A garbage disposal system with automatic barrel replacement

Abstract

The present invention relates to the field of garbage information processing and discloses a garbage disposal system with automatic bucket exchange. The system performs dual detection of bucket exchange images and weight, and performs edge detection, weight detection, and return detection on the garbage bucket. Upon overflow detection, this information is transmitted to a garbage transfer vehicle via a network. By dispatching garbage vehicles and triggering edge detection, garbage accumulation can be reduced, thereby improving garbage transfer efficiency.

Description

Technical Field

[0001] The present invention relates to the field of garbage disposal information, and in particular to a garbage disposal method with automatic barrel replacement. Background Art

[0002] Garbage disposal is a common scenario in urban life. Residential waste bins are used to collect garbage. Existing garbage collection systems, such as those for domestic waste, rely on garbage trucks to collect and transport garbage at fixed times. Overflowing garbage points require manual oversight, which is time-consuming, labor-intensive, and untimely. The timing of garbage trucks also fails to meet dynamic requirements, and the placement of garbage bins is not intelligent enough. Once a bin is full, if it is not cleared promptly, community residents will continue to dump garbage, causing it to pile up.

[0003] With the development of Internet of Things and communication network technologies, how to achieve the convenience of garbage disposal and the rapid replacement of garbage bins, so as to actually realize garbage removal, maintain environmental hygiene, and improve garbage disposal efficiency has become an urgent problem to be solved in the field of intelligent garbage disposal. Summary of the Invention

[0004] In order to solve at least one of the above technical problems, the present application proposes a garbage disposal system with automatic barrel changing.

[0005] The system includes a control center, a garbage station and a garbage removal device;

[0006] The garbage station includes a plurality of garbage bins, which are connected to each other via short-range communication. The garbage station is provided with a weight sensor and an image sensor. The garbage station determines the overflow status of the garbage bin based on the weight and image detection information.

[0007] The control center communicates with the garbage collection device and the garbage station through the network. The location information of the garbage station and the garbage collection device is displayed on the map of the control center. The control center plans the navigation route of the garbage collection device according to the obtained overflow status; the garbage collection device performs the bucket changing operation according to the overflow status of the garbage station.

[0008] Preferably, the trash can includes: a fixed position sensor and a weighing sensor and a flip drive motor, a belt guide rail and a belt drive motor.

[0009] Preferably, the garbage station is provided with a camera sensor, and the overflow detection is configured to respectively judge whether the weight threshold is exceeded and the image detection edge overflow is detected. When one of them meets the threshold, the overflow status signal is triggered, the garbage can triggers the overflow mark status, and sends an overflow signal to the control center, while triggering the garbage can's overflow status warning signal to prompt the user.

[0010] Preferably, the image detection overflows, and edge detection is used to compare the sensor signal obtained by the camera with the standard image of the control center. When the edge detection exceeds the boundary, it is determined to be overflow.

[0011] Preferably, the image detection edge overflow further includes: when it is determined that the line segment of the edge detection information in the graphic exceeds the preset standard image edge, further detecting whether the edge information in the image in the exceeding part is in an irregular state, if it is an irregular state, determining it to be overflowing, if not, determining it to be to be overflowing.

[0012] Preferably, the image overflow detection specifically includes: performing grayscale and binarization processing on the RGB image to obtain a binary image; and performing noise filtering processing and morphological processing on the binary image in sequence to obtain a pre-processed image.

[0013] Preferably, in the image overflow detection, the edge detection uses the Canny operator to obtain an edge image with clear edges.

[0014] Preferably, the detection and comparison of the edge image includes: extracting edge information of the first edge detection image and matching it with standard feature information in the second edge detection image, wherein the feature information is line information obtained based on edge detection of the garbage bin.

[0015] Preferably, the step of extracting edge information from the first edge detection image and matching it with standard feature information from the second edge detection image specifically includes: selecting feature information with the same position information from the two images for matching.

[0016] Preferably, the second edge detection image is different edge detection images at preset time intervals.

[0017] The present invention discloses a garbage bin exchange processing system. The method performs dual detection of bin exchange images and weight, performs edge detection and weight detection on the garbage bin, and transmits overflow detection status information to a garbage transport vehicle via a network after overflow detection occurs. By dispatching garbage vehicles and triggering edge detection, garbage accumulation can be reduced, thereby improving garbage transfer efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1This is a schematic diagram of the framework of this system.

[0020] Figure 2 This is a structural and functional diagram of this system.

[0021] Figure 3 This is a schematic diagram of the spam sites in this system. DETAILED DESCRIPTION

[0022] These and other features and characteristics of the present disclosure, methods of operation, functions of related elements of the structure, combinations of parts, and economies of manufacture may be better understood with reference to the following description and accompanying drawings, which form a part of this specification. However, it is to be clearly understood that the drawings are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of the present disclosure. It is to be understood that the drawings are not drawn to scale. Various structural diagrams are used in this disclosure to illustrate various variations of embodiments according to the present disclosure.

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] It should be noted that the “ / ” in this article means or, for example, A / B can mean A or B; the “and / or” in this article is only a way to describe the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0025] It should be noted that, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish between identical or similar items having substantially the same function or effect. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or order of execution. For example, the first information and the second information are used to distinguish different information, rather than to describe a specific order of information.

[0026] It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0027] Example 1

[0028] like Figure 1-2 This is a schematic diagram of the structure of the present invention. The trash cans are connected to the control center of the intermodal platform system via a 4G network. Cameras and wireless internet access systems are installed at the trash can stations, and the wireless internet access system communicates with the intermodal platform system via the network. Each trash station is equipped with a location identification code. The electronic image of the location identification is displayed in the intermodal platform system. The status information of the trash can location is transmitted via network information via a flag bit.

[0029] When the automatic bucket changing system receives the garbage bin information containing location information and status information sent by the location information, it obtains the location information of the sweeper, that is, the garbage collection device, and plans the path navigation information of the sweeper for executing the bucket changing through the location information of the garbage bin and the sweeper.

[0030] The overflow detection method of the trash can is to perform weight and graphic detection in the display of trash placement. Standardized load-bearing values and capacity values are set for different trash can specifications. The load-bearing value of the trash can can be detected by a weighing sensor or a deformation sensor.

[0031] like Figure 3 As shown, in this application, a unified camera is installed at a garbage station, i.e., an environmental protection house, to first perform edge detection on the image of the garbage bin. The camera position can be fixed or adaptively adjusted. Standard graphical frame features are extracted. When the shape extracted from the edge features of the garbage bin does not exceed the boundary, the possibility of overflowing of the garbage bin is determined. A secondary determination of whether overflow is possible is then made based on a threshold value for the weight of the garbage bin. The matching feature extracts feature information at a fixed location, which is obtained through image processing matching overlap, reducing the amount of computation required.

[0032] The trash can may be provided with a panel control which implements an overflow indication signal for controlling a satisfactory state.

[0033] The trash can can also include a door opening motor, an IC card reader, a QR code scanner and a human body sensor, and a travel switch is provided for opening the box body in the trash can. The travel switch is used to record the opening data information of the cabinet door.

[0034] Optionally, while detecting the edge features of the waste bin, edge detection can be performed on the image of the waste bin to extract the shapes of the waste items in the image, thereby assisting in determining whether the bin is likely to be overflowing. The characteristic of false overflowing can be that the waste bin is supported by a rod, resulting in abnormal edge detection of the waste bin.

[0035] Exemplarily, the RGB image is grayscaled and binarized to obtain a binary image; the binary image is subjected to noise filtering and morphological processing in sequence to obtain a preprocessed image; wherein, median filtering is selected for noise filtering to remove noise so that the image contour maintains good clarity; according to the opening operation set in the morphological processing, impurities outside the contour of the garbage bin are removed, and the pores within the contour of the garbage pile are filled to prepare the image for preprocessing by the subsequent edge detection system.

[0036] After obtaining the preprocessed image, the control center performs garbage overflow detection on the preprocessed image to obtain an area image of the garbage bin with an external matrix marking the garbage bin; the preprocessed image is subjected to garbage pile detection to obtain an edge image of the garbage pile area with a minimum external matrix marking the garbage pile.

[0037] The edge detection process uses the Canny operator to obtain a clear edge image. For edge images that extend beyond the standard image area, i.e., the location information of protruding garbage piles, the minimum circumscribed matrix method is used to detect the garbage pile area in the edge image, obtaining an edge image of the garbage pile area marked with a minimum circumscribed matrix. This minimum circumscribed matrix size and location information is used for subsequent image cropping. If the edge feature information in the area does not contain irregular line segment overflow information, and the weight information is below the standard value, it is judged as a false alarm, indicating false overflow.

[0038] Optionally, the edge image detection and comparison may include extracting feature information from the first edge detection image and the second edge detection image, where the feature information is preferably line information obtained through edge detection. Specifically, the first edge detection image and the second edge detection image are compared and matched for similarities and differences, and feature information that matches or partially matches between the two images is selected as feature information of the characteristic portion; the feature information is information in the same location area. Optionally, rotational symmetry operations may be performed on the edge detection image information.

[0039] The feature information in the second edge detection image may be standard image information or different edge detection images at a preset time interval. The user can obtain abnormal features of different trash bins through the frame information in the image to determine whether the trash bin is full.

[0040] Exemplarily, and preferably, the line segments are filtered based on the line segment set in the first edge detection image to remove interfering line segments. Interfering line segments are line segments of non-target objects (i.e., non-trash can areas), such as line segments of trash in a trash can, background line segments of the target object's surroundings, etc. After removing the interfering line segments, the line segments of the target object are retained in the candidate line segment set and their position information is recorded.

[0041] In a preferred embodiment, the length distribution of line segments can be calculated during line segment filtering. The lengths of all identified line segments are counted and arranged in descending order of length. Overflow can be determined by the number of long line segments. For example, the length and width of a standard trash can have fixed edge values. When overflowing, due to the presence of garbage, the detection results in a variety of line segment feature information of varying lengths.

[0042] Preferably, a filtering threshold can be selected based on the frequency of line segment lengths. Line segments are filtered based on the selected filtering threshold. The filtering threshold can be set to line length, and line segments with lengths less than the filtering threshold can be removed based on the filtering threshold.

[0043] For example, we can remove the garbage line segments in the trash can and retain the line segments that are greater than or equal to the filtering threshold, such as the line segment at the top edge of the trash can mouth. We also set the line segments for the garbage outlet. The line segments in the candidate line segment set remove some interfering line segments, reducing the amount of subsequent data calculations.

[0044] Preferably, statistics can be performed in the form of a distribution graph, and a filtering threshold can be selected based on the line length distribution. The filtering threshold can be selected based on the length of the line segment (which can be the longest line segment, the shortest line segment, the median line, the average line segment, or the quartile).

[0045] Example 2

[0046] Based on the solution of Example 1, in the overflow detection of the garbage bin, the control center obtains data information of the travel detection switch when the garbage bin is opened. When no return information is set after the travel switch information is turned on, the acquisition of image frame information of the corresponding garbage bin is triggered.

[0047] After obtaining the preprocessed image, the control center performs garbage overflow detection on the preprocessed image to obtain an area image of the garbage bin with an external matrix marking the garbage bin; the preprocessed image is subjected to garbage pile detection to obtain an edge image of the garbage pile area with a minimum external matrix marking the garbage pile.

[0048] The edge detection process uses the Canny operator to obtain a clear edge image. For edge images that extend beyond the standard image area, i.e., for location information of protruding garbage piles, the minimum circumscribed matrix method is used to detect the garbage pile area in the edge image, obtaining an edge image of the garbage pile area marked with a minimum circumscribed matrix. This minimum circumscribed matrix size and location information is used for subsequent image cropping. If the edge feature information in the area does not contain irregular line segment overflow information and the weight information is below the standard value, a false alarm is determined as false overflow.

[0049] Example 3

[0050] Based on the examples described above, in one embodiment, the features involving method steps can be implemented by a computer device / or system provided by the present invention, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any one of the methods in the above embodiments is implemented.

[0051] Those skilled in the art will appreciate that all or part of the processes in the above-described embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. For example, in the embodiments of the present invention, the program can be stored in a storage medium of a computer system and executed by at least one processor in the computer system to implement the processes including the embodiments of the above-described video playback methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0052] Accordingly, a storage medium is also provided, on which a computer program is stored, wherein when the program is executed by a processor, any method steps involved in the above embodiments are implemented.

[0053] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0054] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A garbage disposal system with automatic barrel changing, characterized in that: The system includes a control center, a garbage station and a garbage removal device; The garbage station includes a plurality of garbage bins, which are connected to each other via short-range communication. The garbage station is provided with a weight sensor and an image sensor. The garbage station determines the overflow status of the garbage bin based on the weight and image detection information. The control center communicates with the garbage collection devices and garbage stations via a network. The location information of the garbage stations and garbage collection devices is displayed on a map on the control center. The control center plans navigation routes for the garbage collection devices based on the acquired overflow status. The garbage collection devices perform bucket changes based on the overflow status of the garbage stations. The garbage station is equipped with a camera sensor, and the overflow detection is configured to determine whether a weight threshold is exceeded and whether an image detection edge overflows. When one of the thresholds is met, an overflow status signal is triggered, and the garbage bin triggers an overflow flag state, sending an overflow signal to the control center, and simultaneously triggering a garbage bin overflow status warning signal to alert the user. The overflow detection is set to judge whether the weight threshold is exceeded and the image detection edge overflow respectively, and also includes: for the edge image that exceeds the standard image area, the minimum circumscribed matrix method is used to detect the garbage pile area in the edge image, and the edge image of the garbage pile area with the minimum circumscribed matrix mark is obtained, and the minimum circumscribed matrix size and position information is used for subsequent image cropping. When the edge feature information in the area does not contain irregular line segment overflow information, the weight information is below the standard value, it is judged as false alarm information, which is false overflow.

2. The system according to claim 1, wherein: The image detection edge overflow adopts edge detection to compare the sensor signal obtained by the camera sensor with the standard image of the control center. When the edge detection exceeds the boundary, it is determined to be overflow.

3. The system according to claim 2, wherein: The image detection edge overflow further includes: when it is determined that the line segment of the edge detection information in the graphic exceeds the preset standard image edge, further detecting whether the edge information in the image in the exceeding part is in an irregular state, if it is an irregular state, determining it to be overflowed, otherwise determining it to be to be overflowed.

4. The system according to claim 3, wherein: The image edge overflow detection method specifically includes: performing grayscale and binarization processing on the RGB image to obtain a binary image; and performing noise filtering processing on the binary image in sequence to obtain a pre-processed image.

5. The system according to claim 4, wherein: In the image detection edge overflow, the Canny operator is selected for edge detection processing to obtain an edge image with clear edges.

6. The system according to claim 5, wherein: The detection and comparison of the edge image includes: extracting edge information of the first edge detection image and matching it with standard feature information in the second edge detection image, wherein the standard feature information is line information obtained based on edge detection of the trash can.

7. The system according to claim 6, wherein: The edge information of the first edge detection image is extracted and matched with the standard feature information in the second edge detection image. Specifically, feature information with the same position information between the two images is selected for matching.

8. The system according to claim 7, wherein: The second edge detection images are different edge detection images at preset time intervals.

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