CN113283374A - Face recognition station passenger state monitoring and early warning system based on Internet of things - Google Patents
Face recognition station passenger state monitoring and early warning system based on Internet of things Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 108
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Abstract
The invention discloses a face recognition station passenger state monitoring and early warning system based on the Internet of things, which comprises: the system comprises an inbound image acquisition module, a passenger position locking module and a monitoring and early warning module, wherein the monitoring and early warning module comprises ticket checking monitoring and early warning and smoking monitoring and early warning. The invention can monitor the state of the passenger according to various conditions, implement different early warning modes according to different states of the passenger, and even remind the passenger point to point according to special conditions.
Description
Technical Field
The invention relates to the technical field of station passenger state monitoring, in particular to a human face recognition station passenger state monitoring and early warning system based on the Internet of things.
Background
With the rapid development of the internet of things, the internet of things gradually enters the visual field of people and is interconnected through everything, so that the actual requirements of people are met, and great convenience is brought to the life of people. With the popularization of the face recognition technology in actual life, people can recognize and confirm the face of people, and then different people can be distinguished.
In the aspect of the current monitoring technology for the state of passengers at a station, only the voice report is carried out on the ticket checking vehicle during ticket checking, but due to some special conditions, the passengers cannot hear the broadcast content in time, so that the ticket checking time is missed, and meanwhile, in the station, although smoking is forbidden, specific monitoring measures are still incomplete, the monitoring degree is not high, the monitoring effect is poor mainly depending on the consciousness of the passengers.
To the above situation, we need a face identification station passenger state monitoring and early warning system based on the internet of things, which can monitor the state of passengers according to various situations, implement different early warning modes according to the difference of the states of the passengers, even carry out point-to-point reminding on the passengers, the mode monitoring and early warning effects are better, the monitoring efficiency on the passengers is higher, the situation that the passengers smoke can be effectively avoided, and meanwhile, the situation that the passengers miss the corresponding train ticket checking time can be effectively avoided.
Disclosure of Invention
The invention aims to provide a human face recognition station passenger state monitoring and early warning system based on the Internet of things, and aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the utility model provides a face identification station passenger state monitoring early warning system based on thing networking, includes: an image acquisition module for entering a station, a passenger position locking module and a monitoring and early warning module, wherein the monitoring and early warning module comprises a ticket checking monitoring and early warning module and a smoking monitoring and early warning module,
the station-entering image acquisition module is used for carrying out face recognition and journey data extraction on passengers when the passengers enter the station through security check equipment of the station, extracting appearance characteristics of the passengers and binding face information, the appearance characteristics and the journey data of the passengers;
the passenger position locking module is used for acquiring images of passengers in each waiting room through the cameras in each waiting room, comparing the acquired images with the face information and the appearance characteristics of passengers entering the station, further determining passengers corresponding to the acquired images, and binding the current positions of the passengers with the passenger information;
the smoking monitoring and early warning module monitors smoke through the smoke collecting devices in the waiting rooms, and when a certain smoke collecting device monitors that the smoke content exceeds a specified index, the smoking monitoring and early warning module can transfer the adjacent cameras of the smoke collecting device to collect images in the area, judge a smoke source, lock the identity of a smoker and give a smoking alarm;
the ticket checking monitoring and early warning module is used for carrying out early warning reminding on passengers corresponding to corresponding trains in corresponding time before and after train ticket checking according to the travel information of passengers entering the station, which is acquired by the image acquisition module, and the positions of the passengers, which are acquired by the passenger position locking module.
The system and the method realize monitoring and early warning of the state of the passengers through the cooperative cooperation of all modules, the inbound image acquisition module mainly acquires the information of the inbound passengers, the passenger position locking module mainly determines the positions of the passengers through a camera and binds the current positions of the passengers with the passengers, the smoking monitoring and early warning module mainly monitors the smoking states of the passengers and takes different early warning measures according to different monitoring results, the ticket checking monitoring and early warning module mainly monitors the states of the passengers in different time periods when ticket checking starts and takes different early warning measures according to different time periods and different states of the passengers.
Further, the appearance features in the inbound image acquisition module include: the hairstyle of passengers when entering the station, the color, pattern and style of the clothes, whether the passengers carry the luggage and the size and color of the carried luggage,
the color, pattern and style of the clothes worn by the passengers are classified as the first type of appearance characteristics,
the hairstyle of passengers when entering the station is classified as a second type of appearance characteristic,
whether the passengers carry the luggage or not and the size and the color of the luggage carried by the passengers are classified into the third type of appearance characteristics;
the trip data includes: the number of the vehicle, the corresponding waiting room number, the ticket number, the seat number and the reserved mobile phone number when the passenger starts from the station.
The appearance characteristics are divided into three types by the inbound image acquisition module, because the hair style is the least easy to change, the color, the pattern and the style of clothes worn by passengers can be influenced by the temperature in a station or personal wishes of the passengers, when the passengers take off the outer clothes, the appearance characteristics can be changed, the appearance characteristics of the third type are also easy to change and even can be transferred to other passengers, and therefore, the appearance characteristics are divided into three types more conveniently when being compared.
Furthermore, the passenger position locking module analyzes images collected by the numbered cameras in the waiting rooms simultaneously in a multithreading mode, identifies passengers in the images according to a specific identification mode, and binds passenger information with the current position, wherein areas shot by the numbered cameras in the waiting rooms are not intersected with each other.
The passenger position locking module controls a plurality of cameras, but in the aspect of data acquisition and analysis, the data needs to be analyzed and processed at the same time, so that the analysis and processing speed of the image can be increased by adopting a multithreading mode. The reason that the areas shot by the numbered cameras in the waiting rooms are not intersected is to avoid that passengers shot by the image intersection parts collected by the cameras are analyzed and processed for multiple times, so that the positions where the passengers are bound are not fixed, and the positions where the passengers are bound are displayed at the same time.
Further, the specific identification mode in the passenger position locking module comprises the following steps:
s1, acquiring the passenger appearance characteristics and the face information obtained from the inbound image acquisition module;
s2, carrying out gray level processing on the images collected by the numbered cameras in the waiting rooms at intervals of first unit time, comparing the difference between the gray levels of adjacent pixel points with a first preset value, recording the position of the pixel point with a larger gray level when the difference is larger than the first preset value, and extracting the corresponding picture information of the contour formed by the recorded pixel points in the original image;
s3, comparing the extracted picture information with the appearance characteristics corresponding to each passenger, and when the picture information contains any two types of appearance characteristics corresponding to a certain passenger, listing the face information and the appearance characteristics corresponding to the passenger into a first comparison database corresponding to the picture information;
s4, extracting the face information corresponding to each passenger in the first comparison database, and comparing the face information with the picture information respectively to obtain the similarity between the face information corresponding to each passenger and the picture information;
s5, taking the passenger corresponding to the highest similarity as the passenger corresponding to the picture information, carrying out timestamp marking on the passenger, and binding the passenger with the camera number corresponding to the waiting room corresponding to the picture information;
s6, counting the number of the timestamp marks acquired by each passenger in the second unit time, when the number of the acquired timestamp marks is greater than a second preset value, carrying out abnormal marking on the timestamp marks acquired by the passengers in the second unit time, re-identifying and comparing the picture information corresponding to the timestamp marks of the abnormal marks, listing the appearance features corresponding to the passengers into reference factors in the acquisition of the similarity, and solving the final similarity between the picture information and each passenger in the corresponding first comparison database;
s7, taking the passenger corresponding to the highest final similarity as the passenger corresponding to the picture information, deleting the timestamp mark of the abnormal mark corresponding to the picture information and the corresponding camera number in the bound corresponding waiting room, carrying out timestamp marking on the passenger corresponding to the highest final similarity, binding the passenger and the camera number corresponding to the waiting room corresponding to the picture information, wherein the position of the numbered camera corresponding to the waiting room corresponding to the picture information is the current position of the passenger.
Further, the smoking monitoring and early warning module acquires images acquired by the adjacent cameras of the smoke acquisition device in the area range, extracts the self and peripheral pictures of each passenger in the images,
processing the extracted picture according to the RGB value of each pixel, comparing the RGB value of each pixel in the extracted picture with a reference RGB value corresponding to the smoke color in a second comparison database, further extracting the pixels of which the RGB values conform to the smoke color in the extracted picture, then performing gray value processing on the obtained result, comparing the difference between the gray values of adjacent pixels after the gray value processing, marking the pixels of which the gray value difference is larger than the gray value corresponding to a first threshold value, acquiring the outline enclosed by the marked pixels according to the position relation among all the marked pixels, superposing the central point of the obtained outline and the central point of the smoke outline recorded in a second comparison database, wherein the smoke outline recorded in the second comparison database is a comparison file of the obtained outline, executing an outline comparison mode to acquire an error value w between the obtained outline and the comparison file,
when the error value w is less than or equal to the second threshold value, the extracted picture is determined to contain smoke, the picture containing smoke is arranged in a third comparison database,
when the error value w is larger than the second threshold value, the extracted picture is determined not to contain smoke,
the outline comparison mode is that a same plane rectangular coordinate system is established by taking a coincident central point as an original point, in the plane rectangular coordinate system, 360-degree circumference angles corresponding to the original point are equally divided by n, the original point is respectively taken as a starting point, each equal division line is established along the direction of each equal division point, coordinates corresponding to the intersection point of each equal division line in the plane rectangular coordinate system and the obtained outline and the comparison file are obtained, the distance between the coordinates and the intersection point of the obtained outline and the comparison file is calculated, the distances corresponding to all the equal division lines are accumulated, the average value is obtained, and the obtained average value is the error value between the obtained outline and the comparison file,
performing gray value processing on each picture in a third comparison database, comparing the gray value difference between adjacent pixel points to further obtain the corresponding contour of the object in the mouth and the hand of the passenger in the picture, coinciding the center point of the contour corresponding to the object in the mouth and the hand of the passenger in the picture with the center point of the contour of the recorded cigarette in a second comparison database, wherein the contour of the recorded cigarette in the second comparison database is a comparison file of the contour corresponding to the object in the mouth and the hand of the passenger in the picture, executing a contour comparison mode to obtain the error value m between the contour corresponding to the object in the mouth and the hand of the passenger in the picture and the comparison file,
when the error value w is smaller than or equal to a third threshold value, determining that the contours corresponding to the objects in the mouth and the hand of the passenger in the picture accord with the comparison file, wherein the picture corresponds to the situation that the passenger smokes;
when the error value w is larger than a third threshold value, judging that the contours corresponding to the objects in the mouth and the hands of the passenger in the picture do not accord with the comparison file, wherein the picture corresponds to the passenger without smoking;
the smoking monitoring and early warning module carries out early warning and reminding on the monitored passengers smoking cigarettes, and the early warning and reminding modes are different according to the monitored duration and smoking times of the passengers.
The smoking monitoring and early warning module of the invention considers that the position of the smoke is relatively fixed when the passenger smokes, and is in the hand or the mouth, so the mouth and the object in the hand of the passenger are matched with the pattern of the smoke recorded in the second comparison database, and whether the passenger smokes or not is judged.
Further, the smoking monitoring and early warning module gives an early warning to the passenger who smokes the cigarette in the following manner:
when the smoking monitoring and early warning module monitors that the passenger smokes for the first time, the smoking monitoring and early warning module can remind the passenger in a short message reminding mode;
when the duration time of one-time smoking of the passenger is less than or equal to a third preset value, the smoking monitoring and early warning module reminds in a short message mode every third unit time;
when the duration time of one-time smoking of the passenger is longer than a third preset value, the smoking monitoring and early warning module reminds the passenger in a short message mode every third unit time within the range that the duration time is shorter than or equal to the third preset value, and transmits the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station within the range that the duration time is longer than the third preset value, so that the smoking behavior of the passenger is stopped and corresponding punishment is made by the patrol personnel in the station;
when the number of times of smoking of the passenger is more than or equal to two times, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station when the passenger smokes for the second time or more, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
The invention considers the duration time of the smoking of the passenger and the number of times of smoking, and carries out point-to-point early warning on the passenger, namely, the passenger is early warned as long as the passenger smoking is monitored, and the early warning mode is different according to different conditions, short message reminding is firstly carried out to remind the passenger to forbid smoking, but when the passenger is not corrected, the passenger can stop the smoking behavior of the passenger through patrol personnel and carry out corresponding punishment, thereby avoiding the passenger from continuing smoking, and leading the passenger to be in the abstinence state.
Furthermore, the ticket checking monitoring and early warning module carries out early warning and reminding on passengers corresponding to the corresponding train in corresponding time before and after ticket checking of the train, the time from the beginning of the ticket checking is different, the early warning and reminding modes for the passengers are different,
when the time before ticket checking and from the beginning of ticket checking is the fourth unit time, the ticket checking monitoring and early warning module can automatically count passengers with the same train number as the number of the vehicle taken when the station departs from the passenger information of the train ticket purchased at the station and the travel information acquired by the inbound image acquisition module, compare the passenger information with the number of the train to obtain the passenger information of the train ticket purchased at the station and not entering the station, and send a short message to the passengers who purchase the train ticket at the station and do not enter the station through the reserved mobile phone number during ticket purchasing to remind and early warn;
when the time before ticket checking and the time from the beginning of ticket checking is less than the fourth unit time, the ticket checking monitoring and early warning module can count passengers with the same number as the train number when the station departs from the train in the passenger information of the train ticket purchased by the station and the journey information acquired by the inbound image acquisition module in real time, further acquire the current position bound by the passengers in the passenger position locking module and judge whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, no reminding is carried out,
if the position does not belong to the waiting room corresponding to the train, carrying out voice reminding once every fifth unit time through a loudspeaker closest to the current position of the passenger to remind the passenger to return to the waiting room to wait as soon as possible;
when the ticket checking is started to the time when the ticket checking is stopped, the ticket checking monitoring and early warning module counts passengers with the same number as the train number of the passenger who takes the train when the station departs from the station in the travel information acquired by the inbound image acquisition module in real time, further acquires the current position bound by the passenger in the passenger position locking module, and judges whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, the voice reminding is carried out through a loudspeaker in the waiting room,
if the position does not belong to the waiting room corresponding to the train, a short message is sent to the passenger who purchases the train ticket at the station and does not check the ticket through the reserved mobile phone number during ticket purchase to remind the passenger to go back to the waiting room to check the ticket as soon as possible.
The ticket checking monitoring and early warning module takes different early warning modes according to different time periods from the ticket checking starting time, whether a passenger enters a station and the current position of the passenger into consideration and different conditions.
Furthermore, after the ticket checking is started, when the smoking monitoring and early warning module monitors the smoking of the passenger, the duration time and the smoking times of the passenger are not considered any more, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
When the smokers are monitored after the ticket checking is started, the patrolling personnel are used for punishing the passengers directly, because the smokers are most dangerous at the moment, when the smokers see the ticket checking state, the cigarette ends can be directly discarded under the condition that the cigarette ends are not extinguished possibly due to the situations of emergency and the like, and therefore the passengers in the smoking state are most likely to cause fire due to self reasons, the patrolling personnel are required to stop in time to ensure that the cigarette ends are extinguished, and meanwhile, the passengers can be reminded to check the tickets in time.
Compared with the prior art, the invention has the following beneficial effects: the invention can monitor the state of the passenger according to various conditions, implement different early warning modes according to different states of the passenger, and even remind the passenger point to point according to special conditions.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a face recognition station passenger state monitoring and early warning system based on the Internet of things;
FIG. 2 is a schematic flow chart of a specific identification mode in a passenger position locking module of a face recognition station passenger state monitoring and early warning system based on the Internet of things;
FIG. 3 is a flow diagram of an early warning mode of a smoking monitoring and early warning module of a face recognition station passenger state monitoring and early warning system based on the Internet of things for a passenger who smokes;
fig. 4 is a flow diagram of an early warning reminding mode of a ticket checking monitoring early warning module of the face recognition station passenger state monitoring early warning system based on the internet of things for passengers.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, the present invention provides a technical solution: the utility model provides a face identification station passenger state monitoring early warning system based on thing networking, includes: an image acquisition module for entering a station, a passenger position locking module and a monitoring and early warning module, wherein the monitoring and early warning module comprises a ticket checking monitoring and early warning module and a smoking monitoring and early warning module,
the station-entering image acquisition module is used for carrying out face recognition and journey data extraction on passengers when the passengers enter the station through security check equipment of the station, extracting appearance characteristics of the passengers and binding face information, the appearance characteristics and the journey data of the passengers;
the passenger position locking module is used for acquiring images of passengers in each waiting room through the cameras in each waiting room, comparing the acquired images with the face information and the appearance characteristics of passengers entering the station, further determining passengers corresponding to the acquired images, and binding the current positions of the passengers with the passenger information;
the smoking monitoring and early warning module monitors smoke through the smoke collecting devices in the waiting rooms, and when a certain smoke collecting device monitors that the smoke content exceeds a specified index, the smoking monitoring and early warning module can transfer the adjacent cameras of the smoke collecting device to collect images in the area, judge a smoke source, lock the identity of a smoker and give a smoking alarm;
the ticket checking monitoring and early warning module is used for carrying out early warning reminding on passengers corresponding to corresponding trains in corresponding time before and after train ticket checking according to the travel information of passengers entering the station, which is acquired by the image acquisition module, and the positions of the passengers, which are acquired by the passenger position locking module.
The system and the method realize monitoring and early warning of the state of the passengers through the cooperative cooperation of all modules, the inbound image acquisition module mainly acquires the information of the inbound passengers, the passenger position locking module mainly determines the positions of the passengers through a camera and binds the current positions of the passengers with the passengers, the smoking monitoring and early warning module mainly monitors the smoking states of the passengers and takes different early warning measures according to different monitoring results, the ticket checking monitoring and early warning module mainly monitors the states of the passengers in different time periods when ticket checking starts and takes different early warning measures according to different time periods and different states of the passengers.
The appearance characteristics in the inbound image acquisition module comprise: the hairstyle of passengers when entering the station, the color, pattern and style of the clothes, whether the passengers carry the luggage and the size and color of the carried luggage,
the color, pattern and style of the clothes worn by the passengers are classified as the first type of appearance characteristics,
the hairstyle of passengers when entering the station is classified as a second type of appearance characteristic,
whether the passengers carry the luggage or not and the size and the color of the luggage carried by the passengers are classified into the third type of appearance characteristics;
the trip data includes: the number of the vehicle, the corresponding waiting room number, the ticket number, the seat number and the reserved mobile phone number when the passenger starts from the station.
The appearance characteristics are divided into three types by the inbound image acquisition module, because the hair style is the least easy to change, the color, the pattern and the style of clothes worn by passengers can be influenced by the temperature in a station or personal wishes of the passengers, when the passengers take off the outer clothes, the appearance characteristics can be changed, the appearance characteristics of the third type are also easy to change and even can be transferred to other passengers, and therefore, the appearance characteristics are divided into three types more conveniently when being compared.
The passenger position locking module analyzes images collected by the numbered cameras in the waiting rooms simultaneously in a multithreading mode, identifies passengers in the images according to a specific identification mode, and binds passenger information with the current position, wherein areas shot by the numbered cameras in the waiting rooms are not intersected.
The passenger position locking module controls a plurality of cameras, but in the aspect of data acquisition and analysis, the data needs to be analyzed and processed at the same time, so that the analysis and processing speed of the image can be increased by adopting a multithreading mode. The reason that the areas shot by the numbered cameras in the waiting rooms are not intersected is to avoid that passengers shot by the image intersection parts collected by the cameras are analyzed and processed for multiple times, so that the positions where the passengers are bound are not fixed, and the positions where the passengers are bound are displayed at the same time.
The specific identification mode in the passenger position locking module comprises the following steps:
s1, acquiring the passenger appearance characteristics and the face information obtained from the inbound image acquisition module;
s2, carrying out gray level processing on the images collected by the numbered cameras in the waiting rooms at intervals of first unit time, comparing the difference between the gray levels of adjacent pixel points with a first preset value, recording the position of the pixel point with a larger gray level when the difference is larger than the first preset value, and extracting the corresponding picture information of the contour formed by the recorded pixel points in the original image;
s3, comparing the extracted picture information with the appearance characteristics corresponding to each passenger, and when the picture information contains any two types of appearance characteristics corresponding to a certain passenger, listing the face information and the appearance characteristics corresponding to the passenger into a first comparison database corresponding to the picture information;
s4, extracting the face information corresponding to each passenger in the first comparison database, and comparing the face information with the picture information respectively to obtain the similarity between the face information corresponding to each passenger and the picture information;
s5, taking the passenger corresponding to the highest similarity as the passenger corresponding to the picture information, carrying out timestamp marking on the passenger, and binding the passenger with the camera number corresponding to the waiting room corresponding to the picture information;
s6, counting the number of the timestamp marks acquired by each passenger in the second unit time, when the number of the acquired timestamp marks is greater than a second preset value, carrying out abnormal marking on the timestamp marks acquired by the passengers in the second unit time, re-identifying and comparing the picture information corresponding to the timestamp marks of the abnormal marks, listing the appearance features corresponding to the passengers into reference factors in the acquisition of the similarity, and solving the final similarity between the picture information and each passenger in the corresponding first comparison database;
s7, taking the passenger corresponding to the highest final similarity as the passenger corresponding to the picture information, deleting the timestamp mark of the abnormal mark corresponding to the picture information and the corresponding camera number in the bound corresponding waiting room, carrying out timestamp marking on the passenger corresponding to the highest final similarity, binding the passenger and the camera number corresponding to the waiting room corresponding to the picture information, wherein the position of the numbered camera corresponding to the waiting room corresponding to the picture information is the current position of the passenger.
The smoking monitoring and early warning module acquires images acquired by the adjacent cameras of the smoke acquisition device in the area range, extracts the self and peripheral pictures of each passenger in the images,
processing the extracted picture according to the RGB value of each pixel, comparing the RGB value of each pixel in the extracted picture with a reference RGB value corresponding to the smoke color in a second comparison database, further extracting the pixels of which the RGB values conform to the smoke color in the extracted picture, then performing gray value processing on the obtained result, comparing the difference between the gray values of adjacent pixels after the gray value processing, marking the pixels of which the gray value difference is larger than the gray value corresponding to a first threshold value, acquiring the outline enclosed by the marked pixels according to the position relation among all the marked pixels, superposing the central point of the obtained outline and the central point of the smoke outline recorded in a second comparison database, wherein the smoke outline recorded in the second comparison database is a comparison file of the obtained outline, executing an outline comparison mode to acquire an error value w between the obtained outline and the comparison file,
when the error value w is less than or equal to the second threshold value, the extracted picture is determined to contain smoke, the picture containing smoke is arranged in a third comparison database,
when the error value w is larger than the second threshold value, the extracted picture is determined not to contain smoke,
the outline comparison mode is that a same plane rectangular coordinate system is established by taking a coincident central point as an original point, in the plane rectangular coordinate system, 360-degree circumference angles corresponding to the original point are equally divided by n, the original point is respectively taken as a starting point, each equal division line is established along the direction of each equal division point, coordinates corresponding to the intersection point of each equal division line in the plane rectangular coordinate system and the obtained outline and the comparison file are obtained, the distance between the coordinates and the intersection point of the obtained outline and the comparison file is calculated, the distances corresponding to all the equal division lines are accumulated, the average value is obtained, and the obtained average value is the error value between the obtained outline and the comparison file,
performing gray value processing on each picture in a third comparison database, comparing the gray value difference between adjacent pixel points to further obtain the corresponding contour of the object in the mouth and the hand of the passenger in the picture, coinciding the center point of the contour corresponding to the object in the mouth and the hand of the passenger in the picture with the center point of the contour of the recorded cigarette in a second comparison database, wherein the contour of the recorded cigarette in the second comparison database is a comparison file of the contour corresponding to the object in the mouth and the hand of the passenger in the picture, executing a contour comparison mode to obtain the error value m between the contour corresponding to the object in the mouth and the hand of the passenger in the picture and the comparison file,
when the error value w is smaller than or equal to a third threshold value, determining that the contours corresponding to the objects in the mouth and the hand of the passenger in the picture accord with the comparison file, wherein the picture corresponds to the situation that the passenger smokes;
when the error value w is larger than a third threshold value, judging that the contours corresponding to the objects in the mouth and the hands of the passenger in the picture do not accord with the comparison file, wherein the picture corresponds to the passenger without smoking;
the smoking monitoring and early warning module carries out early warning and reminding on the monitored passengers smoking cigarettes, and the early warning and reminding modes are different according to the monitored duration and smoking times of the passengers.
The smoking monitoring and early warning module of the invention considers that the position of the smoke is relatively fixed when the passenger smokes, and is in the hand or the mouth, so the mouth and the object in the hand of the passenger are matched with the pattern of the smoke recorded in the second comparison database, and whether the passenger smokes or not is judged.
The smoking monitoring and early warning module has the following early warning mode for the passengers who smoke:
when the smoking monitoring and early warning module monitors that the passenger smokes for the first time, the smoking monitoring and early warning module can remind the passenger in a short message reminding mode;
when the duration time of one-time smoking of the passenger is less than or equal to a third preset value, the smoking monitoring and early warning module reminds in a short message mode every third unit time;
when the duration time of one-time smoking of the passenger is longer than a third preset value, the smoking monitoring and early warning module reminds the passenger in a short message mode every third unit time within the range that the duration time is shorter than or equal to the third preset value, and transmits the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station within the range that the duration time is longer than the third preset value, so that the smoking behavior of the passenger is stopped and corresponding punishment is made by the patrol personnel in the station;
when the number of times of smoking of the passenger is more than or equal to two times, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station when the passenger smokes for the second time or more, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
The invention considers the duration time of the smoking of the passenger and the number of times of smoking, and carries out point-to-point early warning on the passenger, namely, the passenger is early warned as long as the passenger smoking is monitored, and the early warning mode is different according to different conditions, short message reminding is firstly carried out to remind the passenger to forbid smoking, but when the passenger is not corrected, the passenger can stop the smoking behavior of the passenger through patrol personnel and carry out corresponding punishment, thereby avoiding the passenger from continuing smoking, and leading the passenger to be in the abstinence state.
The ticket checking monitoring and early warning module carries out early warning reminding on passengers corresponding to a corresponding train in corresponding time before and after ticket checking of the train, the time from the beginning of ticket checking is different, the early warning reminding modes for the passengers are different,
when the time before ticket checking and from the beginning of ticket checking is the fourth unit time, the ticket checking monitoring and early warning module can automatically count passengers with the same train number as the number of the vehicle taken when the station departs from the passenger information of the train ticket purchased at the station and the travel information acquired by the inbound image acquisition module, compare the passenger information with the number of the train to obtain the passenger information of the train ticket purchased at the station and not entering the station, and send a short message to the passengers who purchase the train ticket at the station and do not enter the station through the reserved mobile phone number during ticket purchasing to remind and early warn;
when the time before ticket checking and the time from the beginning of ticket checking is less than the fourth unit time, the ticket checking monitoring and early warning module can count passengers with the same number as the train number when the station departs from the train in the passenger information of the train ticket purchased by the station and the journey information acquired by the inbound image acquisition module in real time, further acquire the current position bound by the passengers in the passenger position locking module and judge whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, no reminding is carried out,
if the position does not belong to the waiting room corresponding to the train, carrying out voice reminding once every fifth unit time through a loudspeaker closest to the current position of the passenger to remind the passenger to return to the waiting room to wait as soon as possible;
when the ticket checking is started to the time when the ticket checking is stopped, the ticket checking monitoring and early warning module counts passengers with the same number as the train number of the passenger who takes the train when the station departs from the station in the travel information acquired by the inbound image acquisition module in real time, further acquires the current position bound by the passenger in the passenger position locking module, and judges whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, the voice reminding is carried out through a loudspeaker in the waiting room,
if the position does not belong to the waiting room corresponding to the train, a short message is sent to the passenger who purchases the train ticket at the station and does not check the ticket through the reserved mobile phone number during ticket purchase to remind the passenger to go back to the waiting room to check the ticket as soon as possible.
The ticket checking monitoring and early warning module takes different early warning modes according to different time periods from the ticket checking starting time, whether a passenger enters a station and the current position of the passenger into consideration and different conditions.
After ticket checking begins, when a smoking monitoring and early warning module monitors that a passenger smokes, the duration time of the passenger smoking and the smoking times are not considered any more, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in a station, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
When the smokers are monitored after the ticket checking is started, the patrolling personnel are used for punishing the passengers directly, because the smokers are most dangerous at the moment, when the smokers see the ticket checking state, the cigarette ends can be directly discarded under the condition that the cigarette ends are not extinguished possibly due to the situations of emergency and the like, and therefore the passengers in the smoking state are most likely to cause fire due to self reasons, the patrolling personnel are required to stop in time to ensure that the cigarette ends are extinguished, and meanwhile, the passengers can be reminded to check the tickets in time.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The utility model provides a face identification station passenger state monitoring early warning system based on thing networking which characterized in that includes: an image acquisition module for entering a station, a passenger position locking module and a monitoring and early warning module, wherein the monitoring and early warning module comprises a ticket checking monitoring and early warning module and a smoking monitoring and early warning module,
the station-entering image acquisition module is used for carrying out face recognition and journey data extraction on passengers when the passengers enter the station through security check equipment of the station, extracting appearance characteristics of the passengers and binding face information, the appearance characteristics and the journey data of the passengers;
the passenger position locking module is used for acquiring images of passengers in each waiting room through the cameras in each waiting room, comparing the acquired images with the face information and the appearance characteristics of passengers entering the station, further determining passengers corresponding to the acquired images, and binding the current positions of the passengers with the passenger information;
the smoking monitoring and early warning module monitors smoke through the smoke collecting devices in the waiting rooms, and when a certain smoke collecting device monitors that the smoke content exceeds a specified index, the smoking monitoring and early warning module can transfer the adjacent cameras of the smoke collecting device to collect images in the area, judge a smoke source, lock the identity of a smoker and give a smoking alarm;
the ticket checking monitoring and early warning module is used for carrying out early warning reminding on passengers corresponding to corresponding trains in corresponding time before and after train ticket checking according to the travel information of passengers entering the station, which is acquired by the image acquisition module, and the positions of the passengers, which are acquired by the passenger position locking module.
2. The face recognition station passenger state monitoring and early warning system based on the internet of things as claimed in claim 1, characterized in that: the appearance characteristics in the inbound image acquisition module comprise: the hairstyle of passengers when entering the station, the color, pattern and style of the clothes, whether the passengers carry the luggage and the size and color of the carried luggage,
the color, pattern and style of the clothes worn by the passengers are classified as the first type of appearance characteristics,
the hairstyle of passengers when entering the station is classified as a second type of appearance characteristic,
whether the passengers carry the luggage or not and the size and the color of the luggage carried by the passengers are classified into the third type of appearance characteristics;
the trip data includes: the number of the vehicle, the corresponding waiting room number, the ticket number, the seat number and the reserved mobile phone number when the passenger starts from the station.
3. The face recognition station passenger state monitoring and early warning system based on the internet of things as claimed in claim 2, characterized in that: the passenger position locking module analyzes images collected by the numbered cameras in the waiting rooms simultaneously in a multithreading mode, identifies passengers in the images according to a specific identification mode, and binds passenger information with the current position, wherein areas shot by the numbered cameras in the waiting rooms are not intersected.
4. The face recognition station passenger state monitoring and early warning system based on the Internet of things as claimed in claim 3, characterized in that: the specific identification mode in the passenger position locking module comprises the following steps:
s1, acquiring the passenger appearance characteristics and the face information obtained from the inbound image acquisition module;
s2, carrying out gray level processing on the images collected by the numbered cameras in the waiting rooms at intervals of first unit time, comparing the difference between the gray levels of adjacent pixel points with a first preset value, recording the position of the pixel point with a larger gray level when the difference is larger than the first preset value, and extracting the corresponding picture information of the contour formed by the recorded pixel points in the original image;
s3, comparing the extracted picture information with the appearance characteristics corresponding to each passenger, and when the picture information contains any two types of appearance characteristics corresponding to a certain passenger, listing the face information and the appearance characteristics corresponding to the passenger into a first comparison database corresponding to the picture information;
s4, extracting the face information corresponding to each passenger in the first comparison database, and comparing the face information with the picture information respectively to obtain the similarity between the face information corresponding to each passenger and the picture information;
s5, taking the passenger corresponding to the highest similarity as the passenger corresponding to the picture information, carrying out timestamp marking on the passenger, and binding the passenger with the camera number corresponding to the waiting room corresponding to the picture information;
s6, counting the number of the timestamp marks acquired by each passenger in the second unit time, when the number of the acquired timestamp marks is greater than a second preset value, carrying out abnormal marking on the timestamp marks acquired by the passengers in the second unit time, re-identifying and comparing the picture information corresponding to the timestamp marks of the abnormal marks, listing the appearance features corresponding to the passengers into reference factors in the acquisition of the similarity, and solving the final similarity between the picture information and each passenger in the corresponding first comparison database;
s7, taking the passenger corresponding to the highest final similarity as the passenger corresponding to the picture information, deleting the timestamp mark of the abnormal mark corresponding to the picture information and the corresponding camera number in the bound corresponding waiting room, carrying out timestamp marking on the passenger corresponding to the highest final similarity, binding the passenger and the camera number corresponding to the waiting room corresponding to the picture information, wherein the position of the numbered camera corresponding to the waiting room corresponding to the picture information is the current position of the passenger.
5. The face recognition station passenger state monitoring and early warning system based on the internet of things as claimed in claim 1, characterized in that: the smoking monitoring and early warning module acquires images acquired by the adjacent cameras of the smoke acquisition device in the area range, extracts the self and peripheral pictures of each passenger in the images,
processing the extracted picture according to the RGB value of each pixel, comparing the RGB value of each pixel in the extracted picture with a reference RGB value corresponding to the smoke color in a second comparison database, further extracting the pixels of which the RGB values conform to the smoke color in the extracted picture, then performing gray value processing on the obtained result, comparing the difference between the gray values of adjacent pixels after the gray value processing, marking the pixels of which the gray value difference is larger than the gray value corresponding to a first threshold value, acquiring the outline enclosed by the marked pixels according to the position relation among all the marked pixels, superposing the central point of the obtained outline and the central point of the smoke outline recorded in a second comparison database, wherein the smoke outline recorded in the second comparison database is a comparison file of the obtained outline, executing an outline comparison mode to acquire an error value w between the obtained outline and the comparison file,
when the error value w is less than or equal to the second threshold value, the extracted picture is determined to contain smoke, the picture containing smoke is arranged in a third comparison database,
when the error value w is larger than the second threshold value, the extracted picture is determined not to contain smoke,
the outline comparison mode is that a same plane rectangular coordinate system is established by taking a coincident central point as an original point, in the plane rectangular coordinate system, 360-degree circumference angles corresponding to the original point are equally divided by n, the original point is respectively taken as a starting point, each equal division line is established along the direction of each equal division point, coordinates corresponding to the intersection point of each equal division line in the plane rectangular coordinate system and the obtained outline and the comparison file are obtained, the distance between the coordinates and the intersection point of the obtained outline and the comparison file is calculated, the distances corresponding to all the equal division lines are accumulated, the average value is obtained, and the obtained average value is the error value between the obtained outline and the comparison file,
performing gray value processing on each picture in a third comparison database, comparing the gray value difference between adjacent pixel points to further obtain the corresponding contour of the object in the mouth and the hand of the passenger in the picture, coinciding the center point of the contour corresponding to the object in the mouth and the hand of the passenger in the picture with the center point of the contour of the recorded cigarette in a second comparison database, wherein the contour of the recorded cigarette in the second comparison database is a comparison file of the contour corresponding to the object in the mouth and the hand of the passenger in the picture, executing a contour comparison mode to obtain the error value m between the contour corresponding to the object in the mouth and the hand of the passenger in the picture and the comparison file,
when the error value w is smaller than or equal to a third threshold value, determining that the contours corresponding to the objects in the mouth and the hand of the passenger in the picture accord with the comparison file, wherein the picture corresponds to the situation that the passenger smokes;
when the error value w is larger than a third threshold value, judging that the contours corresponding to the objects in the mouth and the hands of the passenger in the picture do not accord with the comparison file, wherein the picture corresponds to the passenger without smoking;
the smoking monitoring and early warning module carries out early warning and reminding on the monitored passengers smoking cigarettes, and the early warning and reminding modes are different according to the monitored duration and smoking times of the passengers.
6. The face recognition station passenger state monitoring and early warning system based on the Internet of things as claimed in claim 5, characterized in that: the smoking monitoring and early warning module has the following early warning mode for the passengers who smoke:
when the smoking monitoring and early warning module monitors that the passenger smokes for the first time, the smoking monitoring and early warning module can remind the passenger in a short message reminding mode;
when the duration time of one-time smoking of the passenger is less than or equal to a third preset value, the smoking monitoring and early warning module reminds in a short message mode every third unit time;
when the duration time of one-time smoking of the passenger is longer than a third preset value, the smoking monitoring and early warning module reminds the passenger in a short message mode every third unit time within the range that the duration time is shorter than or equal to the third preset value, and transmits the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station within the range that the duration time is longer than the third preset value, so that the smoking behavior of the passenger is stopped and corresponding punishment is made by the patrol personnel in the station;
when the number of times of smoking of the passenger is more than or equal to two times, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in the station when the passenger smokes for the second time or more, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
7. The face recognition station passenger state monitoring and early warning system based on the internet of things as claimed in claim 1, characterized in that: the ticket checking monitoring and early warning module carries out early warning reminding on passengers corresponding to a corresponding train in corresponding time before and after ticket checking of the train, the time from the beginning of ticket checking is different, the early warning reminding modes for the passengers are different,
when the time before ticket checking and from the beginning of ticket checking is the fourth unit time, the ticket checking monitoring and early warning module can automatically count passengers with the same train number as the number of the vehicle taken when the station departs from the passenger information of the train ticket purchased at the station and the travel information acquired by the inbound image acquisition module, compare the passenger information with the number of the train to obtain the passenger information of the train ticket purchased at the station and not entering the station, and send a short message to the passengers who purchase the train ticket at the station and do not enter the station through the reserved mobile phone number during ticket purchasing to remind and early warn;
when the time before ticket checking and the time from the beginning of ticket checking is less than the fourth unit time, the ticket checking monitoring and early warning module can count passengers with the same number as the train number when the station departs from the train in the passenger information of the train ticket purchased by the station and the journey information acquired by the inbound image acquisition module in real time, further acquire the current position bound by the passengers in the passenger position locking module and judge whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, no reminding is carried out,
if the position does not belong to the waiting room corresponding to the train, carrying out voice reminding once every fifth unit time through a loudspeaker closest to the current position of the passenger to remind the passenger to return to the waiting room to wait as soon as possible;
when the ticket checking is started to the time when the ticket checking is stopped, the ticket checking monitoring and early warning module counts passengers with the same number as the train number of the passenger who takes the train when the station departs from the station in the travel information acquired by the inbound image acquisition module in real time, further acquires the current position bound by the passenger in the passenger position locking module, and judges whether the position belongs to a waiting room corresponding to the train or not,
if the position belongs to the waiting room corresponding to the train, the voice reminding is carried out through a loudspeaker in the waiting room,
if the position does not belong to the waiting room corresponding to the train, a short message is sent to the passenger who purchases the train ticket at the station and does not check the ticket through the reserved mobile phone number during ticket purchase to remind the passenger to go back to the waiting room to check the ticket as soon as possible.
8. The face recognition station passenger state monitoring and early warning system based on the Internet of things as claimed in claim 6, characterized in that: after ticket checking begins, when a smoking monitoring and early warning module monitors that a passenger smokes, the duration time of the passenger smoking and the smoking times are not considered any more, the smoking monitoring and early warning module can directly transmit the face image of the passenger and the current position of the passenger obtained by the passenger position locking module to patrol personnel in a station, and the patrol personnel in the station can stop the smoking behavior of the passenger and make corresponding punishment.
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