Intelligent garbage classification processing system based on Internet big data

Abstract

The invention discloses an intelligent garbage classification processing system based on internet big data, which comprises a mosquito detection module, an environment monitoring module and a garbage classification processing module, and is characterized in that the mosquito detection module is used for identifying mosquitoes in a garbage station and carrying out counting statistics; the environment monitoring module is used for monitoring field environment data in a garbage station in real time, the mosquito detection module and the environment monitoring module are both electrically connected with the garbage classification processing module, and the garbage classification processing module is used for receiving data from the mosquito detection module and the environment monitoring module, performing comprehensive analysis and sending the data to the environment monitoring module. The mosquito detection module comprises a high-precision image acquisition module, a real-time feature recognition module and a counting module, and the intelligent garbage treatment system has the advantages of being capable of intelligently recognizing and optimizing the garbage treatment efficiency.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to an intelligent garbage classification and processing system based on Internet big data. Background Art

[0002] With the acceleration of urbanization, the amount of domestic waste has risen sharply. Therefore, waste sorting has become a key measure to alleviate the environmental burden and promote the efficient recycling of resources. However, the traditional waste sorting model faces many challenges such as inefficiency and inaccurate classification, especially in the treatment of kitchen waste that is easy to attract mosquitoes. If it is not cleaned up in time, it will not only seriously damage environmental sanitation, but also may induce a public health crisis.

[0003] The garbage disposal methods used in the past, such as cleaning at fixed times and locations or waiting until the garbage bin is full before cleaning, seem to be inadequate to curb the problem of mosquito breeding. Although there are currently some methods to evaluate and adjust the frequency of classification and treatment based on ambient temperature and recent mosquito breeding conditions, these methods are not omnipotent. Because not all domestic garbage will become a breeding ground for mosquitoes. Even if it is the same kitchen waste, different types of kitchen waste have different properties and degrees of deterioration, and their attractiveness to mosquito breeding also varies significantly. Therefore, the existing methods of adjusting the frequency of classification and treatment are difficult to achieve real-time garbage classification and treatment timing reminders based on the actual situation on site, resulting in inaccurate treatment timing and ineffective use of human resources.

[0004] Therefore, it is particularly important to design an intelligent garbage sorting and processing system based on Internet big data that can intelligently identify and optimize garbage disposal efficiency, especially for kitchen waste that is a specific mosquito attraction source. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent garbage sorting and processing system based on Internet big data to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent garbage sorting and processing system based on Internet big data, comprising a mosquito detection module, an environmental monitoring module and a garbage sorting and processing module, the mosquito detection module is used to identify mosquitoes in a garbage station and count them, the environmental monitoring module is used to monitor the on-site environmental data in the garbage station in real time, the mosquito detection module and the environmental monitoring module are both electrically connected to the garbage sorting and processing module, and the garbage sorting and processing module is used to receive data from the mosquito detection module and the environmental monitoring module, perform comprehensive analysis, and determine the timing of garbage sorting and processing.

[0007] According to the above technical solution, the mosquito detection module includes a high-precision image acquisition module, a real-time feature recognition module and a counting module. The high-precision image acquisition module is used to collect images in the garbage station in real time. The real-time feature recognition module is electrically connected to the high-precision image acquisition module. The real-time feature recognition module is used to retrieve the real-time image collected by the high-precision image acquisition module and perform mosquito feature recognition. The counting module is used to record the number of mosquito features recognized in the real-time image.

[0008] According to the above technical solution, the environmental monitoring module includes a gas concentration monitoring module and a garbage remainder monitoring module. The gas concentration monitoring module is used to monitor the gas concentration in the garbage station in real time, and the garbage remainder monitoring module is used to monitor the garbage remainder in the garbage station in real time. The garbage remainder monitoring module further includes a weighing submodule and a dot matrix scanning unit. The weighing submodule is used to weigh the garbage remainder in the garbage station, and the dot matrix scanning unit is suitable for emitting a dot matrix scanning laser in the garbage station to measure the garbage loading amount in the garbage station.

[0009] According to the above technical solution, the garbage classification and processing module includes a data receiving module, a detection accuracy control module, a processing timing judgment module and a sound and light alarm module. The data receiving module is electrically connected to the mosquito detection module and the environmental monitoring module. The data receiving module is used to receive data from the mosquito detection module and the environmental monitoring module. The detection accuracy control module is used to dynamically adjust the detection accuracy of the mosquito detection module according to the monitoring results of the environmental monitoring module. The processing timing judgment module is used to judge the timing of garbage classification processing in the garbage station according to the data of the mosquito detection module. The sound and light alarm module is electrically connected to the processing timing judgment module. The sound and light alarm module is used to send out a sound and light alarm when the judgment criteria of the processing timing judgment module are met.

[0010] According to the above technical solution, the detection accuracy control module further includes an image resolution adjustment submodule and a feature recognition database. The image resolution adjustment submodule is used to adjust the resolution of the collected image upload during mosquito detection, and the feature recognition database is used to store mosquito feature data.

[0011] According to the above technical solution, the operation method of the intelligent garbage classification and processing system includes the following steps:

[0012] S1. Deploy a high-precision image acquisition module in the garbage station, and detect and identify the number of mosquitoes Q in the garbage station through the mosquito detection module;

[0013] S2, the environmental monitoring module synchronously monitors the on-site environmental data in the garbage station, and respectively monitors the gas concentration E and the garbage residual index R in the output garbage station;

[0014] S3, the garbage classification processing module uses the data receiving module to receive data from the mosquito detection module and the environment monitoring module, and the detection accuracy control module controls the detection accuracy of the mosquito detection module according to the data received from the environment monitoring module;

[0015] S4, based on the data of the mosquito detection module after feedback control by the detection accuracy control module, when Q>Q0, where Q0 is the threshold value of the number of mosquitoes in the garbage station, it is determined that the garbage classification and processing time has been reached;

[0016] S5. When it is determined that the garbage classification and processing timing standards are met, the processing timing judgment module triggers the induction electrical signal to the sound and light alarm module, and the sound and light alarm module sends out a sound and light alarm, intelligently prompting the staff to classify the garbage in the target garbage station, and efficiently classify the kitchen waste with specific mosquito attraction sources and remove it in time.

[0017] According to the above technical solution, the specific working process of the mosquito detection module in step S1 includes the following steps:

[0018] S11, using a high-precision image acquisition module to capture live images of the garbage site at a period T, wherein the live image consists of the captured image frame and images within 1.5 seconds before and after it;

[0019] S12, performing live feature recognition on the live image through a live feature recognition module, calling a feature recognition database in the system, firstly performing static mosquito feature matching based on the captured image frame, identifying mosquito features in the captured image frame, and counting them by a counting module to obtain the number m of static mosquito features in the captured image frame;

[0020] S13, then supplement the recognition of dynamic features of mosquitoes in the live image, capture the moving target features in the continuous picture frames of the live image, and count them by a counting module to obtain the number n of dynamic features of mosquitoes in the live image;

[0021] S14, tracking and identifying the live image, when the live image reaches the time of capturing the image frame, capturing the number b of features that overlap between n dynamic features of mosquitoes and m static features of mosquitoes;

[0022] S15. The mosquito detection module calculates and identifies the number of mosquitoes in the garbage site Q=m+nb.

[0023] According to the above technical solution, the specific working process of the environmental monitoring module in step S2 includes the following steps:

[0024] S21, monitoring the gas concentration E of mosquito-attracting gas in the garbage station through a gas concentration monitoring module;

[0025] S22. The weighing sub-module senses the garbage weight G in the garbage station;

[0026] S23. The dot matrix scanning unit is deployed at the top inside the garbage station and projects dot matrix scanning lasers onto the garbage inside the station, and the dot matrix lasers evenly cover the garbage surface;

[0027] S24. Capture the feedback signal values D1, D2, …, D x , where x is the total number of dot matrix scanning lasers emitted by the dot matrix scanning unit;

[0028] S25. Calculate the volume of the garbage inside the monitored garbage station where k1 is a conversion coefficient;

[0029] S26. The garbage remaining amount monitoring module calculates and outputs the monitored garbage remaining amount index R through the formula R = α·G + β·V, where α and β are the weight coefficients of the garbage weight and the garbage volume respectively.

[0030] According to the above technical solution, the specific working process of the detection accuracy control module in step S3 includes the following steps:

[0031] S31. Set the dynamic threshold standard E0 of the gas concentration, where E0 = k2·R and k2 is a conversion coefficient, set the garbage remaining amount index threshold R0, and when R = R0, it means that the garbage amount in the garbage station is full. Set the resolution levels for collecting and uploading images during mosquito detection, including low, medium, and high levels;

[0032] S32. Compare the gas concentration E in the real-time monitored garbage station with the dynamic threshold standard E0;

[0033] S33. When E < E0, output the ratio When f ≤ 30%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "low" level; when 30% < f ≤ 60%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "medium" level; when f > 60%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "high" level;

[0034] S34. When E ≥ E0, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "high" level.

[0035] According to the above technical solution, the specific working process of the detection accuracy control module in S3 further includes:

[0036] S35. Establish a feature recognition database, store the recorded mosquito feature data in the feature recognition database, and store the static mosquito feature standard and the minimum movement standard of the dynamic mosquito feature for adjacent picture frames in the open feature recognition database according to the resolution level of the image uploaded during mosquito detection.

[0037] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by providing a mosquito detection module, an environmental monitoring module and a garbage classification and processing module, can add additional judgment criteria for detecting the number of specific mosquitoes on the basis of traditional timed and quantitative garbage cleaning. When the garbage station of the detection target meets the judgment criteria, no matter how much garbage is left in the garbage station, an audible and visual alarm is triggered to immediately prompt the staff to classify the target garbage station, and screen out and clean up the kitchen waste that is very likely to attract some mosquitoes that are easy to bite nearby pedestrians, thereby reducing the impact of such kitchen waste on the entire garbage station environment, greatly reducing the problem of mosquito breeding, effectively reducing the risk of mosquito bites to pedestrians, and improving the level of public environmental sanitation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0039] In the attached picture:

[0040] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 The present invention provides a technical solution: an intelligent garbage sorting and processing system based on Internet big data, including a mosquito detection module, an environmental monitoring module and a garbage sorting and processing module. The mosquito detection module is used to identify mosquitoes in a garbage station and count them. The environmental monitoring module is used to monitor the on-site environmental data in the garbage station in real time. The mosquito detection module and the environmental monitoring module are both electrically connected to the garbage sorting and processing module. The garbage sorting and processing module is used to receive data from the mosquito detection module and the environmental monitoring module, conduct a comprehensive analysis, and determine the timing of garbage sorting and processing.

[0043] The mosquito detection module includes a high-precision image acquisition module, a real-time feature recognition module and a counting module. The high-precision image acquisition module is used to collect images in the garbage station in real time. The real-time feature recognition module is electrically connected to the high-precision image acquisition module. The real-time feature recognition module is used to retrieve the real-time images collected by the high-precision image acquisition module and perform mosquito feature recognition. The counting module is used to record the number of mosquito features recognized in the real-time images.

[0044] The environmental monitoring module includes a gas concentration monitoring module and a garbage remainder monitoring module. The gas concentration monitoring module is used to monitor the gas concentration in the garbage station in real time, and the garbage remainder monitoring module is used to monitor the garbage remainder in the garbage station in real time. The garbage remainder monitoring module further includes a weighing submodule and a dot matrix scanning unit. The weighing submodule is used to weigh the garbage remainder in the garbage station, and the dot matrix scanning unit is suitable for emitting a dot matrix scanning laser in the garbage station to measure the garbage loading amount in the garbage station.

[0045] The garbage classification and processing module includes a data receiving module, a detection accuracy control module, a processing timing judgment module and a sound and light alarm module. The data receiving module is electrically connected to the mosquito detection module and the environmental monitoring module. The data receiving module is used to receive data from the mosquito detection module and the environmental monitoring module. The detection accuracy control module is used to dynamically adjust the detection accuracy of the mosquito detection module according to the monitoring results of the environmental monitoring module. The processing timing judgment module is used to judge the timing of garbage classification and processing in the garbage station according to the data of the mosquito detection module. The sound and light alarm module is electrically connected to the processing timing judgment module. The sound and light alarm module is used to send out a sound and light alarm when the judgment criteria of the processing timing judgment module are met.

[0046] The detection accuracy control module further includes an image resolution adjustment submodule and a feature recognition database. The image resolution adjustment submodule is used to adjust the resolution of the collected image upload during mosquito detection, and the feature recognition database is used to store mosquito feature data.

[0047] The operation method of the intelligent garbage classification and processing system comprises the following steps:

[0048] S1. Deploy a high-precision image acquisition module in the garbage station, and detect and identify the number of mosquitoes Q in the garbage station through the mosquito detection module;

[0049] S2, the environmental monitoring module synchronously monitors the on-site environmental data in the garbage station, and respectively monitors the gas concentration E and the garbage residual index R in the output garbage station;

[0050] S3, the garbage classification processing module uses the data receiving module to receive data from the mosquito detection module and the environment monitoring module, and the detection accuracy control module controls the detection accuracy of the mosquito detection module according to the data received from the environment monitoring module;

[0051] S4, based on the data of the mosquito detection module after feedback control by the detection accuracy control module, when Q>Q0, where Q0 is the threshold value of the number of mosquitoes in the garbage station, it is determined that the garbage classification and processing time has been reached;

[0052] S5. When it is determined that the garbage classification and processing timing standards are met, the processing timing judgment module triggers the induction electrical signal to the sound and light alarm module, and the sound and light alarm module sends out a sound and light alarm, intelligently prompting the staff to classify the garbage in the target garbage station, and efficiently classify the kitchen waste with specific mosquito attraction sources and remove it in time.

[0053] The specific working process of the mosquito detection module in step S1 includes the following steps:

[0054] S11, using a high-precision image acquisition module to capture live images of the garbage site at a period T, wherein the live image consists of the captured image frame and images within 1.5 seconds before and after it;

[0055] S12, performing live feature recognition on the live image through a live feature recognition module, calling a feature recognition database in the system, firstly performing static mosquito feature matching based on the captured image frame, identifying mosquito features in the captured image frame, and counting them by a counting module to obtain the number m of static mosquito features in the captured image frame;

[0056] S13, then supplement the recognition of dynamic features of mosquitoes in the live image, capture the moving target features in the continuous picture frames of the live image, and count them by a counting module to obtain the number n of dynamic features of mosquitoes in the live image;

[0057] S14, tracking and identifying the live image, when the live image reaches the time of capturing the image frame, capturing the number b of features that overlap between n dynamic features of mosquitoes and m static features of mosquitoes;

[0058] S15. The mosquito detection module calculates and identifies the number of mosquitoes in the garbage site, Q = m + nb; for some tiny mosquitoes, which happen to be under the dark garbage background or between many garbage gaps, it is impossible to accurately identify and judge them by static mosquito feature recognition alone. By introducing the supplementary recognition of dynamic features, some mosquitoes that are difficult to define by static images alone can be additionally identified under the interaction, thereby effectively improving the accuracy of mosquito detection and identification and improving the reliability of on-site data.

[0059] The specific working process of the environmental monitoring module in step S2 includes the following steps:

[0060] S21, monitoring the gas concentration E of mosquito-attracting gas in the garbage station through a gas concentration monitoring module;

[0061] S22. The weighing sub-module senses the garbage weight G in the garbage station;

[0062] S23. The dot matrix scanning unit is deployed on the top inside the garbage station, and projects dot matrix scanning lasers onto the garbage inside the garbage station, and the dot matrix lasers evenly cover the garbage surface;

[0063] S24. Capture the feedback signal values D1, D2, …, D of each laser beam x , where x is the total number of dot matrix scanning lasers emitted by the dot matrix scanning unit;

[0064] S25. Calculate the volume of the garbage inside the monitored garbage station where k1 is a conversion coefficient;

[0065] S26. The garbage remaining amount monitoring module calculates and outputs the monitored garbage remaining amount index R through the formula R = α·G + β·V, where α and β are the weight coefficients of the garbage weight and the garbage volume respectively.

[0066] The specific working process of the detection accuracy control module in step S3 includes the following steps:

[0067] S31. Set the dynamic threshold standard E0 of the gas concentration, where E0 = k2·R, and k2 is a conversion coefficient. Set the garbage remaining amount index threshold R0. When R = R0, it means that the garbage amount in the garbage station is full. Set the resolution levels for collecting and uploading images during mosquito detection, including low, medium, and high levels;

[0068] S32. Compare the real-time monitored gas concentration E in the garbage station with the dynamic threshold standard E0;

[0069] S33. When E < E0, output the ratio When f ≤ 30%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "low" level; when 30% < f ≤ 60%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "medium" level; when f > 60%, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "high" level;

[0070] S34. When E ≥ E0, the image resolution adjustment sub-module adjusts the resolution of the collected and uploaded image to the "high" level; The gas concentration increases in direct proportion to the garbage amount in the garbage station. When E ≥ E0, it means that the amount of gas attracting mosquitoes emitted by the garbage in the current garbage station exceeds the normal range of the garbage amount in the current garbage station. Therefore, there is a high probability that there is a certain type of kitchen waste with unique biochemical characteristics that is extremely easy to attract mosquitoes that bite easily. Therefore, the detection accuracy is improved to avoid untimely garbage classification due to detection errors.

[0071] The specific working process of the detection accuracy control module in S3 also includes:

[0072] S35, establishing a feature recognition database, storing the recorded mosquito feature data in the feature recognition database, and corresponding to the static mosquito feature standard quantity and the minimum movement quantity standard of the dynamic mosquito feature to the adjacent picture frames stored in the open feature recognition database according to the resolution level of the image uploaded during mosquito detection; the system intelligently adjusts the detection parameters according to the actual environmental conditions, avoiding unnecessary maximum computing power consumption, reducing the data storage load, and realizing efficient use of computing resources;

[0073] The purpose of this application is to address the rare cases where there is kitchen waste in garbage stations that is extremely likely to attract mosquitoes that easily bite nearby pedestrians. Once the kitchen waste is not processed for a long time, it will attract many mosquitoes. By setting up a mosquito detection module, the number of mosquitoes can be collected and analyzed in real time, and environmental analysis of the garbage station can be introduced. When the amount of garbage remaining in the garbage station is small and there is no obvious irritating odor due to the high concentration of fermentation gas, the probability of this type of kitchen waste appearing in the garbage station is low, and the small amount of garbage is generally in a short period after the garbage is cleaned up. Therefore, in combination with the above situation, by setting up a detection accuracy control module, the mosquito detection accuracy can be dynamically controlled. When the amount of garbage remaining is small and there is no obvious irritating odor due to the high concentration of fermentation gas, a lower detection accuracy can be used, thereby indirectly reducing the judgment standard for the timing of garbage classification and processing. Conversely, the detection accuracy is improved, and detection and identification are more sensitive. This can achieve a dynamic balance between more accurate and timely detection of the number of mosquitoes and reduced computing power data consumption and hardware standards. Compared with traditional timed and quantitative cleaning, the present invention can additionally add a judgment standard for the detection of a specific number of mosquitoes. When the garbage station of the detection target meets the judgment standard, no matter how much garbage is left in the garbage station, an audible and visual alarm will be triggered to immediately prompt the staff to classify the target garbage station, and kitchen waste that is very likely to attract mosquitoes that are likely to bite nearby pedestrians will be screened out and cleaned, thereby reducing the impact of such kitchen waste on the entire garbage station environment, greatly reducing the problem of mosquito breeding, effectively reducing the risk of mosquito bites to pedestrians, and improving the level of public environmental sanitation.

[0074] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0075] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent garbage classification and processing system based on Internet big data, characterized by: The intelligent garbage sorting and processing system includes a mosquito detection module, an environmental monitoring module and a garbage sorting and processing module. The mosquito detection module is used to identify mosquitoes in the garbage station and count them. The environmental monitoring module is used to monitor the on-site environmental data in the garbage station in real time. The mosquito detection module and the environmental monitoring module are both electrically connected to the garbage sorting and processing module. The garbage sorting and processing module is used to receive data from the mosquito detection module and the environmental monitoring module, conduct comprehensive analysis, and determine the timing of garbage sorting and processing.

2. The intelligent garbage classification and processing system based on Internet big data according to claim 1 is characterized by: The mosquito detection module includes a high-precision image acquisition module, a real-time feature recognition module and a counting module. The high-precision image acquisition module is used to collect images in the garbage station in real time. The real-time feature recognition module is electrically connected to the high-precision image acquisition module. The real-time feature recognition module is used to retrieve the real-time image collected by the high-precision image acquisition module and perform mosquito feature recognition. The counting module is used to record the number of mosquito features recognized in the real-time image.

3. The intelligent garbage classification and processing system based on Internet big data according to claim 1 is characterized by: The environmental monitoring module includes a gas concentration monitoring module and a garbage remainder monitoring module. The gas concentration monitoring module is used to monitor the gas concentration in the garbage station in real time, and the garbage remainder monitoring module is used to monitor the garbage remainder in the garbage station in real time. The garbage remainder monitoring module further includes a weighing submodule and a dot matrix scanning unit. The weighing submodule is used to weigh the garbage remainder in the garbage station, and the dot matrix scanning unit is suitable for emitting a dot matrix scanning laser in the garbage station to measure the garbage loading amount in the garbage station.

4. The intelligent garbage classification and processing system based on Internet big data according to claim 1 is characterized by: The garbage classification and processing module includes a data receiving module, a detection accuracy control module, a processing timing judgment module and a sound and light alarm module. The data receiving module is electrically connected to the mosquito detection module and the environmental monitoring module. The data receiving module is used to receive data from the mosquito detection module and the environmental monitoring module. The detection accuracy control module is used to dynamically adjust the detection accuracy of the mosquito detection module according to the monitoring results of the environmental monitoring module. The processing timing judgment module is used to judge the timing of garbage classification processing in the garbage station according to the data of the mosquito detection module. The sound and light alarm module is electrically connected to the processing timing judgment module. The sound and light alarm module is used to send out a sound and light alarm when the judgment criteria of the processing timing judgment module are met.

5. The intelligent garbage classification and processing system based on Internet big data according to claim 4 is characterized by: The detection accuracy control module further includes an image resolution adjustment submodule and a feature recognition database. The image resolution adjustment submodule is used to adjust the resolution of the collected image upload during mosquito detection, and the feature recognition database is used to store mosquito feature data.

6. The intelligent garbage classification and processing system based on Internet big data according to claim 1 is characterized by: The operation method of the intelligent garbage classification and processing system comprises the following steps: S1. Deploy a high-precision image acquisition module in the garbage station, and detect and identify the number of mosquitoes Q in the garbage station through the mosquito detection module; S2, the environmental monitoring module synchronously monitors the on-site environmental data in the garbage station, and respectively monitors the gas concentration E and the garbage residual index R in the output garbage station; S3, the garbage classification processing module uses the data receiving module to receive data from the mosquito detection module and the environment monitoring module, and the detection accuracy control module controls the detection accuracy of the mosquito detection module according to the data received from the environment monitoring module; S4, based on the data of the mosquito detection module after feedback control by the detection accuracy control module, when Q>Q0, where Q0 is the threshold value of the number of mosquitoes in the garbage station, it is determined that the garbage classification and processing time has been reached; S5. When it is determined that the garbage classification and processing timing standards are met, the processing timing judgment module triggers the induction electrical signal to the sound and light alarm module, and the sound and light alarm module sends out a sound and light alarm, intelligently prompting the staff to classify the garbage in the target garbage station, and efficiently classify the kitchen waste with specific mosquito attraction sources and remove it in time.

7. The intelligent garbage classification and processing system based on Internet big data according to claim 6 is characterized by: The specific working process of the mosquito detection module in the above step S1 includes the following steps: S11, using a high-precision image acquisition module to capture live images of the garbage site at a period T, wherein the live image consists of the captured image frame and images within 1.5 seconds before and after it; S12, performing live feature recognition on the live image through a live feature recognition module, calling a feature recognition database in the system, firstly performing static mosquito feature matching based on the captured image frame, identifying mosquito features in the captured image frame, and counting them by a counting module to obtain the number m of static mosquito features in the captured image frame; S13, then supplement the recognition of dynamic features of mosquitoes in the live image, capture the moving target features in the continuous picture frames of the live image, and count them by a counting module to obtain the number n of dynamic features of mosquitoes in the live image; S14, tracking and identifying the live image, when the live image reaches the time of capturing the image frame, capturing the number b of features that overlap between n dynamic features of mosquitoes and m static features of mosquitoes; S15. The mosquito detection module calculates and identifies the number of mosquitoes in the garbage site Q=m+nb.

8. The intelligent garbage classification and processing system based on Internet big data according to claim 6 is characterized by: The specific working process of the environmental monitoring module in the above step S2 includes the following steps: S21, monitoring the gas concentration E of mosquito-attracting gas in the garbage station through a gas concentration monitoring module; S22, the weighing submodule senses the weight G of the garbage in the garbage station; S23, the dot matrix scanning unit is deployed on the top of the garbage station, and projects a dot matrix scanning laser to the garbage in the garbage station, and the dot matrix laser evenly covers the surface of the garbage; S24, capturing each laser beam feedback signal value D1, D2, ..., D x , where x is the total number of dot scanning lasers emitted by the dot scanning unit; S25. Calculate the volume of garbage in the monitored garbage station Where k1 is the conversion coefficient; S26. The garbage remaining amount monitoring module calculates and outputs the monitored garbage remaining amount index R through the formula R=α·G+β·V, where α and β are weight coefficients of garbage weight and garbage volume respectively.

9. The intelligent garbage classification and processing system based on Internet big data according to claim 8 is characterized by: The specific working process of the detection accuracy control module in the above step S3 includes the following steps: S31, set the dynamic threshold standard E0 of gas concentration, where E0=k2·R, and k2 is the conversion coefficient, set the garbage residue index threshold R0, when R=R0, it means that the garbage amount in the garbage station is full, set the resolution level of the image collected and uploaded during mosquito detection, including low, medium and high levels; S32, comparing the gas concentration E in the garbage site monitored in real time with the dynamic threshold standard E0; S33. When E < E0, output the ratio When f ≤ 30%, the image resolution adjustment sub-module adjusts the resolution of the captured image uploaded to the "low" level; when 30% < f ≤ 60%, the image resolution adjustment sub-module adjusts the resolution of the captured image uploaded to the "medium" level; when f > 60%, the image resolution adjustment sub-module adjusts the resolution of the captured image uploaded to the "high" level; S34. When E≥E0, the image resolution adjustment submodule adjusts the resolution of the captured image to be uploaded to the "high" level.

10. The intelligent garbage classification and processing system based on Internet big data according to claim 9 is characterized by: The specific working process of the detection accuracy control module in S3 also includes: S35. Establish a feature recognition database, store the recorded mosquito feature data in the feature recognition database, and store the static mosquito feature standard and the minimum movement standard of the dynamic mosquito feature for adjacent picture frames in the open feature recognition database according to the resolution level of the image uploaded during mosquito detection.

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