Intelligent environment-friendly garbage recycling system based on Internet of Things

Abstract

The invention provides an intelligent environment-friendly garbage recycling system based on the Internet of Things, and relates to the technical field of garbage recycling, and the intelligent environment-friendly garbage recycling system based on the Internet of Things comprises an attribute configuration unit, a data acquisition and transmission unit, a capacity early warning time prediction unit, a recycling route time prediction unit and a control execution unit. The garbage level is monitored in real time by adopting a sensor technology, quick response and treatment are realized through a wireless network, the manpower and material resource cost is reduced through intelligent monitoring and automatic collection, the garbage treatment speed is increased, the cleaning cost is reduced, the environmental pollution caused by garbage overflow is reduced, and the intelligent urban garbage management system has the advantages that the intelligent urban garbage management is realized. And the overall level of urban management and the living quality of residents can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of garbage recycling, and in particular to an intelligent and environmentally friendly garbage recycling and processing system based on the Internet of Things. Background Art

[0002] In the current era of rapid urbanization, efficient and environmentally friendly garbage collection systems are becoming increasingly important. With the rapid development of the Internet of Things, big data analysis and artificial intelligence technologies, the future urban garbage management system will be more intelligent and automated. Smart trash cans can more accurately predict when garbage is full and automatically optimize garbage collection routes and schedules. At the same time, the development of unmanned driving technology has made self-driving garbage trucks possible, further improving the efficiency and safety of garbage collection. The use of clean energy, such as solar energy, is also an important trend in the development of future urban garbage management systems, which will help reduce carbon emissions and promote sustainable development.

[0003] At present, the global urbanization process is accelerating, and the problem of urban waste management is becoming more and more prominent, becoming an important factor restricting the sustainable development of cities. Traditional garbage collection methods are not only inefficient and difficult to cope with the growing amount of garbage generated, but also often cause garbage accumulation and overflow due to untimely recycling and treatment, seriously affecting urban environmental sanitation. What's more serious is that improper garbage disposal methods may also cause secondary pollution to the environment and increase ecological pressure.

[0004] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0005] In view of this, the present invention provides an intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things to solve the above-mentioned problems.

[0006] In order to solve the above problems, the specific technical solutions adopted by the present invention are as follows:

[0007] An intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things, the intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things includes: an attribute configuration unit, a data acquisition and transmission unit, a capacity warning time prediction unit, a recycling route time prediction unit and a control execution unit;

[0008] An attribute configuration unit, used to configure attribute information of sensors and positioning devices respectively based on the types of recycled garbage;

[0009] A data acquisition and transmission unit, used to acquire capacity status data of different types of garbage in the garbage recycling device according to the configured sensors, and transmit the capacity status data to the cloud platform through the Internet of Things;

[0010] A capacity warning time prediction unit, used to predict the capacity warning time of different types of garbage in the garbage recycling device through a growth function analysis method based on the capacity status data of different types of garbage;

[0011] The recycling route time prediction unit is used to obtain the location information of the intelligent garbage collection vehicle according to the configured positioning device, and dynamically analyze the garbage collection route and recycling time of the intelligent garbage collection vehicle through the path optimization algorithm in combination with the capacity warning time of different types of garbage in the garbage collection device;

[0012] The control execution unit is used to control the intelligent garbage collection vehicle to execute garbage collection based on the garbage collection route and collection time of the intelligent garbage collection vehicle.

[0013] The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things also includes a garbage recycling device for realizing garbage recycling. The garbage recycling device consists of a garbage bin main body arranged on the ground and a pull-out placement rack located inside the garbage bin main body.

[0014] Preferably, based on the types of recycled garbage, the attribute information of the sensors and positioning devices respectively configured includes:

[0015] Obtain the type of garbage to be recycled by the garbage recycling device, and encode the type of garbage to be recycled according to the type of garbage;

[0016] A sensor for detecting the garbage collection capacity is configured on the garbage collection device, and the sensor is associated with the type of garbage collected by the garbage collection device;

[0017] A positioning device for position monitoring is configured on the smart garbage collection truck, and the positioning device is associated with the type of garbage collected by the smart garbage collection truck.

[0018] Preferably, based on the capacity status data of different types of garbage, predicting the capacity warning time of different types of garbage in the garbage recycling device by growth function analysis method includes:

[0019] Collecting capacity status data of different types of garbage in the garbage collection device within a preset time period;

[0020] Setting target capacity thresholds for recycling different types of garbage based on attribute parameters of the garbage recycling device;

[0021] A capacity growth function of garbage in a garbage collection device is constructed according to the capacity status data, and the capacity warning time of different types of garbage in the garbage collection device is predicted based on the capacity growth function and the target capacity threshold.

[0022] Preferably, constructing a capacity growth function of garbage in the garbage collection device according to the capacity status data, and predicting the capacity warning time of different types of garbage in the garbage collection device based on the capacity growth function and the target capacity threshold comprises:

[0023] Taking time as the independent variable and garbage capacity as the dependent variable, the capacity growth function of garbage in the garbage recycling device is established by linear regression method.

[0024] According to the capacity growth function, calculate the capacity growth rate of different types of garbage in the garbage recycling device;

[0025] According to the capacity growth rate and the target capacity threshold, the capacity warning time when different types of garbage in the garbage recycling device reach the target capacity threshold is determined.

[0026] Preferably, according to the capacity growth function, calculating the capacity growth rate of different types of garbage in the garbage recycling device includes:

[0027] According to the capacity growth function, the difference between the garbage capacity data corresponding to the last unit time in the preset time period and the garbage capacity data corresponding to the earliest unit time is calculated;

[0028] Determining the number of time units included in the preset time period;

[0029] Divide the calculated garbage capacity difference by the quantity per unit time to get the garbage capacity growth rate per unit time.

[0030] Preferably, according to the capacity growth rate and the target capacity threshold, determining the capacity warning time for different types of garbage in the garbage recycling device to reach the target capacity threshold includes:

[0031] The garbage capacity data corresponding to the last unit time in the preset time period is used as the current garbage capacity;

[0032] Calculate the difference between the target capacity threshold and the current garbage capacity to obtain the capacity demand values ​​of different types of garbage in the garbage collection device to reach the target capacity threshold;

[0033] According to the capacity demand value and the capacity growth rate, the capacity demand time for different types of garbage in the garbage recycling device to reach the target capacity threshold is calculated, and the capacity demand time is used as the capacity warning time.

[0034] Preferably, the location information of the intelligent garbage collection vehicle is obtained according to the configured positioning device, and the garbage collection route and collection time of the intelligent garbage collection vehicle are dynamically analyzed by the path optimization algorithm in combination with the capacity warning time of different types of garbage in the garbage collection device, including:

[0035] Obtain information about all garbage collection devices that need to be emptied, and establish a garbage collection task set based on the capacity warning time of the garbage collection devices;

[0036] Based on the positioning device, the location data of each smart garbage collection vehicle is obtained in real time, and the garbage collection service area of ​​the smart garbage collection vehicle is established;

[0037] Based on the garbage collection service area of ​​the intelligent garbage collection truck, the optimal garbage collection route and collection time of each intelligent garbage collection truck are planned through the path optimization algorithm according to the garbage collection task set.

[0038] Preferably, based on the positioning device, the location data of each intelligent garbage collection vehicle is obtained in real time, and the garbage collection service area of ​​the intelligent garbage collection vehicle is established, including:

[0039] Determine the service boundary of garbage collection based on the location information of the garbage collection device;

[0040] Deploy a base station matrix at the service boundary of garbage collection, and use the positioning equipment on the smart garbage collection vehicle to obtain the location data of the smart garbage collection vehicle;

[0041] According to the garbage collection type and location data of the smart garbage collection truck, the garbage collection service area of ​​each smart garbage collection truck is determined.

[0042] Preferably, based on the garbage collection service area of ​​the intelligent garbage collection vehicle, according to the garbage collection task set, the optimal garbage collection route and collection time of each intelligent garbage collection vehicle are planned by the path optimization algorithm, including:

[0043] Based on the garbage collection service area of ​​the intelligent garbage collection vehicle, a garbage collection device that each intelligent garbage collection vehicle needs to collect garbage is selected from the garbage collection task set;

[0044] Based on the basic information of each intelligent garbage collection vehicle, the location information of the garbage collection device, the garbage collection time and the geographical information of the garbage collection service area, a route optimization model is constructed;

[0045] The constructed path optimization model is solved using a genetic algorithm to obtain the optimal garbage collection route and time for each intelligent garbage collection vehicle.

[0046] The beneficial effects of the present invention are:

[0047] 1. The present invention adopts sensor technology to monitor garbage levels in real time and achieves rapid response and processing through wireless networks. It reduces manpower and material costs through intelligent monitoring and automatic collection, improves garbage disposal speed, reduces cleaning costs, and reduces environmental pollution caused by garbage overflow. Based on intelligent urban garbage management, it can improve the overall level of urban management and the quality of life of residents.

[0048] 2. The present invention uses the linear regression method to establish a garbage capacity growth function. Combined with positioning equipment and path optimization algorithms, it can realize dynamic monitoring and intelligent scheduling of intelligent garbage collection vehicles, improve the accuracy and efficiency of garbage collection, and obtain the location data of intelligent garbage collection vehicles in real time. By establishing a garbage recycling service area, it can ensure the coverage and timeliness of garbage collection services and improve citizens' satisfaction with garbage collection services. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0050] Figure 1 This is a principle block diagram of an intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to an embodiment of the present invention;

[0051] Figure 2 It is a structural schematic diagram of a garbage recycling device in an intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to an embodiment of the present invention.

[0052] In the figure:

[0053] 1. Attribute configuration unit; 2. Data acquisition and transmission unit; 3. Capacity warning time prediction unit; 4. Recycling route time prediction unit; 5. Control execution unit; 6. Trash bin body; 7. Pull-out placement rack. DETAILED DESCRIPTION

[0054] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0055] According to an embodiment of the present invention, an intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things is provided.

[0056] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1-Figure 2As shown, according to an embodiment of the present invention, an intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things includes: an attribute configuration unit 1, a data acquisition and transmission unit 2, a capacity warning time prediction unit 3, a recycling route time prediction unit 4 and a control execution unit 5;

[0057] The attribute configuration unit 1 is used to configure the attribute information of the sensor and the positioning device respectively based on the type of recycled garbage;

[0058] As a preferred implementation, based on the type of recycled garbage, the attribute information of the sensors and positioning devices respectively includes:

[0059] Obtain the type of garbage to be recycled by the garbage recycling device, and encode the type of garbage to be recycled according to the type of garbage;

[0060] A sensor for detecting the garbage collection capacity is configured on the garbage collection device, and the sensor is associated with the type of garbage collected by the garbage collection device;

[0061] A positioning device for position monitoring is configured on the smart garbage collection truck, and the positioning device is associated with the type of garbage collected by the smart garbage collection truck.

[0062] Specifically, the intelligent garbage collection vehicle can navigate autonomously and includes a solar power supply system and a shock absorption system. The solar power supply system integrates solar panels as the energy supply of the electronic control device, promotes the use of clean energy, reduces dependence on traditional energy, and reduces the carbon footprint of the entire system. The shock absorption system can ensure the stability and carrying capacity of the unmanned vehicle on the sidewalk, and can drive smoothly even on uneven roads.

[0063] It should be noted that the types of garbage to be recycled by the garbage recycling device include recyclables, hazardous waste, wet garbage (kitchen waste) and dry garbage (other garbage), etc., which are determined according to the local garbage classification standards, and each type of garbage is uniquely coded. The code can be in the form of numbers, letters, or a combination of numbers and letters to facilitate system identification and processing.

[0064] The data acquisition and transmission unit 2 is used to acquire the capacity status data of different types of garbage in the garbage recycling device according to the configured sensors, and transmit the capacity status data to the cloud platform through the Internet of Things;

[0065] It should be noted that the sensor monitors the state changes of the garbage in the trash can in real time through non-contact methods (such as ultrasound, infrared, etc.) and converts the collected data into electrical signals. Using the Internet of Things communication technology, the data is transmitted to the cloud platform through the wireless network. The cloud platform has powerful data processing and storage capabilities, and can receive and store the capacity status data transmitted from the sensor in real time.

[0066] The capacity warning time prediction unit 3 is used to predict the capacity warning time of different types of garbage in the garbage recycling device through the growth function analysis method based on the capacity status data of different types of garbage;

[0067] As a preferred implementation, based on the capacity status data of different types of garbage, the capacity warning time of different types of garbage in the garbage recycling device is predicted by the growth function analysis method, including:

[0068] Collecting capacity status data of different types of garbage in the garbage collection device within a preset time period;

[0069] Specifically, the preset time period may be one hour, two hours, three hours, etc.

[0070] Setting target capacity thresholds for recycling different types of garbage based on attribute parameters of the garbage recycling device;

[0071] Specifically, by analyzing the attribute parameters of the garbage recycling device, including the volume of the garbage bin, garbage compression ratio, garbage density, etc., according to actual needs, a suitable target capacity threshold is set for each type of garbage. The target capacity threshold should not only meet the needs of garbage recycling, but also avoid overloading the garbage bin or wasting resources.

[0072] A capacity growth function of garbage in a garbage collection device is constructed according to the capacity status data, and the capacity warning time of different types of garbage in the garbage collection device is predicted based on the capacity growth function and the target capacity threshold.

[0073] As a preferred implementation, constructing a capacity growth function of garbage in a garbage collection device according to capacity status data, and predicting the capacity warning time of different types of garbage in the garbage collection device based on the capacity growth function and the target capacity threshold value includes:

[0074] Taking time as the independent variable and garbage capacity as the dependent variable, the capacity growth function of garbage in the garbage recycling device is established by linear regression method.

[0075] Specifically, it is assumed that there is a linear relationship between the growth of garbage capacity and time, that is, the change of garbage capacity over time can be approximated by a straight line. Let the garbage capacity be Y and the time be X, then the linear regression model can be expressed as: Y = aX + b;

[0076] Among them, a is the slope, which represents the rate of change of garbage capacity over time; b is the intercept, which represents the garbage capacity at the initial moment.

[0077] The parameters of the linear regression model are solved based on the collected data using parameter estimation methods such as the least squares method. The goal of the least squares method is to find a straight line that minimizes the sum of the distances between the straight line and all data points (i.e., the residual sum of squares), thereby obtaining the best fitting effect.

[0078] According to the capacity growth function, calculate the capacity growth rate of different types of garbage in the garbage recycling device;

[0079] As a preferred implementation, according to the capacity growth function, calculating the capacity growth rate of different types of garbage in the garbage recycling device includes:

[0080] According to the capacity growth function, the difference between the garbage capacity data corresponding to the last unit time in the preset time period and the garbage capacity data corresponding to the earliest unit time is calculated;

[0081] Determining the number of time units included in the preset time period;

[0082] Divide the calculated garbage capacity difference by the quantity per unit time to get the garbage capacity growth rate per unit time.

[0083] According to the capacity growth rate and the target capacity threshold, the capacity warning time when different types of garbage in the garbage recycling device reach the target capacity threshold is determined.

[0084] As a preferred implementation, according to the capacity growth rate and the target capacity threshold, determining the capacity warning time for different types of garbage in the garbage recycling device to reach the target capacity threshold includes:

[0085] The garbage capacity data corresponding to the last unit time in the preset time period is used as the current garbage capacity;

[0086] Calculate the difference between the target capacity threshold and the current garbage capacity to obtain the capacity demand values ​​of different types of garbage in the garbage collection device to reach the target capacity threshold;

[0087] According to the capacity demand value and the capacity growth rate, the capacity demand time for different types of garbage in the garbage recycling device to reach the target capacity threshold is calculated, and the capacity demand time is used as the capacity warning time.

[0088] Specifically, the calculated garbage capacity difference is divided by the quantity per unit time to obtain the garbage capacity growth rate per unit time.

[0089] The recycling route time prediction unit 4 is used to obtain the location information of the intelligent garbage collection vehicle according to the configured positioning device, and dynamically analyze the garbage collection route and recycling time of the intelligent garbage collection vehicle through the path optimization algorithm in combination with the capacity warning time of different types of garbage in the garbage collection device;

[0090] As a preferred implementation, the location information of the intelligent garbage collection vehicle is obtained according to the configured positioning device, and combined with the capacity warning time of different types of garbage in the garbage collection device, the garbage collection route and collection time of the intelligent garbage collection vehicle are dynamically analyzed through the path optimization algorithm, including:

[0091] Obtain information about all garbage collection devices that need to be emptied, and establish a garbage collection task set based on the capacity warning time of the garbage collection devices;

[0092] Specifically, by obtaining the location, garbage type and current capacity status of all garbage collection devices, when the capacity of a garbage collection device reaches the warning threshold, a garbage collection task is automatically generated, and these tasks are aggregated into a task set.

[0093] Based on the positioning device, the location data of each smart garbage collection vehicle is obtained in real time, and the garbage collection service area of ​​the smart garbage collection vehicle is established;

[0094] Specifically, high-precision positioning equipment, such as GPS or Beidou navigation system, is installed on each smart garbage collection truck. The service area of ​​the garbage collection truck can be defined according to the geographical boundaries of the city or a specific area. It can be the administrative division of the entire city, or a smaller community or specific area.

[0095] As a preferred implementation, based on the positioning device, the location data of each smart garbage collection vehicle is obtained in real time, and the garbage collection service area of ​​the smart garbage collection vehicle is established, including:

[0096] Determine the service boundary of garbage collection based on the location information of the garbage collection device;

[0097] Deploy a base station matrix at the service boundary of garbage collection, and use the positioning equipment on the smart garbage collection vehicle to obtain the location data of the smart garbage collection vehicle;

[0098] According to the garbage collection type and location data of the smart garbage collection truck, the garbage collection service area of ​​each smart garbage collection truck is determined.

[0099] Specifically, the location information of all garbage collection devices is collected, including geographic coordinates such as longitude and latitude. Based on this location information, a reasonable service boundary is delineated using geographic information system technology. This boundary should include all garbage collection devices that need service. Within the delineated service boundary, a series of base stations are deployed. These base stations can be fixed wireless communication devices that are used to receive and transmit signals from positioning devices on smart garbage collection vehicles. Positioning devices such as GPS receivers or Beidou navigation systems are installed on each smart garbage collection vehicle. These positioning devices should be compatible with the base station matrix and be able to send location data to the base station in real time.

[0100] By analyzing the types of garbage collected by smart garbage collection vehicles, such as recyclables, hazardous waste, wet garbage (kitchen waste), dry garbage (other garbage), etc., and combining the location information of garbage recycling devices and the location data of smart garbage collection vehicles, a specific garbage recycling service area is defined for each smart garbage collection vehicle using GIS technology.

[0101] Based on the garbage collection service area of ​​the intelligent garbage collection truck, the optimal garbage collection route and collection time of each intelligent garbage collection truck are planned through the path optimization algorithm according to the garbage collection task set.

[0102] As a preferred implementation, based on the garbage collection service area of ​​the intelligent garbage collection vehicle, according to the garbage collection task set, the optimal garbage collection route and collection time of each intelligent garbage collection vehicle are planned by the path optimization algorithm, including:

[0103] Based on the garbage collection service area of ​​the intelligent garbage collection vehicle, a garbage collection device that each intelligent garbage collection vehicle needs to collect garbage is selected from the garbage collection task set;

[0104] It should be noted that, first, it is necessary to confirm whether each garbage collection device is located within the service area of ​​a certain intelligent garbage collection vehicle, which can be achieved by comparing the location information of the garbage collection device with the service area boundary of the intelligent garbage collection vehicle.

[0105] Among them, smart garbage collection trucks are usually designed to collect specific types of garbage. When selecting a garbage recycling device, it is necessary to ensure that the type of garbage it collects matches the collection type of the smart garbage collection truck.

[0106] Based on the basic information of each intelligent garbage collection vehicle, the location information of the garbage collection device, the garbage collection time and the geographical information of the garbage collection service area, a route optimization model is constructed;

[0107] Specifically, building a path optimization model includes the following steps:

[0108] Define model parameters, including vehicle information, garbage collection device information, service area information, and time information;

[0109] Determine the objective function. The goal of a route optimization model is usually to minimize the total travel distance, total travel time, or total cost.

[0110] Establish constraints, including:

[0111] Capacity constraints ensure that each smart garbage collection vehicle does not exceed its load capacity when performing tasks.

[0112] Time constraints ensure that the smart garbage collection truck can complete the garbage collection task within the specified time, taking into account factors such as traffic conditions and garbage dumping time.

[0113] Route constraints ensure that smart garbage collection vehicles follow the prescribed routes and avoid entering prohibited areas or violating traffic regulations.

[0114] Service area constraint: Ensure that each smart garbage collection vehicle only performs tasks within its service area.

[0115] According to the objective function and constraints, a mathematical model is constructed. This model is usually an integer programming or mixed integer programming problem, which can be modeled using graph theory, network flow and other theories. For example, the locations of garbage recycling devices and smart garbage collection vehicles can be regarded as nodes in the graph, and the roads can be regarded as edges, and the weight of the edges represents the driving distance or time.

[0116] The constructed path optimization model is solved using a genetic algorithm to obtain the optimal garbage collection route and time for each intelligent garbage collection vehicle.

[0117] It should be noted that the use of genetic algorithms to solve the path optimization problem of intelligent garbage collection vehicles involves multiple steps, including coding scheme design, initial population generation, fitness function evaluation, genetic operation execution, and iterative optimization. Each individual in the population represents a possible path solution. The path coding is formed by assigning unique numbers to garbage collection devices and sorting them; the initial population is generated randomly or heuristically; the fitness function is designed to consider the path length, time, recycling volume, and load restrictions; selection, crossover, and mutation operations are performed to optimize the path; after iterating until the stop condition is met, the optimal path solution is selected.

[0118] The control execution unit 5 is used to control the intelligent garbage collection vehicle to execute garbage collection based on the garbage collection route and collection time of the intelligent garbage collection vehicle.

[0119] Specifically, the optimized garbage collection route and collection time are assigned to each smart garbage collection vehicle, and the task information is sent to the vehicle system of each smart garbage collection vehicle. The task information includes the route, schedule, location and type of the target garbage collection device, etc. The smart garbage collection vehicle starts the automatic driving system according to the sent task information and automatically navigates to the first garbage collection device according to the planned route.

[0120] The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things also includes a garbage recycling device for realizing garbage recycling. The garbage recycling device consists of a garbage bin main body 6 arranged on the ground and a pull-out placement rack 7 located inside the garbage bin main body 6.

[0121] In summary, with the help of the above technical solutions of the present invention, the present invention uses sensor technology to monitor the garbage level in real time, and realizes rapid response and processing through wireless networks. Through intelligent monitoring and automatic collection, it reduces the cost of manpower and material resources, improves the garbage processing speed, reduces the cleaning cost, and reduces the environmental pollution caused by garbage overflow. Based on intelligent urban garbage management, it can improve the overall level of urban management and the quality of life of residents. The present invention uses linear regression method to establish a garbage capacity growth function, combined with positioning equipment and path optimization algorithm, it can realize dynamic monitoring and intelligent scheduling of intelligent garbage collection vehicles, improve the accuracy and efficiency of garbage collection, and obtain the location data of intelligent garbage collection vehicles in real time. Establishing a garbage recycling service area can ensure the coverage and timeliness of garbage collection services and improve citizens' satisfaction with garbage collection services.

[0122] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code.

[0123] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things, characterized in that: The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things includes: an attribute configuration unit, a data acquisition and transmission unit, a capacity warning time prediction unit, a recycling route time prediction unit and a control execution unit; The attribute configuration unit is used to configure the attribute information of the sensor and the positioning device respectively based on the type of recycled garbage; The data acquisition and transmission unit is used to acquire the capacity status data of different types of garbage in the garbage recycling device according to the configured sensors, and transmit the capacity status data to the cloud platform through the Internet of Things; The capacity warning time prediction unit is used to predict the capacity warning time of different types of garbage in the garbage recycling device through a growth function analysis method based on the capacity status data of different types of garbage; The recycling route time prediction unit is used to obtain the location information of the intelligent garbage collection vehicle according to the configured positioning device, and dynamically analyze the garbage collection route and recycling time of the intelligent garbage collection vehicle through a path optimization algorithm in combination with the capacity warning time of different types of garbage in the garbage collection device; The control execution unit is used to control the intelligent garbage collection vehicle to execute garbage collection based on the garbage collection route and collection time of the intelligent garbage collection vehicle.

2. According to claim 1, the intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things is characterized in that: The attribute information of configuring the sensor and the positioning device respectively based on the type of recycled garbage includes: Obtain the type of garbage to be recycled by the garbage recycling device, and encode the type of garbage to be recycled according to the type of garbage; A sensor for detecting the garbage collection capacity is configured on the garbage collection device, and the sensor is associated with the type of garbage collected by the garbage collection device; A positioning device for position monitoring is configured on the smart garbage collection truck, and the positioning device is associated with the type of garbage collected by the smart garbage collection truck.

3. According to the Internet of Things-based intelligent environmentally friendly garbage recycling and processing system of claim 1, it is characterized in that: The method of predicting the capacity warning time of different types of garbage in the garbage recycling device by the growth function analysis method based on the capacity status data of different types of garbage includes: Collecting capacity status data of different types of garbage in the garbage collection device within a preset time period; Setting target capacity thresholds for recycling different types of garbage based on attribute parameters of the garbage recycling device; A capacity growth function of garbage in a garbage collection device is constructed according to the capacity status data, and the capacity warning time of different types of garbage in the garbage collection device is predicted based on the capacity growth function and the target capacity threshold.

4. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 3 is characterized in that: The method of constructing a capacity growth function of garbage in the garbage collection device according to the capacity status data, and predicting the capacity warning time of different types of garbage in the garbage collection device based on the capacity growth function and the target capacity threshold comprises: Taking time as the independent variable and garbage capacity as the dependent variable, the capacity growth function of garbage in the garbage recycling device is established by linear regression method. According to the capacity growth function, calculate the capacity growth rate of different types of garbage in the garbage recycling device; According to the capacity growth rate and the target capacity threshold, the capacity warning time when different types of garbage in the garbage recycling device reach the target capacity threshold is determined.

5. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 4 is characterized in that: Calculating the capacity growth rate of different types of garbage in the garbage collection device according to the capacity growth function includes: According to the capacity growth function, the difference between the garbage capacity data corresponding to the last unit time in the preset time period and the garbage capacity data corresponding to the earliest unit time is calculated; Determining the number of time units included in the preset time period; Divide the calculated garbage capacity difference by the quantity per unit time to get the garbage capacity growth rate per unit time.

6. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 4 is characterized in that: Determining the capacity warning time when different types of garbage in the garbage collection device reach the target capacity threshold according to the capacity growth rate and the target capacity threshold includes: The garbage capacity data corresponding to the last unit time in the preset time period is used as the current garbage capacity; Calculate the difference between the target capacity threshold and the current garbage capacity to obtain the capacity demand values ​​of different types of garbage in the garbage collection device to reach the target capacity threshold; According to the capacity demand value and the capacity growth rate, the capacity demand time for different types of garbage in the garbage recycling device to reach the target capacity threshold is calculated, and the capacity demand time is used as the capacity warning time.

7. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 1 is characterized in that: The method of obtaining the location information of the intelligent garbage collection vehicle according to the configured positioning device, and combining the capacity warning time of different types of garbage in the garbage collection device, and dynamically analyzing the garbage collection route and collection time of the intelligent garbage collection vehicle through the path optimization algorithm includes: Obtain information about all garbage collection devices that need to be emptied, and establish a garbage collection task set based on the capacity warning time of the garbage collection devices; Based on the positioning device, the location data of each smart garbage collection vehicle is obtained in real time, and the garbage collection service area of ​​the smart garbage collection vehicle is established; Based on the garbage collection service area of ​​the intelligent garbage collection truck, the optimal garbage collection route and collection time of each intelligent garbage collection truck are planned through the path optimization algorithm according to the garbage collection task set.

8. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 7 is characterized in that: The positioning device is used to obtain the location data of each intelligent garbage collection vehicle in real time, and the garbage collection service area of ​​the intelligent garbage collection vehicle is established, including: Determine the service boundary of garbage collection based on the location information of the garbage collection device; Deploy a base station matrix at the service boundary of garbage collection, and use the positioning equipment on the smart garbage collection vehicle to obtain the location data of the smart garbage collection vehicle; According to the garbage collection type and location data of the smart garbage collection truck, the garbage collection service area of ​​each smart garbage collection truck is determined.

9. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 7 is characterized in that: The garbage collection service area based on the intelligent garbage collection vehicle plans the optimal garbage collection route and collection time of each intelligent garbage collection vehicle through a path optimization algorithm according to the garbage collection task set, including: Based on the garbage collection service area of ​​the intelligent garbage collection vehicle, a garbage collection device that each intelligent garbage collection vehicle needs to collect garbage is selected from the garbage collection task set; Based on the basic information of each intelligent garbage collection vehicle, the location information of the garbage collection device, the garbage collection time and the geographical information of the garbage collection service area, a route optimization model is constructed; The constructed path optimization model is solved using a genetic algorithm to obtain the optimal garbage collection route and time for each intelligent garbage collection vehicle.

10. The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things according to claim 1 is characterized in that: The intelligent environmentally friendly garbage recycling and processing system based on the Internet of Things also includes a garbage recycling device for realizing garbage recycling, and the garbage recycling device consists of a garbage bin main body arranged on the ground and a pull-out placement rack located inside the garbage bin main body.

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