CN113361914B - Dangerous waste transportation risk management and control early warning method and system - Google Patents
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Abstract
The application discloses a dangerous waste transportation risk management and control early warning method and system. The method comprises the following steps: identifying real-time location information of the hazardous waste transport vehicle; determining an abnormal stopping point of the hazardous waste transport vehicle, and determining an abnormal stopping area of the hazardous waste transport vehicle based on the abnormal stopping point; determining a suspicious illegal dumping area by using a satellite image of an abnormal staying area of the dangerous waste transport vehicle shot by a high-resolution satellite and comparing the characteristics of the satellite image of the abnormal staying area before and after the abnormal staying of the dangerous waste transport vehicle; and (3) aerial photographing the suspicious illegal dumping area by using an unmanned aerial vehicle, and comparing a picture set of aerial photographing pictures of the unmanned aerial vehicle with a known image set of dangerous waste dumping points, thereby screening the illegal dumping area determined by the system from the suspicious illegal dumping area. The abnormal stopping point of the dangerous waste transport vehicle and whether the abnormal stopping point illegally dumps the dangerous waste can be judged in real time.
Description
Technical Field
The application relates to the field of hazardous waste transportation, in particular to a method and a system for risk management and control early warning of hazardous waste transportation.
Background
The hazardous waste (also called hazardous waste for short) refers to the waste with hazardous characteristics listed in the national hazardous waste list or identified according to the national hazardous waste identification standard and identification method, has the characteristics of toxicity, corrosivity, chemical reactivity, infectivity, radioactivity and the like, and forms potential risks for human health and natural environment. Industrialization and urbanization in China are rapidly developing, and the yield of dangerous wastes is also in a rapid increasing trend. Corresponding to the rapid increase of the yield of the hazardous waste, the hazardous waste treatment capacity is insufficient, the management difficulty is high, in recent years, the illegal dumping of the hazardous waste in China frequently occurs, severe environmental consequences are caused to water environment, soil environment and atmospheric environment, and the life health of residents is threatened. The property of illegally dumping dangerous waste is severe, the harm is great, the concealment is strong, meanwhile, the illegal events are difficult to discover and pursue, and further, the dangerous waste transportation link has a large link risk.
At present, the method for managing and controlling the transportation risk of hazardous wastes is mainly based on a hazardous waste transportation union manifest system, namely, a production and waste unit, a hazardous waste transportation unit and a hazardous waste disposal unit respectively fill related information, and according to the accuracy of information verified by multiple parties, the hazardous wastes are prevented from being illegally dumped in the processes of treatment and utilization, so that the link risk of the transportation process of the hazardous wastes is reduced.
However, the above control method has the following disadvantages: (1) the hazardous waste transfer coupon information can only match information of different nodes in a transportation link, and cannot give an early warning to the processes among the nodes, particularly the behaviors of vehicles; (2) although some dangerous waste transport vehicles are provided with satellite positioning equipment according to requirements, most of the existing positioning data are used for evidence obtaining after the illegal dumping event of dangerous waste is found, and the illegal dumping of the dangerous waste cannot be early warned in time.
Disclosure of Invention
The application provides a method and a system for dangerous waste transportation risk management and control early warning to carry out effective early warning on illegal dumping in a dangerous waste transportation process.
According to one aspect of the application, a method for hazardous waste transportation risk management and control early warning is provided, and the method comprises the following steps:
and 4, carrying out aerial photography on the suspicious illegal dumping area by using an unmanned aerial vehicle, and comparing the picture set of aerial pictures of the unmanned aerial vehicle with the image set of known dangerous waste dumping points, thereby screening the illegal dumping area determined by the system from the suspicious illegal dumping area.
Wherein, the real-time positional information of hazardous waste haulage vehicle accessible positioning system is like GPS system, beidou system etc. confirms to can confirm the concrete position of haulage vehicle in real time.
In step 4, the image set of the known hazardous waste dumping points refers to: the suspected illegal dumping area corresponds to a set of thermal images of known dumping points of hazardous waste in the study area and can be obtained by historical sampling. The research area is selected as an administrative area for the hazardous waste transportation system, such as administrative province, administrative city, etc. Because the production and waste units and the treatment units in the same administrative area are generally fixed, when the image set of the known dangerous waste dumping points in the same administrative area is selected as a reference, the result of the illegal dumping area determined by the screening system in the suspicious illegal dumping area is more accurate.
In step 4, the illegal dumping area determined by the system is as follows: by adopting the method, the probability of actual illegal dumping in the illegal dumping area determined by the systems is higher than that of the suspicious illegal dumping area in the step 3 through the further determination of the illegal dumping area from the suspicious illegal dumping area by the unmanned aerial vehicle, but the illegal dumping area determined by the systems does not necessarily have actual illegal dumping, and finally the actual illegal dumping area needs to be investigated and determined in the field. That is, in step 4, the illegal dumping region determined by the system is the address basis provided by the early warning method for the relevant personnel to investigate in the field.
When the transportation vehicle needs to illegally dump the hazardous waste, the transportation vehicle is generally stopped or slowly moved at or near the dumping point and transfers the hazardous waste from the transportation vehicle, that is, the transportation vehicle is slowly moved or not moved while illegally dumping the hazardous waste, so that the abnormal parking area can be preliminarily determined according to the real-time position of the transportation vehicle. When the dangerous waste is illegally dumped, information related to illegal dumping must exist before and after the illegal dumping in an abnormal staying area, for example, dangerous waste or a dangerous waste container exists on the ground; at the moment, satellite pictures taken by the high-resolution satellite before and after the transportation vehicle abnormally stops are compared, so that suspicious illegal dumping areas can be preliminarily determined in the abnormally stopped areas; further combining with the aerial photography of the unmanned aerial vehicle, comparing the image set of the aerial photography image of the unmanned aerial vehicle with the image set of the known dangerous waste dumping points, and screening out the illegal dumping areas determined by the screening system in the suspicious illegal dumping areas.
Thus, according to the method and the device, a positioning system, a high-resolution satellite and unmanned aerial vehicle are combined for aerial photography, illegal dumping areas determined by the system are screened through three layers of screening processes, firstly, abnormal parking areas of dangerous waste transport vehicles are screened, secondly, suspicious illegal dumping areas are screened out in the abnormal parking areas, and finally, the illegal dumping areas determined by the system are further screened out in the suspicious illegal dumping areas.
Optionally, the abnormal stop area is a circle or a rectangle centered on the abnormal stop point of the transportation vehicle. The radius of the circle and the length and width of the rectangle can be set according to requirements. Because the area scope of high-resolution satellite and unmanned aerial vehicle aerial photography is generally rectangle, the shape of these unusual dwell area is also preferably rectangle, and the length of side of rectangle can be according to the scope demand of high-resolution satellite and unmanned aerial vehicle aerial photography setting.
Optionally, the process of determining an abnormal stopping point of the hazardous waste transport vehicle comprises:
determining a time threshold for abnormal dwell of the hazardous waste transport vehicle;
determining the actual residence time of the hazardous waste transport vehicle at a certain residence point according to the real-time position information;
and comparing the actual stay time with the time threshold of the abnormal stay, and determining the stay point as an abnormal stay point when the actual stay time is greater than the time threshold of the abnormal stay.
The stopping point can be a fixed point with a definite position, or a distance, for example, when the transport vehicle is stationary, the stopping point is a fixed point, and when the transport vehicle moves, the stopping point is a distance where the transport vehicle moves; the dwell time corresponds to the time that the transport vehicle has passed at the dwell point.
Thus, by setting an abnormal stop time threshold and comparing the actual stop time of the hazardous waste transport vehicle with the threshold, it can be determined whether the transport vehicle has passed the stop point in normal time. When the actual stay time is larger than the time threshold of the abnormal stay, determining the stay point as an abnormal stay point; conversely, when the actual dwell time is less than the time threshold for abnormal dwell, then the dwell point may be excluded.
Optionally, given a distance threshold D, the time threshold is denoted as T, and is defined as follows:
T＝F(H、G、F、U、Y) (1)
in the formula (1), H is a transport vehicle type, G is a transport vehicle load, F is a road type, U is a transport vehicle parking spot land use type, and Y is a transport hazardous waste type. The function type of the time threshold T may employ a multiple linear regression model.
By setting the distance threshold value D and the time threshold value T, when the time used by the transport vehicle for driving the road section to be the distance threshold value D is greater than the time threshold value T, the driving road section is determined as the abnormal stop point.
In the function of the time threshold T, according to the information corresponding to the hazardous waste bill of the transport vehicle, the vehicle type H, the vehicle load G and the transport hazardous waste type Y can be confirmed, and according to the specific position of the abnormal stopping point, the land utilization type U and the road type F corresponding to the abnormal stopping point can be confirmed.
Optionally, in step 2, exempting the special abnormal staying area is further included. Special abnormal stopping areas include gas stations, high-speed service stations and the like, and the stopping at the places belongs to normal stopping, so that the stopping is not included in a suspicious illegal dumping point.
Optionally, the process of comparing the satellite image characteristics of the abnormal staying area before and after the abnormal staying of the hazardous waste transport vehicle includes:
comparing the satellite image characteristics of the dangerous waste transport vehicle at two time points before and after the abnormal stop by using a perceptual hash algorithm, setting a length threshold of a Hamming distance, and if the Hamming distance of the satellite image characteristics of the two time points is greater than the length threshold, determining that the area is a suspicious illegal dumping area.
The determination process regarding the two points of time before and after the abnormal stop of the hazardous waste transport vehicle is as follows: the point in time before the abnormal stop of the hazardous waste transport vehicle may be selected to be any time before the abnormal stop, and in one embodiment, the point in time before the abnormal stop is selected to be the moment when the transport vehicle enters the suspected illegal dumping area; the point in time after the abnormal stop of the hazardous waste transport vehicle may be selected to be any time after the abnormal stop, and in one embodiment, the point in time after the abnormal stop is selected to be the moment when the transport vehicle leaves the suspected illegal dumping area. In addition, the two time points before and after the abnormal stop may also be set as fixed time points, for example, the time point before the abnormal stop is selected as the time when the transportation vehicle departs from the waste unit, and the time point after the abnormal stop is selected as the time when the transportation vehicle arrives at the disposal unit.
The specific process of comparing the image characteristics of the dangerous waste transport vehicle at two time points before and after the abnormal stop by using the perceptual hash algorithm is as follows:
changing the images of the two time points to the same pixel size, and carrying out graying treatment;
calculating the gray average value of all pixels of the images at two time points;
comparing the gray scale of each pixel with the average value, and recording the gray scale which is greater than or equal to the average value as 1 and the gray scale which is smaller than the average value as 0 so as to construct the information of the images of two time points;
calculating the Hamming distance of the images at the two time points based on the information of the images at the two time points;
given a hamming distance length threshold, when the hamming distance of the images at two time points is smaller than the hamming distance length threshold, the images at two time points are considered to have no obvious difference.
In this way, by comparing the image characteristics of two time points by using the perceptual hash algorithm, the degree of difference between the two images can be quickly identified, wherein the degree of difference is measured by the hamming distance of the images, and when the hamming distance of the two images is greater than a given length threshold, the two images can be considered to have a larger difference, and the area is determined to be a suspicious illegal dumping area.
Optionally, the process of comparing the image set of the aerial photo of the unmanned aerial vehicle with the image set of the known hazardous waste dumping points is as follows:
acquiring an image set of known hazardous waste dumping points in a research area corresponding to an unmanned aerial vehicle shooting area, and extracting image features;
and comparing the picture set of the pictures shot by the unmanned aerial vehicle with the image set of the known dangerous waste dumping points, classifying the images by using an SVM classifier, and regarding the image set approaching to the known dangerous waste dumping points as an illegal dumping area determined by the system.
Optionally, in step 4, the unmanned aerial vehicle aerial photography includes digital camera shooting and thermal infrared imager shooting.
The digital camera can be used for installing a digital camera with proper precision for the unmanned aerial vehicle, and meanwhile, the soil is used for covering the illegal dumping place of part of dangerous waste, so that the unmanned aerial vehicle can be additionally provided with a thermal infrared imager for observation. The image range shot by the unmanned aerial vehicle is the suspicious illegal dumping area determined in the step 3.
Therefore, by combining the shooting of the digital camera and the shooting of the thermal infrared imager, the dangerous waste in the area which is possibly illegally dumped can be clearly and comprehensively observed. And the union set of the illegal dumping areas respectively determined by camera shooting and thermal infrared imager shooting is the illegal dumping area set determined by the system finally screened.
Optionally, the process of screening the picture shot by the digital camera for the illegal dumping area determined by the system is as follows:
shooting an image set corresponding to a known hazardous waste dumping area in a research area by using a digital camera, and extracting image characteristics;
and removing interference information contained in the pictures shot by the digital camera, classifying the images by using an SVM classifier, and identifying an image set approaching to the known dangerous waste dumping point in the corresponding research area as an illegal dumping area determined by the system.
Optionally, the process of screening the picture shot by the thermal infrared imager for the illegal dumping area determined by the system is as follows:
shooting a thermal image set of a known hazardous waste dumping area in a corresponding research area by using a thermal infrared imager, and extracting thermal image characteristics;
and removing interference information contained in the picture shot by the thermal infrared imager, classifying the image by using an SVM classifier, and identifying the thermal image set approaching the known dangerous waste dumping point in the corresponding research area as an illegal dumping area determined by the system.
Optionally, in the step 4, after the illegal dumping region determined by the system is screened from the suspected illegal dumping region, the method further includes performing a field investigation on the illegal dumping region determined by the system, so as to determine an actual illegal dumping region.
The results of the field survey can be divided into two categories: (1) if the system determines that the illegal dumping area does not have actual illegal dumping, the system rejects the area to form an illegal dumping area; (2) and if the actual illegal dumping exists in the illegal dumping area determined by the system, rapidly processing the illegal dumping dangerous waste.
Therefore, according to the method, the process that the actual illegal dumping area is confirmed is very timely, so that the illegal dumping dangerous waste can be more conveniently treated, and the environment is prevented from being damaged more.
According to another aspect of the present application, there is provided a system for managing and warning risk of hazardous waste transportation, the system comprising: the system comprises a vehicle-mounted device module, a remote server module and an unmanned aerial vehicle image identification module;
the vehicle-mounted device module comprises a position sensing module, and the position sensing module reads real-time position information of the transport vehicle and sends the real-time position information to the remote server module;
the vehicle-mounted device module comprises a position sensing module, and the position sensing module reads real-time position information of the transport vehicle and sends the real-time position information to the remote server module;
the remote server module comprises a position information analysis module and a satellite identification module, wherein the position information analysis module receives the data read by the position sensing module and determines an abnormal staying area of the hazardous waste transport vehicle, and the satellite identification module compares satellite image characteristics of the abnormal staying area before and after the abnormal staying of the hazardous waste transport vehicle by using a satellite image of the abnormal staying area of the hazardous waste transport vehicle shot by a high-resolution satellite and determines a suspicious illegal dumping area;
the unmanned aerial vehicle image identification module carries out aerial photography on the suspicious illegal dumping area, the result is transmitted to the remote server module, the remote server module compares the picture set of the aerial photography picture of the unmanned aerial vehicle with the image set of the known dangerous waste dumping point, and therefore the illegal dumping area determined by the system is screened from the suspicious illegal dumping area.
Has the advantages that:
by constructing a system comprising a remote server module, a vehicle-mounted device module and an unmanned aerial vehicle image recognition module, carrying out multi-dimensional comprehensive monitoring and real-time early warning on units and vehicles related to hazardous waste transportation; judging the abnormal stopping point of the hazardous waste transport vehicle and whether the abnormal stopping point illegally dumps the hazardous waste in real time through a position information sensing and image recognition technology, and finishing the tracing of the illegal dumping of the hazardous waste by combining with field investigation; the dangerous waste state in the transportation process is monitored in real time by combining the sensor equipment, and an alarm is given out on an abnormal state, so that the risk emergency in advance is realized.
Drawings
Certain specific embodiments of the present application will hereinafter be described in detail by way of example and not limitation with reference to the accompanying drawings, in which like reference numerals identify the same or similar parts or features, and it will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. In the drawings:
FIG. 1 is a schematic view of a hazardous waste transportation risk management and control early warning system according to an embodiment;
FIG. 2 is a flow chart of a hazardous waste transportation risk management and control early warning method according to an embodiment;
FIG. 3 is a flow diagram of the establishment of a hazardous waste transfer transportation platform, screening transportation units and disposal units, and the establishment of an electronic coupon management system, in one embodiment;
FIG. 4 is a flow chart of the determination of an abnormal stopping point for a hazardous waste transport vehicle in one embodiment;
FIG. 5 is a flow diagram of determining a suspected illegal dumping area in one embodiment;
FIG. 6 is a flow diagram of a system for screening suspected illegal dumping areas for illegal dumping areas, according to one embodiment.
Detailed Description
In order that the manner in which the above-recited objects, features and advantages of the present application are obtained will be readily apparent, a more particular description of the invention briefly described above will be rendered by reference to specific details that are set forth in the appended description, which are indicative of but are capable of being practiced in a variety of ways other than those specifically described herein, and which are readily apparent to those of ordinary skill in the art, and which are therefore not limited to the specific embodiments disclosed below.
Fig. 1 is a schematic view of a system for managing and warning risks in hazardous waste transportation according to an embodiment of the present disclosure. The system consists of three modules: the system comprises an on-board device module, a remote server module and an unmanned aerial vehicle image identification module.
The vehicle-mounted device module comprises a position sensing module, and the position sensing module is specifically composed of a GPS satellite 1 and a GPS device 9 installed on a transport vehicle 2. The position sensing module positions the transport vehicle and transmits the position information to the remote server module through wireless transmission.
The vehicle-mounted device module can also comprise a vehicle-mounted sensor 6 which is arranged on the transport vehicle 2 and used for monitoring the state of the dangerous waste, and the vehicle-mounted sensor 6 is used for sensing the real-time state of the dangerous waste, so that real-time early warning of the dangerous waste is formed, and when the vehicle-mounted device module is combined with the real-time position information of the transport vehicle, illegal dumping can be determined in advance. The in-vehicle sensor 6 includes: at least one of a pressure sensor, a liquid level sensor, a temperature sensor, a toxic gas sensor, and a smoke sensor.
In addition, the vehicle-mounted device module further comprises a vehicle-mounted display screen 7 and an embedded vehicle-mounted computer 8 which are installed on the transport vehicle 2, the embedded vehicle-mounted computer 8 is used for receiving information sent by the position sensing module and the vehicle-mounted sensor 6, the vehicle-mounted display screen 7 displays relevant parameter information, and meanwhile the vehicle-mounted display screen 7 is used for receiving results sent by the remote server module and displaying the results.
The remote server module comprises a position information analysis module and a satellite identification module. The position information analysis module is specifically selected from the central processing unit 4, and the satellite identification module is specifically selected from the high-resolution satellite 3. The central processor 4 receives the data read by the position sensing module, thereby determining the abnormal staying area of the hazardous waste transport vehicle; according to the abnormal staying area, calling the satellite images of the transportation vehicles in the abnormal staying area shot by the high-resolution satellite 3, and comparing the image characteristics of the abnormal staying area at two time points before and after the abnormal staying of the dangerous waste transportation vehicles, thereby determining the suspicious illegal dumping area.
The remote server module may also include a hazardous waste platform module for establishing waste transfer transport platforms, screening transport units and disposal units, establishing electronic coupon management systems, and the like.
The unmanned aerial vehicle image recognition module is selected from unmanned aerial vehicle equipment 5, and the unmanned aerial vehicle equipment carries a digital camera and a thermal infrared imager. The unmanned aerial vehicle device 5 carries out aerial photography on the suspicious illegal dumping area, the result is transmitted to the central processing unit 4 of the remote server module, the central processing unit 4 compares the picture set of the aerial photography picture of the unmanned aerial vehicle with the image set of the known dangerous waste dumping point, and therefore the illegal dumping area determined by the system is screened from the suspicious illegal dumping area.
As shown in fig. 2, it is a flowchart of a method for hazardous waste transportation risk management and control early warning in an embodiment of the present application, and the method includes 4 steps:
and 4, carrying out aerial photography on the suspicious illegal dumping area by using an unmanned aerial vehicle, and comparing the picture set of aerial pictures of the unmanned aerial vehicle with the image set of known dangerous waste dumping points, thereby screening the illegal dumping area determined by the system from the suspicious illegal dumping area.
Before the dangerous waste transport vehicle starts to transport, the processes of establishing a dangerous waste transfer transport platform, screening a transport unit and a disposal unit and establishing an electronic bill management system are further included. As shown in fig. 3, a flow chart for establishing a hazardous waste transfer transportation platform, a screening transportation unit and a disposal unit and an electronic bill management system is provided.
Wherein, the process of establishing the hazardous waste transfer transportation platform comprises: (1) establishing a database of a production and waste unit, wherein the content of the database comprises information such as name, position, establishment time, product type, process characteristics, type of produced hazardous waste, industry, production value and the like of the production and waste unit; (2) establishing a database of a transportation unit, wherein the database comprises the name of the transportation unit, the license plate numbers, the loads and the models of all transportation vehicles, personal information of drivers and the like; (3) establishing a database of disposal units, wherein the database comprises information such as names, positions, establishment time, types of the hazardous wastes capable of being treated, design treatment capacity, treatment modes and the like of the disposal units; (4) and establishing a dangerous waste transfer transportation platform, and importing the database information established by the waste production unit, the transportation unit and the disposal unit into the platform.
The process of screening transportation units and disposal units includes: (1) determining the type of hazardous waste, and giving each hazardous waste a serial number, and recording the serial number as Y ═ Y1、Y2、……、Yn}; (2) according to the recorded unit information of production waste, transportation and disposal in the database, the matching number is YiThe hazardous waste has units for generating, transferring and disposing the qualification; (3) the production waste unit inputs the serial number Y of the dangerous waste to be disposed on the dangerous waste transfer transportation platformiAnd the platform lists the corresponding transportation units and handling units according to the principle that the handling capacity and the transportation distance are shortest.
The process of establishing the electronic coupon management system comprises the following steps: (1) before the transportation of the dangerous waste, the production and waste unit, the transportation unit and the disposal unit are respectively filled on the platformThe dangerous waste transfer coupon fills in the content which comprises the detailed names of the three units, the transportation time, the transportation vehicle information and the basic information of the dangerous waste; (2) the platform receives the hazardous waste transfer coupon information, and imports corresponding information matched in the database, the platform automatically generates the transportation serial number of the hazardous waste transportation, and the serial number is recorded as V ═ V1、V2、……、Vn}; (3) respectively establishing two sub-platforms, namely an intra-provincial transportation platform and a trans-provincial transportation platform according to two conditions that whether the position of a waste production unit and the position of a disposal unit are in the same province, and if the position of the waste production unit and the position of the disposal unit are in the same province, importing the information of the dangerous waste transportation into the intra-provincial transportation platform; and if the cross-provincial transportation condition exists, importing the information of the dangerous waste transportation into a cross-provincial transportation platform.
FIG. 4 is a flow chart illustrating the determination of the abnormal stopping point of the hazardous waste transport vehicle in step 2 in one embodiment. The specific process comprises the following steps:
setting a distance threshold D and a time threshold T, where the distance threshold D may be selected as a short suitable distance, such as 5 meters or 10 meters;
the time threshold T is defined as follows:
T＝F(H、G、F、U、Y) (1)
in the formula (1), H is a transport vehicle type, G is a transport vehicle load, F is a road type, U is a transport vehicle parking spot land utilization type, and Y is a transport hazardous waste type;
according to the hazardous waste union ViThe information corresponding to the number, the vehicle type H, the vehicle load G and the type Y of the transported dangerous waste are confirmed according to the determined place ZiPoint-determining a region land utilization type U corresponding to the point-determining point and a road type F where the point-determining point is located; and according to ZiInformation of relevant parameters of points, and a set of obtained { H }i、Gi、Fi、Ui、YiCalculating the position Z of the dangerous waste transport vehicleiTime threshold T of pointi；
Next, Z is determinediWhether the point is a special exemptable area, if so, Z is determinediRegions corresponding to points are not abnormalA dwell area; if not, further judging to obtain the Z position of the dangerous waste transport vehicle according to the information recorded by the vehicle-mounted GPS equipmentiThe actual stay time of the point is recorded as Ti ', namely the running distance of the transport vehicle on Ti ' does not exceed a distance threshold value D, the size of Ti and Ti ' is compared, and when Ti is used, the actual stay time is recorded as Ti ', namely the running distance of the transport vehicle on Ti ' does not exceed the distance threshold value D>When Ti', the Zi point is not regarded as an abnormal stop point, when Ti<When Ti' is used, Zi points are regarded as abnormal stopping points, and all the abnormal stopping points are recorded as Z ═ Z1、Z2、Z3、……、Zn}。
Fig. 5 is a flowchart illustrating the determination of a suspected illegal dumping area in step 3 according to an embodiment. The specific process comprises the following steps:
determining a target area, selecting a proper high-resolution satellite, and acquiring abnormal stay areas corresponding to the abnormal stay points Z on related websites or data interfaces provided by the high-resolution satellite at time t1、t2Respectively, recording the images as Rzi1And Rzi2Here time t1The selection is selectable as the point in time before the transport vehicle enters the abnormal stay area, time t2Selecting a time point after the transport vehicle leaves the abnormal staying area;
according to the abnormal staying area, the set Z ═ Z of the contrast graph of the abnormal staying area can be determined1(Rz11、Rz12)、Z2(Rz21、Rz22)、Z3(Rz31、Rz32)、……、Zn(Rzn1、Rzn2)}；
Comparing Rz using perceptual hashing algorithmsi1、Rzi2If there is a significant difference, the position information of this partial region is set as M ═ M1、M2、M3、……、MnA set M is a suspicious illegal dumping area, and an illegal dumping area determined by a system is further screened from the suspicious illegal dumping area of the set M through a step 4; if there is no difference, the position information of the partial area is recorded as a set N ═ N1、N2、N3、……、NnAt this time canTo directly exclude the set N, i.e. the set N does not belong to a suspected illegal dumping area.
Comparing Rz using perceptual hashing algorithmsi1、Rzi2The process of image feature of (1) is as follows:
reduction of Rzi1、Rzi2The image of (1) is reduced to 8 multiplied by 8, and the total number of pixels is 64, so that the details of the image are removed, the image difference caused by different sizes/proportions is abandoned, the reduced image is subjected to graying treatment and is converted into 64-level gray, namely all pixel points have 64 colors in total;
calculating the gray level average value of all pixels;
comparing the gray scale of the pixels, comparing the gray scale of each pixel with the average value, and recording the gray scale which is greater than or equal to the average value as 1 and the gray scale which is smaller than the average value as 0;
combining the obtained 0 and 1 values to form a 64-bit integer which is equivalent to the 'fingerprint' of the corresponding picture;
comparison of Rzi1、Rzi2The number of bits in the 64-bit "fingerprint" obtained by the two is different, i.e. the Hamming distance, is recorded as DnIn the information theory, the Hamming distance between two character strings with equal length is the number of different characters at the corresponding positions of the two character strings;
setting a length threshold D of Hamming distanceNWhen D is presentnGreater than or equal to DNWhen will look at Rzi1、Rzi2The images of (a) have obvious differences and are listed in a set M; on the contrary, when DnIs less than DNThen, it will be considered as Rzi1、Rzi2Are substantially identical and are listed in set N.
Fig. 6 is a flowchart illustrating the step 4 of screening the suspected illegal dumping area for the illegal dumping area determined by the system according to an embodiment. The specific process comprises the following steps:
selecting a proper unmanned aerial vehicle, installing a digital camera with proper precision for the unmanned aerial vehicle, and meanwhile, considering that the illegal dumping place of a part of dangerous waste is covered by soil, installing a thermal infrared imager for the unmanned aerial vehicle for observation;
an unmanned aerial vehicle is used for shooting a digital camera and a thermal infrared imager in the region M, and a group of pictures obtained by shooting the region by the digital camera is recorded as A { a1、a2、a3、……、anAnd a group of images shot by a thermal infrared imager are marked as B { B }1、b2、b3、……、bnTransmitting the data of the A atlas and the B atlas to a remote server, and then respectively analyzing the data of the A atlas and the data of the B atlas;
(1) with respect to the analysis of the atlas a,
before classifying the atlas A, preprocessing image data to remove interference information contained in the image; the reason for preprocessing is that the image data contains not only useful information but also much disturbing information, e.g. wheat fields, houses, roads, etc. should be ignored, a spatial filter can be used to remove unwanted multi-order energy peaks and extract only the central maxima of the diffraction pattern, and a spatial filter matrix is used for a "sharpening" (edge enhancement) filter to classify the image.
An image set shot by a digital camera with a known dangerous waste dumping point in a corresponding research area is shot by an unmanned aerial vehicle, and the image set is obtained through historical sampling and is recorded as S { S1、s2、s3、……、snExtracting image features from the atlas;
comparing the A atlas with the S atlas, establishing an SVM classifier to classify the A atlas, and dividing the A atlas into two image sets: the image set approaching the S-map set is marked as U { U }1、u2、u3、……、unThe U set is an illegal dumping area determined by the system and further screened from the A atlas, and the point position of the illegal dumping site corresponding to the illegal dumping area determined by the system is recorded as E { E }1、e2、e3、……、en}。
(2) With respect to the analysis of the atlas B,
processing an atlas B recorded by using a thermal infrared imager, wherein the principle is that invisible infrared energy emitted by different objects is converted into visible thermal images, and different colors on the thermal images represent different temperatures of the measured object;
the method comprises the steps of utilizing an unmanned aerial vehicle equipped with a thermal infrared imager to shoot thermal images of known dangerous waste dumping points in a research area (for example, if the dangerous waste transferring and transporting system aims at a certain province, the research area is regarded as the province), obtaining through historical sampling, and recording a set of thermal images of the known dangerous waste dumping points as C { C }1、c2、c3、……、cnExtracting the thermal image characteristics of the atlas;
and (3) comparing the B picture set with the C picture set, establishing an SVM classifier to classify the B picture set, and dividing the B picture set into two picture sets: set of images Q { Q } that approach the C atlas1、q2、q3、……、qnAnd a set of images I { I } that deviate from the C atlas1、i2、i3、……、inRecording the illegal dumping site point position corresponding to the illegal dumping area determined by the system as W { W }1、w2、w3、……、wn}；
Illegal dumping site set E { E) corresponding to illegal dumping region determined by system1、e2、e3、……、enAnd the set W { W }1、w2、w3、……、wnGet union set R { R }1(x1，y1)、r2(x2，y2)、r3(x3，y3)、……、rn(xn，yn) In which r isi(xi，yi) And longitude and latitude information of illegal dumping points corresponding to the illegal dumping areas determined by the system and generated by the dangerous waste transportation link with the representative number Vi, wherein the R set is the illegal dumping points corresponding to the illegal dumping areas determined by the system and finally screened by the unmanned aerial vehicle image recognition link.
The method and the system have the advantages that through the construction of the early warning system comprising the remote server module, the vehicle-mounted device module and the unmanned aerial vehicle image recognition module, multi-dimensional comprehensive monitoring and real-time early warning are carried out on units and vehicles related to hazardous waste transportation; judging the abnormal stopping point of the hazardous waste transport vehicle and whether the abnormal stopping point illegally dumps the hazardous waste in real time through a position information sensing and image recognition technology, and finishing the tracing of the illegal dumping of the hazardous waste by combining with field investigation; the dangerous waste state in the transportation process is monitored in real time by combining the sensor equipment, and an alarm is given out on an abnormal state, so that the risk emergency in advance is realized.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the present application have been illustrated and described in detail herein, many other variations and modifications consistent with the principles of the application may be ascertained or derived directly from the disclosure herein without departing from the spirit and scope of the application. Accordingly, the scope of the present application should be understood and interpreted to cover all such other variations or modifications.
Claims (9)
1. A hazardous waste transportation risk management and control early warning method is characterized by comprising the following steps:
step 1, identifying real-time position information of a hazardous waste transport vehicle;
step 2, determining an abnormal stopping point of the hazardous waste transport vehicle, and determining an abnormal stopping area of the hazardous waste transport vehicle based on the abnormal stopping point;
step 3, comparing the characteristics of the satellite images of the abnormal staying areas before and after the abnormal staying of the hazardous waste transport vehicle by using the satellite images of the abnormal staying areas of the hazardous waste transport vehicle shot by the high-resolution satellite, and determining suspicious illegal dumping areas;
and 4, carrying out aerial photography on the suspicious illegal dumping area by using an unmanned aerial vehicle, and comparing a picture set of aerial pictures of the unmanned aerial vehicle with a known image set of dangerous waste dumping points, thereby screening the illegal dumping area determined by the system from the suspicious illegal dumping area.
2. The method of claim 1, wherein the abnormal parking area is a rectangle centered on an abnormal parking point of the transportation vehicle.
3. The method of claim 1, wherein the process of determining an abnormal stopping point for the hazardous waste transport vehicle comprises: determining a time threshold for abnormal dwell of the hazardous waste transport vehicle; determining the actual residence time of the hazardous waste transport vehicle at a certain residence point according to the real-time position information; and comparing the actual stay time with the time threshold of the abnormal stay, and determining the stay point as an abnormal stay point when the actual stay time is greater than the time threshold of the abnormal stay.
4. The method of claim 1, wherein step 2 further comprises exempting from special abnormal stay areas.
5. The method of claim 1, wherein the process of comparing the satellite image characteristics of the abnormal parking area before and after the abnormal parking of the hazardous waste transport vehicle comprises: comparing the satellite image characteristics of the dangerous waste transport vehicle at two time points before and after the abnormal stop by using a perceptual hash algorithm, setting a length threshold of a Hamming distance, and if the Hamming distance of the satellite image characteristics of the two time points is greater than the length threshold, determining that the area is a suspicious illegal dumping area.
6. The method according to claim 1, wherein in the step 4, the unmanned aerial vehicle aerial photography comprises digital camera photography and thermal infrared imager photography.
7. The method of claim 1, wherein the comparing of the set of images of the aerial photo of the drone to the set of images of known hazardous waste dump points is as follows: utilizing an unmanned aerial vehicle to shoot an image set of known hazardous waste dumping points in a corresponding research area, and extracting image features; and comparing the picture set of the picture shot by the unmanned aerial vehicle with the image set of the known dangerous waste dumping points in the corresponding research area, classifying the images by using an SVM classifier, and identifying the image set approaching to the known dangerous waste dumping points in the corresponding research area as an illegal dumping area determined by the system.
8. The method as claimed in claim 1, wherein in step 4, after screening the illegal dumping area determined by the system from the suspected illegal dumping area, the method further comprises performing a field investigation on the illegal dumping area determined by the system, thereby determining an actual illegal dumping area.
9. A hazardous waste transportation risk management and control early warning system, the system comprising: the system comprises a vehicle-mounted device module, a remote server module and an unmanned aerial vehicle image identification module; the vehicle-mounted device module comprises a position sensing module, and the position sensing module reads real-time position information of the transport vehicle and sends the real-time position information to the remote server module;
the remote server module comprises a position information analysis module and a satellite identification module, wherein the position information analysis module receives the data read by the position sensing module and determines an abnormal staying area of the hazardous waste transport vehicle, and the satellite identification module compares satellite image characteristics of the abnormal staying area before and after the abnormal staying of the hazardous waste transport vehicle by using a satellite image of the abnormal staying area of the hazardous waste transport vehicle shot by a high-resolution satellite and determines a suspicious illegal dumping area;
the unmanned aerial vehicle image identification module carries out aerial photography on the suspicious illegal dumping area, the result is transmitted to the remote server module, the remote server module compares the picture set of the aerial photography picture of the unmanned aerial vehicle with the image set of the known dangerous waste dumping point, and therefore the illegal dumping area determined by the system is screened from the suspicious illegal dumping area.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE1430023A1 (en) * | 2013-05-21 | 2014-11-09 | Martin Andreas Olsson | Digital expiration date unit |
| CN106971488A (en) * | 2017-04-19 | 2017-07-21 | 北京京城环保股份有限公司 | A kind of fire for disposing feed system for rotary kiln danger wastes prevents and treats system and method |
| CN109081000A (en) * | 2018-06-19 | 2018-12-25 | 张淏瑞 | Biohazard Waste monitoring management system |
| CN209859006U (en) * | 2019-05-30 | 2019-12-27 | 南京盛滨环境研究院有限公司 | Dangerous solid waste storage and transportation and monitoring management device based on Internet of things |
| CN111661531A (en) * | 2020-06-05 | 2020-09-15 | 广东慧福信息科技有限公司 | Medical waste recovery system and data storage method thereof |
| CN111815223A (en) * | 2020-05-25 | 2020-10-23 | 阿里巴巴集团控股有限公司 | Object tracking system, method, apparatus and storage medium |
| CN112085241A (en) * | 2019-06-12 | 2020-12-15 | 江苏汇环环保科技有限公司 | Environment big data analysis and decision platform based on machine learning |
| CN112085929A (en) * | 2020-09-10 | 2020-12-15 | 湖南科技大学 | Dangerous chemical road transportation risk early warning system and method |
| CN112488667A (en) * | 2020-12-15 | 2021-03-12 | 河南新辰环保科技有限公司 | Industrial solid waste overall process real-time monitoring system and method |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE541634C2 (en) * | 2018-03-06 | 2019-11-19 | Scania Cv Ab | Method and control arrangement for identification of parking areas |
| US20200150643A1 (en) * | 2018-05-07 | 2020-05-14 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for data collection, learning, and streaming of machine signals for analytics and maintenance using the industrial internet of things |
| CN112560574A (en) * | 2020-10-30 | 2021-03-26 | 广东柯内特环境科技有限公司 | River black water discharge detection method and recognition system applying same |
-
2021
- 2021-06-04 CN CN202110624155.2A patent/CN113361914B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE1430023A1 (en) * | 2013-05-21 | 2014-11-09 | Martin Andreas Olsson | Digital expiration date unit |
| CN106971488A (en) * | 2017-04-19 | 2017-07-21 | 北京京城环保股份有限公司 | A kind of fire for disposing feed system for rotary kiln danger wastes prevents and treats system and method |
| CN109081000A (en) * | 2018-06-19 | 2018-12-25 | 张淏瑞 | Biohazard Waste monitoring management system |
| CN209859006U (en) * | 2019-05-30 | 2019-12-27 | 南京盛滨环境研究院有限公司 | Dangerous solid waste storage and transportation and monitoring management device based on Internet of things |
| CN112085241A (en) * | 2019-06-12 | 2020-12-15 | 江苏汇环环保科技有限公司 | Environment big data analysis and decision platform based on machine learning |
| CN111815223A (en) * | 2020-05-25 | 2020-10-23 | 阿里巴巴集团控股有限公司 | Object tracking system, method, apparatus and storage medium |
| CN111661531A (en) * | 2020-06-05 | 2020-09-15 | 广东慧福信息科技有限公司 | Medical waste recovery system and data storage method thereof |
| CN112085929A (en) * | 2020-09-10 | 2020-12-15 | 湖南科技大学 | Dangerous chemical road transportation risk early warning system and method |
| CN112488667A (en) * | 2020-12-15 | 2021-03-12 | 河南新辰环保科技有限公司 | Industrial solid waste overall process real-time monitoring system and method |
Non-Patent Citations (3)
| Title |
|---|
| Assessment of pollution of potentially harmful elements in soils surrounding a municipal solid waste incinerator, China;Ying Han;《Frontiers of Environmental Science & Engineering》;20161201;第10卷(第6期);全文 * |
| 河北省医疗废物焚烧污染物排放及控制要求;李歆琰;《四川环境》;20170831;第36卷(第4期);第128-134页 * |
| 社会源危险废弃物的全过程追踪机制研究;侯英杰;《黑龙江生态工程职业学院学报》;20200930;第33卷(第5期);第1-5页 * |
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