CN113393177A - Urban cleaning intelligent monitoring system and method - Google Patents
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Abstract
The invention discloses an intelligent monitoring method for urban cleanness, which comprises the following processing steps: A. establishing an urban cleanliness evaluation model system based on different regional characteristics, and performing model evaluation on cleanliness of each region of the city; B. based on the evaluation of the cleaning degree model of each area in the city, the cleaning degree of each area in the future time period is predicted and evaluated; C. and (4) correcting the cleaning degree of each area in the future time by using a cleaning degree feedback system of each area in the city at the current time. The method uniformly classifies different buildings in each area of the city, combines the buildings with the pedestrian flow, and is simple in calculation of the established cleanliness evaluation model, high in reliability and suitable for various urban environments with complex characteristics; in addition, the method and the system combine the urban cleanliness in different time periods and different festivals in the city, greatly improve the accuracy of cleanliness prediction, and obtain correction parameters to enable the prediction result to be more accurate by extracting a large amount of cleanliness data before the time t and performing relevant processing.
Description
Technical Field
The invention relates to the field of intelligent computing, in particular to an intelligent monitoring system and method for urban cleaning.
Background
Along with the rapid development of social economy, the urban environmental sanitation is more and more emphasized by people, the living standard of people can be improved by the good urban environment, and the spread of viruses is greatly reduced. At the present stage, urban road cleaning detection is limited to uploading urban images to a monitoring control center in real time, and cleaning workers are dispatched to clean after areas needing cleaning are detected. A great deal of time is wasted by dispatching workers, so that the sanitary condition of the area to be cleaned cannot be solved in time, and the working efficiency is greatly reduced in the process. The method has the advantages that the cleanliness of each area of the city is predicted in advance, the garbage is cleaned in time, and the cleaning efficiency is improved, so that the important significance is realized on the improvement of the urban environment.
Disclosure of Invention
The invention discloses an intelligent monitoring system and method for urban cleaning, which are used for solving the technical problems that the distance between workers and an area needing cleaning seriously influences the sanitation condition of the area and the working efficiency is low at present.
The intelligent detection method for the urban cleanliness comprises the following specific treatment processes:
an intelligent monitoring method for urban cleaning comprises the following steps:
A. establishing an urban cleanliness evaluation model system based on different regional characteristics, and performing model evaluation on cleanliness of each region of the city;
B. based on the evaluation of the cleaning degree model of each area in the city, the cleaning degree of each area in the future time period is predicted and evaluated;
C. and (4) correcting the cleaning degree of each area in the future time by using a cleaning degree feedback system of each area in the city at the current time.
Preferably, the step a specifically includes the following steps:
establishing an urban cleanness evaluation model based on the influence of different buildings on urban cleanness, and evaluating the cleanness degree of each area through the influence of different building types of each area of the city on the cleanness and the difference of pedestrian volume;
Skthe influence degree of all buildings with different grades in the k area of the city on environmental cleanness, RiTo a cleanliness class, DiA cleanliness class R in the k regioniThe number of the buildings to be constructed,β iis rated as R for cleanlinessiThe cleanliness affecting characteristic variable refers to the influence coefficient of the building quantity with the same cleanliness grade on the overall environmentCan be obtained according to actual conditions
The lower the cleanliness grade, the smaller the characteristic variable;
defining the sum of the number of people passing through the same place in unit time as the flow rate of people, carrying out exponential operation on the flow rate of people, and multiplying the flow rate of people by the environmental cleanliness influence degree of urban buildings to obtain the cleanliness evaluation value of each area:
z iskAnd (5) obtaining the cleanliness of the k area by establishing a cleaning evaluation model, wherein w is the real-time pedestrian volume.
Preferably, step B specifically comprises:
the city cleanliness in the past different time is taken as a parameter to predict the city cleanliness in the future smaller time, and the prediction is carried outf k (t)The cleanliness of the city k area at the time t is as follows:
wherein the content of the first and second substances,
for real-time cleanliness at time t in the k area of the city,
for the cleanliness of city k at the same time t1 each day,
the cleanliness of a city k at the same time t2 every week, t is a time parameter, and t1 represents the ring ratio t time of each dayAt t2, the comparison of the cleanliness of each day and each week shows the influence parameter epsilon of the cleanliness of the past time period on the cleanliness of the time t:
adding the cleanliness influence parameters at the time t through the actual city cleanliness at the time t and the past time to obtain a cleanliness prediction result of a K area in the city in a future time period:
initialf k (0) =0, α represents whether the area is cleaned, if a cleaner is sent to clean, α =0, if not, α = 1; τ represents a variable with a time length τ after time t; and predicting the cleanliness of the same area at the next moment by selecting the city cleanliness at different time periods.
Preferably, step C specifically comprises:
by time period
Selecting the actual cleanliness of eta time points before t time of each region of k city as step length
Said period of time
Can be freely set according to actual requirements, and carries out normalization processing on X:
wherein the content of the first and second substances,
and
respectively, the maximum and minimum values in the cleanliness set X.
The cleanliness of the past time period can be reduced to 0-1 by normalization processing]In the following operation, the inaccuracy of the correction parameter caused by too large data can be avoided, and the data after normalization processing is compared with the average number to obtain the correction parameter
；
Will correct the parameters
The corrected cleanliness obtained in combination with the prediction results is:
an intelligent monitoring system for urban cleaning comprises a monitoring system,
the city monitoring equipment is used for acquiring real-time images of all areas of a city and acquiring people flow information;
the central processor is in communication connection with the city monitoring equipment and is used for receiving the image transmitted by the city monitoring equipment, performing regional cleanliness model evaluation on each region of the city, and performing fitting calculation on all cleanliness influencing factors in the city region to obtain cleanliness evaluation of each region of the city; the method comprises the steps of collecting and analyzing the cleanliness of each area of a city in the past time period, extracting the cleanliness of the city areas in the past time period in different time periods, and predicting the cleanliness of each area of the city in a smaller time period in the future based on the influence of time on the cleanliness;
and the display processing module is in communication connection with the city monitoring equipment and the central processor, and is used for displaying the cleanliness result predicted by the central processor on one hand, receiving the information of the monitoring equipment on the other hand, and verifying and correcting the cleanliness prediction result of the central processor on the other hand.
Preferably, the operation flow is as follows:
the city monitoring equipment collects real-time images of all areas of a city, the images are transmitted to the central processor, the central processor adopts the intelligent monitoring method to perform modeling evaluation on the cleanliness of all areas of the city, then predicts the cleanliness of all areas of the city in a smaller time in the future, the prediction result is transmitted to the display processing module, and the display processing module performs verification and correction on the cleanliness prediction result through the real-time cleanliness of all areas of the city by receiving the image information sent by the city monitoring equipment.
The invention has at least the following beneficial effects:
(1) the invention classifies different buildings in each area of the city uniformly, reduces the complexity of the influence of a plurality of buildings on the environment, is combined with the pedestrian flow, has simple calculation and high reliability of the established cleanliness evaluation model, and is suitable for various urban environments with complex characteristics.
(2) The method and the system combine the urban cleanliness in different time periods in the city, and greatly improve the accuracy of cleanliness prediction.
(3) According to the invention, a large amount of cleanliness data before the time t is extracted and relevant processing is carried out, and the obtained correction parameters enable the prediction result to be more accurate.
Drawings
FIG. 1 is a diagram of an exemplary configuration of an intelligent monitoring method with a central processor according to the present invention;
FIG. 2 is a flow chart of an intelligent monitoring method for city cleaning according to the present invention.
The specific implementation mode is as follows:
for a better understanding of the present invention, reference will now be made in detail to the embodiments illustrated in the accompanying drawings.
Referring to fig. 1, the urban cleaning intelligent monitoring system of the invention comprises: the city monitoring device 10 is provided with a central processor 20 for processing images and intelligently calculating the cleanliness, and a device 30 for displaying the city cleanliness.
The city monitoring equipment 10 is used for acquiring real-time images of all areas of a city and acquiring people flow information, and on one hand, transmitting the image information to the central processor 20; on one hand, the image information is transmitted to the display processing module 30, and the cleanliness prediction result is adjusted in real time.
The city monitoring device 10 has a communication connection with a central processor 20 and a display processing module 30.
The central processor 20 receives the image transmitted by the city monitoring device 10, and performs the regional cleanliness model evaluation on each region of the city, and the invention divides all buildings in the city into four grades according to different influences of each building on the city cleanliness: clean, cleaner, unclean, sloppy, with RiThe grade quantification is carried out by using the value of {1,2,3,4}, and the influence of the building on the urban cleanliness is the influence of the building on municipal public areas and roads, but not the cleanliness of the building. Locations that are substantially free of garbage, such as administrative units, schools, etc., may be defined as first-class (clean), locations that are very easily free of garbage, such as stalls, night cities, etc., may be defined as fourth-class (sloppy), and levels of cleanliness may be demarcated according to actual circumstances. And performing fitting calculation on all cleanliness influencing factors in the urban area to obtain the cleanliness evaluation of each area of the city. The method comprises the steps of collecting and analyzing the cleanliness of each area of the city in the past time period, extracting the cleanliness of the city areas in the past time period in different time periods, and predicting the cleanliness of each area of the city in a future smaller time period based on the influence of time on the cleanliness.
The central processor 20 has a communication connection with a display processing module 30.
The display processing module 30 is configured to display the result of the cleanliness predicted by the central processor 20, receive information of the monitoring device 10, and perform verification and correction on the predicted result.
The city monitoring equipment 10 collects real-time images of all areas of a city, and transmits the images to the central processor 20, referring to fig. 2, the central processor 20 firstly carries out modeling evaluation on the cleanliness of all areas of the city by adopting the intelligent monitoring method, then predicts the cleanliness of all areas of the city in a smaller time in the future, and transmits the prediction result to the display processing module 30; the display processing module 30 checks and corrects the prediction result through real-time cleanliness of each area of the city by receiving the image information sent by the monitoring equipment 10.
The intelligent detection method for the urban cleanliness comprises the following specific treatment processes:
A. and establishing an urban cleanness evaluation model system based on different regional characteristics, and performing model evaluation on the cleanness degree of each region of the city.
The method establishes an urban cleanness evaluation model based on the influence of different buildings on urban cleanness, and evaluates the cleanness degree of each area through the influence of different building types of each area of the city on the cleanness and the difference of the flow of people. The data of building types, quantity and the like in different areas can be acquired from information published by land authorities of various areas or called from the existing map big data through an API (application program interface), and the invention is not limited too much here.
The building categories may be classified into residential buildings, public buildings including educational buildings, office buildings, commercial buildings, medical buildings, traffic buildings, and the like, industrial buildings, and agricultural buildings according to the use function. Different building types vary in cleanliness due to their different uses.
In the present invention, SkThe influence degree of all buildings with different grades in the k area of the city on environmental cleanness, RiTo a cleanliness class, DiA cleanliness class R in the k regioniThe number of the buildings to be constructed,β iis rated as R for cleanlinessiThe cleanliness influencing characteristic variable refers to the influence coefficient of the building quantity with the same cleanliness grade on the overall environment, and can be obtained according to the actual condition
. Generally, the lower the cleanliness class, the smaller the characteristic variable.
The influence degree of the urban buildings on environmental cleanness obtained by the method classifies different urban buildings uniformly, reduces the complexity of influence of a plurality of buildings on the environment, and is suitable for urban environments with various complex characteristics.
The sum of the number of people passing through the same place in unit time is defined as the human flow, and the determination of the unit time can be defined according to the actual situation. The flow of people influences the cleanliness of the urban environment to a great extent, but a large amount of data shows that the influence of the flow of people on the cleanliness of the city tends to be constant to a certain extent. The method carries out exponential operation on the pedestrian flow, and then multiplies the result by the influence degree of the urban building on environmental cleanliness to obtain the cleanliness evaluation value of each area.
Z iskThe cleanliness obtained by establishing a cleanliness evaluation model for the k region. The urban area cleanliness evaluation model obtained by the method is simple in calculation and high in reliability.
B. And based on the model evaluation of the cleanliness of each area in the city, carrying out prediction evaluation on the cleanliness of each area in the future time.
According to the method, the urban cleanliness is predicted in a smaller time in the future by taking the urban cleanliness in different past times as parameters. Note the bookf k (t)The cleanliness of the city k area at the time t is as follows:
wherein the content of the first and second substances,
for real-time cleanliness at time t in the k area of the city,
for the cleanliness of city k at the same time t1 each day,
the cleanliness of the city k at the same time t2 every week, t is a time parameter, t1 represents the ring ratio t time of each day, and t2 is the same ratio t time of the past week. M and N respectively represent the quantity of the acquired urban cleanliness in the past time in day units and week units, and the influence parameter epsilon of the cleanliness in the past time period on the cleanliness at the time t is obtained by comparing the cleanliness every day with the cleanliness every week.
Wherein i is the number of days and j is the number of weeks. According to the method, a large amount of data of past time periods are obtained, and the accuracy of cleanliness influence parameters is greatly improved.
Adding the cleanliness influence parameters at the time t through the actual city cleanliness at the time t and the past time to obtain a cleanliness prediction result of a K area in the city in a future time period:
initialf k (0) =0, α represents whether the area is cleaned, if a cleaner is sent to clean, α =0, if not, α = 1; τ represents a variable of time length τ after time t. And predicting the cleanliness of the same area at the next moment by selecting the city cleanliness at different time periods. The invention introduces the same cyclic ratio t moment combined with every day and the same time every weekThe urban cleanliness characteristic predicts the future cleanliness, and can eliminate the fluctuation influence of different urban cleanliness at the same time of working days and rest days, so that the prediction is more stable.
C. And (4) correcting the cleaning degree of each area in the future time by using a cleaning degree feedback system of each area in the city at the current time.
By time period
Selecting the actual cleanliness of eta time points before t time of each region of k city as step length
Said period of time
Can be freely set according to actual requirements, and carries out normalization processing on X:
wherein the content of the first and second substances,
and
respectively, the maximum and minimum values in the cleanliness set X.
The cleanliness of the past time period can be reduced to 0-1 by normalization processing]Therefore, the inaccuracy of the correction parameters caused by too large data can be avoided in the subsequent operation. Comparing the normalized data with the average to obtain the correction parameterδ。
In the above equation, m represents a time count. The correction parameter obtained by the formula is simple in calculation mode, and the obtained correction parameter is more accurate by extracting a large amount of cleanliness data before the time t.
Will correct the parameters
The corrected cleanliness obtained in combination with the prediction results is:
in conclusion, the urban cleaning intelligent monitoring method is realized. The invention classifies different buildings in each area of the city uniformly, reduces the complexity of the influence of a plurality of buildings on the environment, is combined with the pedestrian flow, has simple calculation and high reliability of the established cleanliness evaluation model, and is suitable for various urban environments with complex characteristics. In addition, the method greatly improves the accuracy of cleanliness prediction by combining the cleanliness of the cities in different time periods, and obtains correction parameters to enable the prediction result to be more accurate by extracting a large amount of cleanliness data before the time t and performing relevant processing.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (6)
1. An intelligent monitoring method for urban cleanness is characterized by comprising the following steps:
A. establishing an urban cleanliness evaluation model system based on different regional characteristics, and performing model evaluation on cleanliness of each region of the city;
B. based on the evaluation of the cleaning degree model of each area in the city, the cleaning degree of each area in the future time period is predicted and evaluated;
C. and (4) correcting the cleaning degree of each area in the future time by using a cleaning degree feedback system of each area in the city at the current time.
2. The intelligent urban cleaning monitoring method according to claim 1, wherein step a specifically comprises the following:
establishing an urban cleanness evaluation model based on the influence of different buildings on urban cleanness, and evaluating the cleanness degree of each area through the influence of different building types of each area of the city on the cleanness and the difference of pedestrian volume;
Skthe influence degree of all buildings with different grades in the k area of the city on environmental cleanness, RiTo a cleanliness class, DiA cleanliness class R in the k regioniThe number of the buildings to be constructed,β iis rated as R for cleanlinessiThe cleanliness influencing characteristic variable refers to the influence coefficient of the building quantity with the same cleanliness grade on the overall environment, and can be obtained according to the actual condition
The lower the cleanliness grade, the smaller the characteristic variable;
defining the sum of the number of people passing through the same place in unit time as the flow rate of people, carrying out exponential operation on the flow rate of people, and multiplying the flow rate of people by the environmental cleanliness influence degree of urban buildings to obtain the cleanliness evaluation value of each area:
z iskAnd (5) obtaining the cleanliness of the k area by establishing a cleaning evaluation model, wherein w is the real-time pedestrian volume.
3. The intelligent urban cleaning monitoring method according to claim 2, wherein step B specifically comprises:
the city cleanliness in the past different time is taken as a parameter to predict the city cleanliness in the future smaller time, and the prediction is carried outf k (t)The cleanliness of the city k area at the time t is as follows:
wherein the content of the first and second substances,
for real-time cleanliness at time t in the k area of the city,
for the cleanliness of city k at the same time t1 each day,
the influence parameter epsilon of the cleanliness of the city k in the past time period on the cleanliness at the time t2 in each week is obtained by comparing the cleanliness of each day with the cleanliness of each week:
adding the cleanliness influence parameters at the time t through the actual city cleanliness at the time t and the past time to obtain a cleanliness prediction result of a K area in the city in a future time period:
initialf k (0) =0, α represents whether the area is cleaned, if a cleaner is sent to clean, α =0, if not, α = 1; τ represents a variable with a time length τ after time t; and predicting the cleanliness of the same area at the next moment by selecting the city cleanliness at different time periods.
4. The intelligent urban cleaning monitoring method according to claim 3, wherein step C specifically comprises:
by time period
Selecting the actual cleanliness of eta time points before t time of each region of k city as step length
Said period of time
Can be freely set according to actual requirements, and carries out normalization processing on X:
wherein the content of the first and second substances,
and
respectively, the maximum and minimum values in the cleanliness set X.
The cleanliness of the past time period can be reduced to 0-1 by normalization processing]In the following operation, the inaccuracy of the correction parameter caused by too large data can be avoided, and the data after normalization processing is compared with the average number to obtain the correction parameter
；
Will correct the parameters
The corrected cleanliness obtained in combination with the prediction results is:
5. the utility model provides a clean intelligent monitoring system in city which characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the city monitoring equipment is used for acquiring real-time images of all areas of a city and acquiring people flow information;
the central processor is in communication connection with the city monitoring equipment and is used for receiving the image transmitted by the city monitoring equipment, performing regional cleanliness model evaluation on each region of the city, and performing fitting calculation on all cleanliness influencing factors in the city region to obtain cleanliness evaluation of each region of the city; the method comprises the steps of collecting and analyzing the cleanliness of each area of a city in the past time period, extracting the cleanliness of the city areas in the past time period in different time periods, and predicting the cleanliness of each area of the city in a smaller time period in the future based on the influence of time on the cleanliness;
and the display processing module is in communication connection with the city monitoring equipment and the central processor, and is used for displaying the cleanliness result predicted by the central processor on one hand, receiving the information of the monitoring equipment on the other hand, and verifying and correcting the cleanliness prediction result of the central processor on the other hand.
6. The intelligent urban cleaning monitoring system according to claim 5, wherein: the operation flow is as follows:
the city monitoring equipment collects real-time images of all areas of a city, the images are transmitted to the central processor, the central processor adopts the intelligent monitoring method to perform modeling evaluation on the cleanliness of all areas of the city, then predicts the cleanliness of all areas of the city in a smaller time in the future, the prediction result is transmitted to the display processing module, and the display processing module performs verification and correction on the cleanliness prediction result through the real-time cleanliness of all areas of the city by receiving the image information sent by the city monitoring equipment.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115115285A (en) * | 2022-08-29 | 2022-09-27 | 江苏思锐装备科技有限公司 | Intelligent control method for water system of sweeper |
| CN115392791A (en) * | 2022-10-21 | 2022-11-25 | 成都秦川物联网科技股份有限公司 | Smart city public facility management method, system and medium based on Internet of things |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115115285A (en) * | 2022-08-29 | 2022-09-27 | 江苏思锐装备科技有限公司 | Intelligent control method for water system of sweeper |
| CN115392791A (en) * | 2022-10-21 | 2022-11-25 | 成都秦川物联网科技股份有限公司 | Smart city public facility management method, system and medium based on Internet of things |
| CN115392791B (en) * | 2022-10-21 | 2023-01-24 | 成都秦川物联网科技股份有限公司 | Smart city public facility management method, system and medium based on Internet of things |
| US11961157B2 (en) | 2022-10-21 | 2024-04-16 | Chengdu Qinchuan Iot Technology Co., Ltd. | Methods for communal facilities management in smart cities based on the internet of things, systems, and mediums |
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