Cloud service based LED bulb management system

Abstract

The application belongs to the technical field of LED bulb management, and relates to an LED bulb management system based on cloud services. The application is self-controlled by running data of each LED bulb corresponding to each specified user, which helps to provide a more comfortable and personalized lighting environment for the user, avoids unnecessary lighting waste, improves the overall efficiency of the lighting system, effectively reduces energy consumption, helps to reduce electricity charges, saves costs for the user, prolongs the service life of the LED bulb, reminds the user of the abnormality of each LED bulb and bulb maintenance and replacement, helps to timely warn each LED bulb used by the user, reduces failure loss, is beneficial to ensuring that the LED bulb always maintains a good working state, provides stable and high-quality lighting, guarantees the lighting needs and experience of the user, and improves the convenience and comfort of the user.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of LED bulb management, and relates to an LED bulb management system based on cloud services. BACKGROUND

[0002] With the continuous progress of LED lighting technology, LED bulbs gradually replace traditional incandescent lamps and fluorescent lamps as mainstream lighting sources due to their energy-saving, long-life, and strong adjustability. On the basis of meeting basic lighting functions, people's demand for intelligent control of lighting is increasing, and they hope to more conveniently and flexibly control the brightness, color, and on-off state of the bulbs to adapt to different life scenes and create diverse atmospheres. Therefore, the LED bulb management system based on the cloud service platform has great significance and role.

[0003] In the prior art, there are also some related solutions for intelligent control of LED bulbs, for example, the invention patent application for a solar LED street lamp system with Internet of Things lithium battery storage and control function, with the publication number CN106524052A. The detection device is connected with the solar LED street lamp, the data acquisition device is connected with the detection device, the data transmission module is connected with the data acquisition device, the voltage detection module and the current and power detection module are connected with the lithium battery pack, and the lithium battery pack is connected with the solar LED street lamp and the solar cell panel. The structure of the system for remote control and setting of the Internet of Things management solar street lamp is simple, and the operation is convenient. The central control system can be set to control the on-off of the solar LED street lamp at fixed times, and manual on-off control is not needed. The on-off state and fault state of the street lamp can be monitored by the detection device without manual inspection. The controller can reasonably and efficiently distribute the use of the electric energy of the lithium battery pack to avoid the shortening of the service life of the lithium battery pack due to improper charging and discharging.

[0004] The above-mentioned scheme proposes some solutions for intelligent control of LED bulbs, but still has certain limitations. On the one hand, the existing scheme mainly controls the on-off of the solar LED street lamp by setting fixed times, and reasonably and efficiently distributes the use of the electric energy of the lithium battery pack, without manual on-off control, and avoids the shortening of the service life of the lithium battery pack due to improper charging and discharging. However, the existing scheme lacks detection and analysis according to the preferences and work and rest of users, so it cannot provide more comfortable and personalized lighting environment for users, and cannot analyze the on-off of the light according to the brightness of the light in the environment, so as to avoid unnecessary lighting waste and improve the overall efficiency of the lighting system.

[0005] On the other hand, the prior art also ignores the detection and analysis of the working state of the LED bulb of the user, so that the abnormal situation and the working state change trend coefficient of the working state of the LED bulb of the user cannot be understood, and the user cannot be reminded of the abnormality and maintenance and replacement of the LED bulb in time, which is not conducive to reducing the failure loss and ensuring that the LED bulb always maintains a good working state, provides stable and high-quality lighting, and protects the lighting needs and experience of the user. SUMMARY

[0006] In view of this, in order to solve the problems raised in the background art, the present application proposes an LED bulb management system based on cloud service.

[0007] The purpose of the application can be achieved by the following technical solutions: the application provides an LED bulb management system based on cloud service, comprising: a data acquisition module, a data analysis module, an external data acquisition module, a bulb self-control management module, a state data acquisition module, a state data analysis module, a bulb abnormality management module and a cloud database.

[0008] The data acquisition module is used to record each user who purchases a target LED bulb as each designated user, record each target LED bulb installed indoors by each designated user as each LED bulb corresponding to each designated user, and acquire the running data of each LED bulb corresponding to each designated user in each period within a detection time period.

[0009] The data analysis module is used to analyze the running parameter preference and the running schedule of each LED bulb corresponding to each designated user.

[0010] The external data acquisition module is used to acquire the external data of the location of each LED bulb corresponding to each designated user.

[0011] The bulb self-control management module is used to perform self-control of the running data of each LED bulb corresponding to each designated user based on the running parameter preference and the running schedule of each LED bulb corresponding to each designated user and the external data of the location of each LED bulb corresponding to each designated user.

[0012] The state data acquisition module is used to acquire the current working state data and the historical working state data of each LED bulb corresponding to each designated user.

[0013] The state data analysis module is used to analyze the working state abnormality and the working state change trend coefficient of each LED bulb corresponding to each designated user, and store the working state change trend coefficient of each LED bulb corresponding to each designated user in the cloud database.

[0014] The lamp bulb anomaly management module is used for reminding the abnormality and bulb maintenance and replacement of each LED lamp bulb corresponding to each specified user based on the working state abnormality and working state change trend coefficient of each LED lamp bulb corresponding to each specified user.

[0015] The cloud database is used for storing the external light brightness threshold of the position of the LED lamp bulb, storing the recommended brightness value and recommended color temperature value corresponding to each user activity mode, storing the reference brightness value and reference color temperature value of each LED lamp bulb corresponding to each specified user, and storing the working state change trend coefficient of each analysis of each LED lamp bulb corresponding to each specified user.

[0016] Compared with the prior art, the beneficial effects of the present application are as follows: 1. The present application performs self-control of the running data of each LED lamp bulb corresponding to each specified user based on the running parameter preference and running schedule of each LED lamp bulb corresponding to each specified user and the external data of the position of each LED lamp bulb corresponding to each specified user, which helps to provide a more comfortable and personalized lighting environment for the user, avoid unnecessary lighting waste, improve the overall efficiency of the lighting system, effectively reduce energy consumption, help to reduce electricity bills, save costs for the user and prolong the service life of the LED lamp bulb.

[0017] 2. The present application performs abnormality reminding and bulb maintenance and replacement reminding of each LED lamp bulb corresponding to each specified user based on the working state abnormality and working state change trend coefficient of each LED lamp bulb corresponding to each specified user, which helps to timely warn each LED lamp bulb used by the user, reduces failure loss, is also conducive to ensuring that the LED lamp bulb always maintains a good working state, provides stable and high-quality lighting, safeguards the lighting needs and experience of the user, and improves the convenience and comfort of the user. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0019] Figure 1 It is a system module connection diagram of the present application.

[0020] Figure 2 It is a module implementation flowchart of the present application.

[0021] Figure 3 It is a bulb maintenance and replacement processing flowchart of the present application. DETAILED DESCRIPTION

[0022] With reference to the accompanying drawings on the basis of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0023] Please refer to Figure 1 As shown in the figure, the present application provides a cloud service-based LED bulb management system, and the specific module distribution is as follows: a data acquisition module, a data analysis module, an external data acquisition module, a bulb self-control management module, a state data acquisition module, a state data analysis module, a bulb anomaly management module, and a cloud database. The connection mode between the modules is as follows: the data acquisition module is connected with the data analysis module, the data analysis module is connected with the external data acquisition module, the external data acquisition module is connected with the bulb self-control management module, the state data acquisition module is connected with the state data analysis module, the state data analysis module is connected with the bulb anomaly management module, and the cloud database is connected with the bulb self-control management module and the state data analysis module respectively.

[0024] The data acquisition module is used to record each user who purchases a target LED bulb as a specified user, record each target LED bulb installed indoors by each specified user as a corresponding LED bulb of each specified user, and acquire the running data of each corresponding LED bulb of each specified user in each period within a detection time period.

[0025] It needs to be further explained that the module implementation process schematic diagram is as shown in the figure. Figure 2 .

[0026] As a preferred feasibility example, the running data of each corresponding LED bulb of each specified user in each period within a detection time period includes each opening and closing time point, and the brightness value and color temperature value of each period within each opening period.

[0027] It needs to be further explained that the reason for taking each opening and closing time point, and the brightness value and color temperature value of each period within each opening period as the running data of each corresponding LED bulb of each specified user in each period within a detection time period is that: (1) recording the opening and closing time points of the LED bulb can reflect its use frequency and use time length, and thus help to understand the user's work and rest habits, thereby providing more personalized lighting solutions for the user.

[0028] (2) The brightness value and color temperature value are key performance indicators of the LED bulb, which can directly affect the user's lighting experience and comfort. It helps to understand the user's lighting needs, thereby providing more personalized lighting solutions for the user and improving the user experience.

[0029] It needs to be further explained that the specific method for obtaining the brightness value and color temperature value of each turn-on and turn-off time points of each cycle of each LED bulb corresponding to each designated user within the detection time period, as well as each time period within each turn-on time period, is as follows: directly extracting the brightness value and color temperature value of each turn-on and turn-off time points of each cycle of each LED bulb corresponding to each designated user within the detection time period, as well as each time period within each turn-on time period, from the cloud service end corresponding to each LED bulb of each designated user.

[0030] The data analysis module is used to analyze the operating parameter preferences and operating schedules of each designated user for each LED bulb.

[0031] As a preferred feasibility example, the operating parameter preferences of the LED bulbs corresponding to the designated users are specifically analyzed by: extracting the brightness values ​​and color temperature values ​​of the LED bulbs corresponding to the designated users for each time period within each on-time period of each cycle within a detection time period, thereby obtaining the brightness values ​​and color temperature values ​​of the LED bulbs corresponding to the designated users for each time period within each on-time period of the same cycle within the detection time period; determining the number of time periods corresponding to the brightness values ​​and the number of time periods corresponding to the color temperature values ​​of the LED bulbs corresponding to the same cycle within the detection time period for the designated users based on the obtained values; comparing the values ​​with the minimum number of time periods corresponding to the operating parameter preferences extracted from the cloud database; and screening out the brightness values ​​of the LED bulbs corresponding to the same cycle within the detection time period for the designated users whose number of time periods corresponding to the brightness values ​​is greater than or equal to the minimum number of time periods corresponding to the operating parameter preferences, and the color temperature values ​​of the LED bulbs corresponding to the same cycle within the detection time period for the designated users whose number of time periods corresponding to the color temperature values ​​is greater than or equal to the minimum number of time periods corresponding to the operating parameter preferences; performing statistical analysis to obtain the preferred brightness values ​​and preferred color temperature values ​​of the LED bulbs corresponding to the designated users, and using the values ​​as the operating parameter preferences of the LED bulbs corresponding to the designated users.

[0032] In a specific example, the detection period is three weeks, and the period within the detection period is 24 hours, that is, each period within the detection period is within 24 hours on Monday, 24 hours on Tuesday, ... 24 hours on Sunday. The identical periods within the detection period are within 24 hours on Mondays, 24 hours on Tuesdays, ... 24 hours on Sundays within the three weeks. The fixed periods are within 24 hours on Mondays, 24 hours on Tuesdays, ... 24 hours on Sundays.

[0033] As a preferred feasibility example, the operation and rest rules of the LED bulbs corresponding to the specified users are analyzed in the following manner: the opening time points of the LED bulbs corresponding to the specified users in each cycle within the detection time period are extracted, the opening time points of the LED bulbs corresponding to the specified users in each same cycle within the detection time period are determined, and the differences between the two are calculated to obtain the differences between the opening time points of the LED bulbs corresponding to the specified users in each same cycle within the detection time period and other opening time points, and the opening time points of the LED bulbs corresponding to the specified users in each same cycle within the detection time period that are within the set difference range are screened out as the regular opening time points of the LED bulbs corresponding to the specified users in each same cycle, and the regular opening time points of the LED bulbs corresponding to the specified users in each same cycle are further averaged to obtain the regular opening time points of the LED bulbs corresponding to the specified users in each fixed cycle.

[0034] Similarly, the closing time points of the LED bulbs corresponding to the specified users in each cycle within the detection time period can be extracted to obtain the regular closing time points of the LED bulbs corresponding to the specified users in each same cycle within the detection time period.

[0035] Further, the regular opening and closing time points of the LED bulbs corresponding to the specified users in each same cycle within the detection time period are collectively referred to as the operation and rest rules of the LED bulbs corresponding to the specified users.

[0036] The external data acquisition module is configured to acquire external data of the positions of the LED bulbs corresponding to the specified users.

[0037] As a preferred feasibility example, the external data of the positions of the LED bulbs corresponding to the specified users includes a user presence index, a user activity pattern, and external light brightness.

[0038] It should be further noted that the user presence index, the user activity pattern, and the external light brightness are used as the external data of the positions of the LED bulbs corresponding to the specified users because: (1) The user presence index reflects the probability or frequency of the user's presence at a specific time and location. When the user is not present, the brightness of the LED bulb can be reduced or the bulb can be turned off, thereby achieving energy-saving effects and avoiding energy waste and safety hazards.

[0039] (2) The user activity pattern describes the behavior or activity rules of the user within a specific time period. According to the user's activity pattern, the brightness and color temperature of the LED bulb can be adjusted to meet the lighting needs in different activity scenarios.

[0040] (3) The external light brightness refers to the brightness of the natural light or the surrounding environment where the LED bulb is located. According to the external light brightness, the brightness of the LED bulb can be adjusted to maintain the coordination of indoor light and external light, and to avoid the discomfort caused by too strong or too weak light. In the case of sufficient natural light, the power of the LED bulb can be reduced or the bulb can be turned off to save energy and reduce the impact on the environment.

[0041] It should be further pointed out that the specific acquisition method of the user presence index, the user activity mode and the external light brightness of the location of each LED bulb corresponding to each designated user is that the smart camera is arranged to take pictures of the location of each LED bulb corresponding to each designated user, and further analyze by using image recognition technology. If there is a user at the location of a certain LED bulb corresponding to a certain designated user, the user presence index of the location of the LED bulb corresponding to the designated user is recorded as 1, otherwise, the user presence index of the location of the LED bulb corresponding to the designated user is recorded as 0. When there is a user at the location of a certain LED bulb corresponding to a certain designated user, the user image in the picture of the location of the LED bulb corresponding to the designated user is matched with the user image corresponding to the user activity mode stored in the cloud database, and the user activity mode of the location of the LED bulb corresponding to the designated user is obtained, and then the user activity mode of the location of each LED bulb corresponding to each designated user is obtained.

[0042] The external light brightness of the location of each LED bulb corresponding to each designated user is directly detected by the light sensor arranged.

[0043] The bulb self-control management module is used to control the running data of each LED bulb corresponding to each designated user based on the running parameter preferences and the running schedule of each designated user corresponding to each LED bulb, and the external data of the location of each designated user corresponding to each LED bulb.

[0044] As a preferred feasible example, the specific operation of the running data self-control of each designated user corresponding to each LED bulb includes: extracting the regular opening and closing time points of each designated user corresponding to each LED bulb in each fixed period, respectively recorded as , wherein , is the number of each designated user, is the number of designated users, , is the number of each LED bulb, is the number of LED bulbs, , is the number of each fixed period, , is the number of the regular on-off time point, is the number of the regular on-off time point, and the on-off time set of each LED bulb corresponding to each specified user is obtained according to the number is the user presence index of the position where each LED bulb corresponding to each specified user is located and the brightness of the external light , wherein .

[0045] It should be further pointed out that the on-off time set of each LED bulb corresponding to each specified user is a set composed of the regular on-off time points of each LED bulb corresponding to each specified user in each fixed period as set elements.

[0046] The on-off representative value of each LED bulb corresponding to each specified user is analyzed , wherein is the brightness threshold of the external light of the position where the LED bulb is located extracted from the cloud database, is the current time point of the th specified user corresponding to the th LED bulb in the current fixed period, , it indicates that the current on-off self-control operation of the th specified user corresponding to the th LED bulb is off, , it indicates that the current on-off self-control operation of the th specified user corresponding to the th LED bulb is on.

[0047] As a preferred feasible example, the specific operation of the operation data self-control of each LED bulb corresponding to each specified user further comprises: extracting the user activity mode of the position where each LED bulb corresponding to each specified user is located, and matching it with the recommended brightness value and the recommended color temperature value corresponding to each user activity mode stored in the cloud database, respectively, to obtain the recommended brightness value and the recommended color temperature value corresponding to the user activity mode of the position where each LED bulb corresponding to each specified user is located.

[0048] Each preferred brightness value of each LED bulb corresponding to each specified user is extracted, which is compared with the recommended brightness value corresponding to the user activity mode of the position where each LED bulb corresponding to each specified user is located, respectively, to obtain the difference between each preferred brightness value of each LED bulb corresponding to each specified user and the recommended brightness value corresponding to the user activity mode, and the preferred brightness value of each LED bulb corresponding to each specified user with the smallest difference from the recommended brightness value corresponding to the user activity mode is selected as the current brightness value of each LED bulb corresponding to each specified user.

[0049] The current color temperature value of each LED bulb corresponding to each specified user can be obtained in the same way.

[0050] The current light self-control operation of each LED bulb corresponding to each specified user is recorded as adjusting the brightness value and color temperature value of each LED bulb corresponding to each specified user to the current brightness value and current color temperature value.

[0051] The present application performs operation data self-control of each LED bulb corresponding to each specified user based on the operation parameter preference and operation schedule of each LED bulb corresponding to each specified user and the external data of the location where each LED bulb corresponding to each specified user is located, which helps to provide a more comfortable and personalized lighting environment for users, avoid unnecessary lighting waste, improve the overall efficiency of the lighting system, effectively reduce energy consumption, help to reduce electricity bills, save costs for users, and prolong the service life of LED bulbs.

[0052] The state data acquisition module is configured to acquire current working state data and historical working state data of each LED bulb corresponding to each specified user.

[0053] As a preferred feasible example, the current working state data of each LED bulb corresponding to each specified user includes an on-off state representative value, a brightness value, and a color temperature value.

[0054] It needs to be further explained that the on-off state representative value, brightness value, and color temperature value are used as the current working state data of each LED bulb corresponding to each specified user because: (1) The on-off state representative value can directly reflect the current working state of the LED bulb, i.e., whether the bulb is in an on or off state. This is the basic information to understand the working state of the bulb.

[0055] (2) The brightness value is an important indicator to measure the lighting effect of the LED bulb. According to the lighting needs of the user, the brightness value of the bulb can be adjusted to achieve the best lighting effect.

[0056] (3) The color temperature value can affect the atmosphere of the lighting environment. By adjusting the color temperature value, different lighting atmospheres such as warmth, comfort, brightness, etc. can be created to meet the different needs of the user.

[0057] It needs to be further explained that the specific acquisition method of the on-off state representative value, brightness value, and color temperature value of each LED bulb corresponding to each specified user is to directly extract the on-off state representative value, brightness value, and color temperature value of each LED bulb corresponding to each specified user from the cloud server corresponding to each LED bulb.

[0058] It should be noted that if a certain LED bulb corresponding to a specified user is in the on state, the switch state representative value of the specified user corresponding to the LED bulb is 1; if a certain LED bulb corresponding to a specified user is in the off state, the switch state representative value of the specified user corresponding to the LED bulb is 0.

[0059] The historical working status data of each LED bulb corresponding to each designated user includes the energy consumption per unit time in each start-up time period.

[0060] It should be further explained that the reason for using the energy consumption per unit time during each power-on time period as the historical working status data of each LED bulb corresponding to each designated user is to intuitively understand the energy-saving effect of the bulb, thereby facilitating the discovery of problems in the lighting system, such as bulb aging, circuit failure, etc., and helping to timely upgrade and maintain lighting equipment, thereby improving system stability and energy efficiency.

[0061] It needs to be further explained that the specific method of obtaining the unit time energy consumption of each LED bulb corresponding to each designated user during each turn-on time period is: directly extracting the unit time energy consumption of each LED bulb corresponding to each designated user during each turn-on time period from the cloud service end of each LED bulb corresponding to each designated user.

[0062] The status data analysis module is used to analyze the abnormal working status and working status change trend coefficient of each LED bulb corresponding to each designated user, and store the working status change trend coefficient of each LED bulb corresponding to each designated user in the cloud database.

[0063] As a preferred feasibility example, the specific analysis method of the abnormal working state of each LED bulb corresponding to each designated user is as follows: extract the representative value of the switch state, brightness value and color temperature value of each LED bulb corresponding to each designated user, and record them as ,in , analyze the abnormal working status evaluation indicators of each LED bulb corresponding to each designated user ,in The first The specified user corresponds to The reference brightness value and reference color temperature value of each LED bulb, They are the allowable difference between the set brightness value and the reference brightness value, and the allowable difference between the color temperature value and the reference color temperature value.

[0064] It needs to be further explained that the Indicates the The specified user corresponds to The switch state of the LED bulb is off, Indicates the the on-off state of the i-th LED bulb is turned on. the on-off state of the i-th LED bulb is turned on.

[0065] a specific example, , respectively, means that a one percent deviation is allowed between the brightness value and the reference brightness value and between the color temperature value and the reference color temperature value.

[0066] The working state abnormality evaluation index of each LED bulb corresponding to each designated user is compared with the preset working state abnormality evaluation index threshold value. If the working state abnormality evaluation index of a certain LED bulb corresponding to a certain designated user is greater than the working state abnormality evaluation index threshold value, the working state abnormality of the LED bulb corresponding to the designated user is recorded as existing abnormality, otherwise, the working state abnormality of the LED bulb corresponding to the designated user is recorded as non-abnormality.

[0067] As a preferred feasibility example, the specific analysis method of the working state change trend coefficient of each LED bulb corresponding to each designated user is to extract the unit time energy consumption of each opening time period of each LED bulb corresponding to each designated user , wherein , is the number of each opening time period, is the number of opening time periods, and the working state change trend coefficient of each LED bulb corresponding to each designated user is analyzed , wherein are the unit time energy consumption of the i-th LED bulb corresponding to the i-th designated user in the j-th and first opening time period, respectively, is the number of each opening time period, is the number of opening time periods, and the working state change trend coefficient of each LED bulb corresponding to each designated user is analyzed is the set permitted unit time energy consumption difference.

[0068] The bulb abnormality management module is used to perform abnormality reminding and bulb maintenance and replacement reminding of each LED bulb corresponding to each designated user based on the working state abnormality and the working state change trend coefficient of each LED bulb corresponding to each designated user.

[0069] As a preferred feasibility example, the specific operation of the abnormality reminding of each LED bulb corresponding to each designated user is to extract the working state abnormality of each LED bulb corresponding to each designated user. If it is abnormal, each LED bulb corresponding to each designated user is automatically powered off, and the corresponding number is sent to the user end through the APP.

[0070] ​As a preferred feasible example, the specific operation of the bulb maintenance and replacement reminder of the LED bulb corresponding to each designated user is that the working state change trend coefficient of each analysis of the LED bulb corresponding to each designated user is extracted from the cloud database, the working state change reason is analyzed, if it is normal attenuation of working life length, the corresponding number of the LED bulb corresponding to each designated user is sent to the user end through the APP, and the user is reminded to maintain or replace, if it is abnormal caused by failure, power off immediately, and the corresponding number of the LED bulb corresponding to each designated user is sent to the user end through the APP, and the user is reminded to maintain or replace.

[0071] It needs to be further explained that the specific analysis of the working state change reason of the LED bulb corresponding to each designated user is that the working state change trend coefficient of each analysis of the LED bulb corresponding to each designated user is compared and analyzed, if the working state change trend coefficient of the LED bulb corresponding to the designated user is stable change, the working state change reason of the LED bulb corresponding to the designated user is recorded as normal attenuation of working life length, if the working state change trend coefficient of the LED bulb corresponding to the designated user is sudden change, the working state change reason of the LED bulb corresponding to the designated user is recorded as abnormal caused by failure.

[0072] It needs to be further explained that the bulb maintenance and replacement processing flow chart is as shown in Figure 3

[0073] The cloud database is used for storing the external light brightness threshold of the position of the LED bulb, storing the recommended brightness value and the recommended color temperature value corresponding to each user activity mode, storing the reference brightness value and the reference color temperature value corresponding to each LED bulb of each designated user, and storing the working state change trend coefficient of each analysis of each LED bulb of each designated user.

[0074] The application helps to timely early warning of each LED bulb used by the user, reduces the failure loss, is also favorable for ensuring that the LED bulb always maintains good working state, provides stable and high quality lighting, guarantees the lighting demand and experience of the user, and improves the convenience and comfort of the user.

[0075] The above content is only an example and description of the concept of the application, and those skilled in the art can make various modifications or supplements or adopt similar ways to replace the described specific embodiments, as long as the concept of the application is not deviated or the scope defined by the application is not exceeded, which should belong to the protection scope of the application.​

Claims

1. Cloud-based LED bulb management system, featuring: include: a data acquisition module, configured to record each user who purchases a target LED bulb as a designated user, record each target LED bulb installed indoors by each designated user as an LED bulb corresponding to each designated user, and acquire operating data of each LED bulb corresponding to each designated user for each cycle within a detection period; Data analysis module, used to analyze the operating parameter preferences and operating schedules of each designated user for each LED bulb; An external data acquisition module is used to obtain external data of the location of each LED bulb corresponding to each designated user; A bulb self-control management module for self-controlling the operating data of each LED bulb corresponding to each designated user based on the operating parameter preferences and operating schedule of each LED bulb corresponding to each designated user and external data on the location of each LED bulb corresponding to each designated user; A status data acquisition module is used to obtain the current working status data and historical working status data of each LED bulb corresponding to each designated user; A status data analysis module is used to analyze the abnormal working status and working status change trend coefficient of each LED bulb corresponding to each designated user, and store the working status change trend coefficient of each LED bulb corresponding to each designated user in a cloud database; The bulb abnormality management module is used to provide abnormality reminders and bulb maintenance and replacement reminders for each designated user's LED bulb based on the abnormal working status and working status change trend coefficient of each designated user's LED bulb; A cloud database is used to store the external light brightness threshold value of the LED bulb's location, store the recommended brightness value and recommended color temperature value corresponding to each user's activity mode, store the reference brightness value and reference color temperature value of each LED bulb corresponding to each designated user, and store the working state change trend coefficient of each analyzed LED bulb corresponding to each designated user; The specific analysis method of the working state change trend coefficient of each LED bulb corresponding to each designated user is as follows: Extract the energy consumption per unit time of each LED bulb corresponding to each specified user during each opening time period ,in , is the number of each opening time period, The number of times the time period is turned on is used to analyze the trend coefficient of the working status of each LED bulb corresponding to each designated user. ,in Respectively The specified user corresponds to LED bulb Energy consumption per unit time during the first and second opening periods, It is the set permitted energy consumption difference per unit time.

2. The cloud-based LED bulb management system according to claim 1, characterized in that: The operating data of each LED bulb corresponding to each designated user in each cycle during the detection time period includes each opening and closing time point and the brightness value and color temperature value of each period within each opening period; The external data of the location of each designated user corresponding to each LED bulb includes a user presence index, a user activity pattern, and external light brightness; The current working state data of each LED bulb corresponding to each designated user includes a switch state representative value, a brightness value, and a color temperature value; The historical working status data of each LED bulb corresponding to each designated user includes the energy consumption per unit time in each start-up time period.

3. The cloud-based LED bulb management system according to claim 2, characterized in that: The specific analysis method of the operating parameter preferences of each designated user corresponding to each LED bulb is as follows: Extract the brightness value and color temperature value of each LED bulb corresponding to each designated user in each turn-on period of each cycle within the detection time period, and obtain the brightness value and color temperature value of each LED bulb corresponding to each designated user in each turn-on period of each same cycle within the detection time period. Based on this, determine the number of time periods corresponding to each brightness value and the number of time periods corresponding to each color temperature value for each LED bulb in each same cycle within the detection time period for each designated user. Compare them with the minimum number of time periods corresponding to the operating parameter preferences extracted from the cloud database, and screen out the brightness values ​​of each LED bulb in each same cycle within the detection time period for each designated user whose number of time periods corresponding to the brightness value is greater than or equal to the minimum number of time periods corresponding to the operating parameter preferences, and the color temperature values ​​of each LED bulb in each same cycle within the detection time period for each designated user whose number of time periods corresponding to the color temperature value is greater than or equal to the minimum number of time periods corresponding to the operating parameter preferences. Statistically obtain the preferred brightness values ​​and preferred color temperature values ​​of each LED bulb corresponding to each designated user, and use them as the operating parameter preferences of each LED bulb corresponding to each designated user.

4. The cloud-based LED bulb management system according to claim 3, characterized in that: The specific analysis method of the operating schedule of each LED bulb corresponding to each designated user is as follows: Extracting each turn-on time point of each LED bulb corresponding to each designated user in each cycle within the detection time period, determining each turn-on time point of each LED bulb corresponding to each designated user in each same cycle within the detection time period, performing a pairwise subtraction to obtain the difference between each turn-on time point of each LED bulb corresponding to each designated user in each same cycle within the detection time period and other turn-on time points, screening each turn-on time point of each LED bulb corresponding to each designated user in each same cycle within the detection time period whose difference with other turn-on time points is less than a set difference range, and using it as each regular turn-on time point of each LED bulb corresponding to each designated user in each same cycle, further performing an averaging process on the same time point to obtain each regular turn-on time point of each LED bulb corresponding to each designated user in each fixed cycle; Extract the shut-off time points of each LED bulb corresponding to each designated user in each cycle within the detection time period. Similarly, the regular shut-off time points of each LED bulb corresponding to each designated user in each fixed cycle can be obtained. Furthermore, the regular on and off time points of each LED bulb corresponding to each designated user in each fixed period are collectively referred to as the operating schedule of each LED bulb corresponding to each designated user.

5. The cloud-based LED bulb management system according to claim 4, characterized in that: The specific operations of the self-control of the operating data of each LED bulb corresponding to each designated user include: Extract the regular on and off time points of each LED bulb corresponding to each specified user in each fixed period and record them as ,in , The number of each designated user, is the number of specified users, , is the number of each LED bulb, is the number of LED bulbs, , is the number of each fixed period, , The number of each regular opening and closing time point, is the number of regular on / off time points, and the on / off time set of each LED bulb corresponding to each designated user is obtained based on this. , extract the user presence index of each designated user corresponding to the location of each LED bulb and external light brightness ,in ; Analyze the representative switch value of each LED bulb corresponding to each designated user ,in is the external light brightness threshold of the LED bulb’s location extracted from the cloud database, For the The specified user corresponds to At the current time point of the current fixed cycle, When The specified user corresponds to The current self-control operation of the switch of the LED bulb is off. When The specified user corresponds to The current self-control operation of the switch of the LED bulb is turned on.

6. The cloud-based LED bulb management system according to claim 5, characterized in that: The specific operations of the self-control of the operating data of each LED bulb corresponding to each designated user also include: Extracting the user activity pattern of each designated user corresponding to the location of each LED bulb, and matching it with the recommended brightness value and recommended color temperature value corresponding to each user activity pattern stored in the cloud database, to obtain the recommended brightness value and recommended color temperature value corresponding to the user activity pattern of each designated user corresponding to the location of each LED bulb; Extracting the preferred brightness values ​​of each LED bulb corresponding to each designated user, comparing them with the recommended brightness values ​​corresponding to the user activity patterns at the locations of the LED bulbs corresponding to each designated user, and obtaining the differences between the preferred brightness values ​​of each LED bulb corresponding to each designated user and the recommended brightness values ​​corresponding to the user activity patterns. Filtering out the preferred brightness values ​​of each LED bulb corresponding to each designated user with the smallest difference with the recommended brightness values ​​corresponding to the user activity patterns, and using them as the current brightness values ​​of each LED bulb corresponding to each designated user; Extract the preferred color temperature values ​​of each LED bulb corresponding to each specified user. Similarly, obtain the current color temperature value of each LED bulb corresponding to each specified user. The current light self-control operation of each LED bulb corresponding to each designated user is recorded as adjusting the brightness value and color temperature value of each LED bulb corresponding to each designated user to the current brightness value and the current color temperature value.

7. The cloud-based LED bulb management system according to claim 5, characterized in that: The specific analysis method for abnormal working status of each LED bulb corresponding to each designated user is as follows: Extract the representative value of the switch state, brightness value and color temperature value of each LED bulb corresponding to each specified user, and record them as ,in , analyze the abnormal working status evaluation indicators of each LED bulb corresponding to each designated user ,in The first The specified user corresponds to The reference brightness value and reference color temperature value of each LED bulb, They are the permissible difference between the set brightness value and the reference brightness value, and the permissible difference between the color temperature value and the reference color temperature value; The working state abnormality evaluation index of each LED bulb corresponding to each designated user is compared with the preset working state abnormality evaluation index threshold. If the working state abnormality evaluation index of a LED bulb of a designated user is greater than the working state abnormality evaluation index threshold, the working state abnormality of the LED bulb of the designated user is recorded as abnormal. Otherwise, the working state abnormality of the LED bulb of the designated user is recorded as non-abnormal.

8. The cloud-based LED bulb management system according to claim 7, characterized in that: The specific operation of the abnormal reminder of each LED bulb corresponding to each designated user is: extracting the abnormal working status of each LED bulb corresponding to each designated user, and if there is an abnormality, automatically cutting off the power of each LED bulb corresponding to each designated user, and sending its corresponding number to the user end through the APP.

9. The cloud-based LED bulb management system according to claim 8, characterized in that: The specific operation of the bulb maintenance and replacement reminder for each LED bulb corresponding to each designated user is: extracting the working status change trend coefficient of each analysis of each LED bulb corresponding to each designated user from the cloud database, analyzing the reason for the change in its working status, and if it is the normal attenuation of the working life, sending the corresponding number of each LED bulb corresponding to each designated user to the user end through the APP, and reminding the user to perform maintenance or replacement; if it is an abnormality caused by a fault, immediately cut off the power, and send the corresponding number of each LED bulb corresponding to each designated user to the user end through the APP, reminding the user to perform maintenance or replacement.

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