LED bulb management system based on cloud service

Abstract

The invention belongs to the technical field of LED bulb management, and relates to an LED bulb management system based on cloud service. According to the invention, through the operation data self-control of each LED bulb corresponding to each specified user, a more comfortable and personalized lighting environment can be provided for the user, unnecessary lighting waste is avoided, the overall efficiency of the lighting system is improved, the energy consumption is effectively reduced, the electric charge expenditure is reduced, and the user experience is improved. According to the method, the cost is saved for users, the service life of the LED bulbs is prolonged, the LED bulbs used by the users can be warned in time through abnormity reminding and bulb maintenance and replacement reminding of the LED bulbs of the specified users, fault loss is reduced, it is ensured that the LED bulbs are always kept in a good working state, stable and high-quality illumination is provided, and the service life of the LED bulbs is prolonged. The lighting requirement and experience of the user are guaranteed, and the convenience and comfort of the user are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of LED bulb management and relates to an LED bulb management system based on cloud services. Background Art

[0002] With the continuous progress of LED lighting technology, LED bulbs have gradually replaced traditional incandescent lamps and fluorescent lamps with many advantages such as energy conservation, long lifespan, and strong adjustability, becoming the mainstream lighting source. On the basis of meeting the basic lighting function, people's demand for intelligent control of lighting is increasing day by day. They hope to be able to more conveniently and flexibly control the brightness, color, switch state, etc. of the bulbs to adapt to different living scenarios and create diverse atmospheres. Therefore, an LED bulb management system based on a cloud service platform has very important significance and functions.

[0003] In the prior art, there are also some related solutions for intelligent control of LED bulbs. For example, in an invention patent application for an Internet of Things lithium battery storage and control function solar LED street lamp system with Chinese patent publication number CN106524052A, the detection device is connected to the solar LED street lamp, the data acquisition device is connected to the detection device, the data transmission module is connected to the data acquisition device, the voltage detection module and the current and power detection module are both connected to the lithium battery pack, and the lithium battery pack is respectively connected to the solar LED street lamp and the solar panel. This Internet of Things management solar street lamp remote control setting system has a simple structure and convenient operation. The set central control system can set a fixed time to control the switch of the solar LED street lamp without manual switch control. For the monitoring of the switch state, fault state, etc. of the street lamp, it can be monitored through the detection device without manual inspection. The set controller can reasonably and efficiently allocate the electrical energy usage of the lithium battery pack to avoid shortening the lifespan of the lithium battery pack due to improper charging and discharging.

[0004] Although the above solution proposes some solutions for intelligent control of LED bulbs, there are still certain limitations: on the one hand, the existing solution mainly controls the switch of the solar LED street lamp by setting a fixed time and reasonably and efficiently allocates the electrical energy usage of the lithium battery pack without manual switch control, and also avoids shortening the lifespan of the lithium battery pack due to improper charging and discharging. However, the existing solution lacks detection and analysis based on user preferences and work and rest schedules, so it cannot provide a more comfortable and personalized lighting environment for users, nor can it analyze turning the lights on and off according to the light brightness in the environment, thus unable to avoid unnecessary lighting waste and improve the overall efficiency of the lighting system.

[0005] On the other hand, existing solutions also neglect to detect and analyze the working status of users' LED bulbs, thus being unable to understand the abnormal conditions and the working status change trend coefficients of users' LED bulbs. Furthermore, it is impossible to give users timely reminders of LED bulb abnormalities and maintenance replacements, which is not conducive to reducing fault losses, nor to ensuring that LED bulbs always maintain a good working status, providing stable and high-quality lighting, and guaranteeing users' lighting needs and experiences. Summary of the Invention

[0006] In view of this, to solve the problems raised in the above-mentioned background technology, a cloud service-based LED bulb management system is proposed.

[0007] The object of the present invention can be achieved through the following technical solutions: The present invention provides a cloud service-based LED bulb management system, including: a data acquisition module, a data analysis module, an external data acquisition module, a bulb self-control management module, a status data acquisition module, a status 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 the target LED bulbs as each designated user, and record each target LED bulb installed indoors by each designated user as each LED bulb corresponding to each designated user, and acquire the operation data of each cycle of each LED bulb corresponding to each designated user within the detection time period.

[0009] The data analysis module is used to analyze the operation parameter preferences and operation work and rest rules 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 where each LED bulb corresponding to each designated user is located.

[0011] The bulb self-control management module is used to perform self-control of the operation data of each LED bulb corresponding to each designated user based on the operation parameter preferences and operation work and rest rules of each LED bulb corresponding to each designated user and the external data of the location where each LED bulb corresponding to each designated user is located.

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

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

[0014] The bulb anomaly management module is used to perform anomaly reminders and bulb maintenance and replacement reminders for each LED bulb corresponding to each designated user based on the abnormal working conditions and the working condition change trend coefficients of each LED bulb corresponding to each designated user.

[0015] The cloud database is used to store the external light brightness thresholds of the locations where the LED bulbs are located, store the recommended brightness values and recommended color temperature values corresponding to each user activity mode, store the reference brightness values and reference color temperature values of each LED bulb corresponding to each designated user, and store the working condition change trend coefficients of each analysis of each LED bulb corresponding to each designated user.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. By performing self-control of the operation data of each LED bulb corresponding to each designated user based on the operation parameter preferences and operation work and rest rules of each LED bulb corresponding to each designated user and the external data of the locations where each LED bulb corresponding to each designated user is located, the present invention 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 reduce electricity bills, save costs for users, and extend the service life of LED bulbs.

[0017] 2. By performing anomaly reminders and bulb maintenance and replacement reminders for each LED bulb corresponding to each designated user based on the abnormal working conditions and the working condition change trend coefficients of each LED bulb corresponding to each designated user, the present invention helps to give timely warnings to each LED bulb used by users, reduce fault losses, and is also beneficial to ensuring that the LED bulbs always maintain a good working state, providing stable and high-quality lighting, guaranteeing the lighting needs and experiences of users, and improving the convenience and comfort of users. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention.

[0020] Figure 2 It is a schematic diagram of the implementation process of the module of the present invention.

[0021] Figure 3 It is a flow chart of the bulb maintenance and replacement process of the present invention. Detailed Embodiments

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Please refer to Figure 1 As shown, the present invention provides an LED bulb management system based on cloud services, 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 status data acquisition module, a status data analysis module, a bulb anomaly management module, and a cloud database. Among them, the connection method between the modules is as follows: the data acquisition module is connected to the data analysis module, the data analysis module is connected to the external data acquisition module, the external data acquisition module is connected to the bulb self-control management module, the status data acquisition module is connected to the status data analysis module, the status data analysis module is connected to the bulb anomaly management module, and the cloud database is respectively connected to the bulb self-control management module and the status data analysis module.

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

[0025] It should be further noted that the schematic diagram of the module implementation process is as Figure 2 shown.

[0026] As a preferred feasible example, the operation data of each cycle of each LED bulb corresponding to each designated user within the detection time period includes each on and off time point, and the brightness value and color temperature value of each time period within each on period.

[0027] It should be further noted that the reason for taking each on and off time point, and the brightness value and color temperature value of each time period within each on period as the operation data of each cycle of each LED bulb corresponding to each designated user within the detection time period is as follows: (1) Recording the on and off time points of the LED bulb can reflect its usage frequency and usage duration, and further help to understand the user's work and rest pattern, so as to provide a more personalized lighting solution 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, so as to provide a more personalized lighting solution for the user and improve the user experience.

[0029] It should be further noted that the specific method for obtaining the opening and closing time points of each cycle, as well as the brightness values and color temperature values of each period within each opening period, for each LED bulb corresponding to each designated user during the detection period is as follows: directly extract from the cloud server corresponding to each LED bulb of each designated user the opening and closing time points of each cycle, as well as the brightness values and color temperature values of each period within each opening period, during the detection period.

[0030] A data analysis module for analyzing the operation parameter preferences and operation schedule rules of each LED bulb corresponding to each designated user.

[0031] As a preferred feasible example, the specific analysis method for the operation parameter preferences of each LED bulb corresponding to each designated user includes: extracting the brightness values and color temperature values of each period within each opening period of each cycle during the detection period for each LED bulb corresponding to each designated user, obtaining from them the brightness values and color temperature values of each period within each opening period of each same cycle during the detection period for each LED bulb corresponding to each designated user, determining accordingly the number of periods corresponding to each brightness value and the number of periods corresponding to each color temperature value within each same cycle during the detection period for each LED bulb corresponding to each designated user, comparing them respectively with the minimum number of periods corresponding to the operation parameter preferences extracted from the cloud database, screening out the brightness values within each same cycle during the detection period for each LED bulb corresponding to each designated user where the number of periods is greater than or equal to the minimum number of periods corresponding to the operation parameter preferences and the color temperature values within each same cycle during the detection period for each LED bulb corresponding to each designated user where the number of periods is greater than or equal to the minimum number of periods corresponding to the operation parameter preferences, and statistically obtaining the preferred brightness values and preferred color temperature values for each LED bulb corresponding to each designated user, and taking them as the operation parameter preferences of each LED bulb corresponding to each designated user.

[0032] In a specific example, the detection period is three weeks, and the cycle within the detection period is 24 hours, that is, each cycle within the detection period is within 24 hours on Monday, within 24 hours on Tuesday... within 24 hours on Sunday. Each same cycle within the detection period is within 24 hours on each Monday, within 24 hours on each Tuesday... within 24 hours on each Sunday within the three weeks. Each fixed cycle is within 24 hours on Monday, within 24 hours on Tuesday... within 24 hours on Sunday.

[0033] As a preferred feasible example, the operating schedules of the LED bulbs corresponding to each designated user include the following specific analysis methods: Extract the opening time points of each cycle of each LED bulb corresponding to each designated user within the detection time period, determine the opening time points of each cycle of each LED bulb corresponding to each designated user within the detection time period, take the difference between them pairwise, and obtain the differences between the opening time points of each cycle of each LED bulb corresponding to each designated user within the detection time period and other opening time points. Screen the opening time points of each cycle of each LED bulb corresponding to each designated user within the detection time period whose differences from other opening time points are within the set difference range, and use them as the regular opening time points of each cycle of each LED bulb corresponding to each designated user. Further, perform an averaging process on them to obtain the regular opening time points of each cycle of each LED bulb corresponding to each designated user at each fixed cycle.

[0034] Similarly, by extracting the closing time points of each cycle of each LED bulb corresponding to each designated user within the detection time period, the regular closing time points of each cycle of each LED bulb corresponding to each designated user within the detection time period can be obtained.

[0035] Furthermore, the regular opening and closing time points of each cycle of each LED bulb corresponding to each designated user within the detection time period are collectively referred to as the operating schedules of the LED bulbs corresponding to each designated user.

[0036] The external data acquisition module is used to acquire the external data of the locations of the LED bulbs corresponding to each designated user.

[0037] As a preferred feasible example, the external data of the locations of the LED bulbs corresponding to each designated user includes the user presence index, the user activity pattern, and the external light brightness.

[0038] It should be further noted that the reasons for taking the user presence index, the user activity pattern, and the external light brightness as the external data of the locations of the LED bulbs corresponding to each designated user are as follows: (1) The user presence index reflects the probability or frequency of the user's appearance at a specific time and location. When the user is absent, the brightness of the LED bulb can be reduced or the bulb can be turned off, thereby achieving an energy-saving effect and avoiding energy waste and safety hazards.

[0039] (2) The user activity pattern describes the behavior or activity pattern 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 requirements in different activity scenarios.

[0040] (3) The brightness of external light refers to the natural light at the location where the LED bulb is located or the brightness of the surrounding environment. According to the brightness of external light, the brightness of the LED bulb can be adjusted to keep the indoor light coordinated with the external light, avoiding discomfort to vision 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 explained that the specific acquisition methods of the user existence index, user activity pattern, and external light brightness corresponding to each designated user at the location of each LED bulb are as follows: Use the deployed intelligent camera to take pictures of the locations corresponding to each designated user at each LED bulb to obtain pictures of the locations corresponding to each designated user at each LED bulb. Further analyze using image recognition technology. If there is a user at the location corresponding to a certain designated user at a certain LED bulb, record the user existence index of the location corresponding to this designated user at this LED bulb as 1; otherwise, record the user existence index of the location corresponding to this designated user at this LED bulb as 0. When there is a user at the location corresponding to a certain designated user at a certain LED bulb, match the user image in the picture of the location corresponding to this designated user at this LED bulb with the user images corresponding to each user activity pattern stored in the cloud database to obtain the user activity pattern of the location corresponding to this designated user at this LED bulb, and then obtain the user activity patterns corresponding to each designated user at the locations of each LED bulb.

[0042] Use the deployed photosensitive sensor to directly detect and obtain the external light brightness corresponding to each designated user at the location of each LED bulb.

[0043] The bulb self-control management module is used to perform self-control of the operation data of each LED bulb corresponding to each designated user based on the operation parameter preferences and operation schedules of each LED bulb corresponding to each designated user, as well as the external data corresponding to the locations of each LED bulb corresponding to each designated user.

[0044] As a preferred feasible example, the specific operations of the self-control of the operation 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 designated user in each fixed cycle, and record them as where 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 cycle. , is the number of the on / off time points of each regular pattern, is the number of on / off time points of the regular pattern. Based on this, the on / off time set of each specified user corresponding to each LED bulb is obtained. , and extract the user presence index of the location of each specified user corresponding to each LED bulb. and the external light brightness , where .

[0045] It should be further noted that the on / off time set of each specified user corresponding to each LED bulb is a set composed of the on / off time points of each regular pattern of each specified user corresponding to each LED bulb in each fixed cycle as set elements.

[0046] Analyze the on / off representative values of each specified user corresponding to each LED bulb. , where is the external light brightness threshold of the location of the LED bulb extracted from the cloud database, is the th specified user corresponding to the th LED bulb at the current time point in the current fixed cycle. When, it indicates that the current on / off self-control operation of the th specified user corresponding to the th LED bulb is off. When, 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 on / off self-control of the operation data of each specified user corresponding to each LED bulb further includes: extracting the user activity patterns of the locations of each specified user corresponding to each LED bulb, and matching them with the recommended brightness values and recommended color temperature values corresponding to each user activity pattern stored in the cloud database to obtain the recommended brightness values and recommended color temperature values corresponding to the user activity patterns of the locations of each specified user corresponding to each LED bulb.

[0048] Extract the preferred brightness values of each specified user corresponding to each LED bulb, compare them with the recommended brightness values corresponding to the user activity patterns of the locations of each specified user corresponding to each LED bulb respectively, obtain the differences between the preferred brightness values of each specified user corresponding to each LED bulb and the recommended brightness values corresponding to the user activity patterns, and screen out the preferred brightness values of each specified user corresponding to each LED bulb with the smallest differences from the recommended brightness values corresponding to the user activity patterns, and use them as the current brightness values of each specified user corresponding to each LED bulb.

[0049] Extract the preferred color temperature values of each LED bulb corresponding to each specified user. Similarly, the current color temperature values of each LED bulb corresponding to each specified user can be obtained.

[0050] Then, record the current lighting self-control operation of each LED bulb corresponding to each specified user 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 invention performs self-control of the operation data of each LED bulb corresponding to each specified user based on the operation parameter preferences and operation schedules of each LED bulb corresponding to each specified user, as well as the external data of the location where each LED bulb corresponding to each specified user is located. This 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, contribute to reducing electricity bills, save costs for users, and extend the service life of LED bulbs.

[0052] A status data acquisition module is used to acquire the current working status data and historical working status data of each LED bulb corresponding to each specified user.

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

[0054] It should be further explained that the reasons for using the switch status representative value, brightness value, and color temperature value as the current working status data of each LED bulb corresponding to each specified user are as follows: (1) The switch status representative value can directly reflect the current working status of the LED bulb, that is, whether the bulb is in the on or off state. This is the basic information for understanding the working status of the bulb.

[0055] (2) The brightness value is an important indicator for measuring the lighting effect of the LED bulb. According to the lighting needs of users, 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 warm, comfortable, and bright, can be created to meet the different needs of users.

[0057] It should be further explained that the specific acquisition methods for the switch status representative value, brightness value, and color temperature value of each LED bulb corresponding to each specified user are: directly extract the switch status representative value, brightness value, and color temperature value of each LED bulb corresponding to each specified user from the cloud server of each LED bulb corresponding to each specified user.

[0058] It should be noted that when a specified user corresponds to an LED bulb in the on state, the representative value of the on / off state of the specified user corresponding to the LED bulb is 1. When a specified user corresponds to an LED bulb in the off state, the representative value of the on / off state of the specified user corresponding to the LED bulb is 0.

[0059] The historical working state data of each specified user corresponding to each LED bulb includes the energy consumption per unit time during each on period.

[0060] It should be further noted that the reason for taking the energy consumption per unit time during each on period as the historical working state data of each specified user corresponding to each LED bulb is as follows: to intuitively understand the energy-saving effect of the bulb, which is conducive to discovering problems existing in the lighting system, such as bulb aging, circuit faults, etc., and helps to upgrade and maintain lighting equipment in a timely manner, improving the stability and energy efficiency of the system.

[0061] It should be further noted that the specific method for obtaining the energy consumption per unit time during each on period of each specified user corresponding to each LED bulb is as follows: directly extract the energy consumption per unit time during each on period of each specified user corresponding to each LED bulb from the cloud server of each specified user corresponding to each LED bulb.

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

[0063] As a preferred feasible example, the specific method for analyzing the abnormal working conditions of each specified user corresponding to each LED bulb is as follows: extract the representative value of the on / off state, the brightness value, and the color temperature value of each specified user corresponding to each LED bulb, and record them as , where , analyze the abnormal working condition evaluation index of each specified user corresponding to each LED bulb , where are respectively the reference brightness value and the reference color temperature value of the th specified user corresponding to the th LED bulb extracted from the cloud database, are respectively the permitted difference between the set brightness value and the reference brightness value and the permitted difference between the color temperature value and the reference color temperature value.

[0064] It should be further noted that the represents that the on / off state of the th specified user corresponding to the th LED bulb is off, and the represents the The switch state of the LED bulbs corresponding to a specified user is on.

[0065] A specific example , with units of dimensionless and Kelvin respectively, means that a deviation of up to one percent is allowed both between the brightness value and the reference brightness value and between the color temperature value and the reference color temperature value.

[0066] Compare the working state abnormality evaluation indexes of each specified user corresponding to each LED bulb with the preset working state abnormality evaluation index thresholds respectively. If the working state abnormality evaluation index of a certain LED bulb of a certain specified user is greater than the working state abnormality evaluation index threshold, record the working state abnormality of the LED bulb of the specified user as existing abnormality; otherwise, record the working state abnormality of the LED bulb of the specified user as non - existing abnormality.

[0067] As a preferred feasible example, the specific analysis method of the working state change trend coefficient of each specified user corresponding to each LED bulb is: extract the energy consumption per unit time during each on - period of each specified user corresponding to each LED bulb , where is the number of each on - period, is the number of on - periods, and analyze the working state change trend coefficient of each specified user corresponding to each LED bulb , where are respectively the energy consumption per unit time during the th and the first on - periods of the LED bulbs corresponding to the specified user, and

[0068] The bulb abnormality management module is used to perform abnormality reminders and bulb maintenance and replacement reminders for each specified user corresponding to each LED bulb based on the working state abnormality conditions and the working state change trend coefficients of each specified user corresponding to each LED bulb.

[0069] As a preferred feasible example, the specific operation of the abnormality reminder for each specified user corresponding to each LED bulb is: extract the working state abnormality conditions of each specified user corresponding to each LED bulb. If it is an existing abnormality, cut off the power supply of each specified user corresponding to each LED bulb automatically and send its corresponding number to the user terminal through the APP.

[0070] As a preferred feasibility example, the specific operation of the bulb maintenance and replacement reminder for each designated user corresponding to each LED bulb is as follows: Extract the working state change trend coefficients of each analysis of each designated user corresponding to each LED bulb from the cloud database, analyze the reasons for the change in its working state. If it is a normal attenuation of the working life duration, send the corresponding numbers of each designated user corresponding to each LED bulb to the user terminal through the APP, and remind 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 numbers of each designated user corresponding to each LED bulb to the user terminal through the APP, reminding the user to perform maintenance or replacement.

[0071] It should be further noted that the specific analysis of the reasons for the change in the working state of each designated user corresponding to each LED bulb is as follows: Compare and analyze the working state change trend coefficients of each analysis of a certain designated user corresponding to a certain LED bulb. If the working state change trend coefficient of this designated user corresponding to this LED bulb shows a stable change, record the reason for the change in the working state of this designated user corresponding to this LED bulb as the normal attenuation of the working life duration. If the working state change trend coefficient of this designated user corresponding to this LED bulb shows a sudden change, record the reason for the change in the working state of this designated user corresponding to this LED bulb as an abnormality caused by a fault.

[0072] It should be further noted that the flow chart of the bulb maintenance and replacement process is as Figure 3 shown.

[0073] The cloud database is used to store the external light brightness threshold of the location where the LED bulb is located, store the recommended brightness values and recommended color temperature values corresponding to each user activity mode, store the reference brightness values and reference color temperature values of each designated user corresponding to each LED bulb, and store the working state change trend coefficients of each analysis of each designated user corresponding to each LED bulb.

[0074] Through the abnormal situation of the working state and the working state change trend coefficients of each designated user corresponding to each LED bulb, the present invention conducts abnormal reminders and bulb maintenance and replacement reminders for each designated user corresponding to each LED bulb, which helps to timely warn each LED bulb used by the user, reduce fault losses, and is also conducive to ensuring that the LED bulb always maintains a good working state, providing stable and high-quality lighting, guaranteeing the lighting needs and experience of the user, and improving the convenience and comfort of the user.

[0075] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. An LED bulb management system based on cloud services, characterized in that: Including: A data acquisition module, which records each user who purchases the target LED bulb as each designated user, and records each target LED bulb installed indoors by each designated user as each LED bulb corresponding to each designated user, and acquires the operation data of each LED bulb corresponding to each designated user in each period within the detection time period; A data analysis module, which analyzes the operation parameter preferences and operation work and rest rules of each LED bulb corresponding to each designated user; An external data acquisition module, which acquires the external data of the location where each LED bulb corresponding to each designated user is located; A bulb self-control management module, which performs self-control of the operation data of each LED bulb corresponding to each designated user based on the operation parameter preferences and operation work and rest rules of each LED bulb corresponding to each designated user and the external data of the location where each LED bulb corresponding to each designated user is located; A status data acquisition module, which acquires the current working status data and historical working status data of each LED bulb corresponding to each designated user; A status data analysis module, which analyzes the working status abnormality and working status change trend coefficient of each LED bulb corresponding to each designated user, and stores the working status change trend coefficient of each LED bulb corresponding to each designated user in the cloud database; A bulb abnormality management module, which performs abnormality reminder and bulb maintenance and replacement reminder for each LED bulb corresponding to each designated user based on the working status abnormality and working status change trend coefficient of each LED bulb corresponding to each designated user; A cloud database, which stores the external light brightness threshold of the location where the LED bulb is located, stores the recommended brightness value and recommended color temperature value corresponding to each user activity mode, stores the reference brightness value and reference color temperature value of each LED bulb corresponding to each designated user, and stores the working status change trend coefficient of each analysis of each LED bulb corresponding to each designated user.

2. The LED bulb management system based on cloud service according to claim 1, wherein: The operation data of each LED bulb corresponding to each designated user in each period within the detection time period includes each on and off time point and the brightness value and color temperature value of each time period within each on period; The external data of the location where each LED bulb corresponding to each designated user is located includes the user presence index, user activity mode, and external light brightness; The current working status data of each LED bulb corresponding to each designated user includes the switch status representative value, brightness value, and color temperature value; The historical working status data of each LED bulb corresponding to each designated user includes the energy consumption per unit time within each on period; 3. The LED bulb management system based on cloud service according to claim 2, characterized in that: The specific analysis method for the operation parameter preferences of each LED bulb corresponding to each designated user is: Extract the brightness values and color temperature values of each period within each on-time period for each LED bulb corresponding to each specified user during the detection time period. From this, obtain the brightness values and color temperature values of each period within each on-time period for each LED bulb corresponding to each specified user during the detection time period in the same cycle. Based on this, determine the number of periods corresponding to each brightness value and the number of periods corresponding to each color temperature value for each LED bulb corresponding to each specified user during the detection time period in the same cycle. Compare them respectively with the minimum number of periods corresponding to the operation parameter preferences extracted from the cloud database. Screen out the brightness values of each LED bulb corresponding to each specified user during the detection time period in the same cycle where the number of periods corresponding to the brightness value is greater than or equal to the minimum number of periods corresponding to the operation parameter preferences, and the color temperature values of each LED bulb corresponding to each specified user during the detection time period in the same cycle where the number of periods corresponding to the color temperature value is greater than or equal to the minimum number of periods corresponding to the operation parameter preferences. And perform statistics on them to obtain the preferred brightness values and preferred color temperature values of each LED bulb corresponding to each specified user, and use them as the operation parameter preferences of each LED bulb corresponding to each specified user.

4. The LED bulb management system based on cloud service according to claim 3, characterized in that: The specific analysis method for the operation and rest rules of each LED bulb corresponding to each specified user is as follows: Extract the on-time points of each period for each LED bulb corresponding to each specified user during the detection time period. Determine the on-time points of each period for each LED bulb corresponding to each specified user during the detection time period in the same cycle. Subtract them pairwise to obtain the differences between the on-time points of each period for each LED bulb corresponding to each specified user during the detection time period in the same cycle and other on-time points. Screen out the on-time points of each period for each LED bulb corresponding to each specified user during the detection time period in the same cycle where the difference from other on-time points is within the set difference range, and use them as the regular on-time points of each period for each LED bulb corresponding to each specified user in the same cycle. Further perform an averaging process on them to obtain the regular on-time points of each period for each LED bulb corresponding to each specified user in each fixed cycle; Extract the off-time points of each period for each LED bulb corresponding to each specified user during the detection time period. Similarly, the regular off-time points of each period for each LED bulb corresponding to each specified user in each fixed cycle can be obtained; Further, collectively refer to the regular on-time and off-time points of each period for each LED bulb corresponding to each specified user as the operation and rest rules of each LED bulb corresponding to each specified user.

5. The LED bulb management system based on cloud service according to claim 4, wherein: The specific operations for the self-control of the operation data of each LED bulb corresponding to each specified 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 respectively as , where , is the number of each specified 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, , is the number of each regular on and off time point, is the number of regular on and off time points. Based on this, obtain the switch time set of each specified user corresponding to each LED bulb. Extract the user existence index of the location where each specified user is corresponding to each LED bulb and the external light brightness , where ; Analyze the switch representative values of each specified user corresponding to each LED bulb , where is the external light brightness threshold of the location of the LED bulb extracted from the cloud database, is the th specified user corresponding to the th LED bulb at the current time point in the current fixed cycle, If it is, it means that the current switch self-control operation of the th specified user corresponding to the th LED bulb is off, If it is, it means that the current switch self-control operation of the th specified user corresponding to the th LED bulb is on.

6. The LED bulb management system based on cloud service according to claim 5, wherein: The specific operations for the self-control of the operation data of each LED bulb corresponding to each specified user also include: Extract the user activity patterns at the locations of each LED bulb corresponding to each specified user, and match them respectively with the recommended brightness values and recommended color temperature values of each user activity pattern stored in the cloud database to obtain the recommended brightness values and recommended color temperature values corresponding to the user activity patterns at the locations of each LED bulb corresponding to each specified user; Extract the respective preferred brightness values of each specified user for each LED bulb, compare them with the recommended brightness values corresponding to the user activity patterns at the locations of each LED bulb corresponding to each specified user, obtain the differences between the respective preferred brightness values of each specified user for each LED bulb and the recommended brightness values corresponding to the user activity patterns, and screen out the preferred brightness values of each specified user for each LED bulb with the smallest differences from the recommended brightness values corresponding to the user activity patterns, and use them as the current brightness values of each specified user for each LED bulb; Extract the respective preferred color temperature values of each specified user for each LED bulb, and similarly, the current color temperature values of each specified user for each LED bulb can be obtained; Then record the current light self-control operation of each specified user for each LED bulb as adjusting the brightness value and color temperature value of each specified user for each LED bulb to the current brightness value and current color temperature value.

7. The LED bulb management system based on cloud service according to claim 5, characterized in that: The specific analysis method for the abnormal working conditions of each specified user for each LED bulb is as follows: Extract the representative values of the on / off states, brightness values, and color temperature values of each specified user for each LED bulb, and record them respectively as , where , analyze the abnormal working state evaluation indicators of each specified user for each LED bulb , where are respectively the reference brightness value and reference color temperature value of the th specified user corresponding to the th LED bulb extracted from the cloud database, are respectively the permitted difference between the set brightness value and the reference brightness value and the permitted difference between the color temperature value and the reference color temperature value; Compare the abnormal working condition evaluation indicators of each specified user for each LED bulb with the preset abnormal working condition evaluation indicator thresholds respectively. If the abnormal working condition evaluation indicator of a certain LED bulb of a certain specified user is greater than the abnormal working condition evaluation indicator threshold, record the abnormal working condition of this LED bulb of this specified user as existing abnormality; otherwise, record the abnormal working condition of this LED bulb of this specified user as non-existing abnormality.

8. The LED bulb management system based on cloud service according to claim 7, characterized in that: The specific analysis method for the working condition change trend coefficient of each specified user for each LED bulb is as follows: Extract the energy consumption per unit time within each turn-on time period of each LED bulb corresponding to each specified user , where , is the number of each turn-on time period, is the number of turn-on time periods, and analyze the working state change trend coefficient of each LED bulb corresponding to each specified user , where are respectively the energy consumption per unit time within the th specified user's corresponding th LED bulb's th and the first turn-on time periods, is the set permitted energy consumption difference per unit time.

9. The LED bulb management system based on cloud service according to claim 8, characterized in that: The specific operation of the abnormal reminder for each specified user for each LED bulb is: Extract the abnormal working conditions of each specified user for each LED bulb. If it is an existing abnormality, automatically cut off the power of each specified user for each LED bulb, and send its corresponding number to the user terminal through the APP.

10. The LED bulb management system based on cloud service according to claim 9, wherein: The specific operation of the bulb maintenance and replacement reminder for each specified user for each LED bulb is: Extract the working condition change trend coefficients of each specified user for each LED bulb for each analysis from the cloud database, analyze the reasons for the change in its working condition. If it is the normal attenuation of the working life duration, send the corresponding number of each specified user for each LED bulb to the user terminal through the APP, and remind 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 specified user for each LED bulb to the user terminal through the APP, and remind the user to perform maintenance or replacement.

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