Monitoring system for environmental sanitation vehicle operation data acquisition and assessment

Abstract

The invention relates to the technical field of data acquisition and analysis, and discloses a sanitation vehicle operation data acquisition and assessment monitoring system, which comprises a data initial acquisition module, a data acquisition module, an operation data analysis module, an operation data assessment module and a real-time monitoring module, through the arrangement of the data acquisition module and the operation data analysis module, the preliminarily collected data can be verified, and the data credibility can be calculated, so that the accuracy and effectiveness of the data can be improved; analyzing the operation data, obtaining the actual operation action of the environmental sanitation vehicle, and calculating the operation track effectiveness and oil consumption efficiency of the environmental sanitation vehicle; therefore, the operation of the sanitation vehicle is assessed by taking a scientific and digital basis as an assessment index, core working parts of the sanitation vehicle are monitored in real time, the actual operation state is accurately judged, and the problems of abnormal detour, repeated operation and the like can be automatically found in combination with data analysis of vehicle tracks, oil consumption and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection and analysis, and more particularly to a monitoring system for collecting and assessing operation data of sanitation vehicles. Background Art

[0002] Sanitation vehicles are used for urban appearance cleaning and play an important role in maintaining urban hygiene. With the gradual increase of sanitation vehicles, the necessity of strengthening the management of sanitation vehicles is becoming more and more prominent.

[0003] The operation management of traditional sanitation vehicles generally adopts a rough management mode of "considering the vehicle out as operation", lacking effective verification means for the actual operation duration and operation area coverage; operation data depends on manual filling, resulting in misreporting and missing reporting; there is a lack of real-time monitoring means for key indicators such as vehicle operation trajectory and operation volume; the assessment criteria are not unified and lack quantitative basis; it is difficult to detect and handle abnormal operation situations in a timely manner.

[0004] In view of this, the present invention proposes a monitoring system for collecting and assessing operation data of sanitation vehicles, which can monitor the actual operation status of sanitation vehicles in real time, analyze the data such as vehicle trajectory and fuel consumption, and monitor the operation of sanitation vehicles. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a monitoring system for collecting and assessing operation data of sanitation vehicles to solve the problems existing in the above background art.

[0006] The present invention provides the following technical solutions: A monitoring system for collecting and assessing operation data of sanitation vehicles, including a data preliminary collection module, a data acquisition module, an operation data analysis module, an operation data assessment module, and a real-time monitoring module;

[0007] The data preliminary collection module uses a multi-source sensor group to preliminarily collect data of sanitation vehicles;

[0008] The data acquisition module is used to verify the data preliminarily collected by the data preliminary collection module and calculate the data credibility;

[0009] The operation data analysis module is used to analyze operation data, obtain the actual operation actions of sanitation vehicles, and calculate the operation trajectory effectiveness and fuel consumption efficiency of sanitation vehicles;

[0010] The operation data assessment module constructs an assessment system by using the analytic hierarchy process and obtains the assessment score of sanitation vehicles based on the operation trajectory effectiveness and fuel consumption efficiency of sanitation vehicles;

[0011] The real-time monitoring module is used to monitor the real-time operation of sanitation vehicles and receive warning prompts for warning display.

[0012] Preferably, the data acquisition module verifies the data initially collected by the data initial acquisition module based on a sliding window, sets a dynamic threshold for the sliding window, and performs verification if the threshold is exceeded;

[0013] YU dynamic = μ window ± 3σ window ;

[0014] Among them, YU dynamic represents the dynamic threshold of the sliding window, μ window represents the arithmetic mean of the data within the current time window; σ window represents the standard deviation of the data within the current time window, characterizing the degree of data dispersion;

[0015] When the data exceeds the dynamic threshold, it is marked as an outlier, triggering the verification process.

[0016] Preferably, the verification process is specifically as follows: Transmit the outlier data to the background terminal for expert determination. If it is a normal fluctuation value, modify the data to a normal value, and the value modified by the background terminal cannot be verified again. If it is an abnormal data value, it is excluded.

[0017] Preferably, the formula for the data acquisition module to calculate the data credibility is expressed as:

[0018] KX a = w a × H a ; Among them, KX a represents the credibility of the data of the a-th sensor, w a represents the credibility weight of the data of the a-th sensor, H a represents the data health of the a-th sensor;

[0019] When the data credibility KX a satisfies KX a ≥ IU2, then increase the data weight of the a-th sensor;

[0020] When the data credibility KX a satisfies IU1 ≤ KX a < IU2, then keep the data weight of the a-th sensor unchanged;

[0021] When the data credibility KX a satisfies KX a < IU1, then decrease the data weight of the a-th sensor.

[0022] Preferably, the calculation method of the data health of the a-th sensor is:

[0023]

[0024] Among them, N valid_a represents the number of valid data of the a-th sensor within a unit time, and N total represents the total amount of data of the a-th sensor within a unit time, and σ offset_a represents the standard deviation of the clock offset of the a-th sensor, and μ offset_a represents the mean value of the clock offset of the a-th sensor; k1 and k2 are respectively corresponding empirical calibration coefficients;

[0025]

[0026] Among them, λ represents the time decay coefficient; t a represents the service life of the a-th sensor, and F error_a represents the number of historical data errors of the a-th sensor, and F total_a represents the total amount of historical data of the a-th sensor.

[0027] Preferably, the actual operation action of the sanitation vehicle, that is, whether the vehicle performs operations, sets the constraint conditions during the operation of the sanitation vehicle. The constraint conditions are the switch states of each working component when the sanitation vehicle performs operations. If the operation data does not meet the constraint conditions during the operation of the sanitation vehicle, mark the actual operation action of the sanitation vehicle as not operating; if the operation data all meet the constraint conditions during the operation of the sanitation vehicle, mark the actual operation action of the sanitation vehicle as operating; when the marked actual operation action of the sanitation vehicle is inconsistent with the preset operation action, send a warning prompt to the real-time monitoring module.

[0028] Preferably, the specific method for the operation data analysis module to calculate the effectiveness of the operation trajectory of the sanitation vehicle is as follows:

[0029] By using the GIS geofencing technology, the operation task area of the sanitation vehicle is divided into n sub-areas, which are distinguished as the core area and the ordinary area, and operation weights are set for the core area and the ordinary area respectively;

[0030]

[0031] Among them, PP represents the effectiveness of the operation trajectory of the sanitation vehicle, and S gh_i represents the preset cleaning area of the i-th area; S acu_i (t) represents the actual cleaning area of the vehicle at the i-th area at time t; Δt represents the operation time window, that is, the selected time interval. If the next moment is t′, then Δt = t′ - t; δ i (t) represents the effectiveness coefficient of the i-th area at time t; i = 1, 2, 3,..., n.

[0032] Preferably, the calculation formula for the actual cleaning area of the vehicle at the t-th moment in the i-th area is:

[0033] S acu_ i(t) = v i (t) × L deuq × P i (t);

[0034] Wherein, v i (t) represents the vehicle speed at the t-th moment in the i-th area; L deuq represents the effective width of the cleaning device; P i (t) represents the hydraulic pressure normalization coefficient at the t-th moment in the i-th area, and its value range is (0, 1).

[0035] Preferably, the calculation formula for the fuel consumption efficiency is expressed as:

[0036]

[0037] Wherein, η represents the fuel consumption efficiency of the sanitation vehicle, H total represents the total fuel consumption of the sanitation vehicle, D i represents the operation mileage of the i-th area, L i represents the garbage loading amount of the i-th area, and ρ1 and ρ2 are the corresponding proportionality factors respectively.

[0038] Preferably, the analytic hierarchy process adopted by the operation data assessment module includes an objective layer, a criterion layer, and an index layer;

[0039] The objective layer is the assessment score, the criterion layer includes operation quality, resource consumption, and compliance, and the index layer includes operation trajectory effectiveness, operation punctuality, fuel consumption efficiency, equipment loss rate, and the number of violations of sanitation vehicles.

[0040] Technical effects and advantages of the present invention:

[0041] By providing a data acquisition module and an operation data analysis module, the present invention is conducive to verifying the preliminarily collected data and calculating the data credibility, so as to improve the accuracy and effectiveness of the data; analyzing the operation data, obtaining the actual operation actions of the sanitation vehicle, and calculating the operation trajectory effectiveness and fuel consumption efficiency of the sanitation vehicle; thus, using scientific and digital basis as assessment indicators to assess the operation of the sanitation vehicle, monitoring the core working components of the sanitation vehicle in real time, accurately judging the actual operation status, and completely eliminating the false reporting problem of "driving the vehicle without working"; combining the analysis of vehicle trajectory, fuel consumption and other data, it can automatically detect problems such as abnormal detouring and repeated operation, and at the same time provide the sanitation company with workload statistics accurate to the road section to ensure that the tasks are completed. Description of the Drawings

[0042] Figure 1 Structural diagram of a monitoring system for collecting and assessing operation data of a sanitation vehicle according to the present invention. Specific implementation manners

[0043] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. In addition, the forms of each structure described in the following implementation manners are merely examples, and a monitoring system for collecting and assessing operation data of a sanitation vehicle involved in the present invention is not limited to the structures described in the following implementation manners. All other implementation manners obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0044] As Figure 1 shown, the present invention provides a monitoring system for collecting and assessing operation data of a sanitation vehicle, including a primary data collection module, a data acquisition module, an operation data analysis module, an operation data assessment module, and a real-time monitoring module;

[0045] The primary data collection module preliminarily collects data of the sanitation vehicle using a multi-source sensor group, and performs preprocessing operations such as cleaning and noise reduction, filtering, and timestamp alignment on the data preliminarily collected by the multi-source sensor group; the multi-source sensor group includes, but is not limited to, GPS / Beidou positioning, an inertial measurement unit, an on-vehicle camera, a dustbin weight sensor, a hydraulic pressure sensor, a fuel consumption flowmeter, and a dust sensor, etc.; the GPS / Beidou positioning can select any one of GPS or Beidou positioning, and the hydraulic pressure sensor is used to detect the cleaning device.

[0046] The data acquisition module is used to verify the data preliminarily collected by the primary data collection module and calculate the data credibility to obtain more reliable data; the data preliminarily collected by the primary data collection module includes, but is not limited to, the position, fuel consumption, and operation duration of the sanitation vehicle, etc.

[0047] The operation data analysis module is used to analyze the operation data, obtain the actual operation actions of the sanitation vehicle, and calculate the effectiveness of the operation trajectory and the fuel consumption efficiency of the sanitation vehicle.

[0048] The operation data assessment module constructs an assessment system by using the analytic hierarchy process to obtain the assessment score of the sanitation vehicle.

[0049] The real-time monitoring module is used to perform real-time operation monitoring on the sanitation vehicle and receive warning prompts for warning display.

[0050] In this embodiment, it should be specifically noted that the data acquisition module verifies the data preliminarily collected by the primary data collection module based on a sliding window, sets a dynamic threshold for the sliding window, and performs verification if the threshold is exceeded.

[0051] YU dynamic = μ window ±3σ window ;

[0052] Among them, YU dynamic represents the dynamic threshold of the sliding window, μ window represents the arithmetic mean of the data within the current time window, reflecting the central tendency of the data; σ window represents the standard deviation of the data within the current time window, characterizing the degree of data dispersion; in this embodiment, the time window is set to 10 seconds, and those skilled in the art can modify it according to the actual situation, and this embodiment does not make specific limitations on this;

[0053] When the data exceeds the dynamic threshold, it is marked as an outlier and the verification process is triggered; the specific verification process is as follows: the outlier data is transmitted to the background terminal for expert determination. If it is a normal fluctuation value, the data is modified to the normal value, and the value modified by the background terminal cannot be verified again. If it is an abnormal data value, it is eliminated; in the actual data acquisition process, the sensor will be affected by the environment. Therefore, expert determination is required, and combined with the actual environmental situation and experience, the outlier is rechecked to improve the accuracy of the data, laying a foundation for subsequent data analysis;

[0054] During the data transmission and storage process, an incremental data marking mechanism based on the MQTT protocol can be adopted to automatically record the position of the last valid data packet when the network is interrupted, and optimize the retransmission of missing data after reconnecting; use a RAID 6 array to store key job data, allowing two hard disks to be damaged simultaneously and still be able to recover the complete data; and the blockchain technology can be combined to store key data to achieve tamper-proof evidence storage.

[0055] In this embodiment, it should be specifically noted that the formula for the data acquisition module to calculate the data credibility is expressed as:

[0056] KX a = w a ×H a ; among them, KX a represents the credibility of the data of the a-th sensor, w a represents the credibility weight of the data of the a-th sensor, H a represents the data health of the a-th sensor;

[0057]

[0058] Among them, N valid_a represents the number of valid data of the a-th sensor within a unit time, N total represents the total amount of data of the a-th sensor within a unit time, σ offset_aDenote the standard deviation of the clock offset of the a-th sensor as μ offset_a Denote the mean of the clock offset of the a-th sensor; k1 and k2 are the corresponding empirical calibration coefficients respectively, which can be specifically set by those skilled in the art according to the actual situation. In this embodiment, k1 = 0.7 and k2 = 0.3 are taken;

[0059]

[0060] Among them, λ represents the time decay coefficient, usually taking λ = 0.01. In case of rain or snow weather, it can be adjusted to λ = 0.015; t a Denote the service life of the a-th sensor, F error_a Denote the number of historical data errors of the a-th sensor, F total_a Denote the total amount of historical data of the a-th sensor;

[0061] When the data credibility KX a Satisfies KX a ≥ IU2, then increase the data weight of the a-th sensor, and assign more weights in subsequent analysis to improve the accuracy and effectiveness of data analysis;

[0062] When the data credibility KX a Satisfies IU1 ≤ KX a < IU2, then keep the data weight of the a-th sensor unchanged; maintain the original set weight unchanged in subsequent analysis;

[0063] When the data credibility KX a Satisfies KX a < IU1, then reduce the data weight of the a-th sensor, and assign less weights in subsequent analysis to prevent inaccurate analysis results caused by too low data accuracy.

[0064] In this embodiment, it should be specifically noted that the actual operation action of the sanitation vehicle, that is, whether the vehicle is operating, sets the constraint conditions during the operation of the sanitation vehicle. The constraint conditions are the switch states of each working component during the operation of the sanitation vehicle, such as the sweeping turntable, water spraying valve, etc. When the working component is opened, it is assigned a value of 1, and when the working component is closed, it is assigned a value of 0; if during the operation of the sanitation vehicle, the operation data does not meet the constraint conditions, then mark the actual operation action of the sanitation vehicle as not operating; if during the operation of the sanitation vehicle, all the operation data meet the constraint conditions, then mark the actual operation action of the sanitation vehicle as operating; when the marked actual operation action of the sanitation vehicle is inconsistent with the preset operation action, send a warning prompt to the real-time monitoring module; the preset operation action is the theoretical operation action of the sanitation vehicle. If the sanitation vehicle is dispatched to perform an operation task, the preset operation action of this sanitation vehicle is operating, and if the sanitation vehicle is not dispatched to perform an operation task, the preset operation action of this sanitation vehicle is not operating.

[0065] In this embodiment, it should be specifically noted that the specific method for the operation data analysis module to calculate the effectiveness of the operation trajectory of the sanitation vehicle is as follows:

[0066] Through the GIS geofencing technology, the operation task area of the sanitation vehicle is divided into n sub-areas, which are classified into a core area and a general area. Operation weights are set for the core area and the general area respectively. The operation weight of the core area is set to 1.2, and the operation weight of the general area is set to 1;

[0067]

[0068] Among them, PP represents the effectiveness of the operation trajectory of the sanitation vehicle, S gh_i represents the preset cleaning area of the i-th area, which can be set as the area of the i-th area or the cleaning area set in advance; S acu_i (t) represents the actual cleaning area of the vehicle in the i-th area at time t, which can be jointly calculated by hydraulic pressure and vehicle speed; Δt represents the operation time window, that is, the selected time interval. If the next moment is t′, then Δt = t′ - t, and the value of Δt can be set or modified by those skilled in the art according to the actual situation. In this embodiment, Δt = 30s is selected; δ i (t) represents the effectiveness coefficient of the i-th area at time t, which is assigned according to the garbage residue situation after cleaning. If garbage residue is detected, then δ i (t) = 0, and the cleaning area during this period is regarded as invalid. If no garbage residue is detected, then δ i (t) = 1; the garbage residue situation can collect images by setting up a camera, identify the garbage residue through the YOLOv5 model, and output a binary result; i = 1, 2, 3,..., n;

[0069] S acu_i (t) = v i (t) × L deuq × P i (t);

[0070] Among them, v i (t) represents the vehicle speed in the i-th area at time t, which can be obtained by the inertial measurement unit; L deuq represents the effective width of the cleaning device, which is a fixed parameter and is set according to the specific situation of the cleaning device of the sanitation vehicle; P i (t) represents the hydraulic pressure normalization coefficient of the i-th area at time t, and the value range is (0, 1).

[0071] In this embodiment, it should be specifically noted that the calculation formula of the fuel consumption efficiency is expressed as:

[0072]

[0073] Among them, η represents the fuel consumption efficiency of the sanitation vehicle, and H total represents the total fuel consumption of the sanitation vehicle, D i represents the operating mileage of the i-th area, L i represents the garbage loading volume of the i-th area, and ρ1 and ρ2 are the corresponding proportionality factors, taking ρ1 = 0.6 and ρ2 = 0.4;

[0074] The fuel consumption efficiency and the effectiveness of the operation trajectory are both calculated after the sanitation vehicle completes each operation task, and are used to evaluate the operation of the sanitation vehicle.

[0075] In this embodiment, it should be specifically noted that the analytic hierarchy process adopted by the operation data assessment module includes an objective layer, a criterion layer, and an index layer; the objective layer is the assessment score, which reflects the overall score of the operation of the sanitation vehicle and is used for horizontal comparison; the criterion layer includes operation quality, resource consumption, and compliance, and the compliance is the implementation situation of the operation specifications and safety procedures of the sanitation vehicle; the index layer includes the effectiveness of the operation trajectory, operation punctuality, fuel consumption efficiency, equipment loss rate, and the number of violations of the sanitation vehicle, and the operation punctuality is whether the time to complete the operation task is within the specified time; the indicators of the operation quality are the effectiveness of the operation trajectory and operation punctuality, the indicators of the resource consumption are the fuel consumption efficiency and equipment loss rate, and the indicator of the compliance is the number of violations of the sanitation vehicle;

[0076] Persons in this field can add or modify the content of the criterion layer and the index layer according to specific situations;

[0077] Based on the criterion layer, a comparison matrix C is constructed, and experts conduct 1-9 scale scoring on the importance of operation quality, resource consumption, and compliance in the criterion layer. For example, if the operation quality B1 is 3 times more important than the resource consumption B2, then c12 = 3;

[0078] By calculating the eigenvector corresponding to the maximum eigenvalue of matrix C, the weight is obtained after normalization, and the consistency test of the calculation matrix is carried out. If the consistency ratio is less than 0.1, the matrix is determined to be effective;

[0079] Based on the index layer, a comparison matrix D is constructed, and experts conduct 1-9 scale scoring on the importance of each index in the index layer; the weight is set based on the data credibility of each sensor data, and the consistency test of the calculation matrix D is carried out. If the consistency ratio is less than 0.1, the matrix is determined to be effective;

[0080] The assessment score is obtained by layer-by-layer weighting of the criterion layer and the index layer, and the value of the objective layer is used as the assessment score of the sanitation vehicle.

[0081] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0082] As described above, this is only the specific implementation manner of this application. However, the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or replacements, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A monitoring system for collecting and assessing operation data of sanitation vehicles, characterized in that: It includes a data initial collection module, a data acquisition module, a job data analysis module, a job data assessment module, and a real-time monitoring module; The data initial collection module uses a multi-source sensor group to initially collect data of sanitation vehicles; The data acquisition module is used to verify the data initially collected by the data initial collection module and calculate the data credibility; The job data analysis module is used to analyze job data, obtain the actual job actions of sanitation vehicles, and calculate the effectiveness of the job trajectories and fuel consumption efficiency of sanitation vehicles; The job data assessment module constructs an assessment system by using the analytic hierarchy process and obtains the assessment score of the sanitation vehicle based on the effectiveness of the job trajectory and fuel consumption efficiency of the sanitation vehicle; The real-time monitoring module is used to conduct real-time job monitoring on sanitation vehicles and receive warning prompts for warning display.

2. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 1, characterized in that: The data acquisition module verifies the data initially collected by the data initial collection module based on a sliding window, sets a dynamic threshold for the sliding window, and conducts verification if the threshold is exceeded; YU dynamic = μ window ± 3σ window ; Among them, YU dynamic represents the dynamic threshold of the sliding window, and μ window represents the arithmetic mean of the data within the current time window; σ window represents the standard deviation of the data within the current time window, characterizing the degree of data dispersion; When the data exceeds the dynamic threshold, it is marked as an outlier and the verification process is triggered.

3. The monitoring system for collecting and assessing operation data of sanitation vehicles according to claim 2, wherein: The specific verification process is as follows: Transmit the outlier data to the background terminal for expert determination. If it is a normal fluctuation value, modify the data to a normal value, and the value modified by the background terminal cannot be verified again. If it is an abnormal data value, it is excluded.

4. The monitoring system for collecting and assessing operation data of sanitation vehicles according to claim 3, wherein: The formula for the data acquisition module to calculate data credibility is expressed as: KX a = w a × H a ; Among them, KX a represents the credibility of the a-th sensor data, w a represents the credibility weight of the a-th sensor data, H a represents the data health of the a-th sensor; When the data credibility KX a satisfies KX a ≥IU2, then increase the data weight of the a-th sensor; When the data credibility KX a satisfies IU1 ≤ KX a < IU2, the data weight of the a-th sensor remains unchanged; When the data credibility KX a satisfies KX a < IU1, the data weight of the a-th sensor is reduced.

5. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 4, wherein: The calculation method for the data healthiness of the a-th sensor is: Among them, N valid_a represents the number of valid data of the a-th sensor within a unit time, and N total represents the total amount of data of the a-th sensor within a unit time. σ offset_a represents the standard deviation of the clock offset of the a-th sensor, and μ offset_a represents the mean value of the clock offset of the a-th sensor; k1 and k2 are the corresponding empirical calibration coefficients respectively; Among them, λ represents the time decay coefficient; t a represents the service life of the a-th sensor, F error_a represents the number of historical data errors of the a-th sensor, F total_a represents the total amount of historical data of the a-th sensor.

6. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 5, characterized in that: The actual job action of the sanitation vehicle is whether the vehicle is performing a job. Set the constraint conditions during the job process of the sanitation vehicle. The constraint conditions are the switch states of each working component when the sanitation vehicle is performing a job. If the job data does not meet the constraint conditions during the job process of the sanitation vehicle, mark the actual job action of the sanitation vehicle as not performing a job; If the job data meets all the constraint conditions during the job process of the sanitation vehicle, mark the actual job action of the sanitation vehicle as having performed a job; When the marked actual job action of the sanitation vehicle is inconsistent with the preset job action, send a warning prompt to the real-time monitoring module.

7. The monitoring system for collecting and assessing operation data of sanitation vehicles according to claim 6, characterized in that: The specific method for the job data analysis module to calculate the effectiveness of the job trajectory of the sanitation vehicle is: Through the GIS geofence technology, divide the job task area of the sanitation vehicle into n sub-areas, distinguish them as core areas and ordinary areas, and set job weights for the core areas and ordinary areas respectively; Among them, PP represents the effectiveness of the operation trajectory of the sanitation vehicle, and S gh_i represents the preset cleaning area of the i-th area; S acu_i (t) represents the actual cleaning area of the vehicle in the i-th area at time t; Δt represents the operation time window, that is, the selected time interval. If the next moment is t′, then Δt = t′ - t; δ i (t) represents the effectiveness coefficient of the i-th area at time t; i = 1, 2, 3,..., n.

8. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 7, characterized in that: The calculation formula for the actual cleaning area of the vehicle at the i-th area and the t-th moment is: S acu_i (t) = v i (t) × L deuq × P i (t); Among them, v i (t) represents the vehicle speed at time t in the i-th area; L deuq represents the effective width of the cleaning device; P i (t) represents the hydraulic pressure normalization coefficient at time t in the i-th area, and its value range is (0, 1).

9. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 8, characterized in that: The calculation formula for the fuel consumption efficiency is expressed as: Among them, η represents the fuel consumption efficiency of the sanitation vehicle, H total represents the total fuel consumption of the sanitation vehicle, D i represents the operating mileage of the i-th area, L i represents the garbage loading volume of the i-th area, and ρ1 and ρ2 are the corresponding proportionality factors respectively.

10. The monitoring system for collecting and assessing operation data of a sanitation vehicle according to claim 9, characterized in that: The analytic hierarchy process adopted by the job data assessment module includes an objective layer, a criterion layer, and an index layer; The objective layer is the assessment score. The criterion layer includes job quality, resource consumption, and compliance. The index layer includes the effectiveness of the job trajectory, job punctuality, fuel consumption efficiency, equipment loss rate, and the number of violations of sanitation vehicles.

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