CN115174647B - Internet of things self-learning seat management system and method based on time rewarding mechanism - Google Patents
Internet of things self-learning seat management system and method based on time rewarding mechanism Download PDFInfo
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Abstract
The invention discloses an internet of things self-learning seat management system and method based on a time rewarding mechanism, belonging to the technical field of the internet of things. The system comprises: the system comprises a cloud server, a user mobile client, a seat management background and an Internet of things subsystem, wherein the system adopts a star topology structure, the cloud server is a central node of the whole system, and other modules are connected with the cloud server through the Internet in a data communication manner; the system uses a seat occupation point control method based on a time rewarding mechanism to control whether a user has the right to occupy a seat. The invention provides a system and a method for managing the self-learning seat of the Internet of things based on a time rewarding mechanism, which introduce the concept of more labor and more energy into the self-learning seat management, can enable a long-time self-learning person to still have the right of using the seat after leaving for a short time, and can effectively reduce the labor intensity of management personnel and improve the management efficiency on the premise of ensuring fair and reasonable use of the seat.
Description
Technical Field
The invention belongs to the technical field of the Internet of things, and particularly relates to an Internet of things self-learning seat management system and method based on a time rewarding mechanism.
Background
Along with popularization of the whole-people education and life-time education concepts, the utilization requirements of public learning resources (such as libraries, study rooms, reading rooms and the like) are increased increasingly, so that self-learning seats in the public learning environment are changed into a shortage of learning resources, and in the self-learning process, the occupied seats are reasonable requirements of self-learners in a short time, but if the occupied seats are occupied for a long time, the learning resources are wasted, and a great amount of time and effort are spent on manual intervention by an administrator in the public learning environment to correct the long-term malicious occupied seat behaviors, so that the use efficiency of the self-learning seats is improved.
The seat management system which takes the two-dimensional code as the carrier in the prior art has the problems that remote code scanning, code substitution, position selection and the like cannot be avoided; the seat management system using the detection system as a carrier has the defects of incapability of subdividing the use scene, high hardware configuration requirement, poor stability and the like, so that the problem to be solved is to be solved urgently on the premise of ensuring fair and reasonable utilization of the self-learning seat by using the technical means, so that the labor intensity of management staff is effectively reduced, and the seat management efficiency is improved.
Disclosure of Invention
The invention aims to provide an internet of things self-learning seat management system based on a time rewarding mechanism, which is characterized by comprising the following steps: the system comprises a cloud server, a user mobile client, a seat management background and an Internet of things subsystem, wherein the management system is of a star topology structure, the cloud server is a central node of the whole system, and other modules are connected with the cloud server in a data communication manner through the Internet;
the cloud server is used for realizing management of seat occupation points of users, management of seat use states, management of user information and providing data interfaces for other modules;
the user mobile client side realizes user login system, exit system, inquires the current seat empty condition, inquires the seat details used by the user, inquires the occupied seat points and realizes the seat-in and seat-out operation;
the seat management background is used for adjusting the parameters of the self-learning seat management system of the Internet of things, checking graphical monitoring data, managing user information and managing equipment topology;
an internet of things subsystem comprising: gateway, MCU, monitoring module, wherein the one end of gateway links to each other with high in the clouds server, and the other end links to each other with m MCU and constitutes LAN, and the value range of m is greater than 0 and is less than the biggest sub-equipment number that this gateway can support, MCU links to each other with n monitoring module, and the value range of n is greater than 0 and is less than the biggest sub-equipment number that this MCU can support, monitoring module and every seat one-to-one that waits to monitor, including human response module and display module for the realization gathers seat service condition and show information.
The internet of things subsystem is based on a Mesh network, the gateway is a Mesh gateway, and the MCU is an MCU with Mesh topology capability.
The monitoring module further comprises NFC labels, and the NFC labels are in one-to-one correspondence with the seats; the user mobile client also comprises an NFC tag reading module for reading NFC tag information.
The cloud server further comprises a message pushing module for realizing that the cloud server actively sends push messages to the user mobile client and the seat management background.
The user mobile client also comprises a setting module, and the user can set default options and custom prompt information when leaving.
The display screen of the display module is an ink screen.
The MCU is powered by a battery.
The invention also provides a seat management method which can be applied to the internet of things self-learning seat management system based on the time rewarding mechanism, and specifically comprises the following steps:
receiving and storing seat use condition information reported by an internet of things subsystem, comprising: seat identification and seat use status;
the seat information is sent to a display module of the appointed seat through the gateway, so that information display is realized, and the information comprises the seat use state and user-defined information;
receiving an operation request reported by a mobile client of a user, wherein the operation request comprises the following steps: logging in the system, logging out the system, inquiring the current seat empty condition, inquiring the seat details used by a user, inquiring the occupied seat point, and requesting to enter and leave;
receiving a data query and a parameter setting request sent by a seat management background, wherein the data query and the parameter setting request comprise: adjusting parameters of an internet of things self-learning seat management system, checking graphical monitoring data, managing user information and managing equipment topology;
the seat occupation point is controlled by using a seat occupation point control method based on a time rewarding mechanism, so that seat state management is realized;
the management method of the internet of things self-learning seat management system is a seat occupation point control method based on a time rewarding mechanism, and comprises the following specific steps:
step 1: judging whether the self-learning seat management system of the Internet of things is in an open state, if not, waiting for one minute, and then judging again, otherwise, executing the step 2;
step 2: read n Empty space 、n Occupying the area of And n By using Wherein n is Empty space Number of seats in "empty" n Occupying the area of And n By using The seat number which is in the occupied state and is occupied by no person and the seat number which is in the occupied state or the occupied state of tourist and is occupied by person are respectively represented;
step 3: judging the seat use state of the current seat, when the seat is in an occupied state, if a person is seated, executing the step 4, and if no person is seated, executing the step 5;
step 4: adding a seat occupation point for a user using the seat, and returning to the step 1 after waiting for one minute;
step 5: judging whether the occupied integral of the user occupying the seat is larger than 0, if so, executing the step 6, otherwise, executing the step 7;
step 6: deducting the occupation point of the occupation user, and returning to the step 1 after waiting for one minute, wherein the score of the deduction point is calculated by a deduction function sigmod (x), and is specifically defined as:
wherein, alpha and beta respectively represent a deduction coefficient and an expected space occupation coefficient, and x is defined as follows:
wherein N is the total number of seats;
step 7: the seat is released and the state of the seat is set to the "empty state".
The mobile client of the user is realized by adopting a WeChat applet
And/or
The operations of requesting to enter and requesting to leave can also be finished with the assistance of NFC labels, and the specific steps are as follows:
writing identification information of the seat in the NFC tag;
starting NFC function of the mobile device;
starting a user mobile client;
bringing the mobile device close to the NFC tag;
reading NFC label information and reporting seat identification information to a cloud server;
and the cloud server automatically performs seating or unseating operation according to the current user state and the seat identification information.
The invention has the beneficial effects that:
the invention introduces the concept of multiple labor and multiple resources into the self-study seat management, can enable a long-time self-study person to still have the seat use right after leaving for a short time, and can effectively reduce the labor intensity of management personnel and improve the management efficiency on the premise of ensuring fair and reasonable use of the seat.
Drawings
FIG. 1 is a hardware block diagram of an Internet of things self-learning seat management system based on a time rewarding mechanism;
FIG. 2 is a network frame diagram of an Internet of things subsystem;
FIG. 3 is a flow chart of a method of controlling seat occupation integration based on a time rewarding mechanism;
FIG. 4 is a graph of sigmod (x) function;
Detailed Description
The invention provides a system and a method for managing a self-learning seat of the Internet of things based on a time rewarding mechanism, and the invention is described in detail below with reference to drawings and embodiments.
As shown in fig. 1, the present invention provides an internet of things self-learning seat management system based on a time rewarding mechanism, comprising: the system comprises a cloud server 100, a seat management background 200, a user mobile client 300 and an Internet of things subsystem 400, wherein the management system is of a star topology, the cloud server 100 is a central node of the whole system, and other modules are in data communication connection with the cloud server 100 through the Internet;
the self-learning seat management system of the Internet of things uses a seat occupation point control method based on a time rewarding mechanism to control whether a user has the right to occupy a seat, wherein the seat occupation point is defined as the number of minutes in which the user can be in a seat occupation state, and the value range is an integer greater than or equal to 0;
the cloud server 100 is used for realizing management of seat occupation points of users, management of seat use states, management of user information and providing data interfaces for other modules;
the seat management background 200 is used for adjusting the parameters of the self-learning seat management system of the Internet of things, checking graphical monitoring data, managing user information and managing equipment topology;
the user mobile client 300 realizes user login, system exit, current seat empty condition inquiry, seat occupation integral inquiry and seat entering and seat leaving operation;
as shown in fig. 2, the internet of things subsystem 400 includes: gateway 410, MCU420 (Microcontroller Unit, micro control unit), monitoring module 430, wherein the one end of gateway links to each other with the high in the clouds server, and the other end links to each other with m MCU420 and constitutes the LAN, and the value range of m is greater than 0 and is less than the biggest sub-equipment number that this gateway can support, MCU420 links to each other with n monitoring module 430, and the value range of n is greater than 0 and is less than the biggest sub-equipment number that this MCU420 can support, monitoring module 430 corresponds with every seat one-to-one that waits to monitor, including human body response module 431 and display module 432 for the realization gathers seat service condition and show information.
In the embodiment, the service condition of the seat is detected and the seat state information is displayed through the subsystem of the Internet of things; inquiring the current seat empty condition and sending an operation request through a user mobile client; modifying system parameters, counting seating information, displaying graphical data, pushing information setting and topological hardware equipment through a seat management background; and the cloud server processes and stores the data in real time through data streaming, and provides a data interface for other modules to call. According to the Internet of things self-learning seat management system based on the time rewarding mechanism, the concept of multiple labor and multiple functions is introduced into self-learning seat management, so that a long-time self-learning person can still have the right of using the seat after leaving for a short time, the malicious occupation of the self-learning person can be effectively prevented, the labor intensity of management personnel can be effectively reduced on the premise of ensuring fair and reasonable use of the seat, and the management efficiency is improved.
In a specific embodiment, the internet of things self-learning seat management system based on the time rewarding mechanism is applied to a library of a certain university to uniformly manage self-learning seats in the library.
As shown in fig. 2, the internet of things subsystem 400 is first built, each to-be-managed exercise seat corresponds to one monitoring module 430 one by one, and the monitoring module 430 includes a human body sensing module 431 and a display module 432, which are used for collecting the seat use condition and displaying information.
In this embodiment, the human body sensing module 431 is an infrared human body sensing module, and is installed at a position capable of sensing whether a person is using the seat to be studied, including but not limited to under a table or a side surface, and a person skilled in the art should select a proper installation position according to a specific seat condition. Compared with other human body sensing modules, such as human body sensing modules based on image recognition, the complex machine learning algorithm can be supported by the computing equipment with higher preparation, so that the energy consumption, the cost and the wiring difficulty are greatly increased; for example, the human body sensing module based on multiple sensors comprises a temperature sensor and a pressure sensor, and human body sensing is performed by adopting multiple data, so that the complexity and the stability of judgment are greatly increased; therefore, the infrared-based human body induction module selected in the embodiment has the advantages of low price, stable performance and wide compatibility.
The display module 432 is a portable lcd, and is mounted on a position of a seat for a user to check and clearly identify the position of the seat for the user, including but not limited to a table or a bookshelf side, and a person skilled in the art should select a proper mounting position according to a specific seat condition. The display module can clearly and intuitively display the state information of the corresponding self-learning seat, is convenient for a self-learning person to observe, and comprises the following specific display logic:
(1) When the non-registered user uses, only the tourist is displayed in use;
(2) When the registered user uses, the user name, the seat use duration and other information can be displayed according to the preference of the user;
(3) When the seat is occupied by no person, displaying a vacant state;
(4) When the seat is not used by people, the user-defined state is displayed when the occupied time is longer;
(5) When the seat is not used by a person, the seat occupying time is 0, and the seat occupying time is displayed as a vacant state.
In an alternative embodiment, the display module 432 can also select an ink screen display for displaying the exercise seat status information, and the ink screen display has the advantages of low energy consumption, low hardware cost and good eye protection effect, and particularly has the characteristic that the ink screen does not need to be refreshed without changing the content, and is particularly suitable for displaying the exercise seat status information which does not need to be changed frequently.
In an alternative embodiment, the display module 432 further includes an NFC (Near Field Communication ) tag, and after the walker enters the library to find an empty exercise seat, the user mobile client is opened to get close to the NFC tag, and the user mobile client will upload the sensed tag and bind the right to use the exercise seat. By introducing the NFC tag, a self-learning seat is not required to be searched in the mobile client of the user by a self-learning person, and seating operation can be conveniently, quickly and accurately finished.
In this embodiment, the MCU420 selects an ESP32 single-chip microcomputer, and the single-chip microcomputer can be connected with multiple groups of monitoring modules 430, which has the advantages of low energy consumption, low heat productivity and high stability. For example, in this embodiment, a table can include four exercise seats, and an ESP32 single-chip microcomputer is connected to four sets of monitoring modules, so as to implement reading and displaying of status information of each exercise seat.
In an alternative embodiment, the ESP32 single-chip microcomputer can also be battery powered, such as 102540 battery. Considering that the ESP32 single-chip microcomputer is low in energy consumption, wiring cost is high in the scenes of libraries, study rooms and the like, and the layout of the study seats cannot be flexibly adjusted at any time after wiring, therefore, the 102540 battery is used for supplying power to the ESP32 single-chip microcomputer, an administrator only needs to charge the battery regularly (for example, the battery is charged every 3 months), the change requirement of the seats in the libraries can be flexibly adapted, the complex wiring process is avoided, and the method has high adaptability and convenience.
In this embodiment, the gateway 410 connects the internet of things subsystem 400 and the cloud server 100 through the internet, on one hand, reports the information of the use condition of the exercise seat collected by each body sensing module 431 in the internet of things to the cloud server 100 for processing, and on the other hand, displays the information of the status of the exercise seat issued by the cloud server 100 in the corresponding display module 432.
In an alternative embodiment, the MCUs 420 are single-chip computers with Mesh (wireless Mesh network) topology capability, the MCUs 420 form a local area network through Mesh, the gateway 410 is a Mesh gateway supporting Mesh networking, and each MCU420 is connected to the Mesh gateway through Mesh networking and performs data interaction with the cloud server 100. By means of the multi-hop and self-organizing characteristics of the Mesh network, the whole subsystem of the internet of things obtains higher reliability and stronger expansibility, is particularly suitable for being used in environments such as libraries and study rooms, and can provide great flexibility and stability.
It is noted that, the above-mentioned internet of things subsystem can realize flexible, efficient and stable collection of the status information of the exercise seat, and clearly and accurately display the service status information of the exercise seat issued by the cloud server to the system user by using the display module, and each listed optional embodiment is not a selection, and those skilled in the art should select a specific implementation according to the situation of the specific implementation environment and the requirement combination of the actual project, which is not repeated herein.
Secondly, a mobile client of the user is constructed, and the user can use the mobile client to realize a login system, an exit system, query the current seat empty condition, query the user for seat details, query the occupied point and realize the seating and unseating operations.
Defining the seat use status includes: an empty state, an occupied state, and a guest occupied state.
The specific steps for defining the user to operate the user mobile client are as follows:
step 1: executing login operation;
step 2: querying available exercise seats;
step 3: selecting an empty seat, executing a seating operation, and changing the seat into an occupied state by the cloud server;
step 4: using the seat, the cloud server increases the occupied seat point according to the occupied seat point control method based on the time rewarding mechanism;
step 5: temporarily leaving the seat, and deducting the seat occupation point by the cloud server according to a seat occupation point control method based on a time rewarding mechanism;
step 6: and executing the seat leaving operation, and changing the seat into a vacant state by the cloud server.
Considering that the self-learning person needs to download and install before using the user mobile client, the installation process is inconvenient, in an optional embodiment, the user mobile client is realized by adopting a WeChat applet, and by means of huge user base owned by WeChat applet and calling the WeChat applet to provide functional interfaces, such as an OpenID login interface, an NFC call interface, a user information query interface, a message push interface and the like, the vast self-learning person can realize installation-free and login-free use of the mobile user client, and has higher convenience and practicability.
Considering that there is a need for a walker to ensure that available walker seats are available for departure from a library or room, in an alternative embodiment, the walker can view the empty seats and remotely select the seats for seating operations via a user mobile client. Compared with the prior art that various complicated technical means are used for preventing the user in the occupied state from maliciously leaving seats for a long time, the Internet of things self-learning seat management system based on the time rewarding mechanism does not need to use scanning two-dimensional codes or erect a high-performance image acquisition and recognition device for each seat, does not need to use a large amount of picture data to train a machine learning model, only needs to use a mature, stable and low-cost infrared human body induction module to judge whether the self-learning seat is used by a person or not, and is matched with a seat occupation integral control method based on the time rewarding mechanism in a cloud server to use the self-learning seat in the occupied state for a practical use, the seat occupation integral is increased, otherwise, the seat is buckled according to a buckling function sigmod (x), and when the seat occupation integral is smaller than or equal to 0, the system automatically sets the seat into the free state, so that the self-learning seat can be reasonably occupied according to a principle of multiple learning, the self-learning seat can be reasonably and reasonably occupied, and the problem that the self-learning seat is wasted for a long time and has practical use due to the fact that the self-learning seat is high in practical use.
Considering that when a self-learner sometimes leaves the seat, forgets to use the user mobile client to execute the seat leaving operation, the occupied seat point of the self-learner is deducted greatly, and precious self-learning seat resources cannot be released in time for other self-learners to use, in an alternative embodiment, the user mobile client can receive and display the push message issued by the cloud server in real time. For example, when a seat is left by a self-learner, the cloud server defaults to consider that the self-learner continues to occupy the seat and deducts the seat occupation point of the self-learner by using a seat occupation point control method based on a time rewarding mechanism. When the integral reaches a critical value set by a user, the cloud server sends push information to remind, and after the leaving self-study person sees the push reminding information, the user mobile client can be used for leaving the seat at any time and any place, so that the use right of the self-study seat can be released as early as possible; when the occupied seat integral is smaller than or equal to 0, the cloud server sends pushing information again to remind, and the self-learning seat associated with the self-learning person is automatically set to be in a vacant state, so that the self-learning seat is prevented from being occupied for a long time.
In another alternative embodiment, the self-learner can also set a default option in leaving through the setting module of the mobile client of the user, namely, whether the self-learner continuously occupies the seat when leaving the seat, for example, the self-learner sets the default option as automatic leaving, so that the self-learner can be ensured not to deduct a large amount of occupied points because of forgetting to carry out the leaving operation; if the default option is set as the automatic seat occupation by the self-learner, the self-learner can be ensured not to lose the right of using the seat due to short leaving of the seat.
Considering that when a self-learner searches a certain self-learning seat in a user mobile client, multiple steps are needed, which is time-consuming and labor-consuming, in an alternative embodiment, the self-learner can realize the seating or unseating operation by approaching the mobile device to the NFC tag corresponding to the self-learning seat on the premise of opening the user mobile client, and the specific steps are as follows:
step 301: writing identification information of the seat in the NFC tag, including but not limited to the serial number of the seat, and setting the format and the content of the identification information according to specific application requirements by a person skilled in the art, which are not described herein;
step 302: starting NFC function of the mobile device;
step 303: starting a user mobile client;
step 304: bringing the mobile device close to the NFC tag;
step 305: reading NFC label information and reporting seat identification information to a cloud server;
step 306: and the cloud server automatically performs seating or unseating operation according to the current user state and the seat identification information.
The mode can obviously provide the efficiency of the sitting or leaving operation of the self-learning person, and improves the user experience.
Considering that when a self-learning seat is temporarily left or used by a self-learning seat, the self-learning seat management system of the invention will display the user name and the seat use time of the self-learning seat by default, and individual users will worry about revealing privacy or hope to display more personalized prompt information.
It should be noted that, the above-mentioned user mobile client can implement operations such as inquiring the occupied seat point, inquiring the seat use state, modifying the seat use state, etc., and has higher usability and stability, and each of the above-mentioned listed optional examples is not a selection, and those skilled in the art should select a specific implementation according to the situation of the specific implementation environment and the combination of requirements of actual projects, which is not repeated herein.
Thirdly, a cloud server is built, and therefore seat occupation integration of a management user, seat use state management, user information management and data interface providing for other modules are achieved. As shown in fig. 3, the seat score control method based on the time rewarding mechanism is used for managing the seat score of the self-learning person, and specifically comprises the following steps:
step 1: judging whether the self-learning seat management system of the Internet of things is in an open state, if not, waiting for one minute, and then judging again, otherwise, executing the step 2;
step 2: read n Empty space 、n Occupying the area of And n By using Wherein n is Empty space Number of seats in "empty" n Occupying the area of And n By using The number of seats in the "occupied state" state and occupied by no person and the number of seats in the "occupied state" or "occupied by guest" state and occupied by person are respectively indicated.
Step 3: judging the seat use state of the current seat, when the seat is in an occupied state, if a person is seated, executing the step 4, and if no person is seated, executing the step 5;
step 4: adding a seat occupation point for a user using the seat, and returning to the step 1 after waiting for one minute;
step 5: judging whether the occupied integral of the user occupying the seat is larger than 0, if so, executing the step 6, otherwise, executing the step 7;
step 6: deducting the occupation point of the occupation user, and returning to the step 1 after waiting for one minute, wherein the score of the deduction point is calculated by a deduction function sigmod (x), and is specifically defined as:
wherein, alpha and beta respectively represent a deduction coefficient and an expected space occupation coefficient, and x is defined as follows:
wherein N is the total number of seats;
step 7: the seat is released and the state of the seat is set to the "empty state".
Wherein:
1. in step 1, step 4 and step 6, the "waiting for one minute" is a reference value, and in theory, the shorter the interval time, the higher the calculation accuracy, but the power consumption increases, so in this embodiment, one minute is selected as the waiting interval, the waiting time is not specifically limited, and the person skilled in the art should adjust according to the actual situation;
2. step 2 and step 3, the step 2 is that a person sits in the seat, specifically, a person is detected to be using the self-learning seat through a human body sensing module, and data is reported to a cloud server through a gateway;
3. step 2 and step 3, the "no-man sitting" specifically means that the human body sensing module detects that no-man is using the self-learning seat, and reports data to the cloud server through the gateway;
4. in the step 6, alpha and beta respectively represent a deduction coefficient and an expected empty seat duty ratio coefficient, and if the seat deduction speed when reaching the expected empty seat proportion is reduced, the value of alpha can be reduced; if the free seats of the library are difficult to meet the exercise requirements, the beta value can be reduced. For example, when α=8, β=0.2, the sigmod (x) curve is as shown in fig. 4;
considering that a self-study person enters a library or a self-study room for the first time, the self-study person does not become a registered user of the internet of things self-study seat management system based on the time rewarding mechanism in the embodiment, or needs to make a short experience on a self-study environment before deciding whether to self-study in the library or the self-study room, in an optional embodiment, a guest occupation state is defined, and a specific processing procedure of the cloud server is as follows:
1. receiving seat state information reported by a human body sensing module, and knowing that a seat in an empty state is actually occupied by a tourist;
2. automatically setting the state of the seat as the occupied state of the tourist;
3. automatically setting the display information of the seat as 'tourist in use', and displaying the display information to all users through a display module;
4. after waiting ten minutes, the state of the seat is automatically set to the empty state.
The requirement that the user experiences before registering is met through the mode that the tourists occupy, and the usability of the system is effectively improved.
It should be noted that the cloud server can implement management of seat occupation points, management of seat use states, management of user information and provision of data interfaces for other modules, has high usability and stability, and the above listed optional embodiments are not alternatives, and those skilled in the art should select specific embodiments according to the specific implementation environment and the combination of requirements of actual projects, which is not described herein.
Finally, the seat management background realizes adjustment of parameters of the self-learning seat management system of the Internet of things, viewing of graphical monitoring data, management of user information and management of equipment topology.
Considering that the study place is not open all day and the business is suspended when the holiday or special situation is met, in an alternative embodiment, the manager can set the business state to be the non-open state through the seat management background, and the cloud server can suspend the increase and decrease of the seat occupation points until the seat management system is in the open state again when the seat occupation points of the self-study person are managed by using the seat occupation point control method based on the time rewarding mechanism. According to the embodiment, by means of suspending increasing and decreasing of the occupied seat integral, the occupied seat integral obtained by a self-learner through effort can be effectively used, and the fairness of the system can be remarkably improved.
Considering uncertainty of the personnel flow of the study site or the need to control the personnel density of the study site for special reasons, a manager adjusts parameters of the deduction function through a seat management background so that the study site reaches an expected management state, for example, in an alternative embodiment, the values of alpha can be reduced if the deduction speed of the seat when the expected empty seat proportion is reached is reduced if alpha and beta are respectively set to represent the deduction coefficient and the expected empty seat duty ratio coefficient; if the free seats of the library are difficult to meet the exercise requirements, the beta value can be reduced. The seat management system provided by the embodiment of the invention has higher practicability.
Considering that the seats of the self-learning place can be increased or decreased and adjusted according to the actual situation, in an alternative embodiment, when new seats are increased or decreased, old seats are eliminated, damaged seats are damaged and the distribution of the seats is adjusted, an administrator can manage the equipment topology through the seat management system, so that the adaptability of the system is improved.
In consideration of the demands of controlling the total number of people entering the study site or counting the personnel distribution condition of each reading room, limiting personnel density and the like, in an alternative embodiment, an administrator checks the graphical monitoring data through the seat management background, thereby achieving the purpose of monitoring the running state of the study site at any time and having higher practicability.
In consideration of the situation that a seat is occupied maliciously or a guest uses the seat by force frequently in a self-learning place, in an optional embodiment, an administrator can actively inquire the seat information of the abnormal situation through a seat management background, or the administrator receives a push message of a cloud server, so that the administrator can check and process the abnormal situation on site in time; or the administrator can manage the user information, specifically including checking or modifying the characteristic information of the user, realizing the marking of the historical behavior of the self-learning person, or setting credit points, and specially managing the self-learning person with malicious behavior for many times. By means of the technical means, the seat management system disclosed by the embodiment can effectively reduce the intensity of the supervision work of an administrator.
It is noted that the seat management background can realize adjustment of parameters of the internet of things self-learning seat management system, viewing of graphical monitoring data, management of user information and management equipment topology, has high usability and stability, and the above listed optional embodiments are not alternatives, and a person skilled in the art should select a specific implementation according to the situation of a specific implementation environment and the combination of requirements of actual projects, which is not repeated herein.
The invention also provides a seat management method applied to the internet of things self-learning seat management system based on the time rewarding mechanism, which comprises the following steps:
receiving and storing seat use condition information reported by an internet of things subsystem, comprising: seat identification and seat use status;
the seat information is sent to a display module of the appointed seat through the gateway, so that information display is realized, and the information comprises the seat use state and user-defined information;
receiving an operation request reported by a mobile client of a user, wherein the operation request comprises the following steps: logging in the system, logging out the system, inquiring the current seat empty condition, inquiring the seat details used by a user, inquiring the occupied seat point, and requesting to enter and leave;
receiving a data query and a parameter setting request sent by a seat management background, wherein the data query and the parameter setting request comprise: adjusting parameters of an internet of things self-learning seat management system, checking graphical monitoring data, managing user information and managing equipment topology;
the seat occupation point is controlled by using a seat occupation point control method based on a time rewarding mechanism, so that seat state management is realized;
and packaging the API, namely packaging the processed data into the API and providing the API for other modules to call so as to realize data query and modification operation. According to the internet of things self-learning seat management method based on the time rewarding mechanism, the concept of multiple labor and multiple functions is introduced into self-learning seat management, so that a long-time self-learning person can still have the right to use the seat after leaving for a short time, and the labor intensity of management personnel can be effectively reduced and the management efficiency can be improved on the premise of ensuring fair and reasonable use of the seat. The embodiments of the present invention refer to all the above embodiments of the internet of things self-learning seat management system based on the time rewarding mechanism, and are not described herein.
Claims (9)
1. The Internet of things self-learning seat management system based on the time rewarding mechanism is characterized by comprising: the system comprises a cloud server, a user mobile client, a seat management background and an Internet of things subsystem, wherein the management system is of a star topology structure, the cloud server is a central node of the whole system, and other modules are connected with the cloud server in a data communication manner through the Internet;
the cloud server is used for realizing management of seat occupation points of users, management of seat use states, management of user information and providing data interfaces for other modules;
the user mobile client side realizes user login system, exit system, current seat empty condition inquiry, seat detail inquiry, seat occupation point inquiry and seat entering and exiting operation;
the seat management background is used for adjusting parameters of the self-learning seat management system of the Internet of things, checking graphical monitoring data, managing user information and managing equipment topology;
the internet of things subsystem comprises: the system comprises a gateway, an MCU and monitoring modules, wherein one end of the gateway is connected with a cloud server, the other end of the gateway is connected with m MCU to form a local area network, the value range of m is larger than 0 and smaller than the maximum number of pieces of sub-equipment which can be supported by the gateway, the MCU is connected with n monitoring modules, the value range of n is larger than 0 and smaller than the maximum number of pieces of sub-equipment which can be supported by the MCU, and the monitoring modules are in one-to-one correspondence with each seat to be monitored, and comprise a human body sensing module and a display module, and are used for acquiring the service condition and display information of the seats;
the management method of the internet of things self-learning seat management system based on the time rewarding mechanism is a seat occupation point control method based on the time rewarding mechanism, and specifically comprises the following steps:
step 1: judging whether the self-learning seat management system of the Internet of things is in an open state, if not, waiting for one minute, and then judging again, otherwise, executing the step 2;
step 2: read n Empty space 、n Occupying the area of And n By using Wherein n is Empty space Number of seats in "empty" n Occupying the area of And n By using The seat number which is in the occupied state and is occupied by no person and the seat number which is in the occupied state or the occupied state of tourist and is occupied by person are respectively represented;
step 3: judging the seat use state of the current seat, when the seat is in an occupied state, if a person is seated, executing the step 4, and if no person is seated, executing the step 5;
step 4: adding a seat occupation point for a user using the seat, and returning to the step 1 after waiting for one minute;
step 5: judging whether the occupied integral of the user occupying the seat is larger than 0, if so, executing the step 6, otherwise, executing the step 7;
step 6: deducting the occupation point of the occupation user, and returning to the step 1 after waiting for one minute, wherein the score of the deduction point is calculated by a deduction function sigmod (x), and is specifically defined as:
wherein, alpha and beta respectively represent a deduction coefficient and an expected space occupation coefficient, and x is defined as follows:
wherein N is the total number of seats;
step 7: the seat is released and the state of the seat is set to the "empty state".
2. The internet of things self-learning seat management system based on the time rewarding mechanism of claim 1, wherein the internet of things subsystem is an internet of things subsystem based on a Mesh network, the gateway is a Mesh gateway, and the MCU is an MCU with Mesh topology capability.
3. The internet of things self-learning seat management system based on a time rewarding mechanism of claim 1 wherein the monitoring module further comprises NFC tags, the NFC tags being in one-to-one correspondence with the seats; the user mobile client also comprises an NFC tag reading module for reading NFC tag information.
4. The internet of things self-learning seat management system based on the time rewarding mechanism of claim 1 wherein the user mobile client and the seat management background further comprise a push message receiving and displaying module, and the cloud server further comprises a message pushing module for enabling the cloud server to actively send push messages to the user mobile client and the seat management background.
5. The internet of things self-learning seat management system based on a time rewarding mechanism of claim 1 wherein the user mobile client further comprises a setting module, the user being able to set default options and custom prompts when away.
6. The internet of things self-learning seat management system based on a time rewarding mechanism of claim 1 wherein the display screen of the display module is an ink screen.
7. The internet of things self-learning seat management system based on a time rewarding mechanism of claim 1 wherein the MCU is battery powered.
8. A seat management method of an internet of things self-learning seat management system utilizing a time rewarding mechanism according to any of claims 1-7, comprising the steps of:
receiving and storing seat use condition information reported by an internet of things subsystem, comprising: seat identification and seat use status;
the seat information is sent to a display module of the appointed seat through the gateway, so that information display is realized, and the information comprises the seat use state and user-defined information;
receiving an operation request reported by a mobile client of a user, wherein the operation request comprises the following steps: logging in the system, logging out the system, inquiring the current seat empty condition, inquiring the seat details used by a user, inquiring the occupied seat point, and requesting to enter and leave;
receiving a data query and a parameter setting request sent by a seat management background, wherein the data query and the parameter setting request comprise: adjusting parameters of an internet of things self-learning seat management system, checking graphical monitoring data, managing user information and managing equipment topology;
the seat occupation point is controlled by using a seat occupation point control method based on a time rewarding mechanism, so that seat state management is realized;
and packaging the API, namely packaging the processed data into the API and providing the API for other modules to call so as to realize data query and modification operation.
9. The method for managing the internet of things self-learning seat management system based on the time rewarding mechanism of claim 8 wherein said user mobile client is implemented by a WeChat applet
And/or
The operations of requesting to enter and requesting to leave can also be finished with the assistance of NFC labels, and the specific steps are as follows:
step 301: writing identification information of the seat in the NFC tag;
step 302: starting NFC function of the mobile device;
step 303: starting a user mobile client;
step 304: bringing the mobile device close to the NFC tag;
step 305: reading NFC label information and reporting seat identification information to a cloud server;
step 306: and the cloud server automatically performs seating or unseating operation according to the current user state and the seat identification information.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103279906A (en) * | 2013-05-12 | 2013-09-04 | 安徽工程大学 | Anti-malicious seat occupying management system of library |
| CN107945411A (en) * | 2017-12-11 | 2018-04-20 | 南京石匠网络科技有限公司 | A kind of public individual study table seat Management System |
| CN109147114A (en) * | 2018-07-25 | 2019-01-04 | 北京红马传媒文化发展有限公司 | Seat control method, device, system and the server of venue |
| CN109635977A (en) * | 2018-12-17 | 2019-04-16 | 枣庄学院 | Room for individual study seat Management System and its reservation management method based on wechat public platform |
| CN109902628A (en) * | 2019-02-28 | 2019-06-18 | 广州大学 | A kind of seat Management System of Library of view-based access control model Internet of Things |
| CN110334826A (en) * | 2019-07-10 | 2019-10-15 | 河海大学常州校区 | A kind of intelligent library and room for individual study seat level monitoring system |
| CN110443392A (en) * | 2019-07-16 | 2019-11-12 | 河海大学常州校区 | A kind of libraries of the universities' seat Management System and method |
| CN113570204A (en) * | 2021-07-06 | 2021-10-29 | 北京淇瑀信息科技有限公司 | User behavior prediction method, system and computer equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2290562A1 (en) * | 2009-08-24 | 2011-03-02 | Amadeus S.A.S. | Segmented main-memory stored relational database table system with improved collaborative scan algorithm |
-
2022
- 2022-07-29 CN CN202210907108.3A patent/CN115174647B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103279906A (en) * | 2013-05-12 | 2013-09-04 | 安徽工程大学 | Anti-malicious seat occupying management system of library |
| CN107945411A (en) * | 2017-12-11 | 2018-04-20 | 南京石匠网络科技有限公司 | A kind of public individual study table seat Management System |
| CN109147114A (en) * | 2018-07-25 | 2019-01-04 | 北京红马传媒文化发展有限公司 | Seat control method, device, system and the server of venue |
| CN109635977A (en) * | 2018-12-17 | 2019-04-16 | 枣庄学院 | Room for individual study seat Management System and its reservation management method based on wechat public platform |
| CN109902628A (en) * | 2019-02-28 | 2019-06-18 | 广州大学 | A kind of seat Management System of Library of view-based access control model Internet of Things |
| CN110334826A (en) * | 2019-07-10 | 2019-10-15 | 河海大学常州校区 | A kind of intelligent library and room for individual study seat level monitoring system |
| CN110443392A (en) * | 2019-07-16 | 2019-11-12 | 河海大学常州校区 | A kind of libraries of the universities' seat Management System and method |
| CN113570204A (en) * | 2021-07-06 | 2021-10-29 | 北京淇瑀信息科技有限公司 | User behavior prediction method, system and computer equipment |
Non-Patent Citations (1)
| Title |
|---|
| "基于混合算法的研究生招生考试考场座位编排系统研究及应用";高昊;《信息科技》;全文 * |
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