CN110851970B - Pedestrian statistics and management method in building evacuation channel based on CO2 concentration - Google Patents
Pedestrian statistics and management method in building evacuation channel based on CO2 concentration Download PDFInfo
- Publication number
- CN110851970B CN110851970B CN201911060109.3A CN201911060109A CN110851970B CN 110851970 B CN110851970 B CN 110851970B CN 201911060109 A CN201911060109 A CN 201911060109A CN 110851970 B CN110851970 B CN 110851970B
- Authority
- CN
- China
- Prior art keywords
- concentration
- density
- personnel
- time
- pedestrian
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/004—Specially adapted to detect a particular component for CO, CO2
Abstract
The invention discloses a method for statistically managing pedestrians in a building evacuation channel based on CO2 concentration, which comprises the following steps: step 1, monitoring personnel density and CO in evacuation channels of buildings in real time 2 Concentration, realizing real-time acquisition of data; step 2, processing the acquired data to obtain a graph of the change of the personnel density along with time and CO 2 A concentration profile over time; step 3, performing function fitting on the obtained graph to obtain CO 2 A quantitative relationship of concentration over time and a quantitative relationship of personnel density over time; step 4, obtaining personnel density and CO 2 Quantitative relation of concentration; and 5, compiling the obtained quantitative relation, embedding the quantitative relation into a computer host, and finally finishing statistics of personnel density and personnel flow in the pedestrian channel.
Description
Technical Field
The invention relates to a statistical technology for pedestrians at entrances, exits, channels and the like of various public buildings, in particular to a method for statistical and management of pedestrians in evacuation channels of buildings based on CO2 concentration, which can be widely applied to pedestrian channels in subways, stations, gymnasiums, exhibition halls, malls and the like for personal statistical and pedestrian management.
Background
With the rapid development of economy, more and more people are rushing into cities. Many public facilities in cities, such as malls, subways, exhibitions, etc., will peak traffic in short time, especially holidays. In recent years, trampling casualties caused by overcrowding pedestrian flows occur in various places, so that real-time statistics and pedestrian flow management on the passenger flow density of pedestrian channels in the places are important. In addition, the crowd density estimation technology plays an important role in the fields of public security, management and control of transportation hubs such as airport stations and the like, and can also provide basis for business decisions and pedestrian flow management.
The statistics method of the current personnel can be mainly summarized as follows: a personnel counting method based on machine vision, a personnel counting method of a sensor, a personnel counting method of a mobile communication network signaling, a personnel counting method based on WiFi and a personnel counting method of a channel gate.
(1) Personnel statistics method based on machine vision
With the improvement of computer hardware technology, a great deal of achievements have been published on the study of machine learning algorithms for image processing in the technology of personnel statistics based on machine vision. These methods accomplish statistics of the number of people by detecting physical features of the human body in the image, but these features are difficult to conform to complex features in the monitored scene. The object characteristics, the shape judgment conditions and the marked object areas are set by adopting a connected component detection algorithm to fulfill the aim of counting the number of people, but larger errors are caused when the distance between people is smaller.
(2) People counting method of sensor
The people counting system based on the flexible force sensor is used for acquiring pressure footprints of pedestrians in real time by utilizing the flexible force sensor, acquiring target footprints and characteristic values thereof by denoising data, dividing graphs, extracting characteristics and the like, and finally realizing people counting by utilizing a characteristic matching and motion trail planning algorithm. The system can respond to the demand quickly and has good stability. The system has higher requirements on the production quality of the sensor, and when the number of people is relatively complex and dense and objects except pedestrians exist, the situation of complex errors caused by the segmentation of the human footprint can occur, so that the accuracy of people counting can be reduced. And the concealment of the system when applied in a real scene is common.
(3) People counting method for mobile communication network signaling
Through the analysis of mobile phone signal data, the real-time statistics of personnel is realized. And (3) utilizing the data acquisition interface mobile phone information original data, and realizing personnel statistics through analysis and processing so as to obtain dynamic information of urban population distribution. The system successfully realizes the intelligent statistics of real-time personnel in the monitoring area, can monitor the distribution condition of the number of people in each area in real time, and provides data support for government related management departments. However, the source data collected by the method is not full-network information, the data result is not strict enough, in addition, the privacy rights of the monitored crowd objects are seriously infringed, and the passive collection of personal information has potential hidden trouble on personal safety.
(4) WiFi-based people counting method
And acquiring WiFi probe data by utilizing communication between mobile devices connected to WiFi of the intelligent routing, taking the MAC address of the mobile device as basic statistical data, and acquiring the traffic situation in the monitoring area in real time through the intelligent routing equipment deployed in the monitoring area. Under ideal conditions, the method not only can realize accurate monitoring of the flow of people, but also can realize the functions of visiting frequency, residence time, distribution condition of new and old customers and the like of a monitoring area. This assumption has a certain subjectivity, for example, one person, one machine, and active access to WiFi, which results in a lower accuracy of the result of the method.
(5) People counting method for channel gate
In modern life, with the acceleration of the pace of life and work, traffic tools such as airports, high-speed rails, subways and the like are indispensible from the life of people, and the traffic tools are placed in gate channels of an import and export, so that the traffic tools are necessary tools for the management party to manage efficiently. The gate usually embeds other modules, such as counting module to count the number of people, pedestrian detection module to control the entrance and exit, ticket module to realize electronic ticket, etc., so as to achieve the effect of intelligent management of gate. The application occasion of the method is limited, the efficiency is low, and the passing experience of people is affected.
At present, the early warning of people stream congestion mainly comprises the following modes:
mode one: and (5) manual intervention. Before a meeting event such as a large-scale event, an exhibition and the like occurs on a large-scale activity site, the number of seats, the seating rate and the number of site service management personnel are required to be analyzed in advance, the total number of personnel during the meeting is estimated, and safe people flow management and emergency measures are formulated according to the predictions of the meeting scale, the user types and the user communication requirements. The first mode has a limited early warning range, depends on the experience of organization personnel, increases the uncertainty of early warning work, has poor real-time responsiveness, and cannot solve the problem of sporadic and unpredictable people flow congestion.
Mode two: and (5) video monitoring. According to the scene monitored by the video, the video information is automatically processed by utilizing the current advanced machine vision and computer graphic image video analysis technology, the people stream of the monitored place is determined, and the people stream is compared with the preset people stream peak value of the monitored place, and the response is carried out according to the preset emergency measure. The second mode needs to deploy the video device in advance, and can only be deployed in important public places such as scenic spots, stations, wharfs and other important areas, otherwise, the cost is high, so that the early warning range of the second mode is limited. In addition, the second mode needs to perform digital feature extraction on the people stream in the video information to perform automatic processing analysis, and the existing crowd feature algorithm based on pixel statistics and the existing crowd feature algorithm based on texture have limitations in terms of description precision and complexity, so that the influence caused by interference factors such as angle transformation of a projection deformity camera is difficult to overcome. Aiming at large-scale groups, the second mode needs to further explore a more efficient and accurate people stream digital characteristic description mode.
Mode three: and monitoring an Internet of things sensor. The third mode is different from the second mode in that: the third mode can obtain more comprehensive and more dimensional people stream information (including crowd speed, global Positioning System (GPS) information and the like) than the second mode by using a sensor installed in a public place such as a transportation hub and even a sensor installed in a vehicle in a moving state. The mode three relies on more advanced mode recognition technology, artificial intelligent machine learning, deep learning and other technologies to perform early warning response. However, the third mode is still in the initial stage, the installation coverage of the sensor is more limited, and a great amount of acquired information has higher requirements on the arithmetic processing capacity and higher required cost.
In addition, in view of the limitation and cost consideration of the computing capability of the front end (i.e., the data acquisition end, the second mode is the field deployment video device, and the third mode is the sensor), the general front-end people stream early warning algorithm cannot be realized at present. If a large amount of video data collected by the front end is transmitted to the background in real time, and then the background carries out people stream early warning, the requirement on network transmission is high. Meanwhile, the complexity of early warning is increased, and great challenges are brought to data analysis, processing and storage.
In addition, as the progress of urban ization increases, various public buildings, particularly commercial buildings, are diversified in form, and as the scale of the buildings increases, pedestrian passages and pedestrian entrances and exits of the buildings also increase. However, pedestrians have a preference for building channels and entrances, so that some of the channels and entrances of the building are too many or overloaded, but other entrances are not reasonably utilized.
Disclosure of Invention
Aiming at the problems, the invention discloses a pedestrian flow management method in a building evacuation channel based on CO2 concentration, and the pedestrian flow management of the building evacuation channel is realized based on the method. Due to the respiration of human body, every pedestrian is CO 2 A source of release by using CO 2 Concentration detector pairs for CO in a channel 2 Monitoring and collecting concentration, and collecting CO 2 And the concentration data is transmitted to a computer host for real-time calculation, analysis and early warning, and finally, statistics of pedestrian flow density and pedestrian flow in the channel and management of pedestrian flow are realized.
The invention is realized by the following scheme:
step 1, monitoring personnel density and CO in evacuation channels of buildings in real time 2 Concentration, realizing real-time acquisition of data;
step 2, processing the data acquired in the step 1 to obtain a graph of the change of the personnel density along with time and CO 2 A concentration profile over time;
step 3, performing function fitting on the graph obtained in the step 2 to obtain CO 2 A quantitative relationship of concentration over time and a quantitative relationship of personnel density over time;
step 4, obtaining personnel density and CO 2 Quantitative relation of concentration;
and 5, compiling the quantitative relation obtained in the step 4, embedding the quantitative relation into a computer host, and finally finishing statistics of personnel density and personnel flow in the pedestrian channel.
Preferably, the person density in step 1 is the number of persons per unit area in a certain area at a given moment, the person per unit/m 2 ；CO 2 CO contained in a gas having a concentration of one million volumes 2 Is given in ppm;
preferably, the data is processed with origin software in step 2, and Gauss curve function fitting is used in step 3.
Preferably, CO in the step 3 2 The quantitative relationship of concentration over time is as follows:
；
wherein C is CO 2 Concentration, ppm; t is time, s;
the quantitative relationship of the change of the personnel density with time is as follows:
；
in the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the t is time, s.
Preferably, the personnel density and CO in the step 4 2 The quantitative relationship of concentration is divided into three stages:
(2) The linear fitting formula of the first stage is:
；
correlation coefficient；
(2) The nonlinear fitting formula of the second stage is:
；
correlation coefficient；
(3) The curve polynomial fitting formula of the third stage is:
；
correlation coefficient；
In the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the C is CO 2 Concentration, ppm.
The invention also discloses a method for managing pedestrian flow in the evacuation channel of the building based on the concentration of CO2, which comprises the following steps:
by CO 2 The concentration detector, the host and the voice broadcasting system form a hardware platform;
wherein: CO 2 The concentration detector is arranged on a pedestrian building channel and used for collecting CO 2 Concentration, host and CO 2 The concentration detector is connected with a data acquisition line for passing CO 2 CO in detector acquisition channel 2 Concentration data and complete the channelCorresponding operation of the density of the inner pedestrian; the voice broadcasting system is automatically triggered when the pedestrian density exceeds the upper limit value specified by the building, and broadcasts the pedestrian use condition of each evacuation channel and each exit in real time to give a passing suggestion, so that pedestrian flow management is realized.
The beneficial effects are that:
(1) Due to respiration of human body, every person is a CO 2 A release source for releasing a certain amount of CO 2 Thereby leading the CO of the evacuation channel to 2 The concentration changes. And CO 2 Sensor pair CO 2 The detection of the concentration is extremely sensitive, so that the personnel density and the personnel flow can be estimated more accurately.
（2）CO 2 The sensor has low price, small volume, no interference and no terminal. Since they are also conventionally available in conventional central air conditioning systems, no additional investment in existing infrastructure is required.
(3) The system automatically triggers the voice broadcasting system, realizes the automatic control of pedestrian flow management, and does not need to additionally input management personnel.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is CO 2 Concentration and personnel density versus time plot;
FIG. 2 is a graph of personnel density and CO 2 A concentration relationship graph;
FIG. 3 is a schematic view of CO in a building evacuation channel 2 And a pedestrian flow detection and voice broadcasting pedestrian flow management system schematic diagram.
In the figure, 1# inlet, 2# inlet, 3# inlet, 4# inlet, 5, CO 2 The detector, 6, the host computer, 7, the voice broadcasting device, 8, the data acquisition line,9. voice transmission line, 10, building passageway.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings of the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.
In the description of the present invention, it should be understood that the terms "inner", "outer", "left", "right" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element in question must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In order to achieve the above purpose, the method for estimating the pedestrian flow and the density of the channel provided by the invention comprises the following steps:
step 1, monitoring the personnel number and CO in a certain representative building evacuation channel in real time 2 Concentration, realizing real-time acquisition of data. Wherein the person density is the number of persons per unit area in a certain area at a given moment, and the unit person/m 2 ；CO 2 CO contained in a gas having a concentration of one million volumes 2 Is given in ppm;
step 2, processing the data acquired in the step 1 by using origin software to obtain personnel density and CO 2 Concentration versus time graph (e.g., fig. 1);
step 3, for the personnel density and CO obtained in step 2 2 Gauss curve function fitting is carried out on a concentration change curve graph with time, and the following steps are obtained:
（1）CO 2 quantitative relationship of concentration over time:
；
wherein C is CO 2 Concentration, ppm; t is time, s;
(2) The quantitative relationship of the change of the personnel density with time is as follows:
；
in the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the t is time, s.
Step 4, obtaining personnel density and CO through the step 1 2 A scatter diagram of the concentration finds that the distribution of the data points has obvious regularity and relativity, and the scatter diagram is subjected to curve fitting to obtain the personnel density and the CO 2 Quantitative relationship of concentration as shown in FIG. 2.
Personnel density and CO 2 The quantitative relationship of concentration is divided into three stages: such as (FIG. 2)
(1) The linear fitting formula of the first stage is:
；
correlation coefficient QUOTE />；
(2) The nonlinear fitting formula of the second stage is:
；
correlation coefficient；
(3) The curve polynomial fitting formula of the third stage is:
；
correlation coefficient；
In the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the C is CO 2 Concentration, ppm.
Step 5, for the personnel density and CO obtained in step 4 2 Compiling a program according to a quantitative relation of concentration, and embedding the program into a host computer; by CO 2 The hardware platform that concentration detector, host computer and pronunciation broadcasting system constitute, wherein: wherein: CO 2 The concentration detector is arranged on the pedestrian building channel (collecting CO) 2 Concentration), the host is an operation part (calculating personnel density), the host and CO 2 The concentration detector is connected with a data acquisition line for passing CO 2 CO in detector acquisition channel 2 Concentration data and completing corresponding operation on pedestrian density in the channel; the voice broadcasting system is automatically triggered when the pedestrian density exceeds the upper limit value specified by the building, and broadcasts the pedestrian use condition of each evacuation channel and each exit in real time to give a passing suggestion, so that pedestrian flow management is realized. Specific CO 2 The concentration pedestrian flow detection and voice broadcast pedestrian flow management system is shown in fig. 3.
As shown in FIG. 3, the invention aims to provide a system based on CO in each passage of a building 2 Concentration variation is used in pedestrian flow management. The method adopts CO 2 The concentration detector (1), the voice broadcasting system (2) and the host computer (3) form a hardware platform to realize the management of pedestrian flow. CO 2 Concentration detector (1)The system is arranged in each passage of a building and near the position of an outlet, is connected with a host (3) through a data acquisition line, transmits data to the host (3), the host (3) completes corresponding operation of pedestrian crowd density estimation in each passage and each outlet, and the host (3) is linked with a voice broadcasting system (2) when the CO is 2 After the concentration exceeds the upper limit value specified by the building, the voice broadcasting system (2) is automatically triggered to broadcast the pedestrian use condition of each channel and outlet in real time, and a passing suggestion is given, so that pedestrian flow management is realized.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (3)
1. The pedestrian counting method for the evacuation channel of the building based on the CO2 concentration is characterized by comprising the following steps of:
step 1, monitoring personnel density and CO in evacuation channels of buildings in real time 2 Concentration, realizing real-time acquisition of data;
step 2, processing the data acquired in the step 1 to obtain a graph of the change of the personnel density along with time and CO 2 A concentration profile over time;
step 3, performing function fitting on the graph obtained in the step 2 to obtain CO 2 A quantitative relationship of concentration over time and a quantitative relationship of personnel density over time;
the quantitative relationship is as follows:
；
wherein C is CO 2 The concentration of the water in the water is higher,ppm; t is time, s;
the quantitative relationship of the change of the personnel density with time is as follows:
；
in the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the t is time, s;
step 4, obtaining personnel density and CO 2 Quantitative relation of concentration; personnel density and CO 2 The quantitative relation of the concentration is divided into three stages;
(1) The linear fitting formula of the first stage is:
；
correlation coefficient；
(2) The nonlinear fitting formula of the second stage is:
；
correlation coefficient；
(3) The curve polynomial fitting formula of the third stage is:
；
correlation coefficient；
In the method, in the process of the invention,for person density, person/m 2 The method comprises the steps of carrying out a first treatment on the surface of the C is CO 2 Concentration, ppm;
and 5, compiling the quantitative relation obtained in the step 4, embedding the quantitative relation into a computer host, and finally finishing statistics of personnel density and personnel flow in the pedestrian channel.
2. The method for counting people in evacuation channels of a building based on concentration of CO2 according to claim 1, wherein the people density in step 1 is the number of people per unit area in a certain area at a given moment, and the number of people per unit/m 2 ；CO 2 CO contained in a gas having a concentration of one million volumes 2 In ppm.
3. The CO2 concentration-based pedestrian evacuation channel interior pedestrian statistics method according to claim 1, wherein the data is processed by origin software in the step 2, and a Gauss curve function fit is adopted in the step 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911060109.3A CN110851970B (en) | 2019-11-01 | 2019-11-01 | Pedestrian statistics and management method in building evacuation channel based on CO2 concentration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911060109.3A CN110851970B (en) | 2019-11-01 | 2019-11-01 | Pedestrian statistics and management method in building evacuation channel based on CO2 concentration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110851970A CN110851970A (en) | 2020-02-28 |
| CN110851970B true CN110851970B (en) | 2023-07-21 |
Family
ID=69599323
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911060109.3A Active CN110851970B (en) | 2019-11-01 | 2019-11-01 | Pedestrian statistics and management method in building evacuation channel based on CO2 concentration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110851970B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012002504A (en) * | 2011-09-05 | 2012-01-05 | Toshiba Corp | Sensor system for measuring carbon dioxide concentration, and carbon dioxide sensor |
| CN104021643A (en) * | 2014-06-17 | 2014-09-03 | 北京化工大学 | Emergency evacuation method and system capable of intelligently changing directions |
| CN106839322A (en) * | 2017-02-23 | 2017-06-13 | 林兴斌 | The real-time ventilation air calculation procedure of multizone and its implementation |
| TWI630578B (en) * | 2017-03-22 | 2018-07-21 | 崑山科技大學 | Member quantity control system and member quantity control method |
| CN108664452A (en) * | 2018-05-07 | 2018-10-16 | 北京工业大学 | A kind of indoor occupant number determination method and determining system |
| CN109442695A (en) * | 2018-11-12 | 2019-03-08 | 清华大学 | Air-conditioning and fresh air system predictability control method and system based on occupancy |
| CN110208459A (en) * | 2019-05-23 | 2019-09-06 | 南京理工大学 | The on-line monitoring method and system of TVOC concentration in crowded place room |
-
2019
- 2019-11-01 CN CN201911060109.3A patent/CN110851970B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012002504A (en) * | 2011-09-05 | 2012-01-05 | Toshiba Corp | Sensor system for measuring carbon dioxide concentration, and carbon dioxide sensor |
| CN104021643A (en) * | 2014-06-17 | 2014-09-03 | 北京化工大学 | Emergency evacuation method and system capable of intelligently changing directions |
| CN106839322A (en) * | 2017-02-23 | 2017-06-13 | 林兴斌 | The real-time ventilation air calculation procedure of multizone and its implementation |
| TWI630578B (en) * | 2017-03-22 | 2018-07-21 | 崑山科技大學 | Member quantity control system and member quantity control method |
| CN108664452A (en) * | 2018-05-07 | 2018-10-16 | 北京工业大学 | A kind of indoor occupant number determination method and determining system |
| CN109442695A (en) * | 2018-11-12 | 2019-03-08 | 清华大学 | Air-conditioning and fresh air system predictability control method and system based on occupancy |
| CN110208459A (en) * | 2019-05-23 | 2019-09-06 | 南京理工大学 | The on-line monitoring method and system of TVOC concentration in crowded place room |
Non-Patent Citations (2)
| Title |
|---|
| 刘德峰 ; 袁锁中 ; .基于二氧化碳测量的室内人数估计算法.兵工自动化.2018,(第02期),全文. * |
| 张茜 ; 陈涛 ; 吕显智 ; .建筑智能疏散系统架构.消防科学与技术.2011,(03),全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110851970A (en) | 2020-02-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109644320B (en) | Method for detecting pedestrian flow in public place by using WI-FI probe | |
| CN106297288B (en) | A kind of acquisition of bus passenger passenger flow data and analysis method | |
| CN110493816A (en) | A kind of real-time predicting method for handing over the subway station volume of the flow of passengers for rail | |
| JP3243234B2 (en) | Congestion degree measuring method, measuring device, and system using the same | |
| CN108200566B (en) | People flow congestion early warning method and device | |
| CN105117683B (en) | Detection and early warning method for dense crowd in public place | |
| WO2004042673A2 (en) | Automatic, real time and complete identification of vehicles | |
| CN207164830U (en) | Structural fire protection emergency evacuation indicates system | |
| CN110545558A (en) | High-speed service area crowd density estimation system based on Wi-Fi data | |
| CN109544946A (en) | Tunnel real-time monitoring and managing system and its implementation based on vehicle flowrate big data | |
| CN113033293A (en) | Access & exit management equipment, system and method | |
| CN107240289A (en) | A kind of bus routes optimum management method and system | |
| Elhamshary et al. | Crowdmeter: Congestion level estimation in railway stations using smartphones | |
| WO2012111138A1 (en) | Pedestrian movement information detection device | |
| CN113077084A (en) | Tourist attraction visitor flow early warning device | |
| CN111380530A (en) | Navigation method and related product | |
| CN112528867B (en) | Early warning method for sudden large passenger flow of subway station and application thereof | |
| CN110851970B (en) | Pedestrian statistics and management method in building evacuation channel based on CO2 concentration | |
| CN114399726A (en) | Method and system for intelligently monitoring passenger flow and early warning in real time | |
| KR101222887B1 (en) | Information System for User in Large Scale facilities | |
| CN111524371A (en) | Traffic flow and road section vehicle quantity detection system | |
| CN110046535B (en) | Intelligent travel time prediction system, method and storage medium based on machine learning | |
| KR102511626B1 (en) | Apparatus and Method for Object Counting by Type Using Artificial Intelligence-Based Edge Computing | |
| JP7246213B2 (en) | Support management device and support management method | |
| CN112785462A (en) | Scenic spot passenger flow volume statistics evaluation system based on big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |