Livestock and poultry manure treatment internet of things platform and livestock and poultry manure treatment method

Abstract

The invention provides a livestock and poultry manure treatment Internet of Things platform and a livestock and poultry manure treatment method. The platform comprises a data sensing layer, a data transmission layer and a data processing layer, the data sensing layer is used for collecting data information of a source end, a transportation end and a processing end of livestock and poultry manure; the data transmission layer is used for transmitting the data information of the source end, the transportation end and the processing end to the data processing layer; the data processing layer is used for generating a collection order, a transportation order and a receiving order based on the data information of the source end, the transportation end and the processing end, and acquiring collection vehicle scheduling resource data, transportation vehicle scheduling resource data and processing end scheduling resource data; and inputting the collection order, the transportation order, the receiving order, the collection vehicle scheduling resource data, the transportation vehicle scheduling resource data and the processing end scheduling resource data into a scheduling model for matching to obtain a collection scheduling result, a transportation scheduling result and a processing scheduling result.

Description

Technical Field

[0001] The present invention relates to the field of environmental protection technology, and in particular to a livestock and poultry manure treatment control system and a livestock and poultry manure treatment method. Background Art

[0002] Livestock and poultry manure is an important part of organic waste. Livestock and poultry manure has the characteristics of large emission, scattered distribution and strong pollution. If the collection and transportation of livestock and poultry manure is not handled properly, it will have a bad impact on the environment and human health, and it is very easy to cause livestock and poultry infectious diseases and parasitic diseases, and even cause zoonotic infectious diseases. With the advancement of urban and rural development planning, the collection, transportation and treatment of livestock and poultry manure has received widespread attention.

[0003] Livestock and poultry farms lack appropriate supporting technologies in source control and processing, resulting in high technology search costs, high operating costs, and high risks in technology adoption. The supporting transformation costs of source control facilities and manure collection equipment are high, which increases the economic burden of farms. The monitoring system for returning manure to the fields is imperfect, the monitoring system is not sound, and there is a lack of information-based supervision and service means, making it difficult to control the quality and utilization of manure.

[0004] In order to effectively help solve the problem of livestock and poultry breeding pollution, it is of great practical significance to study a method to optimize and improve the livestock and poultry manure collection and treatment system. In the existing technology, there is a technical problem that the collection and treatment of livestock and poultry manure is not accurate enough, which leads to poor collection and treatment of livestock and poultry manure. Summary of the invention

[0005] The present invention provides an Internet of Things platform for livestock and poultry manure treatment and a method for livestock and poultry manure treatment, which are used to solve the defects of the prior art in that the collection and transportation and treatment of livestock and poultry manure are not accurate enough and the collection and transportation and treatment effect is not good.

[0006] The present invention provides an Internet of Things platform for livestock and poultry manure treatment, comprising: a data perception layer, a data transmission layer and a data processing layer; The data perception layer is used to collect data information on the source, transportation and treatment of livestock and poultry manure; The data transmission layer is used to transmit data information from the source end, the transportation end and the processing end to the data processing layer; The data processing layer is used to generate collection orders, transport orders and receiving orders based on the data information of the source end, the transportation end and the processing end, and obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; the collection order, transport order and receiving order are matched with the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data input into the scheduling model to obtain the collection scheduling results, transportation scheduling results and processing scheduling results.

[0007] The data information at the source end includes the location of the farm, the scale of farming, the type of farming, the method of manure cleaning, the amount of manure produced and / or the characteristics of manure composition; The data information on the transport side includes the vehicle type, license plate number, carrier, transport time, transport location, transport weight and / or transport process information of the manure transport vehicle; Among them, the data information at the processing end includes the incoming material location, incoming material quantity, incoming material type, transport vehicle, processing end receiving quantity, factory processing flow and / or resource utilization data.

[0008] Among them, the collection vehicle dispatching resource data and the transport vehicle dispatching resource data respectively include the transport vehicle, the carrier, the transport time, the transport location, the transported garbage weight and the transport process.

[0009] The scheduling model further includes a data input layer, a resource matching layer, a resource allocation layer and an information output layer; Data input layer, input scheduling resource data and collection order, transportation order, and receiving order; Resource matching layer, matching the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer allocates and analyzes the matching information to obtain collection scheduling results, transportation scheduling results, and processing scheduling results; The information output layer will output the collection scheduling results, transportation scheduling results and processing scheduling results.

[0010] The collected scheduling results include resource adaptability evaluation and target resource matching list; the data processing layer is also used for: Determine the initial collection scheduling result based on the target resource matching list; Conduct real-time status monitoring of the initial collection scheduling results to obtain the operating status of the collection resources; When there are conflicting factors in the running status of the collection resources, the initial collection scheduling result is reassigned and corrected based on the target resource matching list to obtain the final collection scheduling result.

[0011] Among them, the data processing layer is also used for: Monitor the status of transport vehicles in real time to obtain the operating status of transport resources; When there are abnormal factors in the operating status of transportation resources, the initial transportation scheduling result is corrected by resource redispatching based on the target vehicle resource matching list to obtain the final transportation scheduling result, which is output through the output layer of the scheduling model.

[0012] Among them, the data processing layer is also used for: According to the final collection and dispatch results and the final transportation and dispatch results, the target livestock and poultry manure is collected and transported in a closed loop to obtain processing data information; Perform data accounting based on the data information at the source, transportation and processing ends to obtain data accounting results and resource utilization data; The data ratio of resource utilization data and source data information is used to generate the waste resource reuse effect coefficient.

[0013] The present invention also provides a method for treating livestock and poultry excrement, comprising: Step 1: Collect data information on the source, transportation and treatment of livestock and poultry manure; Step 2: Transmit data information between the source end, the transport end and the processing end; Step 3: Generate a collection order, a transport order and a receiving order based on the data information of the source end, the transport end and the processing end, and obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; The collection order, transport order and receiving order are matched with the collection vehicle scheduling resource data, transport vehicle scheduling resource data and processing end scheduling resource data into the scheduling model to obtain the collection scheduling results, transportation scheduling results and processing scheduling results.

[0014] The scheduling model in step 3 includes a data input layer, a resource matching layer, a resource allocation layer, and an information output layer; Data input layer, input scheduling resource data and collection order, transportation order, and receiving order; Resource matching layer, matching the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer allocates and analyzes the matching information to obtain collection scheduling results, transportation scheduling results, and processing scheduling results; The information output layer will output the collection scheduling results, transportation scheduling results and processing scheduling results.

[0015] The present invention establishes an Internet of Things platform data perception system from the source end to the processing terminal, collects and obtains the data information required to be collected from the source section to the processing terminal, and comprehensively solves the technical problem that the collection, transportation and treatment of livestock and poultry manure and sewage in the prior art are insufficiently accurate, thereby resulting in poor treatment effect of livestock and poultry manure and sewage; through system data analysis, the collection, transportation and treatment scheduling management of manure and sewage is adaptive, timely and efficient, the accuracy of the collection and transportation and treatment of livestock and poultry manure and sewage is improved, the effect of quality control of the collection and transportation and treatment of livestock and poultry manure and sewage is improved, and the closed-loop precise control of the entire chain of manure and sewage emission, collection, transportation and treatment of target emission sources is achieved, greatly improving the overall treatment level of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 It is a schematic diagram of an Internet of Things platform for livestock and poultry manure treatment provided by the present invention.

[0018] Figure 2 It is a schematic diagram of the scheduling model provided by the present invention.

[0019] Figure 3 The present invention is a schematic flow chart of a method for treating livestock and poultry manure. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Combine the following Figure 1-Figure 3 The present invention describes an Internet of Things platform for livestock and poultry manure treatment and a method for livestock and poultry manure treatment.

[0022] The present invention provides an Internet of Things platform for livestock and poultry manure treatment, comprising: a data perception layer, a data transmission layer and a data processing layer; The data perception layer is used to collect data information on the source, transportation and treatment of livestock and poultry manure; The data transmission layer is used to transmit data information from the source end, the transportation end and the processing end to the data processing layer; The data processing layer is used to generate collection orders, transport orders and receiving orders based on the data information of the source end, the transportation end and the processing end, and obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; the collection order, transport order and receiving order are matched with the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data input into the scheduling model to obtain the collection scheduling results, transportation scheduling results and processing scheduling results.

[0023] The platform of the present invention improves the accuracy of the collection, transportation and treatment of livestock and poultry manure from the source end to the treatment end, supervises the discharge of livestock and poultry manure, and manages the collection, transportation and dispatching in a timely and efficient manner, thereby realizing intelligent and accurate collection and transportation treatment, and improving the collection, transportation and treatment quality of livestock and poultry manure.

[0024] Among them, the data information of the source end, the transportation end and the processing end are matched with the collection order, the transportation order and the receiving order file templates respectively to obtain the collection order, the transportation order and the receiving order.

[0025] Among them, the data information at the source end includes the location of the farm, the scale of farming, the type of farming, the method of manure cleaning, the amount of manure generated and / or the characteristics of the manure composition.

[0026] Among them, the location of the farm includes the specific address of the farm, such as the province (municipality directly under the Central Government, autonomous region), city (prefecture-level city, league), county (city, district, banner), township (town) and village where the farm is located; the location of the farm also includes the route information required to travel to the farm, the location of the farm entrance, the storage location of livestock and poultry manure to be processed in the farm, etc.

[0027] Among them, breeding scale includes the number of animals slaughtered and the number of animals on hand.

[0028] Among them, the manure cleaning methods include manual manure cleaning, mechanical manure cleaning, water flushing manure cleaning, water soaking manure and / or fermentation bed, etc.

[0029] Among them, the characteristics of manure composition include organic matter content, nitrogen (N) content, phosphorus (P) content, potassium (K) content; heavy metal content, such as arsenic (As), copper (Cu), zinc (Zn), chromium (Cr), etc.; antibiotic residues, such as tetracycline antibiotics, etc.; malodorous gas content, such as ammonia (NH3), hydrogen sulfide (H2S), volatile fatty acids (VFAs), p-cresol, etc.; greenhouse gas content, such as methane (CH4), nitrous oxide (N2O), etc.; salt content; microbial content, etc.

[0030] Among them, the data information on the transportation end includes the vehicle type, license plate number, carrier, transportation time, transportation location, transportation weight and / or transportation process information of the manure transport vehicle.

[0031] Among them, vehicle types include box-type livestock and poultry manure transport trucks, tank-type livestock and poultry manure transport trucks, swing arm transport trucks, wingspan transport trucks, sewage suction trucks, etc.

[0032] Among them, the carrier includes the carrier’s identity, carrier qualifications, etc.

[0033] Among them, the carrying weight includes the carryable weight of the manure transport truck and the weight already carried by the manure transport truck.

[0034] Among them, the transportation process information includes the departure information of the manure and sewage transport vehicle, the arrival information of the manure and sewage transport vehicle, the route information of the manure and sewage transport vehicle, etc.

[0035] Among them, the data information at the processing end includes the incoming material location, incoming material quantity, incoming material type, transport vehicle, processing end receiving quantity, factory processing flow and / or resource utilization data.

[0036] Among them, the incoming material types include liquid manure, solid manure, water-flushed manure, water-soaked manure, and anaerobic treated manure.

[0037] Among them, the factory processing process includes solid-liquid separation, anaerobic fermentation, homogenization adjustment, biogas storage, aeration tank, sedimentation tank, further solid-liquid separation, composting, aerobic fermentation, odor treatment, etc.

[0038] Among them, the resource utilization data include the amount of livestock and poultry manure generated, nitrogen (N) generated, phosphorus (P) generated, biogas production ratio, compost utilization ratio, compost utilization ratio, biogas fertilizer utilization ratio, fertilizer and water utilization ratio, commercial organic fertilizer utilization ratio, bedding utilization ratio, substrate utilization ratio, etc.

[0039] Among them, the collection vehicle dispatching resource data and the transport vehicle dispatching resource data respectively include the transport vehicle, the carrier, the transport time, the transport location, the transported garbage weight and the transport process.

[0040] The data perception layer obtains the scheduling resource data, encrypts it and transmits it to the data processing layer for analysis through the data transmission layer, and establishes a scheduling resource database.

[0041] The scheduling model further includes a data input layer, a resource matching layer, a resource allocation layer and an information output layer; Data input layer, input scheduling resource data and collection order, transportation order, and receiving order; Resource matching layer, matching the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer allocates and analyzes the matching information to obtain collection scheduling results, transportation scheduling results, and processing scheduling results; The information output layer will output the collection scheduling results, transportation scheduling results and processing scheduling results.

[0042] The scheduling resource data and collection form, transportation form, and receiving form are input into the resource matching layer through the data input layer to obtain resource matching information; the resource matching information is allocated and analyzed through the resource allocation layer to collect scheduling results, transportation scheduling results, and processing scheduling results; the manure collection scheduling results are output as model output results through the information output layer.

[0043] The collected scheduling results include resource adaptability evaluation and target resource matching list; the data processing layer is also used for: Determine the initial collection scheduling result based on the target resource matching list; Conduct real-time status monitoring of the initial collection scheduling results to obtain the operating status of the collection resources; When there are conflicting factors in the running status of the collection resources, the initial collection scheduling result is reassigned and corrected based on the target resource matching list to obtain the final collection scheduling result.

[0044] Conflict factors include route conflicts, capacity conflicts, conflicts in livestock and poultry manure types, etc.

[0045] Among them, the data processing layer is also used for: Carry out real-time status monitoring of transport vehicles to obtain the operating status of transport resources; the real-time status includes the real-time vehicle status of the transport vehicle, the real-time status of the carrier, the real-time operating route, and the real-time operating location.

[0046] When there are abnormal factors in the operating status of transportation resources, the initial transportation scheduling result is corrected by resource redispatching based on the target vehicle resource matching list to obtain the final transportation scheduling result, which is output through the output layer of the scheduling model.

[0047] Abnormal factors include vehicle failure, abnormal operating route, abnormal operating position, abnormal health status of the carrier, the operating route of the carrier vehicle is impassable, or there is serious traffic jam on the operating route of the manure and sewage carrier vehicle corresponding to the initial transport scheduling result.

[0048] Resource reassignment corrections include reallocation of collection and transportation tasks, modification of operating routes, adjustment of collection and transportation sequence, etc.

[0049] Among them, the data processing layer is also used for: According to the final collection and dispatch results and the final transportation and dispatch results, the target livestock and poultry manure is collected and transported in a closed loop to obtain processing data information; Perform data accounting based on the data information at the source, transportation and processing ends to obtain data accounting results and resource utilization data; The data ratio of resource utilization data and source data information is used to generate the waste resource reuse effect coefficient. The waste resource reuse effect coefficient is an indicator to measure the efficiency and effect of waste treatment, including waste resource utilization rate and recycling rate. The waste resource utilization rate reflects the proportion of waste converted into energy or other useful substances after treatment, as well as the proportion of recycled waste in the total amount of waste.

[0050] The present invention also provides a method for treating livestock and poultry excrement, comprising: Step 1: Collect data information on the source, transportation and treatment of livestock and poultry manure; Step 2: Transmit data information between the source end, the transport end and the processing end; Step 3: Generate a collection order, a transport order and a receiving order based on the data information of the source end, the transport end and the processing end, and obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; The collection order, transport order and receiving order are matched with the collection vehicle scheduling resource data, transport vehicle scheduling resource data and processing end scheduling resource data into the scheduling model to obtain the collection scheduling results, transportation scheduling results and processing scheduling results.

[0051] The scheduling model in step 3 includes a data input layer, a resource matching layer, a resource allocation layer, and an information output layer; Data input layer, input scheduling resource data and collection order, transportation order, and receiving order; Resource matching layer, matching the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer allocates and analyzes the matching information to obtain collection scheduling results, transportation scheduling results, and processing scheduling results; The information output layer will output the collection scheduling results, transportation scheduling results and processing scheduling results.

[0052] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An Internet of Things platform for livestock and poultry manure treatment, characterized in that: include: Data perception layer, data transmission layer and data processing layer; The data perception layer is used to collect data information on the source, transportation and treatment of livestock and poultry manure; A data transmission layer, used for transmitting the data information of the source end, the transport end and the processing end to the data processing layer; The data processing layer is used to generate a collection order, a transport order and a receiving order based on the data information of the source end, the transportation end and the processing end, and obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; the collection order, the transport order and the receiving order are matched with the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data input into the scheduling model to obtain the collection scheduling result, the transportation scheduling result and the processing scheduling result.

2. The Internet of Things platform according to claim 1, characterized in that: The data information at the source end includes the location of the farm, the scale of breeding, the type of breeding, the method of manure cleaning, the amount of manure generated and / or the characteristics of the manure composition; the data information at the transportation end includes the vehicle type, license plate number, carrier, transportation time, transportation location, transportation weight and / or transportation process information of the manure transport vehicle; the data information at the processing end includes the incoming material point, incoming material quantity, incoming material type, carrier vehicle, processing end reception quantity, factory processing flow and / or resource utilization data.

3. The Internet of Things platform according to claim 1, characterized in that: The collection vehicle dispatching resource data and the transport vehicle dispatching resource data respectively include a transport vehicle, a transporter, a transport time, a transport location, a transported garbage weight and / or a transport process.

4. The Internet of Things platform according to claim 1, characterized in that: The scheduling model further includes a data input layer, a resource matching layer, a resource allocation layer and an information output layer; wherein, A data input layer, used to input the dispatch resource data and the collection order, transportation order, and receiving order; A resource matching layer, used to match the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer is used to allocate and analyze the matching information to obtain the collection scheduling result, transportation scheduling result and processing scheduling result; The information output layer is used to output the collection scheduling results, transportation scheduling results and processing scheduling results.

5. The Internet of Things platform according to claim 1, characterized in that: The collected scheduling results include resource adaptability evaluation and target resource matching list; the data processing layer is also used for: Determining an initial collection scheduling result according to the target resource matching list; Conduct real-time status monitoring of the initial collection scheduling results to obtain the operating status of the collection resources; When there are conflicting factors in the running status of the collection resources, the initial collection scheduling result is modified by resource reallocation based on the target resource matching list to obtain a final collection scheduling result.

6. The Internet of Things platform according to claim 1, characterized in that: The data processing layer is also used for: Performing real-time status monitoring on the transport vehicle to obtain the operating status of the transport resources; When there are abnormal factors in the operating status of the transportation resources, the initial transportation scheduling result is corrected by resource redispatching based on the target vehicle resource matching list to obtain the final transportation scheduling result, which is output through the output layer of the scheduling model.

7. The Internet of Things platform according to claim 1, characterized in that: The data processing layer is also used for: Performing closed-loop collection and transportation processing on the target livestock and poultry manure according to the final collection scheduling result and the final transportation scheduling result to obtain processing data information; Perform data calculation based on the data information of the source end, the transportation end and the processing end to obtain data calculation results and resource utilization data; The data ratio of the resource utilization data and the source data information is used to generate the waste resource reuse effect coefficient.

8. A method for treating livestock and poultry manure, characterized in that: include: Step 1: Collect data information on the source, transportation and treatment of livestock and poultry manure; Step 2, transmitting the data information of the source end, the transport end and the processing end; Step 3, based on the data information of the source end, the transportation end and the processing end, generate a collection order, a transport order and a receiving order, obtain the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data; input the collection order, the transport order and the receiving order with the collection vehicle scheduling resource data, the transport vehicle scheduling resource data and the processing end scheduling resource data into the scheduling model for matching, and obtain the collection scheduling result, the transportation scheduling result and the processing scheduling result.

9. The method according to claim 8, characterized in that In step 3, the scheduling model includes a data input layer, a resource matching layer, a resource allocation layer and an information output layer; wherein, Data input layer, inputting the dispatch resource data and the collection order, transportation order, and receiving order; A resource matching layer matches the dispatch resource data with the collection order, transportation order, and receiving order to obtain matching information; The resource allocation layer performs allocation and analysis on the matching information to obtain the collection scheduling result, transportation scheduling result and processing scheduling result; The information output layer outputs the collection scheduling results, transportation scheduling results and processing scheduling results.

10. The method according to claim 9, characterized in that The collected scheduling results include resource adaptability evaluation and target resource matching list; The step 3 also includes: Determining an initial collection scheduling result according to the target resource matching list; Conduct real-time status monitoring of the initial collection scheduling results to obtain the operating status of the collection resources; When there are conflicting factors in the running status of the collection resources, the initial collection scheduling result is modified by resource reallocation based on the target resource matching list to obtain a final collection scheduling result.

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