CN113896063B - Intelligent elevator dispatching system based on AI intelligence - Google Patents
Intelligent elevator dispatching system based on AI intelligence Download PDFInfo
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- CN113896063B CN113896063B CN202111237950.2A CN202111237950A CN113896063B CN 113896063 B CN113896063 B CN 113896063B CN 202111237950 A CN202111237950 A CN 202111237950A CN 113896063 B CN113896063 B CN 113896063B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/24—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration
- B66B1/2408—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration where the allocation of a call to an elevator car is of importance, i.e. by means of a supervisory or group controller
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
- B66B1/3423—Control system configuration, i.e. lay-out
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
- B66B1/3446—Data transmission or communication within the control system
- B66B1/3461—Data transmission or communication within the control system between the elevator control system and remote or mobile stations
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3476—Load weighing or car passenger counting devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/46—Adaptations of switches or switchgear
- B66B1/468—Call registering systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B11/00—Main component parts of lifts in, or associated with, buildings or other structures
- B66B11/02—Cages, i.e. cars
- B66B11/0226—Constructional features, e.g. walls assembly, decorative panels, comfort equipment, thermal or sound insulation
- B66B11/024—Ventilation systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0012—Devices monitoring the users of the elevator system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/20—Details of the evaluation method for the allocation of a call to an elevator car
- B66B2201/211—Waiting time, i.e. response time
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/20—Details of the evaluation method for the allocation of a call to an elevator car
- B66B2201/243—Distribution of elevator cars, e.g. based on expected future need
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/402—Details of the change of control mode by historical, statistical or predicted traffic data, e.g. by learning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/403—Details of the change of control mode by real-time traffic data
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4623—Wherein the destination is registered after boarding
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/46—Switches or switchgear
- B66B2201/4607—Call registering systems
- B66B2201/4638—Wherein the call is registered without making physical contact with the elevator system
- B66B2201/4646—Wherein the call is registered without making physical contact with the elevator system using voice recognition
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Mechanical Engineering (AREA)
- Civil Engineering (AREA)
- Structural Engineering (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
- Elevator Control (AREA)
Abstract
The invention belongs to the technical field of elevators, in particular to an intelligent elevator dispatching system based on AI (intelligent interface) intelligence. According to the elevator intelligent scheduling system based on the AI intelligent scheduling system, through setting the peak time mode, the AI intelligent scheduling module marks peak time stamps according to a preset algorithm and uploads the peak time stamps to the cloud server, the cloud server analyzes the data of the peak time stamps, creates a starting time stamp according to a preset condition and sends the starting time stamp to the AI intelligent scheduling module, and the AI intelligent scheduling module waits for taking according to time information and floor information recorded by the starting time stamp to a floor with the largest number of appointed people in the appointed time, so that the technical problem that the existing elevator cannot intelligently identify the peak time and cannot reach the floor with the largest number of people in advance in the peak time is effectively solved.
Description
Technical Field
The invention relates to the technical field of elevators, in particular to an intelligent elevator dispatching system based on AI (intelligent interface) intelligence.
Background
At present, the continuous development of economy and the daily and monthly variation of science and technology are realized, and the height of the building is grown at the same speed as the economic development. Elevators have become an integral part of our daily lives as the primary means of transportation in buildings, as well as other means of transportation. From the current use situation of the traditional elevator, the safety and stability (hardware technology of the elevator) of the traditional elevator are developed more mature, but the convenience and the more passenger-friendly aspect are still to be improved. In particular, the problems with the current conventional elevators include;
1. the existing elevator cannot intelligently identify the peak period, and cannot reach the floor with the largest number of people in advance in the peak period;
2. the existing elevator cannot intelligently control the speed, and cannot quickly reach a call floor when no call exists in the elevator car;
3. the existing elevators cannot learn the elevator taking demands of passengers, cannot dispatch the elevators in advance, and judge the floors to which the passengers will go.
Disclosure of Invention
Based on the technical problems that the existing elevator cannot intelligently identify peak time, cannot intelligently control speed and cannot learn elevator taking demands of passengers, the invention provides an intelligent elevator scheduling system based on AI intelligence.
The invention provides an intelligent elevator dispatching system based on AI (advanced technology attachment), which comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and the AI intelligent dispatching module sends an instruction to the elevator controller to control the elevator to run according to a preset algorithm;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the peak period mode intelligently identifies the peak period, and the floor with the largest number of people is reached in the appointed elevator taking peak period;
the APP reservation mode submits a reservation riding form through a user, so that an elevator can reach a designated floor at a contracted time;
the pre-judging scheduling mode can learn the elevator taking requirement of the passengers so as to pre-mobilize the elevators to reach the appointed floors when the passengers appear;
the intelligent speed control mode is used for intelligently controlling the speed according to passengers in the elevator, and the elevator can quickly reach a call floor when no person exists;
the intelligent ventilation mode is intelligently opened or closed according to the number of passengers in the elevator;
the voice interaction mode can identify the voice elevator taking information of the passengers and reach the appointed floor according to the voice elevator taking information.
Preferably, the peak period mode includes a cloud server and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module marks a peak time stamp according to a preset algorithm and uploads the peak time stamp to the cloud server.
Through the technical scheme, the pressure sensor detects the weight in the elevator car and sends data to the data analysis processing module, if the weight in the elevator car exceeds two thirds of the elevator carrying capacity, the data analysis processing module marks a peak time stamp, the peak time stamp contains riding time information and floor information, and the peak time stamp is uploaded to the cloud server.
Preferably, the cloud server analyzes the peak time stamp and creates or deletes the start time stamp according to a preset algorithm, and the cloud server sends the start time stamp to the AI intelligent scheduling module, and the AI intelligent scheduling module controls the elevator to operate according to the preset algorithm.
According to the technical scheme, each time a peak time stamp is stored, the cloud server performs data analysis once, if three peak time stamps appear in ten minutes and more than two consecutive days, the first peak time stamp in the time period is converted into the starting time stamp, if no peak time stamp is recorded in half an hour after the starting time stamp in two consecutive days, the corresponding starting time stamp is automatically deleted, the cloud server sends the starting time stamp to the AI intelligent scheduling module, the AI intelligent scheduling module sends an instruction to the elevator controller, and the elevator is controlled to reach a designated floor in advance according to time information recorded by the starting time stamp and floor information, and waits for taking.
Preferably, the pre-judging scheduling mode comprises a face recognition module, and the face recognition module collects face information and submits the face information to the data analysis processing module.
Through the technical scheme, the entrance face recognition module of the gate entrance of the first floor and the safety exits of each floor can collect face information in advance and make judgment in advance, and the face information is collected through the face recognition module and transmitted to the data analysis module.
Preferably, the data analysis processing module compares and analyzes the face data, the analyzed face data is transmitted to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the elevator to operate.
According to the technical scheme, the data analysis processing module inquires a user riding information database in the cloud server, inquires user riding information through comparing and analyzing face data, automatically enters a voice interaction mode if the user riding information is not found in the database, automatically creates a user riding information database according to riding floor information of passengers, generates a predicted riding model through the riding information, (the predicted riding model comprises X and Y values, X is a starting floor frequently ridden and Y is a target floor frequently ridden), directly calls the predicted riding model of the user if the user is found in the database, transmits the predicted riding model to the AI intelligent scheduling module, the AI intelligent scheduling module reaches an X building according to the predicted riding model, after the passengers enter, the AI intelligent scheduling module controls the voice broadcasting module to report whether the passengers get to the X building, the passengers answer is submitted to the voice recognition module for recognition, if the passengers answer is a positive answer, the elevator controller controls an elevator front line Y building, and automatically enters the voice interaction control mode if the answer of the passengers is negative.
Preferably, the intelligent speed control module comprises the pressure sensor, the pressure sensor transmits the collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the elevator running speed.
According to the technical scheme, the pressure sensor collects pressure data in the car and transmits the pressure data to the data analysis module, the data analysis module analyzes the pressure data in the car, the data analysis module judges that no person exists according to a preset value, if the weight in the car is equal to zero, the AI intelligent dispatching module sends a command to the elevator controller, the elevator controller controls a driving unit of the car to quickly reach a specified floor at a speed of 5M/S, according to the preset value, if the weight in the car is less than one third, the AI intelligent dispatching module judges that fewer persons exist, the AI intelligent dispatching module sends a command to the elevator controller, the elevator controller controls the driving unit of the car to reach the specified floor at a speed of 2M/S, according to the preset value, if the weight in the car is more than one third, the AI intelligent dispatching module judges that more persons exist, the AI intelligent dispatching module sends a command to the elevator controller, and the elevator controller controls the driving unit of the car to reach the specified floor at the speed of 1.25M/S.
Preferably, the APP pre-call mode includes a mobile phone APP, the mobile phone APP collects face data and submits a reservation riding form to the cloud server, the cloud server analyzes the face data and processes the reservation riding form, the cloud server sends the analyzed face data and the processed reservation riding form to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller to control elevator operation according to a preset algorithm.
According to the technical scheme, when a user uses the system for the first time, face data are required to be acquired through the mobile phone APP, the face data are uploaded to the cloud server, then the cloud server creates a reservation user database, when the user reserves, the reservation riding form is filled in according to prompts, (the reservation riding form comprises riding floors, going floors and reservation riding time, wherein the filled floors are invalid when the information of the filled floors exceeds the floor range of the riding floors or the reservation riding time exceeds the current time for five minutes), the reservation riding form can be submitted to the cloud server effectively, the reservation riding form is sent to the AI intelligent scheduling module by the cloud server, an instruction is sent to the elevator controller by the AI intelligent scheduling module to control the elevator to go to the appointed floors at the appointed time, after the elevator reaches the appointed floors, the face recognition module detects that the elevator submits passengers, the passengers automatically go to the appointed floors after the elevator enters the appointed floors (after the appointed floors, the passenger can select manual selection floors or voice interaction control modes control the elevator to change the going floors), after the elevator does not detect the elevator to withdraw from the form, the elevator exits from the AI intelligent scheduling module, and the elevator is not called to the appointed floors.
Preferably, the intelligent ventilation mode comprises a fresh air ventilator and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the fresh air ventilator to operate.
Through the technical scheme, the pressure sensor collects the pressure in the lift car and transmits the pressure data to the data analysis and processing module, the data analysis and processing module analyzes the pressure data, if the pressure sensor detects that the weight in the lift car is less than one third of the maximum load of the elevator, the AI intelligent scheduling module sends an instruction to the elevator controller to close the fresh air ventilator, and if the pressure sensor detects that the weight in the lift car is greater than one third of the maximum load of the elevator, the AI intelligent scheduling module sends an instruction to the elevator controller to open the fresh air ventilator.
Preferably, the voice interaction mode comprises a voice broadcasting module, a voice recognition module and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module controls and starts the voice broadcasting module to broadcast preset contents according to a preset algorithm.
Through the technical scheme, after passengers enter the car, the pressure sensor collects pressure data in real time and transmits the pressure data to the data analysis processing module, if the data analysis processing module detects that the pressure data changes, an interaction signal is sent to the AI intelligent scheduling module, the AI intelligent scheduling module starts the voice broadcasting module, and the' honored passengers are broadcast according to preset contents, namely, the passengers are good, and want to go to which floor.
Preferably, the voice recognition module intelligently recognizes voice information of passengers, converts the voice information into digital information and transmits the digital information to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller to control the elevator to operate according to a preset algorithm.
According to the technical scheme, the voice recognition module recognizes the answers of the passengers, converts voice information into digital information, transmits the digital information to the data analysis processing module for analysis and processing, and sends an instruction to the elevator controller through the AI intelligent scheduling module to control the elevator to go to the floors answered by the passengers.
The beneficial effects of the invention are as follows:
1. through setting the peak time mode, the AI intelligent scheduling module marks the peak time stamp according to a preset algorithm and uploads the peak time stamp to the cloud server, the cloud server performs data analysis on the peak time stamp, a preset condition is achieved, an initial time stamp is created, the initial time stamp is sent to the AI intelligent scheduling module, the AI intelligent scheduling module waits for taking according to the time information and the floor information recorded by the initial time stamp from the appointed time to the floor with the largest appointed number of people in advance, and the technical problem that the existing elevator cannot intelligently identify the peak time and cannot reach the floor with the largest appointed number of people in advance in the peak time is effectively solved.
2. Through setting up intelligent accuse speed module, gather the weight in the car by pressure sensor, if the weight in the car is zero, then elevator controller control car 'S drive unit reaches appointed floor with 5M/S' S speed, if the weight in the car is less than one third, elevator controller control car 'S drive unit reaches appointed floor with 2M/S' S speed, if the weight in the car is greater than two thirds, elevator controller control car 'S drive unit reaches appointed floor with 1.25M/S' S speed, make the demand floor of arriving fast when unmanned, the elevator drive unit of protection is gone up and down slowly to many times, the effectual elevator that has solved now can not intelligent control speed, when unmanned call in the car, can not arrive the call floor fast.
3. The passenger face data are collected by the face recognition module through setting the pre-judging scheduling mode, the user riding information database in the cloud server is queried by the data analysis processing module, the user riding information is queried by comparing and analyzing the face data, if the user riding information is not found in the database, the voice interaction mode is automatically entered, if the user is found in the database, the predicted riding model of the user is directly called (the predicted riding model comprises X and Y values, X is a frequently-riding initial floor and Y is a frequently-riding target floor), the AI intelligent scheduling module reaches X in advance according to the predicted riding model, the waiting time is saved, the trouble that the passenger manually selects floors is avoided, the problem that the existing elevator cannot learn the riding requirement of the passenger, the elevator cannot be pre-scheduled, and the floor to which the passenger is going is judged is effectively solved.
Drawings
Fig. 1 is a schematic diagram of an intelligent elevator dispatching system based on AI intelligence;
fig. 2 is an elevator control schematic diagram of an intelligent elevator dispatching system based on AI intelligence according to the present invention;
fig. 3 is a control schematic diagram of an embodiment of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 4 is a control schematic diagram of an embodiment of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 5 is a schematic diagram of a second control of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 6 is a schematic diagram of a third control of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 7 is a schematic diagram of a fourth control of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 8 is a schematic diagram of a fifth control of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Fig. 9 is a schematic diagram of a sixth control of an intelligent elevator dispatching system based on AI intelligence according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Example 1
Referring to fig. 1-4, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller to control the elevator to operate according to a preset algorithm;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the peak period mode intelligently identifies the peak period, and the floor with the largest number of people is reached in the appointed elevator taking peak period.
The peak period mode comprises a cloud server and a pressure sensor, the pressure sensor transmits collected pressure data to a data analysis processing module, the data analysis processing module transmits the analyzed pressure data to an AI intelligent scheduling module, the AI intelligent scheduling module marks a peak time stamp according to a preset algorithm and uploads the peak time stamp to the cloud server, the cloud server analyzes the peak time stamp and creates a starting time stamp or deletes the starting time stamp according to the preset algorithm, the cloud server transmits the starting time stamp to the AI intelligent scheduling module, and the AI intelligent scheduling module controls elevator operation according to the preset algorithm.
The method comprises the steps that a pressure sensor detects the weight in a lift car and sends data to a data analysis processing module, if the weight in the lift car exceeds two thirds of the loading capacity of the lift car, the data analysis processing module marks a peak time stamp, the peak time stamp comprises riding time information and floor information, the peak time stamp is uploaded to a cloud server, each time one peak time stamp is stored, the cloud server performs data analysis, if three peak time stamps occur in ten minutes and more than two consecutive days, the first peak time stamp in the time period is converted into a starting time stamp, if no peak time stamp is recorded in half hours after the starting time stamp in two consecutive days, the corresponding starting time stamp is automatically deleted, the cloud server sends the starting time stamp to an AI intelligent scheduling module, the AI intelligent scheduling module sends a command to an elevator controller, the elevator is controlled to reach a designated floor in advance according to the time recorded by the starting time stamp, the elevator is waited for riding, in a peak period mode, if the weight in the lift car reaches the maximum capacity of the lift car, the two-third of the maximum loading capacity of the lift car does not reach the maximum loading capacity of the lift car, the elevator is controlled to stop the elevator in a normal mode, and if the elevator door is not closed continuously, the elevator door is controlled to be closed again in a three-third elevator operation mode.
Through setting the peak time mode, the AI intelligent scheduling module marks the peak time stamp according to a preset algorithm and uploads the peak time stamp to the cloud server, the cloud server performs data analysis on the peak time stamp, a preset condition is achieved, an initial time stamp is created, the initial time stamp is sent to the AI intelligent scheduling module, the AI intelligent scheduling module waits for taking according to the time information and the floor information recorded by the initial time stamp from the appointed time to the floor with the largest appointed number of people in advance, and the technical problem that the existing elevator cannot intelligently identify the peak time and cannot reach the floor with the largest appointed number of people in advance in the peak time is effectively solved.
Example two
Referring to fig. 1-2 and fig. 5, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller according to a preset algorithm to control the elevator to run;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the pre-judging and scheduling mode can learn the elevator taking requirement of the passengers, and pre-mobilize the elevators to reach the appointed floor when the passengers appear;
the pre-judging scheduling mode comprises a face recognition module, the face recognition module collects face information and submits the face information to a data analysis processing module, the data analysis processing module compares and analyzes the face data, the analyzed face data is transmitted to an AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to an elevator controller according to a preset algorithm to control the elevator to operate.
The entrance face recognition module of the gate entrance of the first floor and the entrance face recognition module of the safety exit of each floor can collect face information in advance and make judgment in advance, face information is collected through the face recognition module and transmitted to the data analysis module, the data analysis processing module inquires a user riding information database in the cloud server, the user riding information is inquired through comparison and analysis of the face data, if the user riding information is not found in the database, a voice interaction mode is automatically entered, the user riding information database is automatically created according to riding floor information of passengers, a predicted riding model is generated through the riding information, the predicted riding model comprises X and Y values, X is a starting floor frequently ridden, Y is a target floor frequently ridden, the predicted riding model of the user is directly called if the user is found in the database, the predicted riding model is transmitted to the AI intelligent scheduling module, the AI intelligent scheduling module reaches the X floor according to the predicted riding model, after the passengers enter, the AI intelligent scheduling module controls the voice module to report whether the passengers go to X' the voice interaction mode, the passengers answer is submitted to the voice recognition module to identify the elevator, if the elevator is an affirmative, the elevator is controlled by the elevator is an automatic controller, and the voice interaction mode is answered if the elevator is answered by the answer to the voice interaction mode.
Example III
Referring to fig. 1-2 and fig. 6, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller according to a preset algorithm to control the elevator to run;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the intelligent speed control mode is used for intelligently controlling the speed according to passengers in the elevator, and the elevator can quickly reach a call floor when no person exists;
the intelligent speed control module comprises a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the elevator running speed.
The method comprises the steps of collecting pressure data in a car by a pressure sensor, transmitting the pressure data to a data analysis module, analyzing the pressure data in the car by the data analysis module, judging that no person exists according to a preset value, if the weight in the car is equal to zero, sending a command to an elevator controller by an AI intelligent scheduling module, controlling a driving unit of the car to quickly reach a specified floor at a speed of 5M/S by the elevator controller, judging that fewer persons exist according to the preset value, if the weight in the car is less than one third, sending a command to the elevator controller by the AI intelligent scheduling module, controlling the driving unit of the car to reach the specified floor at a speed of 2M/S by the elevator controller, judging that more persons exist according to the preset value, if the weight in the car is more than one third, sending a command to the elevator controller by the AI intelligent scheduling module, and controlling the driving unit of the car to reach the specified floor at a speed of 1.25M/S by the elevator controller.
Through setting up intelligent accuse speed module, gather the weight in the car by pressure sensor, if the weight in the car is zero, then elevator controller control car 'S drive unit reaches appointed floor with 5M/S' S speed, if the weight in the car is less than one third, elevator controller control car 'S drive unit reaches appointed floor with 2M/S' S speed, if the weight in the car is greater than two thirds, elevator controller control car 'S drive unit reaches appointed floor with 1.25M/S' S speed, make the demand floor of arriving fast when unmanned, the elevator drive unit of protection is gone up and down slowly to many times, the effectual elevator that has solved now can not intelligent control speed, when unmanned call in the car, can not arrive the call floor fast.
Example IV
Referring to fig. 1-2 and fig. 7, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller according to a preset algorithm to control elevator operation;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the APP reservation mode submits a reservation riding form through a user, and the elevator can reach a designated floor at a contracted time;
the APP pre-call mode comprises a mobile phone end APP, the mobile phone end APP collects face data and submits a reservation riding form to a cloud server, the cloud server analyzes the face data and processes the reservation riding form, the cloud server sends the analyzed face data and the processed reservation riding form to an AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to an elevator controller to control elevator operation according to a preset algorithm.
When the mobile phone terminal APP is used for the first time, face data are required to be acquired through the mobile phone terminal APP, the face data are uploaded to the cloud server, then a reservation user database is created by the cloud server, when a user reserves, the reservation riding form is filled in according to prompts, the reservation riding form comprises riding floors, a destination floor and reservation riding time, wherein the information of the filled floors exceeds the floor range of the riding floors or the reservation riding time exceeds the current time for five minutes and is invalid, the reservation riding form is effectively submitted to the cloud server, the reservation riding form is sent to the AI intelligent scheduling module by the cloud server, an instruction is sent to the elevator controller by the AI intelligent scheduling module to control the elevator to go to the designated floors at the designated times, after the elevator reaches the designated floors at the designated times, the face recognition module detects that the passenger submits the form, the passenger automatically goes to the designated floors after the elevator enters the designated floors (the passenger can select the manual selection floors or the voice interaction control mode to control the elevator to change the destination floors in the process of going to the designated floors), after the elevator does not detect the fact that the form is submitted by the module, the elevator exits the pre-call mode, and the elevator does not go to the designated floors.
Example five
Referring to fig. 1-2 and fig. 8, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller according to a preset algorithm to control the elevator to run;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the intelligent ventilation mode is intelligently opened or closed according to the number of passengers in the elevator;
the intelligent ventilation mode comprises a fresh air ventilator and a pressure sensor, the pressure sensor transmits collected pressure data to a data analysis processing module, the data analysis processing module transmits the analyzed pressure data to an AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to an elevator controller according to a preset algorithm to control the fresh air ventilator to operate.
The pressure sensor collects pressure data in the elevator car and transmits the pressure data to the data analysis and processing module, the data analysis and processing module analyzes the pressure data, if the pressure sensor detects that the weight in the elevator car is less than one third of the maximum load of the elevator, the AI intelligent scheduling module sends an instruction to the elevator controller to close the fresh air ventilator, and if the pressure sensor detects that the weight in the elevator car is greater than one third of the maximum load of the elevator, the AI intelligent scheduling module sends an instruction to the elevator controller to open the fresh air ventilator.
Example six
Referring to fig. 1-2 and fig. 9, an intelligent elevator dispatching system based on AI intelligence comprises an AI intelligent dispatching module, wherein the AI intelligent dispatching module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller according to a preset algorithm to control the elevator to run;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode, a voice interaction mode and a voice interaction mode;
the voice interaction mode can identify the voice elevator taking information of the passengers and reach the appointed floor according to the voice elevator taking information;
the voice interaction mode comprises a voice broadcasting module, a voice recognition module and a pressure sensor, wherein the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, the AI intelligent scheduling module controls and starts the voice broadcasting module to report preset contents according to a preset algorithm, the voice recognition module intelligently recognizes voice information of passengers and converts the voice information into digital information to be transmitted to the AI intelligent scheduling module, and the AI intelligent scheduling module sends instructions to the elevator controller to control elevator operation according to the preset algorithm.
When passengers enter the elevator car, the pressure sensor collects pressure data in real time and transmits the pressure data to the data analysis processing module, if the data analysis processing module detects that the pressure data changes, an interactive signal is sent to the AI intelligent scheduling module, the AI intelligent scheduling module starts the voice broadcasting module, the voice recognition module recognizes the answer of the passengers according to the preset content to broadcast the 'honored passengers are good, the passengers want to go to which floor', the voice recognition module converts the voice information into digital information and transmits the digital information to the data analysis processing module for analysis processing, and the AI intelligent scheduling module sends an instruction to the elevator controller to control the elevator to go to the floor answered by the passengers.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (7)
1. The utility model provides an elevator intelligent scheduling system based on AI intelligence, includes AI intelligent scheduling module, its characterized in that: the AI intelligent scheduling module comprises a data analysis processing module and an elevator controller, and sends an instruction to the elevator controller to control the elevator to run according to a preset algorithm;
the AI intelligent scheduling module comprises a rush hour mode, an APP reservation mode, a pre-judging scheduling mode, an intelligent speed control mode, an intelligent ventilation mode and a voice interaction mode;
the peak period mode intelligently identifies the peak period, and the floor with the largest number of people is reached in the appointed elevator taking peak period;
the APP reservation mode submits a reservation riding form through a user, and the elevator can reach a designated floor at a contracted time;
the pre-judging and scheduling mode can learn the elevator taking requirement of the passengers, and pre-mobilize the elevators to reach the appointed floors when the passengers appear;
the pre-judging scheduling mode comprises a face recognition module, wherein the face recognition module collects face information and submits the face information to the data analysis processing module;
the data analysis processing module automatically creates a user riding information database according to riding floor information of passengers and generates a prediction riding model through riding information;
the intelligent speed control mode is used for intelligently controlling the speed according to passengers in the elevator, and the elevator can quickly reach a call floor when no person exists;
the intelligent ventilation mode is intelligently opened or closed according to the number of passengers in the elevator;
the voice interaction mode can identify the voice elevator taking information of the passengers and reach the appointed floor according to the voice elevator taking information;
the peak period mode comprises a cloud server and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module marks a peak time stamp according to a preset algorithm and uploads the peak time stamp to the cloud server;
the APP reservation mode comprises a mobile phone end APP, the mobile phone end APP collects face data and submits reservation riding forms to the cloud server, the cloud server analyzes the face data and processes the reservation riding forms, the cloud server sends the analyzed face data and the processed reservation riding forms to the AI intelligent scheduling module, and the AI intelligent scheduling module sends instructions to the elevator controller to control elevator operation according to a preset algorithm.
2. The intelligent elevator dispatching system based on AI intelligence of claim 1, wherein: the cloud server analyzes the peak time stamp, creates or deletes the starting time stamp according to a preset algorithm, and sends the starting time stamp to the AI intelligent scheduling module, and the AI intelligent scheduling module controls the elevator to operate according to the preset algorithm.
3. The intelligent elevator dispatching system based on AI intelligence of claim 1, wherein: the data analysis processing module compares and analyzes the face data, the analyzed face data is transmitted to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the elevator to operate.
4. The intelligent elevator dispatching system based on AI intelligence of claim 1, wherein: the intelligent speed control module comprises the pressure sensor, the pressure sensor transmits the collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the elevator running speed.
5. The intelligent elevator dispatching system based on AI intelligence of claim 1, wherein: the intelligent ventilation mode comprises a fresh air ventilator and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control the fresh air ventilator to operate.
6. The intelligent elevator dispatching system based on AI intelligence of claim 1, wherein: the voice interaction mode comprises a voice broadcasting module, a voice recognition module and a pressure sensor, the pressure sensor transmits collected pressure data to the data analysis processing module, the data analysis processing module transmits the analyzed pressure data to the AI intelligent scheduling module, and the AI intelligent scheduling module controls and starts the voice broadcasting module to broadcast preset contents according to a preset algorithm.
7. The intelligent elevator dispatching system based on AI intelligence of claim 6, wherein: the voice recognition module intelligently recognizes voice information of passengers, converts the voice information into digital information and transmits the digital information to the AI intelligent scheduling module, and the AI intelligent scheduling module sends an instruction to the elevator controller according to a preset algorithm to control elevator operation.
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