Intelligent conference room management system and method based on Internet of Things

Abstract

The invention discloses an intelligent conference room management system and method based on the Internet of Things, and relates to the technical field of the Internet of Things, and the system comprises an intelligent scheduling module, a parameter dynamic updating module, and an equipment cooperation module. According to the system, the intelligent scheduling module can establish a scheduling model between devices, so that the states of the devices are highly coordinated; the parameter dynamic updating module dynamically adjusts equipment operation parameters according to environment data collected in real time and optimizes resource allocation; and the equipment cooperation module provides remote management and monitoring through the cloud platform, and promotes data sharing and cross-equipment cooperation among the equipment, and the three modules complement each other, so that the conference room equipment can automatically and optimally operate in a dynamically changing environment, the energy efficiency is improved, the manpower management cost is reduced, and the system is suitable for popularization and application. And more intelligent and comfortable environment experience is provided for users in the conference room.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an intelligent conference room management system and method based on the Internet of Things. Background Art

[0002] With the rapid development of Internet of Things technology, more and more devices are interconnected through wireless communication technology to form an intelligent and networked system. Internet of Things technology is widely used in many fields such as home automation, industrial control, smart cities, etc., especially in the field of smart conference room management. The application of Internet of Things has brought great convenience. Modern conference rooms usually contain multiple devices, such as air conditioners, lights, audio, projectors and video conferencing equipment. These devices are connected to the Internet through sensors, can obtain environmental data in real time and automatically adjust according to needs. With the development of cloud computing technology, remote management, data sharing and collaboration of equipment have also become key ways to achieve intelligent management. Based on the combination of these technologies, the smart conference room management system realizes real-time monitoring of environmental data and intelligent scheduling of equipment status.

[0003] However, there are still many problems in the existing intelligent conference room management system, especially in the coordination and scheduling between devices and adaptive adjustment of the environment. Most of the existing technologies rely on simple preset rules or locally optimized scheduling methods, which makes it difficult to achieve efficient and accurate management in a complex multi-device, multi-scenario environment. In addition, most systems lack the design of intelligent scheduling models and cannot dynamically adjust the operating parameters of the equipment based on the real-time status of the equipment and environmental changes, resulting in energy waste and unstable equipment status. Specifically, the following problems are common in current technologies: First, it is impossible to comprehensively and dynamically obtain the status data of various types of equipment and establish dependencies between devices based on this; second, the existing scheduling models are mostly limited to a single device or a single scenario, and lack intelligent collaboration under multiple devices and multiple scenarios; third, most systems lack effective resource optimization algorithms, making it difficult to achieve automatic adjustment of equipment status and optimal allocation of resources. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing smart conference room management methods have the problems of being unable to collect device status data in real time, lack of effective modeling of the dependency relationship between devices, imperfect resource optimization algorithms, and how to achieve cross-device and cross-regional data sharing and collaboration through a cloud platform.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: an intelligent conference room management system based on the Internet of Things, including an intelligent scheduling module, a parameter dynamic update module, and a device collaboration module; the intelligent scheduling module is used to obtain the working status data of various types of equipment, analyze the dependencies between devices, and establish an intelligent scheduling model between devices; the parameter dynamic update module is used to dynamically update the operating parameters of the equipment based on the real-time collected conference room environment data, automatically adjust the working status of the equipment, and optimize resource allocation and conference room environment; the device collaboration module is used to realize remote management and monitoring of equipment through a cloud platform, and to carry out cross-regional and cross-device data sharing and collaboration.

[0007] As a preferred solution of the smart conference room management system based on the Internet of Things described in the present invention, wherein: the establishment of the intelligent scheduling model between devices includes obtaining real-time working status data of lighting, air conditioning, and video conferencing equipment in the conference room, coordinating the working status of the equipment, using the Markov model to model the dependency relationship between the equipment, and forming a multi-dimensional scheduling model by modeling the state transition of different equipment. The establishment of the intelligent scheduling model between devices is expressed as:

[0008]

[0009] Among them, Q ij (t state ) represents the similarity measure between device i and device j during the state transfer process, S i (t state ) represents the time step t of device i state The state at time t state is the time for the device status to change, S j (t state ) represents the time step t of device j state The state at the moment, S k (t state ) indicates that device k is at time step t sate The state at the moment, σ ij represents the standard deviation of the state difference between device i and device j, n represents the total number of devices, k represents the index of the kth device in the system, which is used to traverse all devices, σ ik Represents the standard deviation of the state difference between device i and device k.

[0010] As a preferred solution of the intelligent conference room management system based on the Internet of Things described in the present invention, wherein: the establishment of the intelligent scheduling model between devices also includes analyzing the device state difference based on the intelligent scheduling model between devices, when the device state difference is equal to 0, it means that the device is completely coordinated, and when the device state difference is equal to 1, it means that the device state is completely uncoordinated; based on the similarity measurement threshold θ Q (tstate ) to judge the coordination between devices. ij (t state )≥θ Q (t state ), the coordination between devices is high and the devices do not need to be adjusted; when Q ij (t state )<θ Q (t state ), the coordination between devices is low and adjustments need to be made between devices.

[0011] As a preferred solution of the intelligent conference room management system based on the Internet of Things described in the present invention, the dynamic updating of the operating parameters of the equipment includes dynamically adjusting the operating status of the equipment after establishing an intelligent scheduling model between the equipment, dynamically updating the operating parameters of each equipment based on the real-time collected conference room environment data, associating the current status of the equipment with the environmental variables, and calculating the power change of the equipment according to the sensitivity of different equipment to environmental changes, and constructing a dynamic power model, which is expressed as:

[0012]

[0013] Among them, P i (t power ) represents the time step t of device i power Dynamic power at time t power is the time for equipment power adjustment, P i0 is the initial power of the device, S j (t power ) represents the time step t of device j power The state at the moment, β ij (t power ) represents the dependency coefficient between device i and device j, X k (t power ) represents the environmental factor m at time step t power The value of γ im (t power ) represents the sensitivity coefficient of device i to environmental factor m, δ i (t power ) represents the adaptive adjustment factor of device i, φ ij represents the influence factor of the state difference between device u and device j on power adjustment, n represents the total number of devices, and M represents the total number of environmental factors; based on the mutual influence between devices, the distance between devices, the device type and the interaction, the dependency coefficient between device i and device j is constructed, which is expressed as:

[0014]

[0015] Among them, α ijis the inductance between device i and device j, D i Indicates the spatial position coordinates of device i, D j represents the spatial position coordinates of device j, σ ij is the standard deviation of the state difference between devices; the sensitivity coefficient of device i to environmental factor m is expressed as:

[0016]

[0017] Among them, λ im is the induction constant of device i to environmental factor m, T m is the current value of the environmental factor m, T env is the expected value of the environment, τ im is the standard deviation of the device’s sensitivity to environmental changes; the adaptive adjustment factor of device i is obtained through training with the device’s historical performance data, expressed as:

[0018]

[0019] Where, ∈ is the adjustment flexibility constant, P i0 is the initial power of the device, P max is the maximum power of the device, μ i is the adaptive adjustment index of the device.

[0020] As a preferred solution of the intelligent conference room management system based on the Internet of Things described in the present invention, wherein: the optimization of resource allocation and conference room environment includes when the temperature exceeds T env When the temperature is lower than T, the power demand of the air conditioning equipment increases, lowering the room temperature. env When the number of people in the conference room decreases, the device state enters standby or low power consumption mode. Through the state differences and environmental factors in the dynamic power model, the system dynamically adjusts the device power. When the number of people in the conference room increases, the environmental data changes with the increase in the number of people, and the power demand of the air conditioner and lighting equipment will increase accordingly. The adaptive factors in the dynamic power model enable the device to respond and automatically increase the power.

[0021] As a preferred solution of the smart conference room management system based on the Internet of Things described in the present invention, the remote management and monitoring of equipment through the cloud platform includes using the cloud platform to provide a remote monitoring function, the conference room administrator monitors the status of the equipment at a remote location, checks the operation status of the equipment in real time, and the administrator remotely controls the equipment in the conference room.

[0022] As a preferred solution of the Internet of Things-based intelligent conference room management system described in the present invention, the data sharing and collaboration include data sharing between different devices based on a cloud platform, collaborative operations between devices, and automatic allocation of device resources to each participant; the different devices include conference room control equipment, video conferencing equipment and air conditioning.

[0023] Another object of the present invention is to provide an intelligent conference room management method based on the Internet of Things, which can dynamically update the operating parameters of the equipment based on the real-time collected conference room environment data, automatically adjust the working status of the equipment, optimize resource allocation and conference room environment, and solve the problem that the current intelligent conference room management technology contains imperfect resource optimization algorithms.

[0024] As a preferred solution of the smart conference room management method based on the Internet of Things described in the present invention, it includes: obtaining the working status data of various types of equipment, analyzing the dependencies between devices, and establishing an intelligent scheduling model between devices; dynamically updating the operating parameters of the equipment based on the real-time collected conference room environment data, automatically adjusting the working status of the equipment, optimizing resource allocation and conference room environment; realizing remote management and monitoring of equipment through a cloud platform, and conducting cross-regional and cross-device data sharing and collaboration.

[0025] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of a smart conference room management method based on the Internet of Things.

[0026] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a smart conference room management method based on the Internet of Things.

[0027] Beneficial effects of the present invention: the intelligent scheduling module of the intelligent conference room management system based on the Internet of Things provided by the present invention can achieve a high degree of coordination between device states by establishing a scheduling model between devices; the parameter dynamic update module dynamically adjusts device operating parameters according to real-time collected environmental data to optimize resource allocation; and the device collaboration module provides remote management and monitoring through a cloud platform to promote data sharing and cross-device collaboration between devices. These three modules complement each other, so that conference room equipment can automatically optimize operation in a dynamically changing environment, improve energy efficiency, reduce manpower management costs, and provide conference room users with a more intelligent and comfortable environment experience. The present invention achieves better results in terms of intelligence, efficiency and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 An overall module diagram of an Internet of Things-based intelligent conference room management system provided for the first embodiment of the present invention.

[0030] Figure 2 An overall flow chart of an intelligent conference room management method based on the Internet of Things provided for the third embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0032] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides an intelligent conference room management system based on the Internet of Things, including:

[0033] Intelligent scheduling module 100, parameter dynamic update module 200, device collaboration module 300.

[0034] Furthermore, the intelligent scheduling module 100 is used to obtain the working status data of various types of equipment, analyze the dependencies between devices, and establish an intelligent scheduling model between devices; the parameter dynamic update module 200 is used to dynamically update the operating parameters of the equipment based on the real-time collected conference room environment data, automatically adjust the working status of the equipment, and optimize resource allocation and conference room environment; the device collaboration module 300 is used to realize remote management and monitoring of equipment through the cloud platform, and conduct cross-regional and cross-device data sharing and collaboration.

[0035] Furthermore, the establishment of an intelligent scheduling model between devices includes obtaining real-time working status data of lighting, air conditioning, and video conferencing equipment in the conference room, coordinating the working status of the equipment, using the Markov model to model the dependencies between the equipment, and modeling the state transition of different equipment to form a multi-dimensional scheduling model. The establishment of an intelligent scheduling model between devices is expressed as:

[0036]

[0037] Among them, Q ij (t state ) represents the similarity measure between device i and device j during the state transfer process, S i (t state ) represents the time step t of device i state The state at time t state is the time for the device status to change, S j (t state ) represents the time step t of device j state The state at the moment, S k (t state ) indicates that device k is at time step t state The state at the moment, σ ij represents the standard deviation of the state difference between device i and device j, reflecting the sensitivity of state transfer between devices, n represents the total number of devices, k represents the index of the kth device in the system, which is used to traverse all devices, σ ik Represents the standard deviation of the state difference between device i and device k.

[0038] It should be noted that establishing an intelligent scheduling model between devices also includes analyzing the differences in device states based on the intelligent scheduling model between devices. i (t state )-S j (t state )| reflects the deviation of the device status. When the device status difference is equal to 0, it means that the device is completely coordinated. When the device status difference is equal to 1, it means that the device status is completely inconsistent. Based on the similarity measurement threshold θ Q (t state ) to judge the coordination between devices. A preferred solution includes a similarity measurement threshold θ Q (t state ) is set to 0.8, when Q ij (t) state )≥θ Q (t state ), the coordination between devices is high and the devices do not need to be adjusted; when Q ij (t state )<θ Q (t state ), the coordination between devices is low and adjustments need to be made between devices.

[0039] It should also be noted that by establishing an intelligent scheduling model between devices, automatic coordination of device status is achieved, eliminating possible inconsistencies and conflicts between devices. This dynamic coordination significantly improves the overall efficiency of the system. In an environment where multiple devices run in parallel, the working status can be adjusted in real time according to the dependencies between devices, avoiding inefficient operation of devices when they interfere with each other and reducing energy consumption. By adopting the Markov model, the process of device status change is quantified and modeled, making the scheduling process highly flexible and accurate, and able to better adapt to the needs of different scenarios.

[0040] Furthermore, dynamically updating the operating parameters of the equipment includes dynamically adjusting the operating status of the equipment after establishing an intelligent scheduling model between the equipment, dynamically updating the operating parameters of each equipment based on the real-time collected conference room environment data, associating the current status of the equipment with the environmental variables, and calculating the power change of the equipment according to the sensitivity of different equipment to environmental changes, and building a dynamic power model, which is expressed as:

[0041]

[0042] Among them, P i (t power ) represents the time step t of device i power Dynamic power at time t power is the time for equipment power adjustment, P i0 is the initial power of the device, S j (t power ) represents the time step t of device j power The state at the moment, β ij (t power ) represents the dependency coefficient between device i and device j, X k (t power ) represents the environmental factor m at time step t power The values ​​at that time include temperature, humidity, light intensity, γ im (t power ) represents the sensitivity coefficient of device i to environmental factor m, δ i (t power ) represents the adaptive adjustment factor of device i, φ ij It represents the influence factor of the state difference between device i and device j on power adjustment, n represents the total number of devices, M represents the total number of environmental factors, and is used to describe various data of the conference room environment; based on the mutual influence between devices, the distance between devices, device types and interactions, the dependence coefficient between device i and device j is constructed, which is expressed as:

[0043]

[0044] Among them, α ij is the inductance between device i and device j, D i Indicates the spatial position coordinates of device i, D j represents the spatial position coordinates of device j, σ ij is the standard deviation of the state difference between devices; environmental factors directly affect the power regulation of devices. Each device responds differently to different environmental factors. The sensitivity coefficient of device i to environmental factor m is expressed as:

[0045]

[0046] Among them, λ in is the induction constant of device i to environmental factor m, T m is the current value of the environmental factor m, T env is the expected value of the environment, τ im is the standard deviation of the device's sensitivity to environmental changes; the adaptive adjustment factor of device i represents the flexibility of device power adjustment, which is adaptively adjusted according to changes in the environment and device status. The adaptive adjustment factor of device i is obtained through training based on the device's historical performance data and is expressed as:

[0047]

[0048] Where, ∈ is the adjustment flexibility constant, P i0 is the initial power of the device, P max is the maximum power of the device, μ i It is the adaptive adjustment index of the device, reflecting the flexibility of the device in responding to adjustment requirements.

[0049] It should be noted that optimizing resource allocation and conference room environment includes env When the temperature is lower than T, the power demand of the air conditioning equipment increases, lowering the room temperature. env When the number of people in the conference room decreases, the device state enters standby or low power consumption mode. Through the state difference and environmental factors in the dynamic power model, the system dynamically adjusts the device power. When the number of people in the conference room increases, the environmental data changes with the increase in the number of people, and the power demand of the air conditioner and lighting equipment will increase accordingly. The adaptive factors in the dynamic power model enable the device to respond and automatically increase the power.

[0050] It should also be noted that through dynamic adjustments based on environmental data, the equipment can automatically respond to environmental changes without human intervention, thereby improving the level of automation and intelligence of equipment operation. The dynamic update of equipment status ensures that the conference room environment is always kept in the optimal state, which not only avoids energy waste, but also ensures environmental comfort and realizes fine control of equipment power. Especially when the equipment works in coordination, the precise adjustment of the status of each device can effectively reduce the redundant operation of the equipment and reduce energy consumption. This dynamic adjustment mechanism based on the environment can also support the flexible change of equipment in different work scenarios, improving the adaptability of the system and the rational allocation of resources.

[0051] Furthermore, remote management and monitoring of equipment can be achieved through the cloud platform, including the use of the cloud platform to provide remote monitoring functions. Conference room administrators can monitor the status of equipment at remote locations and view the operation of equipment in real time. Administrators can remotely control equipment in the conference room, including adjusting air conditioning temperature, light brightness, and equipment switches.

[0052] It should be noted that data sharing and collaboration include data sharing between different devices based on a cloud platform, collaborative operations between devices, and automatic allocation of device resources to each participant; different devices include conference room control equipment, video conferencing equipment and air conditioning.

[0053] It should also be noted that through the remote management function of the cloud platform, administrators can adjust the conference room equipment anytime and anywhere, greatly improving the convenience and flexibility of the system. The collaborative function of the cloud platform enables data sharing between different devices, realizes efficient collaborative operation between devices, and ensures that equipment resources can be flexibly allocated according to demand, avoiding waste of resources. The remote monitoring and adjustment function not only improves the management efficiency of the conference room, but also can respond to emergencies in a timely manner, such as equipment failure or drastic changes in the environment, to ensure the stability and comfort of the conference room environment.

[0054] Example 2 is an embodiment of the present invention, which provides an intelligent conference room management system based on the Internet of Things. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0055] First, a conference room equipment management system is built in a simulation environment, covering common conference room equipment such as air conditioning, intelligent lighting and video conferencing equipment. Three types of equipment are selected: air conditioning, intelligent lighting and video conferencing equipment. The power demand of air conditioning is set to 300W, the maximum power is 800W, and the initial power is 500W. The power demand of intelligent lighting is set to 100W, the maximum power is 250W, and the initial power is 150W. The power demand of video conferencing equipment is 150W, the maximum power is 400W, and the initial power is 200W. The real-time working status of the equipment is collected through sensors. Data such as the current power, temperature, humidity, light intensity, etc. of the equipment are analyzed using the Markov model, and a scheduling model between devices is established through the state transfer matrix. For example, the power adjustment of air conditioning is closely related to temperature changes, while the power demand of intelligent lighting is affected by light intensity. The dependency between devices is realized by calculating the difference in device status. When the difference in device status is small, the system believes that the devices work well together. The working status of the equipment is dynamically adjusted by collecting the environmental data of the conference room in real time (such as temperature, humidity, and light intensity). Assuming that the temperature in the conference room is 25℃ and the light intensity is 850lux, the system automatically adjusts the power of air conditioning and lighting equipment. By analyzing the relationship between the equipment and environmental factors, the power requirements of air conditioning, lighting and video conferencing equipment are dynamically updated. With the support of the conference room equipment collaboration module, the cloud platform provides remote management functions for the equipment. The administrator can monitor and adjust the equipment status in real time. The administrator remotely adjusts the air conditioning temperature, light brightness, equipment switch and other functions. All devices share data through the cloud platform to ensure that the equipment works together. For example, when the number of people in the conference room increases, the system automatically increases the power of air conditioning and lighting to maintain a comfortable environment. Refer to Table 1. During the experiment, the data is recorded in real time. The operating power, environmental data, and equipment status changes of the equipment are all recorded for subsequent analysis. The main data of the experiment include equipment status differences, power requirements, equipment response time, etc.

[0056] Table 1 Experimental data record table

[0057]

[0058]

[0059] Through the analysis of the differences in device states, it can be seen that the differences in the states of air conditioning, lighting, and video conferencing equipment remain within a small range (0.1-0.3) in each time step, indicating that these devices work well together under the scheduling model. According to the intelligent scheduling model, the similarity measure between devices is always higher than 0.8, indicating that the coordination between devices is high.

[0060] The table shows that as the time step increases, the air conditioning power demand is gradually adjusted to meet the changes in the ambient temperature of the conference room. When the indoor temperature changes slightly, the air conditioning power is slightly adjusted to always remain within the appropriate power range. The change in air conditioning power in 6 time steps does not exceed 30W, reflecting the flexibility and energy-saving capabilities of the equipment.

[0061] When the light intensity exceeds the set value, the power of the lighting device is reduced in time. For example, at time step 2, the lighting power is reduced from 150W to 120W, which shows that the system automatically adjusts the equipment to reduce energy consumption.

[0062] Changes in the power demand of the equipment are closely related to environmental factors, especially when the temperature and light intensity change. The equipment can respond quickly and adjust the power to optimize the comfort of the meeting room. For example, when the number of people in the meeting room increases, the air conditioning and lighting power will increase accordingly to ensure that the indoor temperature and brightness are maintained within the set range.

[0063] In the prior art, devices are usually unable to adaptively adjust power based on real-time environmental data, while the dynamic adjustment mechanism of the present invention enables the device to respond to environmental changes in real time, thereby achieving the goals of optimizing energy consumption and improving the comfort of the conference room.

[0064] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides an intelligent conference room management method based on the Internet of Things, including S1: obtaining working status data of various types of equipment, analyzing the dependencies between devices, and establishing an intelligent scheduling model between devices; S2: based on the real-time collected conference room environment data, dynamically updating the operating parameters of the equipment, automatically adjusting the working status of the equipment, optimizing resource allocation and conference room environment; S3: realizing remote management and monitoring of equipment through a cloud platform, and conducting cross-regional and cross-device data sharing and collaboration.

[0065] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0066] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0067] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0068] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. An intelligent conference room management system based on the Internet of Things, characterized in that: include: Intelligent scheduling module (100), parameter dynamic update module (200), device collaboration module (300); The intelligent scheduling module (100) is used to obtain the working status data of various types of equipment, analyze the dependency relationship between the equipment, and establish an intelligent scheduling model between the equipment; The parameter dynamic updating module (200) is used to dynamically update the operating parameters of the equipment based on the real-time collected conference room environment data, automatically adjust the working state of the equipment, and optimize resource allocation and conference room environment; The device collaboration module (300) is used to realize remote management and monitoring of devices through a cloud platform, and to carry out cross-regional and cross-device data sharing and collaboration.

2. The intelligent conference room management system based on the Internet of Things as claimed in claim 1, characterized in that: The establishment of the intelligent scheduling model between devices includes obtaining the real-time working status data of lighting, air conditioning, and video conferencing equipment in the conference room, coordinating the working status of the equipment, using the Markov model to model the dependency between the equipment, and forming a multi-dimensional scheduling model by modeling the state transition of different equipment. The establishment of the intelligent scheduling model between devices is expressed as: Among them, Q ij (t state ) represents the similarity measure between device i and device j during the state transfer process, S i (t state ) represents the time step t of device i state The state at time t state is the time for the device status to change, S j (t state ) represents the time step t of device j state The state at the moment, S k (t state ) indicates that device k is at time step t state The state at the moment, σ ij represents the standard deviation of the state difference between device i and device j, n represents the total number of devices, k represents the index of the kth device in the system, which is used to traverse all devices, σ ik Represents the standard deviation of the state difference between device i and device k.

3. The intelligent conference room management system based on the Internet of Things as claimed in claim 2, characterized in that: The establishing of the intelligent scheduling model between devices also includes analyzing the device status difference based on the intelligent scheduling model between devices, when the device status difference is equal to 0, it means that the devices are completely coordinated, and when the device status difference is equal to 1, it means that the device status is completely uncoordinated; Based on the similarity measurement threshold θ Q (t state ) to judge the coordination between devices. When Q ij (t state )≥θ O (t state ) When the equipment is in close coordination, no equipment adjustment is required; When Q ij (t state )<θ Q (t state ), the coordination between devices is low and adjustments need to be made between devices.

4. The intelligent conference room management system based on the Internet of Things as claimed in claim 3, characterized in that: The dynamic updating of the operating parameters of the device includes dynamically adjusting the operating status of the device after establishing an intelligent scheduling model between devices, dynamically updating the operating parameters of each device based on the real-time collected conference room environment data, associating the current status of the device with the environmental variables, and calculating the power change of the device according to the sensitivity of different devices to environmental changes, and building a dynamic power model, which is expressed as: Among them, P i (t power ) represents the time step t of device i power Dynamic power at time t power is the time for equipment power adjustment, P i0 is the initial power of the device, S j (t power ) represents the time step t of device j power The state at the moment, β ij (t power ) represents the dependency coefficient between device i and device j, X k (t power ) represents the environmental factor m at time step t power The value of γ im (t power ) represents the sensitivity coefficient of device i to environmental factor m, δ i (t oower ) represents the adaptive adjustment factor of device i, φ ij represents the influence factor of the status difference between device i and device j on power adjustment, n represents the total number of devices, and M represents the total number of environmental factors; Based on the mutual influence between devices, the distance between devices, device types and interactions, the dependency coefficient between device i and device j is constructed and expressed as: Among them, α ij is the inductance between device i and device j, D i Indicates the spatial position coordinates of device i, D j represents the spatial position coordinates of device j, σ ij is the standard deviation of the state differences between devices; The sensitivity coefficient of device i to environmental factor m is expressed as: Among them, λ im is the induction constant of device i to environmental factor m, T m is the current value of the environmental factor m, T env is the expected value of the environment, τ im is the standard deviation of the device’s sensitivity to environmental changes; The adaptive adjustment factor of device i is obtained by training the historical performance data of the device and is expressed as: Where, ∈ is the adjustment flexibility constant, P i0 is the initial power of the device, P max is the maximum power of the device, μ i is the adaptive adjustment index of the device.

5. The intelligent conference room management system based on the Internet of Things as claimed in claim 4, characterized in that: The optimization of resource allocation and conference room environment includes when the temperature exceeds T env When the temperature is lower than T, the power demand of the air conditioning equipment increases, lowering the room temperature. env When the lower limit is reached, the air conditioning power demand is reduced or even shut down; When the light intensity in the conference room exceeds the set value, the intelligent lighting equipment automatically lowers the brightness to reduce power consumption; Dynamically adjust the equipment based on the change of people in the conference room. When the number of people in the conference room decreases, the equipment state enters standby or low power consumption mode. The system dynamically adjusts the equipment power based on the state difference and environmental factors in the dynamic power model. When more people enter the conference room, the environmental data will change with the increase in the number of people, and the power demand of air conditioning and lighting equipment will increase accordingly. The adaptive factors in the dynamic power model enable the equipment to respond and automatically increase power.

6. The intelligent conference room management system based on the Internet of Things as claimed in claim 5, characterized in that: The remote management and monitoring of equipment through the cloud platform includes using the cloud platform to provide a remote monitoring function, where the conference room administrator monitors the status of the equipment at a remote location, views the operation of the equipment in real time, and the administrator remotely controls the equipment in the conference room.

7. The intelligent conference room management system based on the Internet of Things as claimed in claim 6, characterized in that: The data sharing and collaboration include sharing data between different devices based on the cloud platform, performing collaborative operations between devices, and automatically allocating device resources to each participant; The different devices include control equipment, video conferencing equipment and air conditioning in the conference room.

8. A method for using the smart conference room management system based on the Internet of Things as claimed in any one of claims 1 to 7, characterized in that: This includes obtaining the working status data of various types of equipment, analyzing the dependencies between equipment, and establishing an intelligent scheduling model between equipment; Based on the real-time collected conference room environment data, the equipment operating parameters are dynamically updated, the equipment working status is automatically adjusted, and resource allocation and conference room environment are optimized; Remote management and monitoring of equipment can be achieved through the cloud platform, and data sharing and collaboration across regions and devices can be carried out.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method of the smart conference room management system based on the Internet of Things described in claim 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method of the smart conference room management system based on the Internet of Things described in claim 8 are implemented.

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