CN117522655B - Data processing method and device for garbage point area - Google Patents
Data processing method and device for garbage point area Download PDFInfo
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Abstract
The application provides a data processing method and device for a garbage point area, and relates to the technical field of electric digital data processing, wherein the method comprises the following steps: monitoring first weight change data of a first garbage point and monitoring second weight change data of a second garbage point; if the first weight change data and the second weight change data are in an abnormal change state, acquiring first image data and acquiring second image data; determining target object data according to the first image data and the second image data, determining first garbage falling data according to the first image data, and determining second garbage falling data according to the second image data; determining a target destruction coefficient of the target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data and the target object data; and determining the accommodation priority and the target accommodation policy of the target object according to the target destruction coefficient, wherein the calculation overhead is low and the living experience of people can be improved.
Description
Technical Field
The application relates to the technical field of electric digital data processing, in particular to a data processing method and device for a garbage point area.
Background
At present, in areas with dense garbage points such as villages in cities, road environments are complex, and how to reasonably utilize the data of the garbage points to improve the life experience of people becomes a problem.
Disclosure of Invention
In view of this, the application provides a data processing method and device for a garbage point area, which can determine a target object to be accommodated and a corresponding accommodating policy based on the weight change of the garbage point and data such as images, has low calculation effort cost and can improve the life experience of people.
In a first aspect, an embodiment of the present application provides a data processing method for a garbage point area, which is applied to a processing module in a data processing system, where the data processing system further includes a first weighing module, a first camera module, and a second weighing module and a second camera module that are disposed at a first garbage point, where the method includes:
monitoring, by the first weighing module, first weight change data of the first garbage point, and monitoring, by the second weighing module, second weight change data of the second garbage point;
if the first weight change data is in an abnormal change state in a first period and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by the first camera module in the first period and acquiring second image data acquired by the second camera module in the second period;
Determining target object data according to the first image data and the second image data, determining first garbage falling data according to the first image data, and determining second garbage falling data according to the second image data;
determining a target destruction coefficient of a target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data and the target object data;
and determining the accommodation priority and the target accommodation policy of the target object according to the target destruction coefficient.
In a second aspect, an embodiment of the present application provides a data processing apparatus for a garbage point area, which is applied to a processing module in a data processing system, where the data processing system further includes a first weighing module, a first camera module, and a second weighing module and a second camera module disposed at a first garbage point, where the apparatus includes:
a monitoring unit for monitoring first weight change data of the first garbage point through the first weighing module and monitoring second weight change data of the second garbage point through the second weighing module;
An acquiring unit, configured to acquire first image data acquired by the first camera module in the first period and acquire second image data acquired by the second camera module in the second period if the first weight change data is in an abnormal change state in the first period and the second weight change data is in the abnormal change state in the second period;
a first determining unit, configured to determine target object data according to the first image data and the second image data, determine first garbage drop data according to the first image data, and determine second garbage drop data according to the second image data;
a second determining unit configured to determine a target destruction coefficient of a target object based on the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data;
and the third determining unit is used for determining the accommodation priority and the target accommodation policy of the target object according to the target destruction coefficient.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing steps in any of the methods of the first aspect of the embodiments of the present application.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program causes a computer to perform some or all of the steps as described in any of the methods of the first aspect of the embodiments of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, wherein the computer program product comprises a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in any of the methods of the first aspect of embodiments of the present application. The computer program product may be a software installation package.
It can be seen that, through the above data processing method and device for the garbage point area, the data processing system further includes a first weighing module, a first camera module, and a second weighing module and a second camera module disposed at a first garbage point, where the first weighing module monitors first weight change data of the first garbage point, and the second weighing module monitors second weight change data of the second garbage point; then, if the first weight change data is in an abnormal change state in a first period and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by the first camera module in the first period and acquiring second image data acquired by the second camera module in the second period; then, determining target object data according to the first image data and the second image data, determining first garbage dropping data according to the first image data, and determining second garbage dropping data according to the second image data; next, determining a target destruction coefficient of a target object from the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data; and finally, determining the accommodation priority and the objective accommodation policy of the objective object according to the objective destruction coefficient. The target object to be accommodated can be accurately determined, the required calculation force is low, the target object to be accommodated and the corresponding accommodation strategy can be determined based on the weight change of the garbage point, the image and other data, and the living experience of people is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is an application scenario diagram of a data processing method for a garbage point area according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 3 is a flow chart of a data processing method for a garbage point area according to an embodiment of the present application;
fig. 4 is a schematic diagram of a first scenario of a data processing method for a garbage point area according to an embodiment of the present application;
fig. 5 is a second schematic view of a data processing method for a garbage point area according to an embodiment of the present application;
fig. 6 is a schematic diagram of a third scenario of a data processing method for a garbage point area according to an embodiment of the present application;
fig. 7 is a functional unit composition block diagram of a data processing apparatus for a garbage point area according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will clearly and completely describe the technical solution in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
It should be understood that the term "and/or" is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, the character "/" indicates that the front and rear associated objects are an "or" relationship. The term "plurality" as used in the embodiments herein refers to two or more.
In the embodiments of the present application, "at least one item(s)" or the like means any combination of these items, including any combination of single item(s) or plural item(s), meaning one or more, and plural means two or more. For example, at least one (one) of a, b or c may represent the following seven cases: a, b, c, a and b, a and c, b and c, a, b and c. Wherein each of a, b, c may be an element or a set comprising one or more elements.
The "connection" in the embodiments of the present application refers to various connection manners such as direct connection or indirect connection, so as to implement communication between devices, which is not limited in any way in the embodiments of the present application.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The following describes related content, concepts, meanings, technical problems, technical solutions, advantageous effects and the like related to the embodiments of the present application.
At present, in areas such as villages in cities, garbage spots are denser, the number of the unrestrained animals is large, if kitchen garbage is large, garbage accumulated at the garbage spots is easy to be turned over by small animals such as unrestrained cats and dogs to cause garbage scattering, public health safety cannot be guaranteed, moreover, in the villages in cities, the building group is denser, the road environment of the small lane is more complex, the road communication points are particularly large, the number of places where the unrestrained animals can hide is large, a large amount of calculation resources are needed to be occupied by simply analyzing images shot by cameras, and the recognition accuracy is low.
In order to solve the problems, the application provides a data processing method and device for a garbage point area, which can accurately determine a target object to be accommodated, is low in data complexity of the garbage point and low in calculation power, and further can determine the target object to be accommodated and a corresponding accommodating strategy based on the weight change of the garbage point, the image and other data, so that the life experience of people is improved.
An application scenario of a data processing method for a garbage area in an embodiment of the present application will be described with reference to fig. 1, where the application scenario may include a first weighing module 110, a first image capturing module 120, a second weighing module 130, a second image capturing module 140, and a processing module 150.
The first weighing module 110 may be disposed at a first garbage site and is configured to weigh garbage contained in the first garbage site, where it may be understood that the first weighing module 110 may include a weighing sensor, a data acquisition terminal, a communication interface, and the like, and is configured to send the acquired first weight change data to the processing module 150.
The first camera module 120 may be disposed at the first garbage point, and is configured to collect an image of an area where the first garbage point is located.
The second weighing module 130 may be disposed at a second garbage point and is configured to weigh garbage contained in the second garbage point, where it may be understood that the second weighing module 130 may include a weighing sensor, a data acquisition terminal, a communication interface, and the like, and is configured to send the acquired second weight change data to the processing module 150.
The second camera module 140 may be disposed at the second garbage point, and is configured to collect an image of an area where the second garbage point is located.
The processing module 150 may control the first camera module 120 to collect first image data in a first period when it is determined that the weight change data of the first garbage point is abnormal in the first period, and the processing module 150 may control the second camera module 140 to collect second image data in a second period when it is determined that the weight change data of the second garbage point is abnormal in the second period, identify target objects existing in both the first image data and the second image data, and determine a storage priority and a storage policy of the target objects.
It can be understood that when more than two garbage points exist, weight change data and image data of each garbage point can be obtained for analysis and processing, and the processing logic is consistent with that of the two garbage points, which is not described herein.
Therefore, through the application scene and the system architecture in the application scene, the target object to be accommodated and the corresponding accommodation strategy can be determined based on the weight change of the garbage point, the image and other data, the calculation overhead is low, and the living experience of people can be improved.
In the following, referring to fig. 2 for describing the electronic device in the embodiment of the present application, fig. 2 is a schematic structural diagram of an electronic device provided in the embodiment of the present application, as shown in fig. 2, the electronic device 20 includes one or more processors 220, a memory 230, a communication module 240, and one or more programs 231, where the processor 220 is communicatively connected to the memory 230 and the communication module 240 through an internal communication bus.
Wherein the one or more programs 231 are stored in the memory 230 and configured to be executed by the processor 220, the one or more programs 231 comprising instructions for performing any of the steps of the method embodiments described above.
The processor 220 may be, for example, a central processing unit (Central Processing Unit, CPU), a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an Application-specific integrated circuit (ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, units and circuits described in connection with this disclosure. Processor 220 may also be a combination that performs computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, and the like.
Memory 230 may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. The volatile memory may be random access memory (random access memory, RAM) which acts as an external cache. By way of example but not limitation, many forms of random access memory (random access memory, RAM) are available, such as Static RAM (SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), synchronous Link DRAM (SLDRAM), and direct memory bus RAM (DR RAM).
It will be appreciated that the electronic device 20 may include more or fewer structural elements than those described in the above-described block diagrams, including, for example, a power module, physical key, wi-Fi module, speaker, bluetooth module, sensor, display module, etc., without limitation. The electronic device 20 may be any module in the above application scenario, which is not described herein.
After understanding the software and hardware architecture of the embodiments of the present application, a method for processing data for a garbage area in the embodiments of the present application is described below with reference to fig. 3, and fig. 3 is a schematic flow chart of a method for processing data for a garbage area provided in the embodiments of the present application, applied to a processing module in a data processing system, where the data processing system further includes a first weighing module, a first image capturing module, and a second weighing module and a second image capturing module disposed at a first garbage point, and specifically includes the following steps:
in step S301, first weight change data of a first garbage point is monitored by a first weighing module, and second weight change data of a second garbage point is monitored by a second weighing module.
The first weight change data represents a change in the weight of the garbage at the first garbage point, and generally, when a person drops the garbage into the first garbage point in a period other than garbage disposal, the first weight change data at the first garbage point increases in weight, and in a period other than garbage disposal, no person picks up the garbage from the first garbage point to cause the first weight change data to decrease in weight, and similarly, the second weight change data represents a change in the weight of the garbage at the second garbage point, and generally, when a person drops the garbage into the second garbage point in a period other than garbage disposal, the second weight change data at the second garbage point becomes an increase in weight, and in a period other than garbage disposal, no person picks up the garbage from the second garbage point to cause the second weight change data to decrease in weight.
Because the first garbage point and the second garbage point are garbage points in different areas, whether the target object exists or not can be identified through the weight change conditions of the two garbage points, so that the determined target object is more accurate, and the target object comprises a wandering animal.
It can be seen that monitoring the first weight change data of the first garbage point by the first weighing module and the second weight change data of the second garbage point by the second weighing module can provide data support for the subsequent determination of the target object.
Step S302, if the first weight change data is in an abnormal change state in a first period, and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by a first camera module in the first period, and acquiring second image data acquired by a second camera module in the second period.
If the first weight change data accords with weight reduction or weight is increased first and then reduced in the first time period, determining that the first weight change data is in the abnormal change state in the first time period; and if the second weight change data accords with weight reduction or weight increase and then weight reduction in the second period, determining that the second weight change data is in the abnormal change state in the second period.
It should be noted that, when a period in which garbage points need to be sorted, such as a period in which garbage disposal personnel performs sorting, collection, and the like, is not determined whether the change in the weight of garbage is abnormal, the garbage generally increases only and cannot be reduced by the aid of a void, when the weight of the garbage decreases, one case is that a circulating animal turns up the garbage from the garbage points, and when the weight of the garbage increases first and then decreases, one case is that a circulating animal enters the garbage points, turns up the garbage from the garbage points, and causes the weight of the garbage to decrease first and then, the starting time of the first period may be the time of the weight increase of the first garbage point when the weight of the first garbage point increases first and then decreases, the ending time of the first period may be the time of the weight stop decreasing after a certain time, and similarly, the starting time of the second period may be the time of the weight increase of the second garbage point when the weight of the second garbage point increases first and then decreases, and the ending time of the second period may not be the time of the weight stop decreasing after a certain time of the garbage.
Therefore, by acquiring the image data of the corresponding garbage point when the weight change of the garbage point is abnormal, the image acquisition at any time is not needed, the calculation overhead is reduced, the accuracy of the subsequent determination of the target object can be improved, and the garbage can be picked up only by the flowing animals, so that the erroneous judgment is avoided.
Step S303, determining target object data according to the first image data and the second image data, determining first garbage dropping data according to the first image data, and determining second garbage dropping data according to the second image data.
If the first image data includes a first object and the second image data includes the first object, the first object is determined to be the target object and the target object data is determined, the target object data includes a target object type and a target object variety, the target object type may include a shoulder height, a length and the like, the target object variety may be an approximate variety category determined based on external features, it may be understood that whether the first image data and the second image data exist the same first object may be determined through image matching, the first object is taken as the target object, this is because a streamer animal generally can pick up food at each garbage point, the determined target object may be more accurate by determining at least two garbage points, and the necessity of accommodation is greater, then the first garbage dropping data may be determined according to the first image data, the first image data includes an image before the first garbage point is changed in weight and an image after the weight change, the first garbage dropping data may reflect the first garbage dropping data and the second image data may include the first garbage point in a relatively large amount, the second garbage dropping data may be determined according to the second image after the first garbage point is dropped in a relatively large amount, the second garbage dropping data includes the second image and the second garbage dropping data may be determined according to the relative distance after the second garbage dropping point is changed in a large amount.
It can be seen that, determining the target object data according to the first image data and the second image data, determining the first garbage dropping data according to the first image data, determining the second garbage dropping data according to the second image data can determine the relevant information of the target object and the picked-up degree of garbage, and providing data support for the subsequent determination of the storage priority and the storage policy of the target object.
Step S304, determining a target destruction coefficient of a target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data.
The target damage coefficient can reflect the garbage damage degree of the target object to the garbage point, and further can reflect the influence of the target object to the public health safety, and the higher the target damage coefficient is, the higher the garbage damage degree of the target object to the garbage point is, and the greater the damage to the public health safety is.
In a possible embodiment, if only the first object is included in the first image data and the second image data, determining a first destruction coefficient of the target object according to the first weight change data and the second weight change data, and/or the first garbage drop data and the second garbage drop data; determining a second destruction coefficient according to the target object body type and the target object variety; the target destruction coefficient is determined from the first destruction coefficient and the second destruction coefficient.
For example, referring to fig. 4, fig. 4 is a schematic view of a first scenario of a data processing method for a garbage point area according to an embodiment of the present application, where analysis of collected first image data and second image data may determine that the first garbage point and the second garbage point only include a rough dog a, and the rough dog a causes complete garbage to drop, so that a first damage coefficient of the rough dog a may be determined according to the first weight change data and the second weight change data, and/or the first garbage drop data and the second garbage drop data, and the first damage coefficient is positively related to the first weight change data, the second weight change data, the first garbage drop data, and the second garbage drop data. Then, the second damage coefficient can be determined according to the body type and variety of the rough dog a, the second damage coefficient is positively correlated with the body type, the wild property corresponding to the variety and the influence level which can be caused are positively correlated, for example, the second damage coefficient corresponding to the strong dog is higher than the second damage coefficient corresponding to the small dog, the second damage coefficient corresponding to the dog is higher than the second damage coefficient corresponding to the cat, and finally, the reliable target damage coefficient can be obtained according to the first damage coefficient and the second damage coefficient.
In a possible embodiment, if the first image data includes the first object and the second image data includes the first object and at least one second object, a first destruction coefficient is determined according to the first weight change data and/or the first garbage drop data; determining a first destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the first damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; the target destruction coefficient is determined from the first destruction coefficient, the second destruction coefficient, and the third destruction coefficient.
It can be understood that the residence time of the first object at the second garbage point can reflect the residence time of the first object at the second garbage point to a great extent, the residence time of each second object at the second garbage point can also reflect the residence time of each second object at the second garbage point to a great extent, the garbage gathering includes gathering garbage from the garbage can at the garbage point and gathering garbage scattered outside the garbage can, and for any object, the longer residence time is the greater the damage proportion, the first residence time proportion of the first object can be determined according to the residence time of the first object at the second garbage point and the residence time of each second object at the second garbage point, and the first damage proportion is determined according to the first residence proportion, and the first damage proportion is in positive correlation with the first residence time proportion. Thus, relatively reliable parameters can be obtained, and the accuracy of the second damage coefficient determined later is improved.
For example, referring to fig. 5, fig. 5 is a schematic diagram of a second scenario of a data processing method for a garbage point area according to an embodiment of the present application, where the first and second image data are collected and analyzed to determine that the first garbage point includes only a rough dog a, the second garbage point includes a rough dog a and a rough cat d, the rough dog a causes a complete garbage drop at the first garbage point and causes a certain proportion of garbage drops at the second garbage point, so that a first damage coefficient of the rough dog a may be determined according to the first weight change data and/or the first garbage drop data, where the first damage coefficient is positively related to the first weight change data and the first garbage drop data. And then determining a first damage proportion of the rough dog a according to the stay time of the rough dog a at the second garbage point and the stay time of the rough cat d at the second garbage point, and then determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the first damage proportion, wherein the second damage coefficient is positively related to the second weight change data and the second garbage drop data. Then, a third destruction coefficient can be determined according to the body type and variety of the rough sea dog a, wherein the third destruction coefficient is positively correlated with the body type, is positively correlated with the wild property corresponding to the variety and the influence level which can be caused, and finally, a reliable target destruction coefficient can be obtained according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient.
In a possible embodiment, if the first image data includes the first object and at least one third object, and the second image data includes the first object and at least one second object, determining a first destruction proportion of the first object according to a stay time of the first object at the first garbage point and a stay time of each third object at the first garbage point; determining a first damage coefficient according to the first weight change data and/or the first garbage drop data and the first damage proportion; determining a second destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the second damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; the target destruction coefficient is determined from the first destruction coefficient, the second destruction coefficient, and the third destruction coefficient.
It can be understood that the residence time of the first object at the first garbage point may reflect the residence time of the first object at the first garbage point to a great extent, and the residence time of each third object at the first garbage point may also reflect the residence time of each third object at the first garbage point to a great extent, where the garbage gathering includes gathering garbage from a garbage can at the garbage point and gathering garbage scattered outside the garbage can, and for any object, the longer the residence time, the greater the damage ratio, where the first residence time ratio of the first object may be determined according to the residence time of the first object at the first garbage point and the residence time of each third object at the first garbage point, and the first damage ratio is determined according to the first residence ratio, where the first damage ratio is directly related to the first residence time ratio. Thus, relatively reliable parameters can be obtained, and the accuracy of the first damage coefficient determined later is improved.
Similarly, a second residence time proportion of the first object can be determined according to the residence time of the first object at the second garbage point and the residence time of each second object at the second garbage point, and a second destruction proportion is determined according to the second residence time proportion, wherein the second destruction proportion is positively correlated with the second residence time proportion. Thus, relatively reliable parameters can be obtained, and the accuracy of the second damage coefficient determined later is improved.
For example, referring to fig. 6, fig. 6 is a schematic diagram of a third scenario of a data processing method for a garbage area according to an embodiment of the present application, where the first garbage point includes a wandering dog a and a wandering dog b, the second garbage point includes a wandering dog a and a wandering dog c, the wandering dog a causes a certain proportion of garbage to drop at the first garbage point, and the second garbage point causes a certain proportion of garbage to drop, so that a first damage proportion of the wandering dog a may be determined according to a stay time of the wandering dog a at the first garbage point and a stay time of the wandering dog b at the first garbage point, and then a first damage coefficient is determined according to the first weight change data and/or the first garbage drop data and the first damage proportion, where the first damage coefficient is in positive correlation with the first weight change data and the first garbage drop data. And then, determining a second damage proportion of the rough dog a according to the stay time of the rough dog a at a second garbage point and the stay time of the rough dog c at the second garbage point, and then determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the second damage proportion, wherein the second damage coefficient is positively related to the second weight change data and the second garbage drop data. Then, a third destruction coefficient can be determined according to the body type and variety of the rough sea dog a, wherein the third destruction coefficient is positively correlated with the body type, is positively correlated with the wild property corresponding to the variety and the influence level which can be caused, and finally, a reliable target destruction coefficient can be obtained according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient.
It can be seen that, according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data and the target object data, the target destruction coefficient of the target object is determined, so that the accurate degree of influence of the target object on public health and public safety can be determined, and data support is provided for the subsequent determination of the accommodation priority and the accommodation policy.
Step S305, determining the accommodation priority and the objective accommodation policy of the objective object according to the objective destruction coefficient.
Wherein, the accommodation priority corresponding to the target destruction coefficient can be determined according to a preset mapping relation; then, determining a target activity range of the target object according to the first position of the first garbage point and the second position of the second garbage point; next, determining a target activity period of the target object according to the first period and the second period; and finally, determining the target accommodating strategy according to the target activity range, the target activity period and the target object data. The target accommodating strategy is used for informing an accommodating department of the variety, the required accommodating equipment, the accommodating area, the accommodating period and other information of the target wandering animal, and improving the experience and the accommodating success rate of accommodating personnel.
It can be seen that, by the above data processing method for a garbage point area, the data processing system further includes a first weighing module, a first camera module, and a second weighing module and a second camera module, which are disposed at a first garbage point, where first weight change data of the first garbage point is monitored by the first weighing module, and second weight change data of the second garbage point is monitored by the second weighing module; then, if the first weight change data is in an abnormal change state in a first period and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by the first camera module in the first period and acquiring second image data acquired by the second camera module in the second period; then, determining target object data according to the first image data and the second image data, determining first garbage dropping data according to the first image data, and determining second garbage dropping data according to the second image data; next, determining a target destruction coefficient of a target object from the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data; and finally, determining the accommodation priority and the objective accommodation policy of the objective object according to the objective destruction coefficient. The target object to be accommodated can be accurately determined, the data complexity of the garbage point is low, the required calculation force is low, the target object to be accommodated and the corresponding accommodating strategy can be determined based on the weight change of the garbage point, the image and other data, and the living experience of people is improved.
The foregoing description of the embodiments of the present application has been presented primarily in terms of a method-side implementation. It will be appreciated that the electronic device, in order to achieve the above-described functions, includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied as hardware or a combination of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The embodiment of the application may divide the functional units of the electronic device according to the above method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated in one processing unit. The integrated units may be implemented in hardware or in software functional units. It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice.
In the case of dividing each functional module by adopting a corresponding function, fig. 7 is a functional unit block diagram of a data processing device for a garbage area according to an embodiment of the present application, which is represented by a data processing device 700, and is applied to a processing module in a data processing system, where the data processing system further includes a first weighing module, a first image capturing module, and a second weighing module and a second image capturing module that are disposed at a first garbage point, and the data processing device 700 includes:
a monitoring unit 710 for monitoring first weight change data of the first garbage point through the first weighing module, and monitoring second weight change data of the second garbage point through the second weighing module;
an obtaining unit 720, configured to obtain first image data collected by the first camera module in the first period and obtain second image data collected by the second camera module in the second period if the first weight change data is in an abnormal change state in the first period and the second weight change data is in the abnormal change state in the second period;
A first determining unit 730, configured to determine target object data according to the first image data and the second image data, determine first garbage drop data according to the first image data, and determine second garbage drop data according to the second image data;
a second determining unit 740 for determining a target destruction coefficient of a target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data;
a third determining unit 750, configured to determine an accommodation priority and a target accommodation policy of the target object according to the target destruction coefficient.
It can be seen that, through the above data processing method and device for the garbage point area, the data processing system further includes a first weighing module, a first camera module, and a second weighing module and a second camera module disposed at a first garbage point, where the first weighing module monitors first weight change data of the first garbage point, and the second weighing module monitors second weight change data of the second garbage point; then, if the first weight change data is in an abnormal change state in a first period and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by the first camera module in the first period and acquiring second image data acquired by the second camera module in the second period; then, determining target object data according to the first image data and the second image data, determining first garbage dropping data according to the first image data, and determining second garbage dropping data according to the second image data; next, determining a target destruction coefficient of a target object from the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data; and finally, determining the accommodation priority and the objective accommodation policy of the objective object according to the objective destruction coefficient. The target object to be accommodated can be accurately determined, the data complexity of the garbage point is low, the required calculation force is low, the target object to be accommodated and the corresponding accommodating strategy can be determined based on the weight change of the garbage point, the image and other data, and the living experience of people is improved.
It should be noted that, the specific implementation of each operation may be described in the above-illustrated method embodiment, and the data processing apparatus 700 may be used to execute the method embodiment of the present application, which is not described herein.
The embodiment of the application also provides electronic equipment, which comprises: a processor, a memory, and one or more programs; the one or more programs are stored in the memory and configured to be executed by the processor, the programs including some or all of the steps for performing any of the methods as recited in the method embodiments above.
The present application also provides a computer storage medium storing a computer program for electronic data exchange, where the computer program causes a computer to execute some or all of the steps of any one of the methods described in the method embodiments above.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform part or all of the steps of any one of the methods described in the method embodiments above. The computer program product may be a software installation package.
For the above embodiments, for simplicity of description, the same is denoted as a series of combinations of actions. It will be appreciated by those skilled in the art that the present application is not limited by the illustrated ordering of acts, as some steps may be performed in other order or concurrently in embodiments of the present application. In addition, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts, steps, modules, units, etc. that are referred to are not necessarily required in the embodiments of the application.
In the foregoing embodiments, the descriptions of the embodiments of the present application are focused on each embodiment, and for a portion of one embodiment that is not described in detail, reference may be made to the related descriptions of other embodiments.
The steps of a method or algorithm described in the embodiments of the present application may be implemented in hardware, or may be implemented by executing software instructions by a processor. The software instructions may be comprised of corresponding software modules that may be stored in RAM, flash memory, ROM, EPROM, electrically Erasable EPROM (EEPROM), registers, hard disk, a removable disk, a compact disk read-only (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. In addition, the ASIC may be located in a terminal device or a management device. The processor and the storage medium may reside as discrete components in a terminal device or management device.
Those of skill in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application may be implemented, in whole or in part, in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a digital video disc (digital video disc, DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
The respective apparatuses and the respective modules/units included in the products described in the above embodiments may be software modules/units, may be hardware modules/units, or may be partly software modules/units, and partly hardware modules/units. For example, for each device or product applied to or integrated on a chip, each module/unit included in the device or product may be implemented in hardware such as a circuit, or at least part of the modules/units may be implemented in software program, where the software program runs on a processor integrated inside the chip, and the rest (if any) of the modules/units may be implemented in hardware such as a circuit; for each device and product applied to or integrated in the chip module, each module/unit contained in the device and product can be realized in a hardware manner such as a circuit, different modules/units can be located in the same component (such as a chip, a circuit module and the like) or different components of the chip module, or at least part of the modules/units can be realized in a software program, the software program runs on a processor integrated in the chip module, and the rest (if any) of the modules/units can be realized in a hardware manner such as a circuit; for each device, product, or application to or integrated with the terminal device, each module/unit included in the device may be implemented in hardware such as a circuit, and different modules/units may be located in the same component (e.g., a chip, a circuit module, etc.) or different components in the terminal device, or at least some modules/units may be implemented in a software program, where the software program runs on a processor integrated within the terminal device, and the remaining (if any) part of the modules/units may be implemented in hardware such as a circuit.
The foregoing embodiments have been provided for the purpose of illustrating the embodiments of the present application in further detail, and it should be understood that the foregoing embodiments are merely illustrative of the embodiments of the present application and are not intended to limit the scope of the embodiments of the present application, and any modifications, equivalents, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application are included in the scope of the embodiments of the present application.
Claims (6)
1. The data processing method for the garbage point area is characterized by being applied to a processing module in a data processing system, wherein the data processing system further comprises a first weighing module, a first camera module, a second weighing module and a second camera module, wherein the first weighing module and the first camera module are arranged at a first garbage point, the second weighing module and the second camera module are arranged at a second garbage point, and the method comprises the following steps:
monitoring, by the first weighing module, first weight change data of the first garbage point, and monitoring, by the second weighing module, second weight change data of the second garbage point;
if the first weight change data is in an abnormal change state in a first period and the second weight change data is in the abnormal change state in a second period, acquiring first image data acquired by the first camera module in the first period and acquiring second image data acquired by the second camera module in the second period;
Determining target object data according to the first image data and the second image data, determining first garbage dropping data according to the first image data, and determining second garbage dropping data according to the second image data, specifically: if the first image data comprises a first object and the second image data comprises the first object, determining the first object as the target object and determining target object data, wherein the target object data comprises a target object body type and a target object variety; determining the first garbage drop data according to the first image data, wherein the first image data comprises an image before the weight change of the first garbage point and an image after the weight change; determining the second garbage drop data according to the second image data, wherein the second image data comprises an image before the weight change of the second garbage point and an image after the weight change;
determining a target destruction coefficient of a target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data and the target object data, specifically: if the first image data and the second image data only comprise the first object, determining a first destruction coefficient of the target object according to the first weight change data and the second weight change data and/or the first garbage drop data and the second garbage drop data; determining a second destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient and the second destruction coefficient;
If the first image data comprises the first object, and the second image data comprises the first object and at least one second object, determining a first destruction coefficient according to the first weight change data and/or the first garbage drop data; determining a first destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the first damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient;
if the first image data comprises the first object and at least one third object, and the second image data comprises the first object and at least one second object, determining a first destruction proportion of the first object according to the stay time of the first object at the first garbage point and the stay time of each third object at the first garbage point; determining a first damage coefficient according to the first weight change data and/or the first garbage drop data and the first damage proportion; determining a second destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the second damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient;
And determining the accommodation priority and the target accommodation policy of the target object according to the target destruction coefficient.
2. The method of claim 1, wherein if the first weight change data is in an abnormally changed state for a first period of time and the second weight change data is in the abnormally changed state for a second period of time, acquiring first image data acquired by the first camera module during the first period of time, and acquiring second image data acquired by the second camera module during the second period of time, the method further comprising:
if the first weight change data accords with weight reduction or weight increase and then weight reduction in the first time period, determining that the first weight change data is in the abnormal change state in the first time period;
and if the second weight change data accords with weight reduction or weight increase and then weight reduction in the second period, determining that the second weight change data is in the abnormal change state in the second period.
3. The method of claim 1, wherein said determining the target object's containment priority and target containment policy from the target destruction coefficient comprises:
Determining the accommodating priority corresponding to the target destruction coefficient according to a preset mapping relation;
determining a target activity range of the target object according to the first position of the first garbage point and the second position of the second garbage point;
determining a target activity period of the target object according to the first period and the second period;
and determining the target accommodating strategy according to the target activity range, the target activity period and the target object data.
4. A data processing device for a garbage point area, characterized in that the data processing device is applied to a processing module in a data processing system, the data processing system further comprises a first weighing module, a first camera module, and a second weighing module and a second camera module, wherein the first weighing module and the first camera module are arranged at a first garbage point, the second camera module are arranged at a second garbage point, and the device comprises:
a monitoring unit for monitoring first weight change data of the first garbage point through the first weighing module and monitoring second weight change data of the second garbage point through the second weighing module;
an acquiring unit, configured to acquire first image data acquired by the first camera module in the first period and acquire second image data acquired by the second camera module in the second period if the first weight change data is in an abnormal change state in the first period and the second weight change data is in the abnormal change state in the second period;
The first determining unit is configured to determine target object data according to the first image data and the second image data, determine first garbage drop data according to the first image data, and determine second garbage drop data according to the second image data, specifically: if the first image data comprises a first object and the second image data comprises the first object, determining the first object as the target object and determining target object data, wherein the target object data comprises a target object body type and a target object variety; determining the first garbage drop data according to the first image data, wherein the first image data comprises an image before the weight change of the first garbage point and an image after the weight change; determining the second garbage drop data according to the second image data, wherein the second image data comprises an image before the weight change of the second garbage point and an image after the weight change;
a second determining unit, configured to determine a target destruction coefficient of a target object according to the first weight change data, the second weight change data, the first garbage drop data, the second garbage drop data, and the target object data, specifically: if the first image data and the second image data only comprise the first object, determining a first destruction coefficient of the target object according to the first weight change data and the second weight change data and/or the first garbage drop data and the second garbage drop data; determining a second destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient and the second destruction coefficient;
If the first image data comprises the first object, and the second image data comprises the first object and at least one second object, determining a first destruction coefficient according to the first weight change data and/or the first garbage drop data; determining a first destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the first damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient;
if the first image data comprises the first object and at least one third object, and the second image data comprises the first object and at least one second object, determining a first destruction proportion of the first object according to the stay time of the first object at the first garbage point and the stay time of each third object at the first garbage point; determining a first damage coefficient according to the first weight change data and/or the first garbage drop data and the first damage proportion; determining a second destruction proportion of the first object according to the stay time of the first object at the second garbage point and the stay time of each second object at the second garbage point; determining a second damage coefficient according to the second weight change data and/or the second garbage drop data and the second damage proportion; determining a third destruction coefficient according to the target object body type and the target object variety; determining the target destruction coefficient according to the first destruction coefficient, the second destruction coefficient and the third destruction coefficient;
And the third determining unit is used for determining the accommodation priority and the target accommodation policy of the target object according to the target destruction coefficient.
5. An electronic device, comprising: a processor, a memory, and one or more programs; the one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-3.
6. A computer storage medium storing a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1-3.
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