation status of each necessary device; After the power adjustment of each high-frequency device is completed, each collection time point is set, and then the power and effect data of each high-frequency device at each collection time point are collected, and the operating status of each high-frequency device is calculated; When the low-frequency devices with a high startup necessity start to start, they are recorded as target devices, and the detection time is set. The actual power and effect data of each target device at each detection time are obtained, and the operating status of each target device is calculated.

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