An integrated sanitation management platform based on the Internet of Things platform integration method

Abstract

The present invention belongs to the field of smart sanitation technology. A comprehensive sanitation management platform based on an Internet of Things platform integration method is provided, including a data integration module, an Internet module, a job scheduling module, and a communication module. The solution of the present invention can determine a more accurate workload to be cleaned in each area based on sanitation data detected in real time from multiple source channels and expected sanitation data, so that the sanitation vehicle scheduling plan determined is more accurate, which is conducive to making the garbage cleaning effect in each area better.

Description

Technical Field

[0001] The present invention relates to the field of smart sanitation technology, and in particular to an integrated sanitation management platform based on an Internet of Things platform integration method. Background Art

[0002] The sanitation integrated management platform is an intelligent system that integrates a variety of information technologies to improve the efficiency and management level of urban sanitation operations. Traditional sanitation integrated management platforms are basically based on statistical analysis of historical sanitation data in the region to predict the sanitation conditions of each region within the current cycle and schedule sanitation operations accordingly.

[0003] With the above existing methods, since the distribution and flow of people in the region are constantly changing, the sanitary conditions in each region are not completely consistent with historical laws, resulting in inaccurate scheduling of sanitation vehicles in each region. Summary of the invention

[0004] In this regard, the present invention provides an integrated sanitation management platform based on an Internet of Things platform integration method to solve the above technical problems.

[0005] The present invention provides an integrated sanitation management platform based on an Internet of Things platform integration method, the platform comprising a data integration module, an Internet module, a job scheduling module, and a communication module; the job scheduling module is connected to the data integration module, the Internet module, and the communication module respectively;

[0006] The data integration module is used to receive the real-time health data of each area from multiple data sources integrated from the Internet of Things platform, and transmit the real-time health data to the job scheduling module;

[0007] The Internet module is used to receive the expected health data of each area from the Internet and transmit the expected health data to the job scheduling module;

[0008] The job scheduling module is used to predict the amount of cleaning work to be done in each area based on the real-time sanitation data and the expected sanitation data, and generate a vehicle scheduling plan based on each amount of cleaning work to be done, wherein the vehicle scheduling plan includes the number of sanitation vehicles required for each area;

[0009] The communication module is used to transmit the vehicle dispatching plan to the vehicle dispatching station.

[0010] In some embodiments, the predicting the amount of cleaning work to be done in each area based on the real-time sanitation data and the expected sanitation data includes:

[0011] deriving a first real-time garbage amount in each area from the real-time sanitation data, and deriving an expected garbage amount in each area from the expected sanitation data;

[0012] Obtaining a first number of sanitation vehicles in operation in each area and their respective cleaning routes, predicting a garbage cleaning volume based on the first number and each of the cleaning routes, and calculating a second real-time garbage volume corresponding to a next cleaning cycle in each area based on the first real-time garbage volume and the garbage cleaning volume;

[0013] The second real-time garbage amount and the expected garbage generation amount are added together to obtain the workload to be cleaned in each area corresponding to the next cleaning cycle.

[0014] In some embodiments, if the expected waste generation is not resolved from the expected hygiene data, then:

[0015] Determine event attribute information of expected events in each area parsed from the expected health data, wherein the event attribute information includes activity type and activity scale, and the activity scale includes the number of participants and activity duration;

[0016] The garbage base is obtained by looking up a table according to the activity type, the amplification coefficient is determined according to the activity scale, and the amplification coefficient is multiplied by the garbage base to obtain the expected garbage generation corresponding to the next cleaning cycle.

[0017] In some embodiments, the expected amount of garbage generated is allocated to a start period, a middle period, and an end period; wherein the predicted values ​​of the amount of garbage corresponding to the end period, the start period, and the middle period decrease in sequence.

[0018] In some embodiments, if the event attribute information only includes the activity subject personnel information, then:

[0019] Inputting the information of the activity subject personnel into a large language model, and the large language model predicts the activity type and activity scale based on the network data obtained by searching;

[0020] The expected garbage generation amount corresponding to the next cleaning cycle is obtained according to the activity type and the activity scale.

[0021] In some embodiments, generating a vehicle dispatching plan according to each of the to-be-cleaned workloads includes:

[0022] Obtain information about all sanitation vehicles configured in each area, including the garbage carrying capacity of each vehicle and the current status; wherein the current status includes the available status;

[0023] Determine the required number of sanitation vehicles corresponding to the area according to the garbage carrying capacity of a single vehicle and the workload to be cleaned, and select available sanitation vehicles according to the required number of sanitation vehicles;

[0024] The vehicle dispatching plan is generated according to the required number of sanitation vehicles and the identity codes of the sanitation vehicles.

[0025] In some embodiments, generating a vehicle dispatching plan according to each of the workloads to be cleaned further includes:

[0026] If the required number of sanitation vehicles exceeds the total number of sanitation vehicles in the corresponding area configuration, a first vehicle scheduling plan is generated according to the start time period and the middle time period, and a second vehicle scheduling plan is generated according to the end time period;

[0027] The first vehicle dispatching scheme includes a first required number of sanitation vehicles and a first cleaning time, wherein the first required number of sanitation vehicles is calculated based on the sum of the predicted values ​​of the garbage volume corresponding to the start period and the middle period and the garbage carrying capacity of a single vehicle, and the first cleaning time is determined based on the middle period;

[0028] The second vehicle scheduling plan includes a second demand number of sanitation vehicles and a second cleaning time. The second demand number of sanitation vehicles is calculated based on the predicted garbage volume corresponding to the end time period and the garbage carrying capacity of a single vehicle. The second cleaning time is determined based on the end time period.

[0029] The present invention also provides an electronic device, which is applied to any of the above-mentioned job scheduling modules; the electronic device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor.

[0030] The present invention also provides a computer storage medium, which is applied to any of the above-mentioned job scheduling modules; the computer storage medium stores a computer program that can be executed by a processor.

[0031] The present invention also provides a computer program product, which is applied to any of the aforementioned job scheduling modules; the computer program product includes a computer program that can be executed by a processor.

[0032] The beneficial effect of the present invention is that the scheme of the present invention can determine a more accurate workload to be cleaned in each area based on the sanitation data detected in real time from multiple source channels and the expected sanitation data, so that the determined sanitation vehicle scheduling plan is more accurate, which is conducive to making the garbage cleaning effect in each area better. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 It is a structural schematic diagram of an environmental sanitation integrated management platform based on an Internet of Things platform integration method disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0036] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0037] like Figure 1 As shown, the embodiment of the present invention discloses an integrated sanitation management platform based on an Internet of Things platform integration method, wherein the platform includes a data integration module, an Internet module, a job scheduling module, and a communication module; the job scheduling module is connected to the data integration module, the Internet module, and the communication module respectively;

[0038] The data integration module is used to receive the real-time health data of each area from multiple data sources integrated from the Internet of Things platform, and transmit the real-time health data to the job scheduling module;

[0039] The Internet module is used to receive the expected health data of each area from the Internet and transmit the expected health data to the job scheduling module;

[0040] The job scheduling module is used to predict the amount of cleaning work to be done in each area based on the real-time sanitation data and the expected sanitation data, and generate a vehicle scheduling plan based on each amount of cleaning work to be done, wherein the vehicle scheduling plan includes the number of sanitation vehicles required for each area;

[0041] The communication module is used to transmit the vehicle dispatching plan to the vehicle dispatching station.

[0042] The integrated sanitation management platform of the present invention analyzes the workload to be cleaned in various areas of the city based on two types of data sources, and then determines the best vehicle dispatching plan for each area of ​​the city.

[0043] Among them, the data integration module can receive integrated real-time sanitation data from multiple data sources from the Internet of Things platform. The Internet of Things platform is connected to a variety of fixed and mobile monitoring devices distributed in the city, such as surveillance cameras installed in various stores, garbage collection stations, etc., garbage volume detection sensors installed in garbage bins, and garbage volume detection sensors installed in special sanitation patrol vehicles (or drones). These surveillance cameras and garbage volume detection sensors can perform real-time detection of the amount of garbage in the area (including garbage bins and on the road surface), and transmit the real-time detected garbage volume data to the Internet of Things platform through the Internet of Things technology. The comprehensive sanitation management platform of the present invention then controls the data integration module to directly receive the real-time sanitation data of each area from the Internet of Things platform.

[0044] At the same time, the sanitation integrated management platform of the present invention also includes an Internet module, which can receive expected sanitation data from the Internet. For example, a user can send expected sanitation data of a certain area to the Internet module through a dedicated website, applet, APP or other ports. The expected sanitation data can be "the sports center will hold a XX concert from 18:00 to 20:00 tonight, and 1.5 tons of garbage is expected to be generated." Therefore, the job scheduling module can combine the above real-time sanitation data and expected sanitation data to predict the amount of garbage in each area, that is, the workload to be cleaned, so as to schedule an appropriate number of sanitation vehicles for each area.

[0045] Therefore, the solution of the present invention can determine a more accurate amount of work to be cleaned in each area based on the sanitation data detected in real time from multiple source channels and the expected sanitation data, so that the determined sanitation vehicle scheduling plan is more accurate, which is conducive to better garbage cleaning effects in various areas.

[0046] In some embodiments, the predicting the amount of cleaning work to be done in each area based on the real-time sanitation data and the expected sanitation data includes:

[0047] deriving a first real-time garbage amount in each area from the real-time sanitation data, and deriving an expected garbage amount in each area from the expected sanitation data;

[0048] Obtaining a first number of sanitation vehicles in operation in each area and their respective cleaning routes, predicting a garbage cleaning volume based on the first number and each of the cleaning routes, and calculating a second real-time garbage volume corresponding to a next cleaning cycle in each area based on the first real-time garbage volume and the garbage cleaning volume;

[0049] The second real-time garbage amount and the expected garbage generation amount are added together to obtain the workload to be cleaned in each area corresponding to the next cleaning cycle.

[0050] In this embodiment, the first real-time garbage volume in a certain area can be analyzed from the received real-time sanitation data, and the first number of sanitation vehicles in operation in the area and their respective cleaning routes can be determined based on the operation data (operation status, positioning) transmitted by each sanitation vehicle, and the amount of garbage that these sanitation vehicles can clean and take away in the area during the current cleaning cycle, that is, the garbage cleaning volume, can be determined. Therefore, the first real-time garbage volume minus the garbage cleaning volume is the starting garbage volume in the area at the next cleaning cycle, that is, the second real-time garbage volume. The expected sanitation data received above includes the expected garbage generation volume. The above-mentioned second real-time garbage volume is added to the above-mentioned expected garbage generation volume, and the result is the workload to be cleaned in the area in the next cleaning cycle. By calculating cyclically in the above manner, the workload to be cleaned in each area in the next cleaning cycle can be obtained.

[0051] It should be noted that only a portion of the cleaning routes of some sanitation vehicles will be located within the corresponding area, so further consideration of the cleaning routes is conducive to obtaining a more accurate amount of garbage cleaned in the corresponding area.

[0052] In some embodiments, if the expected waste generation is not resolved from the expected hygiene data, then:

[0053] Determine event attribute information of expected events in each area parsed from the expected health data, wherein the event attribute information includes activity type and activity scale, and the activity scale includes the number of participants and activity duration;

[0054] The garbage base is obtained by looking up a table according to the activity type, the amplification coefficient is determined according to the activity scale, and the amplification coefficient is multiplied by the garbage base to obtain the expected garbage generation corresponding to the next cleaning cycle.

[0055] In this embodiment, the expected sanitation data received above may include the expected amount of garbage generated, or may only include the corresponding expected event. In this case, it is necessary to predict the amount of garbage left in the area when the expected event is held, that is, the expected amount of garbage generated, based on the attribute information of the expected event.

[0056] Event attribute information includes activity type and subject personnel information. Among them, activity types include concerts, sports events, and exams (middle school entrance exams, college entrance exams, etc.); the scale of the activity is mainly determined by the number of participants and the duration of the activity. The more participants and the longer the activity, the larger the scale of the activity. The amount of garbage generated by different types of expected events is obviously different. The amount of garbage generated by exams is relatively small, mainly a small amount of mineral water bottles, waste paper, etc.; while during concerts and sports events, fluorescent sticks, flags, matching clothing, raincoats, etc. are used, and the amount of garbage generated is significantly more than that of exam activities. At the same time, the larger the scale of the expected event, that is, the more participants and the longer the activity, the more garbage generated, and vice versa.

[0057] Therefore, this embodiment of the present invention determines in advance the average amount of garbage that can be generated by different types of activities, that is, the garbage base, by means of big data statistics, and statistically calculates the probability distribution of garbage retention by a single person under different personnel sizes and activity durations. The greater the probability, the greater the corresponding amplification coefficient. Construct a first comparison table of activity types and garbage bases, and a second comparison table of activity scales and amplification coefficients, respectively. By looking up the table, the garbage base and amplification coefficient corresponding to the above-mentioned expected events can be quickly determined, and the expected amount of garbage generated can be obtained by multiplying the amplification coefficient by the garbage base (that is, the amplification coefficient is used to appropriately increase the corresponding garbage base). For example, activity scale = (number of participants * activity duration) / benchmark duration.

[0058] In some embodiments, the expected amount of garbage generated is allocated to a start period, a middle period, and an end period; wherein the predicted values ​​of the amount of garbage corresponding to the end period, the start period, and the middle period decrease in sequence.

[0059] In this embodiment, at the beginning and end of concerts, sports events and other activities, more participants are outside the venue (waiting to enter, leaving after the event), and the amount of garbage left behind will be significantly greater. During the event, there are fewer people outside the venue, and the amount of garbage left behind during this period will be less. Therefore, the present invention sets the garbage volume prediction value at the beginning and end periods to account for a higher proportion of the expected garbage generation, for example, the garbage volume prediction value at the beginning period = expected garbage generation * 0.3, the garbage volume prediction value at the end period = expected garbage generation * 0.4, and the garbage volume prediction value in the middle period = expected garbage generation * 0.2.

[0060] In some embodiments, if the event attribute information only includes the activity subject personnel information, then:

[0061] Inputting the information of the activity subject personnel into a large language model, and the large language model predicts the activity type and activity scale based on the network data obtained by searching;

[0062] The expected garbage generation amount corresponding to the next cleaning cycle is obtained according to the activity type and the activity scale.

[0063] In some embodiments, event attribute information may also only include information about the main personnel of the activity. For example, the expected hygiene data is "The sports activity center will hold Zhou XX's concert from 18:00 to 20:00 tonight." The activity type and scale cannot be parsed out from it, but the main personnel information of the activity, namely "Zhou XX", can be parsed out. "Zhou XX" is input into the large language model obtained through fine-tuning. The large language model can predict the activity type and scale of the expected event based on the searched network data, thereby predicting the expected garbage generation corresponding to the next cleaning cycle in the aforementioned manner.

[0064] The large language model is preferably constructed based on the BERT model or the GPT model (ChatGPT is preferably used). The large language model can search for network data related to "Zhou XX" from the Internet, mainly including categories (entertainment stars, sports stars, musicians, etc.), popularity, event plans, etc. Based on this information, the activity type and scale of the expected event to be held by "Zhou XX" in the city can be predicted.

[0065] The large language model is constructed by calling a trained BERT model or GPT model to obtain double-labeled training data, which includes a feature matrix and double labels. The feature matrix is ​​obtained by integrating the corresponding sub-feature matrices constructed by the categories, popularity, and activity plans of each well-known person, while the double labels are the manually labeled activity types and activity scales. Use these training data to retrain the trained BERT model or GPT model, that is, to achieve fine-tuning, so as to obtain the large language model required by the present invention.

[0066] In some embodiments, generating a vehicle dispatching plan according to each of the workloads to be cleaned includes:

[0067] Obtain information about all sanitation vehicles configured in each area, including the garbage carrying capacity of each vehicle and the current status; wherein the current status includes the available status;

[0068] Determine the required number of sanitation vehicles corresponding to the area according to the garbage carrying capacity of a single vehicle and the workload to be cleaned, and select available sanitation vehicles according to the required number of sanitation vehicles;

[0069] The vehicle dispatching plan is generated according to the required number of sanitation vehicles and the identity codes of the sanitation vehicles.

[0070] In this embodiment, after the workload to be cleaned in each area is obtained, the garbage carrying capacity of each sanitation vehicle configured in the area and the current status are further determined, and the current status includes available, waiting for cleaning work, and under maintenance. The workload to be cleaned is divided by the garbage carrying capacity of each vehicle to obtain the number of sanitation vehicles that need to be dispatched in the next cleaning cycle in the area. Based on this, the corresponding number of sanitation vehicles are selected from the "available" sanitation vehicles, and a vehicle dispatch plan is generated based on the number of sanitation vehicle requirements and the identity codes of the sanitation vehicles.

[0071] After receiving the vehicle dispatch plan, if all the sanitation vehicles with the above-mentioned identity codes are in the "available" state, the vehicle dispatch station will arrange drivers to drive these sanitation vehicles to perform the next cycle of cleaning operations. If some of the sanitation vehicles with the above-mentioned identity codes are no longer in the "available" state, the vehicle dispatch station will select a corresponding number of vehicles from other sanitation vehicles according to the required number of sanitation vehicles for replacement.

[0072] In some embodiments, generating a vehicle dispatching plan according to each of the workloads to be cleaned further includes:

[0073] If the required number of sanitation vehicles exceeds the total number of sanitation vehicles in the corresponding area configuration, a first vehicle scheduling plan is generated according to the start time period and the middle time period, and a second vehicle scheduling plan is generated according to the end time period;

[0074] The first vehicle dispatching scheme includes a first required number of sanitation vehicles and a first cleaning time, wherein the first required number of sanitation vehicles is calculated based on the sum of the predicted values ​​of the garbage volume corresponding to the start period and the middle period and the garbage carrying capacity of a single vehicle, and the first cleaning time is determined based on the middle period;

[0075] The second vehicle scheduling plan includes a second demand number of sanitation vehicles and a second cleaning time. The second demand number of sanitation vehicles is calculated based on the predicted garbage volume corresponding to the end time period and the garbage carrying capacity of a single vehicle. The second cleaning time is determined based on the end time period.

[0076] In this embodiment, when the amount of garbage generated by certain activities is large and the number of "available" sanitation vehicles configured in the area is insufficient, pre-cleaning can be implemented by making full use of the characteristics of the middle period of these activities, that is, there are fewer people outside the venue, which is conducive to efficient cleaning. That is, according to the sum of the predicted values ​​of the amount of garbage corresponding to the start period and the middle period of the activity calculated above and the garbage carrying capacity of a single vehicle, the corresponding number of sanitation vehicles is determined, and they are dispatched to clean and transport the garbage that has been generated once at a certain moment in the middle period. Then, at the end of the activity, according to the predicted value of the amount of garbage at the end of the activity calculated above and the garbage carrying capacity of a single vehicle, the corresponding number of sanitation vehicles is determined, and they are dispatched to clean and transport the garbage that has been generated twice at a certain moment in the end period. Therefore, the present invention indirectly solves the problem of insufficient available sanitation vehicles by means of secondary cleaning and transportation. In the case of insufficient sanitation vehicles, the distribution of people outside the venue before and after the event is fully utilized to select the appropriate time for primary / secondary cleaning, thereby ensuring the cleaning efficiency and cleaning effect.

[0077] The first cleaning time is a certain moment in the middle period (based on the cleaning capacity of the sanitation vehicle, and a cleaning operation needs to be completed before reaching the end period), that is, the sanitation vehicle arrives at the activity site at this time to perform a cleaning operation. The second cleaning time is a certain moment after the end period, that is, the sanitation vehicle arrives at the activity site at a certain moment after the end of the activity (for example, 20 minutes after the end of the activity) to perform a second cleaning operation. This setting can effectively reduce the obstruction of people and vehicles in the activity area to sanitation vehicles, thereby improving the efficiency of cleaning operations.

[0078] An embodiment of the present invention further discloses an electronic device, which is applied to any of the above-mentioned job scheduling modules; the electronic device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor.

[0079] An embodiment of the present invention further discloses a computer storage medium, which is applied to any of the above-mentioned job scheduling modules; the computer storage medium stores a computer program that can be executed by a processor.

[0080] An embodiment of the present invention further discloses a computer program product, which is applied to any of the aforementioned job scheduling modules; the computer program product includes a computer program that can be executed by a processor.

[0081] The computer storage media involved in the present invention include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. Computer storage media include random access memory (RAM), read-only memory (ROM), flash memory or other solid-state storage technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, tape cassettes, magnetic tapes, disk storage or other magnetic storage devices. Of course, those skilled in the art will know that the computer storage media is not limited to the above-mentioned ones.

[0082] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented with hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein the communication media include any media that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that a general or special-purpose computer can access.

[0083] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An integrated sanitation management platform based on the Internet of Things platform integration method, characterized by: The platform includes a data integration module, an Internet module, a job scheduling module, and a communication module; the job scheduling module is connected to the data integration module, the Internet module, and the communication module respectively; The data integration module is used to receive the real-time health data of each area from multiple data sources integrated from the Internet of Things platform, and transmit the real-time health data to the job scheduling module; The Internet module is used to receive the expected health data of each area from the Internet and transmit the expected health data to the job scheduling module; The job scheduling module is used to predict the amount of work to be cleaned in each area based on the real-time sanitation data and the expected sanitation data, and generate a vehicle scheduling plan based on each amount of work to be cleaned, wherein the vehicle scheduling plan includes the number of sanitation vehicles required for each area; The communication module is used to transmit the vehicle dispatching plan to the vehicle dispatching station; If the expected waste generation is not resolved from the expected sanitation data, then: Determine event attribute information of expected events in each area parsed from the expected health data, wherein the event attribute information includes activity type and activity scale, and the activity scale includes the number of participants and activity duration; The garbage base number is obtained by looking up a table according to the activity type, the amplification coefficient is determined according to the activity scale, and the amplification coefficient is multiplied by the garbage base number to obtain the expected garbage generation corresponding to the next cleaning cycle, including: determining the average amount of garbage that can be generated by different types of activities, i.e., the garbage base number, in advance by means of big data statistics, and statistically analyzing the probability distribution of garbage retention by a single person under different numbers of people and activity durations. The greater the probability, the greater the corresponding amplification coefficient. A first comparison table between activity type and garbage base number, and a second comparison table between activity scale and amplification coefficient are constructed respectively; the garbage base number and amplification coefficient corresponding to the expected event are determined by looking up a table, and the expected garbage generation is obtained by multiplying the amplification coefficient by the garbage base number; The expected garbage generation amount is allocated to a start period, a middle period and an end period; wherein the garbage amount prediction values ​​corresponding to the end period, the start period and the middle period decrease in sequence.

2. According to claim 1, a comprehensive sanitation management platform based on the Internet of Things platform integration method is characterized by: The predicting of the amount of cleaning work to be done in each area based on the real-time sanitation data and the expected sanitation data includes: deriving a first real-time garbage amount in each area from the real-time sanitation data, and deriving an expected garbage amount in each area from the expected sanitation data; Obtaining a first number of sanitation vehicles in operation in each area and their respective cleaning routes, predicting a garbage cleaning volume based on the first number and each of the cleaning routes, and calculating a second real-time garbage volume corresponding to a next cleaning cycle in each area based on the first real-time garbage volume and the garbage cleaning volume; The second real-time garbage amount and the expected garbage generation amount are added together to obtain the workload to be cleaned in each area corresponding to the next cleaning cycle.

3. According to claim 2, a comprehensive sanitation management platform based on the Internet of Things platform integration method is characterized by: If the event attribute information only includes the activity subject personnel information, then: Inputting the activity subject personnel information into a large language model, and the large language model predicts the activity type and activity scale based on the network data obtained by searching; The expected garbage generation amount corresponding to the next cleaning cycle is obtained according to the activity type and the activity scale.

4. According to claim 3, a comprehensive sanitation management platform based on the Internet of Things platform integration method is characterized by: The generating of a vehicle dispatching plan according to each of the workloads to be cleaned includes: Obtain information about all sanitation vehicles configured in each area, including the garbage carrying capacity of each vehicle and the current status; wherein the current status includes the available status; Determine the required number of sanitation vehicles corresponding to the area according to the garbage carrying capacity of a single vehicle and the workload to be cleaned, and select available sanitation vehicles according to the required number of sanitation vehicles; The vehicle dispatching plan is generated according to the required number of sanitation vehicles and the identity codes of the sanitation vehicles.

5. According to claim 4, a comprehensive sanitation management platform based on the Internet of Things platform integration method is characterized by: The generating of the vehicle dispatching scheme according to each of the workloads to be cleaned also includes: If the required number of sanitation vehicles exceeds the total number of sanitation vehicles in the corresponding area configuration, a first vehicle scheduling plan is generated according to the start time period and the middle time period, and a second vehicle scheduling plan is generated according to the end time period; The first vehicle dispatching scheme includes a first required number of sanitation vehicles and a first cleaning time, wherein the first required number of sanitation vehicles is calculated based on the sum of the predicted values ​​of the garbage volume corresponding to the start period and the middle period and the garbage carrying capacity of a single vehicle, and the first cleaning time is determined based on the middle period; The second vehicle scheduling plan includes a second demand number of sanitation vehicles and a second cleaning time. The second demand number of sanitation vehicles is calculated based on the predicted garbage volume corresponding to the end time period and the garbage carrying capacity of a single vehicle. The second cleaning time is determined based on the end time period.

6. An electronic device, characterized in that: The electronic device is applied to the job scheduling module described in any one of claims 1-5; it is characterized in that the electronic device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor.

7. A computer storage medium, characterized in that: The computer storage medium is applied to the job scheduling module described in any one of claims 1 to 5; the computer storage medium stores a computer program that can be executed by a processor.

8. A computer program product, characterized in that: The computer program product is applied to the job scheduling module described in any one of claims 1 to 5; the computer program product includes a computer program executable by a processor.

Images