Grain logistics information tracking method and system based on Internet of Things

Abstract

The invention provides a grain logistics information tracking method and system based on the Internet of Things, and the method comprises the steps: firstly constructing a three-dimensional view model, namely a grain logistics information view model, according to the logistics information of a grain logistics vehicle, thereby enabling the visual observation of the logistics information of various attributes of different logistics vehicles from multiple dimensions in real time, and improving the real-time observation of the logistics information of different logistics vehicles. The display efficiency of the logistics information is improved, and the situation that the logistics attribute information can only be expressed or presented from a single dimension in forms or charts and the like is avoided. Secondly, on the basis of the grain logistics information view model, a sphere is constructed by taking the attribute value of each piece of logistics information as a radius, so that the real-time state of the logistics information with multiple attributes is intuitively displayed; whether the vehicle is in the abnormal state or not is judged based on the mass center of the plane where the sphere is located and the volume change of the sphere corresponding to the logistics information attribute value of the vehicle, vehicle abnormal state judgment based on the three-dimensional view is achieved, and the intuition and accuracy of abnormal information judgment are greatly improved.

Description

Technical Field

[0001] The present application relates to the technical field of food logistics information tracking, and in particular to a food logistics information tracking method based on the Internet of Things. Background Art

[0002] Developing modern grain logistics is a complex systems project, spearheaded by logistics information technology and integrating all aspects of grain distribution, including production, processing, storage, transportation, and trading. By modernizing grain logistics technology and equipment, networking grain logistics channels, and leveraging rapidly advancing modern information technology to establish a highly centralized grain logistics information platform, a truly modern grain logistics system can be truly built. The widespread application of IoT technology in grain logistics will undoubtedly drive the rapid development of the grain industry. From the perspective of IoT applications in logistics, the IoT can be divided into three components: real-time logistics information collection, logistics information transmission, and logistics information dissemination. The specific grain logistics tracking process can be categorized into tracking information on grain inbound, storage, outbound, transportation, processing, and sales.

[0003] In the prior art, document CN111199371A discloses a blockchain-based grain circulation traceability release and verification method and system. The method and system utilize the tamper-proof nature of blockchain technology to achieve secure traceability of each node through the blockchain; through grain quality traceability, grain production can be recorded, information can be queried, flow can be tracked, and quality can be traced. However, the grain circulation traceability in the above document focuses on achieving the accuracy and traceability of logistics information through blockchain technology. It is a solution that facilitates the tracing of logistics information after the completion of the grain logistics transportation link. Its logistics information recording and query methods are targeted at digital display methods such as data lists, and cannot achieve real-time display and real-time analysis of multi-dimensional logistics information during the grain logistics transportation process. Therefore, it is necessary to propose a grain logistics information tracking method based on the Internet of Things to solve the above problems. Summary of the Invention

[0004] In order to solve the technical problems in the prior art of grain logistics information tracking, such as the lack of intuitive display and analysis of multi-dimensional logistics information and the lack of accuracy and efficiency in logistics information analysis and early warning, the present invention provides a grain logistics information tracking method based on the Internet of Things, which includes the following steps: Step S1, obtaining multiple logistics track information and vehicle information of multiple grain logistics vehicles based on the Internet of Things, wherein the vehicle information includes at least grain type, grain weight, grain temperature and humidity, and grain loading and unloading information, and the logistics track information includes at least the vehicle's driving route and real-time speed; Step S2: constructing a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalizing the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and constructing a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis indicates the vehicle number, the positive direction of the y-axis indicates the various attributes of the vehicle logistics information array, and the positive direction of the z-axis indicates time; Step S3: identifying each attribute of the vehicle logistics information array at each unit coordinate point in the three-dimensional space of the grain logistics information view model based on each value of the normalized vehicle logistics information array, wherein each attribute is identified by constructing a sphere with the unit coordinate point in the three-dimensional space as the center and the attribute value corresponding to the unit coordinate point as the radius; Step S4, calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane at each unit time, and determining whether the centroid coordinates are offset from the geometric center by more than a first threshold. If so, executing step S5; otherwise, re-performing the calculation at each unit time; the geometric center is the geometric center of the planar figure enclosed by the spheres corresponding to the attribute values on the x0z plane. Step S5, obtaining the first sphere with the largest volume change among the spheres corresponding to the attribute values on the x0z plane from the previous unit time to the current unit time, and determining whether the change of the first sphere complies with the attribute value change rule corresponding to the current attribute. If not, highlighting the first sphere.

[0005] As a preferred embodiment, the vehicle logistics information array is constructed based on the logistics track information and vehicle information of each grain logistics vehicle, specifically including: Different logistics track information and vehicle information attribute information are configured at each identification position of the vehicle logistics information array, and the logistics track information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle.

[0006] As a preferred embodiment, calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located, and determining whether the centroid coordinates offset the geometric center is greater than a first threshold, specifically includes: Get the position and radius of the unit coordinate point of the sphere corresponding to each attribute value on the x0z plane of the same attribute. Assuming that all spheres on the current x0z plane are homogeneous spheres of the same material, calculate the coordinates of the center of mass of all spheres on the current x0z plane, and use the coordinates of the center of mass as the center of mass coordinates. The first threshold is updated every unit time, and it is determined whether the centroid coordinate offset geometric center is greater than the updated first threshold.

[0007] As a preferred embodiment, determining whether the change of the first spherical shape complies with the attribute value change rule corresponding to the current attribute further includes: If the first sphere identifies the vehicle's route, the route is divided into multiple sub-routes based on the vehicle's route and its transfer points. A determination is made as to whether the change in the first sphere conforms to a route compliance parameter corresponding to the current vehicle's route. The route compliance LF is calculated as follows: , Among them, LF represents the route compliance parameter, represents the total length of the i-th sub-route, Indicates the length of the ith sub-route traveled. Indicates the total length of the driving route. Indicates the total length of the remaining route, n indicates the number of sub-routes, and K indicates the scaling factor.

[0008] As a preferred embodiment, it also includes: If the first sphere identifies the grain loading and unloading information of the vehicle, then it is determined whether the change in the first sphere complies with the loading and unloading compliance parameter of the current vehicle based on the loading and unloading information of the plurality of transfer points; the loading and unloading compliance parameter ZXF is calculated as follows: , Among them, ZXF represents the loading and unloading compliance parameter, sh represents the loss value of the jth loading and unloading point, and represents the inbound and outbound weight of the current vehicle at the jth loading and unloading point, and Represents the scaling factor and correction coefficient.

[0009] As a preferred embodiment, it also includes: If the first sphere identifies the grain temperature information corresponding to the grain type of the vehicle, then based on the grain temperature information of the vehicle traveling on multiple sub-routes, it is determined whether the change in the first sphere meets the grain temperature compliance parameter of the current vehicle; the grain temperature compliance parameter TF is calculated as follows: , Among them, TF represents the grain temperature compliance parameter, T represents the preset grain transportation temperature, represents the average transport temperature measurement value of the i-th sub-route, Indicates the error value of the temperature sensor used for measurement, and Indicates the correction factor of the measured temperature and the correction factor of the temperature sensor, Indicates the grain temperature adjustment coefficient.

[0010] As a preferred embodiment, it also includes: If the first sphere identifies the real-time speed information of the vehicle, then it is determined whether the change of the first sphere conforms to the real-time speed compliance parameter of the current vehicle based on the multiple real-time speed information; the real-time speed compliance parameter VF is calculated as follows: , Among them, VF represents the real-time speed compliance parameter, V represents the preset reference speed, represents the detection speed at the i-th detection time point, n represents the number of detection time points, e represents a natural constant, Indicates the speed correction factor.

[0011] As another embodiment, the present invention provides a food logistics information tracking system based on the Internet of Things, the system comprising the following modules: A logistics information acquisition module is used to obtain multiple logistics track information and vehicle information of multiple grain logistics vehicles based on the Internet of Things. The vehicle information includes at least the type of grain, grain weight, grain temperature and humidity, and grain loading and unloading information. The logistics track information includes at least the vehicle's driving route and real-time speed. A grain logistics information view model construction module is used to construct a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalize the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and construct a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis indicates the vehicle number, the positive direction of the y-axis indicates the various attributes of the vehicle logistics information array, and the positive direction of the z-axis indicates time; a unit coordinate point identification module, configured to identify each attribute of the vehicle logistics information array at each unit coordinate point in the three-dimensional space of the grain logistics information view model based on each value of the normalized vehicle logistics information array, wherein each attribute is identified by constructing a sphere with the unit coordinate point in the three-dimensional space as the center and the attribute value of the attribute corresponding to the unit coordinate point as the radius; A centroid coordinate offset detection module is used to calculate the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane at intervals, and determine whether the centroid coordinate offset geometric center is greater than a first threshold. If so, the logistics information identification module is executed; otherwise, the calculation is repeated at intervals; the geometric center is the geometric center of the plane figure enclosed by the spheres corresponding to the attribute values on the x0z plane; The logistics information identification module is used to obtain the first sphere with the largest volume change among the spheres corresponding to each attribute value on the x0z plane from the previous unit time to the current unit time, and determine whether the change of the first sphere conforms to the attribute value change rule corresponding to the current attribute. If not, the first sphere is highlighted and identified.

[0012] As a preferred embodiment, the vehicle logistics information array is constructed based on the logistics track information and vehicle information of each grain logistics vehicle, specifically including: Different logistics track information and vehicle information attribute information are configured at each identification position of the vehicle logistics information array, and the logistics track information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle.

[0013] As a preferred embodiment, calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located, and determining whether the centroid coordinates offset the geometric center is greater than a first threshold, specifically includes: Get the position and radius of the unit coordinate point of the sphere corresponding to each attribute value on the x0z plane of the same attribute. Assuming that all spheres on the current x0z plane are homogeneous spheres of the same material, calculate the coordinates of the center of mass of all spheres on the current x0z plane, and use the coordinates of the center of mass as the center of mass coordinates. The first threshold is updated every unit time, and it is determined whether the centroid coordinate offset geometric center is greater than the updated first threshold.

[0014] As a preferred embodiment, determining whether the change of the first spherical shape complies with the attribute value change rule corresponding to the current attribute further includes: If the first sphere identifies the vehicle's route, the route is divided into multiple sub-routes based on the vehicle's route and its transfer points. A determination is made as to whether the change in the first sphere conforms to a route compliance parameter corresponding to the current vehicle's route. The route compliance LF is calculated as follows: , Among them, LF represents the route compliance parameter, represents the total length of the i-th sub-route, Indicates the length of the ith sub-route traveled. Indicates the total length of the driving route. Indicates the total length of the remaining route, n indicates the number of sub-routes, and K indicates the scaling factor.

[0015] As a preferred embodiment, it also includes: If the first sphere identifies the grain loading and unloading information of the vehicle, then it is determined whether the change in the first sphere complies with the loading and unloading compliance parameter of the current vehicle based on the loading and unloading information of the plurality of transfer points; the loading and unloading compliance parameter ZXF is calculated as follows: , Among them, ZXF represents the loading and unloading compliance parameter, sh represents the loss value of the jth loading and unloading point, and represents the inbound and outbound weight of the current vehicle at the jth loading and unloading point, and Represents the scaling factor and correction coefficient.

[0016] As a preferred embodiment, it also includes: If the first sphere identifies the grain temperature information corresponding to the grain type of the vehicle, then based on the grain temperature information of the vehicle traveling on multiple sub-routes, it is determined whether the change in the first sphere meets the grain temperature compliance parameter of the current vehicle; the grain temperature compliance parameter TF is calculated as follows: , Among them, TF represents the grain temperature compliance parameter, T represents the preset grain transportation temperature, represents the average transport temperature measurement value of the i-th sub-route, Indicates the error value of the temperature sensor used for measurement, and Indicates the correction factor of the measured temperature and the correction factor of the temperature sensor, Indicates the grain temperature adjustment coefficient.

[0017] As a preferred embodiment, it also includes: If the first sphere identifies the real-time speed information of the vehicle, then it is determined whether the change of the first sphere conforms to the real-time speed compliance parameter of the current vehicle based on the multiple real-time speed information; the real-time speed compliance parameter VF is calculated as follows: , Among them, VF represents the real-time speed compliance parameter, V represents the preset reference speed, represents the detection speed at the i-th detection time point, n represents the number of detection time points, e represents a natural constant, Indicates the speed correction factor.

[0018] As another embodiment, the present invention provides a food logistics information tracking device based on the Internet of Things, and the system executes the food logistics information tracking method based on the Internet of Things.

[0019] As another embodiment, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program executes the food logistics information tracking method based on the Internet of Things.

[0020] It can be seen that the present invention provides a method and system for tracking food logistics information based on the Internet of Things. First, the present invention constructs a three-dimensional view model, namely a food logistics information view model, based on the logistics information of food logistics vehicles, so that the logistics information of various attributes of different logistics vehicles can be intuitively observed in real time and visually from multiple dimensions, thereby improving the display efficiency of logistics information and avoiding the fact that tables or charts can only represent or present logistics attribute information from a single dimension. Secondly, on the basis of the food logistics information view model, a sphere is constructed based on the attribute value of each logistics information as the radius, thereby realizing the intuitive display of the real-time status of logistics information of various attributes. Based on the center of mass of the plane where the sphere is located corresponding to the attribute value of the vehicle's logistics information and the volume change of the sphere, it is judged whether the vehicle is in an abnormal state, thereby realizing the judgment of the vehicle's abnormal state based on the three-dimensional view, which greatly improves the intuitiveness and accuracy of the judgment of abnormal information. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments and the description of the prior art. 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 paying any creative work.

[0022] Figure 1 This is a schematic diagram showing the display effect of the grain logistics information view model of the present invention; Figure 2 It is a structural diagram of the food logistics information tracking system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0023] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0024] Example 1: The present invention provides a method for tracking food logistics information based on the Internet of Things, the method comprising the following steps: Step S1, based on the Internet of Things, multiple logistics track information and vehicle information of multiple grain logistics vehicles are obtained, wherein the vehicle information at least includes the type of grain, weight of grain, temperature and humidity of grain, and loading and unloading information of grain, and the logistics track information at least includes the driving route and real-time speed of the vehicle. It should be noted that, based on the Internet of Things, multiple logistics track information and vehicle information of multiple grain logistics vehicles are obtained, for example, the weight of grain loaded on the vehicle, temperature and humidity of grain, and other information are obtained respectively through the temperature and humidity sensors and pressure sensors of the Internet of Things terminals, the driving route information of the vehicle is obtained through GPS and Beidou positioning sensors, and the real-time speed information of the vehicle is obtained through the speed sensor. The type of grain can be obtained by manual input or image recognition, and the loading and unloading information of grain can be obtained by positioning, vehicle weight, and other methods, but it is not limited to the above-mentioned acquisition methods to obtain the vehicle information and the logistics track information in real time or at a fixed time. In addition, the present invention takes into account that grain logistics transportation is often in large quantities, and therefore obtains the logistics track information and vehicle information of each vehicle, and simultaneously realizes real-time tracking of multiple logistics vehicles.

[0025] Step S2, constructing a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalizing the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and constructing a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis identifies the vehicle number, the positive direction of the y-axis identifies the various attributes of the vehicle logistics information array, and the positive direction of the z-axis identifies the time; it should be noted that in order to realize the monitoring and tracking of each logistics vehicle, first, a vehicle logistics information array is constructed based on the logistics trajectory information and vehicle information of each grain logistics vehicle, the vehicle logistics information array can be updated regularly according to the data obtained by the above-mentioned Internet of Things sensors, thereby saving multiple vehicle logistics information arrays for each logistics vehicle for subsequent data processing and analysis; then, the vehicle logistics information arrays of all grain logistics vehicles are normalized based on the same attributes to obtain a normalized vehicle logistics information array. In order to facilitate normalization processing based on the same attributes, it is preferred to set the same identification bit and the number of identification bits for the vehicle logistics information array. For example, the vehicle logistics information array A1 = [grain type a01, grain weight a02, grain temperature and humidity a03, grain loading and unloading information a04, driving route / location a05, real-time speed a06], where A1 represents the vehicle logistics information array collected by vehicle A at the first time collection point, and B1 represents the vehicle logistics information array collected by vehicle B at the first time collection point. The collected vehicle logistics information array is B1 = [grain type b01, grain weight b02, grain temperature and humidity b03, grain loading and unloading information b04, driving route / location b05, real-time speed b06]. Based on this, the vehicle logistics information array of all grain logistics vehicles is normalized based on the same attributes. For example, for the real-time speed attribute information, a06 = 60km / h, b06 = 80km / h, and c06 = 70km / h, then the three are normalized. This will not be described in detail here. It should be noted that for non-numeric attributes, only the identification bit is required, and no normalization is required. For example, for grain type a01, grain type b01, and other grain type attribute information, it is only necessary to classify them in the identification bit, such as corn is identified as 1, wheat is identified as 2, and rice is identified as 3. Similarly, non-numeric attributes such as grain loading and unloading information and driving route do not need to be normalized. Only the identification bit is required. This will not be described in detail here. Finally, the grain logistics information view model is constructed based on all normalized vehicle logistics information arrays; Figure 1As shown, the food logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis identifies the vehicle number, the positive direction of the y-axis identifies the various attributes of the vehicle logistics information array, and the positive direction of the z-axis identifies time; the normalized logistics information array of each vehicle collected every unit time (for example, 1 minute) is identified in the three-dimensional view model, wherein the positive direction of the z-axis identifies time as a unit time (for example, 1 minute). For example, in Figure 1 In the yoz plane with x coordinate 0, the three coordinate points (a01, a02, a03) of the vehicle logistics information array corresponding to the first logistics vehicle are identified. Their meaning is that at time t=0, in vehicle A1, a01 identifies the type of grain transported by vehicle A1, a02 identifies the weight of grain transported by vehicle A1, and a03 identifies the temperature of grain transported by vehicle A1. Similarly, the coordinate points (a11, a12, a13) mean that at time t=1 (for example, 1 minute) in vehicle A1, a11 identifies the type of grain transported by vehicle A1, a12 identifies the weight of grain transported by vehicle A1, and a13 identifies the temperature of grain transported by vehicle A1. Vehicles B and C are identified in the three-dimensional coordinate system in a similar way, and as shown in the following example: Figure 1 As shown, no further details are given here. This enables the construction of the grain logistics information view model based on multiple attributes at different times and for different vehicles, thereby achieving the identification of multiple attributes of multiple vehicles and multi-dimensional information at different times on a single view, improving the efficiency of information identification and display, and avoiding the use of tables or charts that can only represent or present logistics attribute information from a single dimension. The three-dimensional view model can be constructed in existing three-dimensional view software such as CAD, Pro / E, or three-dimensional view plug-ins / components, and no further details are given here.

[0026] Step S3, according to each value of the normalized vehicle logistics information array, each attribute of each unit coordinate point in the three-dimensional space of the grain logistics information view model is identified, and the method of identifying each attribute is: constructing a sphere with the unit coordinate point in the three-dimensional space as the center of the circle and the attribute value of the attribute corresponding to the unit coordinate point as the radius; it should be noted that the present invention not only realizes the coordinate point identification of attribute information in the three-dimensional coordinate system by the above method, but also realizes the spherical volume identification based on the attribute value size of the coordinate point, which greatly increases the intuitiveness of the attribute identification. Specifically, the method of identifying each attribute is: constructing a sphere with the unit coordinate point in the three-dimensional space as the center of the circle and the attribute value of the attribute corresponding to the unit coordinate point as the radius, for example Figure 1 The coordinate point where a11 is shown is the center of the circle, and a sphere is constructed with the attribute value 0.5 of the attribute corresponding to the coordinate point as the radius; preferably, different colors can be rendered for different spheres according to the attribute category or vehicle identification, so that users can view it efficiently according to the three-dimensional view model.

[0027] Step S4, calculate the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located every unit time, and judge whether the centroid coordinate offset geometric center is greater than the first threshold value. If so, execute step S5, otherwise, re-execute the calculation at intervals of unit time; the geometric center is the geometric center of the plane figure enclosed by the spheres corresponding to the attribute values on the x0z plane; it should be noted that, since each x0z plane identifies the attribute values corresponding to the same attribute information of different vehicles at different times, and the attribute values are expressed by the radius / volume of the corresponding sphere, it is assumed that the density of each sphere is the same, for example, the density is 1kg / m3, so that the centroid formed by all spheres on each x0z plane can be used to judge the progress of time. Whether there is an abnormal change in attribute value caused by the centroid coordinate offset from the geometric center, specifically, the centroid coordinates of the sphere corresponding to each attribute value on the x0z plane where the same attribute is located are calculated every unit time (for example, 1 minute), and it is judged whether the centroid coordinate offset from the geometric center is greater than a first threshold. For example, at time t=1, the centroid coordinate O01 formed by the sphere corresponding to each attribute value of the coordinate point set [a01, b01, c01, a11, b11, c11] (the attribute corresponding to the attribute value can be any one of the aforementioned attributes or any one of the normalized attributes) is offset from the geometric center O1 where the above coordinate point set is located, and it is judged whether the degree of the above offset (i.e., the centroid distance) is greater than the preset first threshold, thereby realizing abnormal judgment of each attribute value. Alternatively, the abnormality judgment of the attribute value can also be performed by the degree of deviation of the above-mentioned centroid coordinate at the current moment from the centroid coordinate at the previous moment. For example, at time t=2, the centroid coordinate O02 formed by the sphere corresponding to each attribute value of the coordinate point set [a01, b01, c01, a11, b11, c11, a21, b21, c21] is compared with the degree of deviation (i.e., the centroid distance) of the centroid coordinate O02 at the current moment t=2 from the centroid coordinate O01 at the previous moment t=1 to see whether it is greater than the preset second threshold, thereby achieving a preliminary abnormality judgment of each attribute value. It can be seen that the present invention proposes a new method of realizing abnormality judgment of attribute values by using centroid coordinates composed of spherical volumes corresponding to numerical values, which improves the intuitiveness and flexibility of abnormality judgment of attribute values and is a method of abnormality judgment of attribute values that is completely different from the prior art.

[0028] Step S5: Obtain the first sphere with the largest volume change among the spheres corresponding to the attribute values on the x0z plane between the previous unit time and the current unit time, and determine whether the change in the first sphere complies with the attribute value change rule corresponding to the current attribute. If not, highlight the first sphere. It should be noted that, based on the above-mentioned attribute value abnormality determination, the first sphere with the largest volume change among the spheres corresponding to the attribute values on the x0z plane within a unit time is obtained, and a warning message is issued based on the first sphere with the largest volume change. Specifically, determine whether the change in the first sphere complies with the attribute value change rule corresponding to the current attribute. For example, if the current attribute is speed and the vehicle's current location is on a highway, the volume change of the sphere corresponding to the current attribute value is a decrease, and the volume of the first sphere with the largest volume change has decreased by more than 1 / 2 compared to the previous moment, while the attribute value change rule corresponding to the current attribute is a change of no more than 1 / 4, indicating that the vehicle speed has decreased significantly and the attribute value change corresponding to the current attribute does not comply with the preset change rule. In this case, the first sphere is highlighted, for example, by flashing or by a darker color line, thereby further determining abnormalities in each attribute value.

[0029] It can be seen that the present invention provides a method for tracking food logistics information based on the Internet of Things. First, the present invention constructs a three-dimensional view model, namely a food logistics information view model, based on the logistics information of food logistics vehicles, so that the logistics information of various attributes of different logistics vehicles can be intuitively observed in real time and visually from multiple dimensions, thereby improving the display efficiency of logistics information and avoiding the fact that tables or charts can only represent or present logistics attribute information from a single dimension. Secondly, on the basis of the food logistics information view model, a sphere is constructed based on the attribute value of each logistics information as the radius, thereby realizing the intuitive display of the real-time status of logistics information of various attributes. Based on the center of mass of the plane where the sphere is located corresponding to the attribute value of the vehicle's logistics information and the volume change of the sphere, it is judged whether the vehicle is in an abnormal state, thereby realizing the judgment of the vehicle's abnormal state based on the three-dimensional view, which greatly improves the intuitiveness and accuracy of the judgment of abnormal information.

[0030] As a preferred embodiment, the vehicle logistics information array is constructed based on the logistics track information and vehicle information of each grain logistics vehicle, specifically including: Different logistics track information and vehicle information attribute information are configured at each identification position of the vehicle logistics information array, and the logistics track information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle. It should be noted that, for example, the identification form of the vehicle logistics information array is [grain type, grain weight, grain temperature and humidity, grain loading and unloading information, driving route / location, real-time speed], and the logistics trajectory information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle. For example, at time t=1, the vehicle logistics information array A1=[grain type a01, grain weight a02, grain temperature and humidity a03, grain loading and unloading information a04, driving route / location a05, real-time speed a06], where A1 represents the vehicle logistics information array collected by vehicle A at the first time t=1 collection point; B1 represents the vehicle logistics information array collected by vehicle B at the first time collection point, and B1=[grain type b01, grain weight b02, grain temperature and humidity b03, grain loading and unloading information b04, driving route / location b05, real-time speed b06]; thereby obtaining the vehicle logistics information arrays of different vehicles at different times.

[0031] As a preferred embodiment, calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located, and determining whether the centroid coordinates offset the geometric center is greater than a first threshold, specifically includes: Obtain the position of the unit coordinate point of the sphere corresponding to each attribute value on the x0z plane of the same attribute and its radius, assuming that all spheres on the current x0z plane are homogeneous spheres of the same material, calculate the coordinates of the center of mass of all spheres on the current x0z plane, and use the coordinates of the center of mass as the center of mass coordinates; update the first threshold every unit time, and determine whether the center of mass coordinate offset from the geometric center is greater than the updated first threshold. It should be noted that, specifically, the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located are calculated every unit time (for example, 1 minute). It is assumed that all spheres on the current x0z plane are homogeneous spheres of the same material, for example, the density of the spheres is 1kg / m3, and it is determined whether the centroid coordinate offset of the geometric center is greater than the first threshold. For example, at time t=1, the centroid coordinates O01 formed by the spheres corresponding to the attribute values (the attribute values corresponding to the spheres can be any one of the aforementioned attributes or any one of the normalized attributes) of the coordinate point set [a01, b01, c01, a11, b11, c11] are offset from the geometric center O1 where the above-mentioned coordinate point set is located, and it is determined whether the degree of the above-mentioned offset (i.e., the centroid distance) is greater than the preset first threshold, thereby realizing abnormal judgment of each attribute value.

[0032] As a preferred embodiment, determining whether the change of the first spherical shape complies with the attribute value change rule corresponding to the current attribute further includes: If the first sphere identifies the vehicle's route, the route is divided into multiple sub-routes based on the vehicle's route and its transfer points. A determination is made as to whether the change in the first sphere conforms to a route compliance parameter corresponding to the current vehicle's route. The route compliance LF is calculated as follows: , Among them, LF represents the route compliance parameter, represents the total length of the i-th sub-route, Indicates the length of the ith sub-route traveled. Indicates the total length of the driving route. represents the total remaining route length, n represents the number of sub-routes, and K represents the scaling factor. The value of K can be set to a constant between 0 and 1 according to actual needs. Thus, when the vehicle attribute information is a driving route, the vehicle's driving route and its transfer points are divided into multiple sub-routes, reducing the granularity of the route and enabling refined management of driving route determination. Furthermore, by determining whether the change in the first sphere conforms to the route conformity parameter corresponding to the current vehicle's driving route, the route conformity parameter is used to quantify and refine the determination of the abstract and difficult-to-quantify vehicle driving route in a three-dimensional coordinate system. This improves the accuracy of driving route determination.

[0033] As a preferred embodiment, it also includes: If the first sphere indicates the grain loading and unloading information of the vehicle, then the change of the first sphere is determined based on the vehicle's driving route and the loading and unloading information of its transfer points to determine whether it complies with the loading and unloading compliance parameter of the current vehicle; the loading and unloading compliance parameter ZXF is calculated as follows: , Among them, ZXF represents the loading and unloading compliance parameter, sh represents the loss value of the jth loading and unloading point, and represents the inbound and outbound weight of the current vehicle at the jth loading and unloading point, m is the number of loading and unloading points, and represents the scaling factor and correction coefficient, The value range is greater than or equal to 1, but not too large. The preferred value range is [1,10). It can be set according to actual needs. The value range of is a number between 0 and 1. Therefore, when the vehicle attribute information is grain loading and unloading information, whether the change in the first spherical shape conforms to the current vehicle's loading and unloading compliance parameters is determined based on the vehicle's travel route and the loading and unloading information at its transfer points. This refines the judgment of the volume-variable spherical shape of the loading and unloading information changes in the three-dimensional coordinate system using the loading and unloading compliance parameters, thereby improving the accuracy of the identification and display of the loading and unloading information.

[0034] As a preferred embodiment, it also includes: If the first sphere identifies the grain temperature information corresponding to the grain type of the vehicle, then based on the grain temperature information of the vehicle traveling on multiple sub-routes, it is determined whether the change in the first sphere meets the grain temperature compliance parameter of the current vehicle; the grain temperature compliance parameter TF is calculated as follows: , Among them, TF represents the grain temperature compliance parameter, T represents the preset grain transportation temperature, represents the average transport temperature measurement value of the i-th sub-route, Indicates the error value of the temperature sensor used for measurement, and Indicates the correction factor of the measured temperature and the correction factor of the temperature sensor, which can be set according to actual needs and The value range is a value between 0 and 1; represents the grain temperature adjustment coefficient, with a value range of 1 or greater, but not too large, and a preferred range of [1, 5]. Therefore, if the vehicle's attribute information is grain temperature information corresponding to the type of grain being loaded, the grain temperature information of the vehicle traveling along multiple subroutes is used to determine whether the changes in the first sphere conform to the grain temperature compliance parameter of the current vehicle. The grain temperature compliance parameter is then used to intuitively display the changes in grain temperature information as a volume-variable sphere in a three-dimensional coordinate system, thereby improving the accuracy of grain temperature information identification and the intuitiveness of the display.

[0035] As a preferred embodiment, it also includes: If the first sphere identifies the real-time speed information of the vehicle, then it is determined whether the change of the first sphere conforms to the real-time speed compliance parameter of the current vehicle based on the multiple real-time speed information; the real-time speed compliance parameter VF is calculated as follows: , Among them, VF represents the real-time speed compliance parameter, V represents the preset reference speed, represents the detection speed at the i-th detection time point, n represents the number of detection time points, e represents a natural constant, represents a speed correction coefficient, and its value range is a value greater than or equal to 1, but should not be too large, and the preferred value range is [1, 8]. Thus, when the vehicle attribute information is real-time speed information, whether the change in the first sphere conforms to the real-time speed compliance parameter of the current vehicle is determined based on multiple pieces of real-time speed information. The change in speed information is then intuitively displayed as a volume-variable sphere in a three-dimensional coordinate system using the real-time speed compliance parameter, thereby improving the accuracy of speed information identification and the intuitiveness of the display.

[0036] As another embodiment, Figure 2 As shown, the present invention provides a food logistics information tracking system based on the Internet of Things, which includes the following modules: The logistics information acquisition module is used to obtain multiple logistics track information and vehicle information of multiple grain logistics vehicles based on the Internet of Things. The vehicle information includes at least the type of grain, weight of grain, temperature and humidity of grain, and loading and unloading information of grain. The logistics track information includes at least the driving route and real-time speed of the vehicle. It should be noted that, based on the Internet of Things, multiple logistics track information and vehicle information of multiple grain logistics vehicles are obtained. For example, the weight of grain loaded on the vehicle, temperature and humidity of grain, and other information are obtained through the temperature and humidity sensors and pressure sensors of the Internet of Things terminals. The driving route information of the vehicle is obtained through GPS and Beidou positioning sensors. The real-time speed information of the vehicle is obtained through the speed sensor. The type of grain can be obtained by manual input or image recognition. The loading and unloading information of grain can be obtained by positioning, vehicle weight, etc., but it is not limited to the above-mentioned acquisition methods to obtain the vehicle information and the logistics track information in real time or at a fixed time. In addition, the present invention takes into account that grain logistics transportation is often in large quantities. Therefore, the logistics track information and vehicle information of each vehicle are obtained, and real-time tracking of multiple logistics vehicles is achieved at the same time.

[0037] A grain logistics information view model construction module is used to construct a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalize the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and construct a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis identifies the vehicle number, the positive direction of the y-axis identifies the various attributes of the vehicle logistics information array, and the positive direction of the z-axis identifies the time; it should be noted that in order to realize the monitoring and tracking of each logistics vehicle, first, a vehicle logistics information array is constructed based on the logistics trajectory information and vehicle information of each grain logistics vehicle, and the vehicle logistics information array can be updated regularly according to the data obtained by the above-mentioned Internet of Things sensors, thereby saving multiple vehicle logistics information arrays for each logistics vehicle for subsequent data processing and analysis; then, the vehicle logistics information arrays of all grain logistics vehicles are normalized based on the same attributes to obtain To the normalized vehicle logistics information array, in order to facilitate the normalization processing based on the same attributes, preferably, the same identification bit and the number of identification bits are set for the vehicle logistics information array. For example, the vehicle logistics information array A1 = [grain type a01, grain weight a02, grain temperature and humidity a03, grain loading and unloading information a04, driving route / location a05, real-time speed a06], where A1 represents the vehicle logistics information array collected by vehicle A at the first time collection point, and B1 represents the vehicle logistics information array collected by vehicle B at the first time. The vehicle logistics information array collected at the collection point is B1=[grain type b01, grain weight b02, grain temperature and humidity b03, grain loading and unloading information b04, driving route / location b05, real-time speed b06]; based on this, the vehicle logistics information array of all grain logistics vehicles is normalized based on the same attributes. For example, for the real-time speed attribute information, a06=60km / h, b06=80km / h, c06=70km / h, then the three are normalized, which will not be repeated here. It should be noted that for non-numeric attributes, only the identification bit is required, and normalization is not required. For example, for grain type a01, grain type b01 and other grain attribute information, it is only necessary to classify them in the identification bit, such as corn is identified as 1, wheat is identified as 2, and rice is identified as 3. Similarly, non-numeric attributes such as grain loading and unloading information and driving routes do not need to be normalized. Only the identification bit is required, which will not be explained here. Finally, the grain logistics information view model is constructed based on all normalized vehicle logistics information arrays; Figure 1As shown, the food logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis identifies the vehicle number, the positive direction of the y-axis identifies the various attributes of the vehicle logistics information array, and the positive direction of the z-axis identifies time; the normalized logistics information array of each vehicle collected every unit time (for example, 1 minute) is identified in the three-dimensional view model, wherein the positive direction of the z-axis identifies time as a unit time (for example, 1 minute). For example, in Figure 1 In the yoz plane with x coordinate 0, the three coordinate points (a01, a02, a03) of the vehicle logistics information array corresponding to the first logistics vehicle are identified. Their meaning is that at time t=0, in vehicle A1, a01 identifies the type of grain transported by vehicle A1, a02 identifies the weight of grain transported by vehicle A1, and a03 identifies the temperature of grain transported by vehicle A1. Similarly, the coordinate points (a11, a12, a13) mean that at time t=1 (for example, 1 minute) in vehicle A1, a11 identifies the type of grain transported by vehicle A1, a12 identifies the weight of grain transported by vehicle A1, and a13 identifies the temperature of grain transported by vehicle A1. Vehicles B and C are identified in the three-dimensional coordinate system in a similar way, and as shown in the following example: Figure 1 As shown, no further details are given here. This enables the construction of the grain logistics information view model based on multiple attributes at different times and for different vehicles, thereby achieving the identification of multiple attributes of multiple vehicles and multi-dimensional information at different times on a single view, improving the efficiency of information identification and display, and avoiding the use of tables or charts that can only represent or present logistics attribute information from a single dimension. The three-dimensional view model can be constructed in existing three-dimensional view software such as CAD, Pro / E, or three-dimensional view plug-ins / components, and no further details are given here.

[0038] The unit coordinate point identification module is used to identify each attribute of the vehicle logistics information array at each unit coordinate point in the three-dimensional space of the grain logistics information view model according to each value of the normalized vehicle logistics information array. The method of identifying each attribute is: constructing a sphere with the unit coordinate point in the three-dimensional space as the center of the circle and the attribute value of the attribute corresponding to the unit coordinate point as the radius; it should be noted that the present invention not only realizes the coordinate point identification of attribute information in the three-dimensional coordinate system by the above method, but also realizes the spherical volume identification based on the attribute value size of the coordinate point, which greatly increases the intuitiveness of the attribute identification. Specifically, the method of identifying each attribute is: constructing a sphere with the unit coordinate point in the three-dimensional space as the center of the circle and the attribute value of the attribute corresponding to the unit coordinate point as the radius, for example Figure 1 The coordinate point where a11 is shown is the center of the circle, and a sphere is constructed with the attribute value 0.5 of the attribute corresponding to the coordinate point as the radius; preferably, different colors can be rendered for different spheres according to the attribute category or vehicle identification, so that users can view it efficiently according to the three-dimensional view model.

[0039] The centroid coordinate offset detection module is used to calculate the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located every unit time, and determine whether the geometric center of the centroid coordinate offset is greater than a first threshold value. If so, the logistics information identification module is executed, otherwise, the calculation is re-executed at intervals of unit time; the geometric center is the geometric center of the plane figure surrounded by the spheres corresponding to the attribute values on the x0z plane; it should be noted that since each x0z plane identifies the attribute values corresponding to the same attribute information of different vehicles at different times, and the attribute values are expressed by the radius / volume of the corresponding sphere, it is assumed that the density of each sphere is the same, for example, the density is 1kg / m3, so that it can be judged by the centroid formed by all spheres on each x0z plane. Whether there is abnormal change in attribute value caused by the displacement of centroid coordinates from the geometric center as time goes by, specifically, the centroid coordinates of the sphere corresponding to each attribute value on the x0z plane where the same attribute is located are calculated every unit time (for example, 1 minute), and it is judged whether the displacement of the centroid coordinates from the geometric center is greater than a first threshold. For example, at time t=1, the centroid coordinates O01 formed by the sphere corresponding to each attribute value (the attribute corresponding to the attribute value can be any one of the aforementioned attributes or any one of the normalized attributes) of the coordinate point set [a01, b01, c01, a11, b11, c11] is offset from the geometric center O1 where the above coordinate point set is located, and it is judged whether the degree of the above displacement (i.e., the centroid distance) is greater than the preset first threshold, thereby realizing abnormal judgment of each attribute value. Alternatively, the abnormality judgment of the attribute value can also be performed by the degree of deviation of the above-mentioned centroid coordinate at the current moment from the centroid coordinate at the previous moment. For example, at time t=2, the centroid coordinate O02 formed by the sphere corresponding to each attribute value of the coordinate point set [a01, b01, c01, a11, b11, c11, a21, b21, c21] is compared with the degree of deviation (i.e., the centroid distance) of the centroid coordinate O02 at the current moment t=2 from the centroid coordinate O01 at the previous moment t=1 to see whether it is greater than the preset second threshold, thereby achieving a preliminary abnormality judgment of each attribute value. It can be seen that the present invention proposes a new method of realizing abnormality judgment of attribute values by using centroid coordinates composed of spherical volumes corresponding to numerical values, which improves the intuitiveness and flexibility of abnormality judgment of attribute values and is a method of abnormality judgment of attribute values that is completely different from the prior art.

[0040] The logistics information identification module is configured to obtain the first sphere with the largest volume change among the spheres corresponding to each attribute value on the x0z plane between the previous unit time and the current unit time, determine whether the change in the first sphere complies with the attribute value change rule corresponding to the current attribute, and if not, highlight and identify the first sphere. It should be noted that, based on the above-mentioned attribute value abnormality determination, the module obtains the first sphere with the largest volume change among the spheres corresponding to each attribute value on the x0z plane within a unit time, and issues a warning message based on the first sphere with the largest volume change. Specifically, the module determines whether the change in the first sphere complies with the attribute value change rule corresponding to the current attribute. For example, if the current attribute is speed and the vehicle's current location is on a highway, the volume change of the sphere corresponding to the current attribute value is a decrease, and the volume of the first sphere with the largest volume change has decreased by more than 1 / 2 compared to the previous moment, while the attribute value change rule corresponding to the current attribute is a change of no more than 1 / 4, indicating that the vehicle speed has decreased significantly and the attribute value change corresponding to the current attribute does not comply with the preset change rule, the first sphere is highlighted and identified, for example, by flashing or by a darker color line, thereby further determining abnormalities in each attribute value.

[0041] It can be seen that the present invention provides a food logistics information tracking system based on the Internet of Things. First, the present invention constructs a three-dimensional view model, namely a food logistics information view model, based on the logistics information of food logistics vehicles, so that the logistics information of various attributes of different logistics vehicles can be observed intuitively and visually in real time from multiple dimensions, thereby improving the display efficiency of logistics information and avoiding the fact that tables or charts can only represent or present logistics attribute information from a single dimension. Secondly, on the basis of the food logistics information view model, a sphere is constructed based on the attribute value of each logistics information as the radius, thereby realizing the intuitive display of the real-time status of logistics information of various attributes. Based on the center of mass of the plane where the sphere is located corresponding to the attribute value of the vehicle's logistics information and the volume change of the sphere, it is judged whether the vehicle is in an abnormal state, thereby realizing the judgment of the vehicle's abnormal state based on the three-dimensional view, which greatly improves the intuitiveness and accuracy of the judgment of abnormal information.

[0042] As a preferred embodiment, the vehicle logistics information array is constructed based on the logistics track information and vehicle information of each grain logistics vehicle, specifically including: Different logistics track information and vehicle information attribute information are configured at each identification position of the vehicle logistics information array, and the logistics track information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle. It should be noted that, for example, the identification form of the vehicle logistics information array is [grain type, grain weight, grain temperature and humidity, grain loading and unloading information, driving route / location, real-time speed], and the logistics trajectory information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle. For example, at time t=1, the vehicle logistics information array A1=[grain type a01, grain weight a02, grain temperature and humidity a03, grain loading and unloading information a04, driving route / location a05, real-time speed a06], where A1 represents the vehicle logistics information array collected by vehicle A at the first time t=1 collection point; B1 represents the vehicle logistics information array collected by vehicle B at the first time collection point, and B1=[grain type b01, grain weight b02, grain temperature and humidity b03, grain loading and unloading information b04, driving route / location b05, real-time speed b06]; thereby obtaining the vehicle logistics information arrays of different vehicles at different times.

[0043] As a preferred embodiment, calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located, and determining whether the centroid coordinates offset the geometric center is greater than a first threshold, specifically includes: Obtain the position of the unit coordinate point of the sphere corresponding to each attribute value on the x0z plane of the same attribute and its radius, assuming that all spheres on the current x0z plane are homogeneous spheres of the same material, calculate the coordinates of the center of mass of all spheres on the current x0z plane, and use the coordinates of the center of mass as the center of mass coordinates; update the first threshold every unit time, and determine whether the center of mass coordinate offset from the geometric center is greater than the updated first threshold. It should be noted that, specifically, the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located are calculated every unit time (for example, 1 minute). It is assumed that all spheres on the current x0z plane are homogeneous spheres of the same material, for example, the density of the spheres is 1kg / m3, and it is determined whether the centroid coordinate offset of the geometric center is greater than the first threshold. For example, at time t=1, the centroid coordinates O01 formed by the spheres corresponding to the attribute values (the attribute values corresponding to the spheres can be any one of the aforementioned attributes or any one of the normalized attributes) of the coordinate point set [a01, b01, c01, a11, b11, c11] are offset from the geometric center O1 where the above-mentioned coordinate point set is located, and it is determined whether the degree of the above-mentioned offset (i.e., the centroid distance) is greater than the preset first threshold, thereby realizing abnormal judgment of each attribute value.

[0044] As a preferred embodiment, determining whether the change of the first spherical shape complies with the attribute value change rule corresponding to the current attribute further includes: If the first sphere identifies the vehicle's route, the route is divided into multiple sub-routes based on the vehicle's route and its transfer points. A determination is made as to whether the change in the first sphere conforms to a route compliance parameter corresponding to the current vehicle's route. The route compliance LF is calculated as follows: , Among them, LF represents the route compliance parameter, represents the total length of the i-th sub-route, Indicates the length of the ith sub-route traveled. Indicates the total length of the driving route. represents the total remaining route length, n represents the number of sub-routes, and K represents the scaling factor. The value of K can be set to a constant between 0 and 1 according to actual needs. Thus, when the vehicle attribute information is a driving route, the vehicle's driving route and its transfer points are divided into multiple sub-routes, reducing the granularity of the route and enabling refined management of driving route determination. Furthermore, by determining whether the change in the first sphere conforms to the route conformity parameter corresponding to the current vehicle's driving route, the route conformity parameter is used to quantify and refine the determination of the abstract and difficult-to-quantify vehicle driving route in a three-dimensional coordinate system. This improves the accuracy of driving route determination.

[0045] As a preferred embodiment, it also includes: If the first sphere indicates the grain loading and unloading information of the vehicle, then the change of the first sphere is determined based on the vehicle's driving route and the loading and unloading information of its transfer points to determine whether it complies with the loading and unloading compliance parameter of the current vehicle; the loading and unloading compliance parameter ZXF is calculated as follows: , Among them, ZXF represents the loading and unloading compliance parameter, sh represents the loss value of the jth loading and unloading point, and represents the inbound and outbound weight of the current vehicle at the jth loading and unloading point, m is the number of loading and unloading points, and represents the scaling factor and correction coefficient, The value range is greater than or equal to 1, but not too large. The preferred value range is [1,10). It can be set according to actual needs. The value range of is a number between 0 and 1. Therefore, when the vehicle attribute information is grain loading and unloading information, whether the change in the first spherical shape conforms to the current vehicle's loading and unloading compliance parameters is determined based on the vehicle's travel route and the loading and unloading information at its transfer points. This refines the judgment of the volume-variable spherical shape of the loading and unloading information changes in the three-dimensional coordinate system using the loading and unloading compliance parameters, thereby improving the accuracy of the identification and display of the loading and unloading information.

[0046] As a preferred embodiment, it also includes: If the first sphere identifies the grain temperature information corresponding to the grain type of the vehicle, then based on the grain temperature information of the vehicle traveling on multiple sub-routes, it is determined whether the change in the first sphere meets the grain temperature compliance parameter of the current vehicle; the grain temperature compliance parameter TF is calculated as follows: , Among them, TF represents the grain temperature compliance parameter, T represents the preset grain transportation temperature, represents the average transport temperature measurement value of the i-th sub-route, Indicates the error value of the temperature sensor used for measurement, and Indicates the correction factor of the measured temperature and the correction factor of the temperature sensor, which can be set according to actual needs and The value range is a value between 0 and 1; represents the grain temperature adjustment coefficient, with a value range of 1 or greater, but not too large, and a preferred range of [1, 5]. Therefore, if the vehicle's attribute information is grain temperature information corresponding to the type of grain being loaded, the grain temperature information of the vehicle traveling along multiple subroutes is used to determine whether the changes in the first sphere conform to the grain temperature compliance parameter of the current vehicle. The grain temperature compliance parameter is then used to intuitively display the changes in grain temperature information as a volume-variable sphere in a three-dimensional coordinate system, thereby improving the accuracy of grain temperature information identification and the intuitiveness of the display.

[0047] As a preferred embodiment, it also includes: If the first sphere identifies the real-time speed information of the vehicle, then it is determined whether the change of the first sphere conforms to the real-time speed compliance parameter of the current vehicle based on the multiple real-time speed information; the real-time speed compliance parameter VF is calculated as follows: , Among them, VF represents the real-time speed compliance parameter, V represents the preset reference speed, represents the detection speed at the i-th detection time point, n represents the number of detection time points, e represents a natural constant, represents a speed correction coefficient, and its value range is a value greater than or equal to 1, but should not be too large, and the preferred value range is [1, 8]. Thus, when the vehicle attribute information is real-time speed information, whether the change in the first sphere conforms to the real-time speed compliance parameter of the current vehicle is determined based on multiple pieces of real-time speed information. The change in speed information is then intuitively displayed as a volume-variable sphere in a three-dimensional coordinate system using the real-time speed compliance parameter, thereby improving the accuracy of speed information identification and the intuitiveness of the display.

[0048] Embodiment 3: The present invention provides a food logistics information tracking device based on the Internet of Things, and the system executes the food logistics information tracking method based on the Internet of Things.

[0049] Embodiment 4: The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program executes the food logistics information tracking method based on the Internet of Things.

[0050] Those skilled in the art will appreciate that the present invention includes devices for performing one or more of the operations described herein. These devices may be specially designed and manufactured for the desired purpose, or they may include known devices found in general-purpose computers. These devices have computer programs stored therein, which are selectively activated or reconfigured. Such computer programs may be stored on a device (e.g., a computer) readable medium or on any type of medium suitable for storing electronic instructions and coupled to a bus, including but not limited to any type of disk (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic cards, or optical cards. In other words, a readable medium includes any medium that can be used by a device (e.g., a computer) to store or transmit information in a form that can be read.

[0051] Those skilled in the art will appreciate that each block in these structural diagrams and / or block diagrams and / or flow charts, as well as combinations of blocks in these structural diagrams and / or block diagrams and / or flow charts, can be implemented using computer program instructions. Those skilled in the art will appreciate that these computer program instructions can be provided to a general-purpose computer, a specialized computer, or a processor of other programmable data processing methods for implementation, thereby executing the schemes specified in the blocks or multiple blocks in the structural diagrams and / or block diagrams and / or flow charts disclosed in the present invention through the processor of the computer or other programmable data processing method.

[0052] Those skilled in the art will appreciate that the steps, measures, and schemes in the various operations, methods, and processes discussed in the present invention may be interchanged, modified, combined, or deleted. Furthermore, other steps, measures, and schemes in the various operations, methods, and processes discussed in the present invention may also be interchanged, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and schemes in the prior art that are similar to those disclosed in the present invention may also be interchanged, modified, rearranged, decomposed, combined, or deleted.

[0053] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention's description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A food logistics information tracking method based on the Internet of Things, characterized in that: The method comprises the following steps: Step S1: obtaining multiple logistics track information and vehicle information of multiple grain logistics vehicles based on the Internet of Things, wherein the vehicle information includes at least grain type, grain weight, grain temperature and humidity, and grain loading and unloading information, and the logistics track information includes at least the vehicle's driving route and real-time speed; Step S2: constructing a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalizing the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and constructing a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis indicates the vehicle number, the positive direction of the y-axis indicates the various attributes of the vehicle logistics information array, and the positive direction of the z-axis indicates time; Step S3: Identifying each attribute of the vehicle logistics information array at each unit coordinate point in the three-dimensional space of the grain logistics information view model according to each value of the normalized vehicle logistics information array, wherein each attribute is identified by constructing a sphere with the unit coordinate point in the three-dimensional space as the center and the attribute value corresponding to the unit coordinate point as the radius; Step S4: Calculate the coordinates of the centroid formed by the spheres corresponding to the attribute values on the x0z plane at every unit time, and determine whether the centroid coordinate offset from the geometric center is greater than a first threshold. If so, execute step S5; otherwise, re-execute the calculation at every unit time; the geometric center is the geometric center of the plane figure enclosed by the spheres corresponding to the attribute values on the x0z plane. Step S5: Obtain the first sphere with the largest volume change among the spheres corresponding to the attribute values on the x0z plane from the previous unit time to the current unit time, and determine whether the change of the first sphere complies with the attribute value change rule corresponding to the current attribute. If not, highlight the first sphere.

2. The method for tracking food logistics information according to claim 1, characterized in that: The vehicle logistics information array is constructed based on the logistics track information and vehicle information of each grain logistics vehicle, specifically including: Different logistics track information and vehicle information attribute information are configured at each identification position of the vehicle logistics information array, and the logistics track information and vehicle information of each grain logistics vehicle are filled into the corresponding identification position to form the vehicle logistics information array of each grain logistics vehicle.

3. The method for tracking food logistics information according to claim 1, wherein: Calculating the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane where the same attribute is located, and determining whether the centroid coordinates offset the geometric center is greater than a first threshold, specifically includes: Get the position and radius of the unit coordinate point of the sphere corresponding to each attribute value on the x0z plane of the same attribute. Assuming that all spheres on the current x0z plane are homogeneous spheres of the same material, calculate the coordinates of the center of mass of all spheres on the current x0z plane, and use the coordinates of the center of mass as the center of mass coordinates. The first threshold is updated every unit time, and it is determined whether the centroid coordinate offset geometric center is greater than the updated first threshold.

4. The method for tracking food logistics information according to claim 1, wherein: Determining whether the change of the first spherical shape complies with the attribute value change rule corresponding to the current attribute further includes: If the first sphere identifies the vehicle's route, the route is divided into multiple sub-routes based on the vehicle's route and its transfer points. A determination is made as to whether the change in the first sphere conforms to a route compliance parameter corresponding to the current vehicle's route. The route compliance LF is calculated as follows: Among them, LF represents the route compliance parameter, represents the total length of the i-th sub-route, Indicates the length of the ith sub-route traveled. Indicates the total length of the driving route. Indicates the total length of the remaining route, n indicates the number of sub-routes, and K indicates the scaling factor.

5. The method for tracking food logistics information according to claim 4, characterized in that: Also includes: If the first sphere identifies the grain loading and unloading information of the vehicle, then it is determined whether the change in the first sphere complies with the loading and unloading compliance parameter of the current vehicle based on the loading and unloading information of the plurality of transfer points; the loading and unloading compliance parameter ZXF is calculated as follows: Among them, ZXF represents the loading and unloading compliance parameter, sh represents the loss value of the jth loading and unloading point, and represents the inbound and outbound weight of the current vehicle at the jth loading and unloading point, m is the number of loading and unloading points, and Represents the scaling factor and correction coefficient.

6. The method for tracking food logistics information according to claim 4, characterized in that: Also includes: If the first sphere identifies the grain temperature information corresponding to the grain type of the vehicle, then based on the grain temperature information of the vehicle traveling on multiple sub-routes, it is determined whether the change in the first sphere meets the grain temperature compliance parameter of the current vehicle; the grain temperature compliance parameter TF is calculated as follows: Among them, TF represents the grain temperature compliance parameter, T represents the preset grain transportation temperature, represents the average transport temperature measurement value of the i-th sub-route, Indicates the error value of the temperature sensor used for measurement, and Indicates the correction factor of the measured temperature and the correction factor of the temperature sensor, Indicates the grain temperature adjustment coefficient.

7. The method for tracking food logistics information according to claim 4, characterized in that: Also includes: If the first sphere identifies the real-time speed information of the vehicle, then it is determined whether the change of the first sphere conforms to the real-time speed compliance parameter of the current vehicle based on the multiple real-time speed information; the real-time speed compliance parameter VF is calculated as follows: Among them, VF represents the real-time speed compliance parameter, V represents the preset reference speed, represents the detection speed at the i-th detection time point, n represents the number of detection time points, e represents a natural constant, Indicates the speed correction factor.

8. A food logistics information tracking system based on the Internet of Things, characterized by: To implement the method for tracking food logistics information based on the Internet of Things according to any one of claims 1 to 7, the system includes the following modules: A logistics information acquisition module is used to obtain multiple logistics track information and vehicle information of multiple grain logistics vehicles based on the Internet of Things. The vehicle information includes at least the type of grain, grain weight, grain temperature and humidity, and grain loading and unloading information. The logistics track information includes at least the vehicle's driving route and real-time speed. A grain logistics information view model construction module is used to construct a vehicle logistics information array based on the logistics trajectory information and vehicle information of each grain logistics vehicle, normalize the vehicle logistics information arrays of all grain logistics vehicles based on the same attributes to obtain a normalized vehicle logistics information array, and construct a grain logistics information view model based on all normalized vehicle logistics information arrays; the grain logistics information view model is a three-dimensional view model, wherein the positive direction of the x-axis indicates the vehicle number, the positive direction of the y-axis indicates the various attributes of the vehicle logistics information array, and the positive direction of the z-axis indicates time; a unit coordinate point identification module, configured to identify each attribute of the vehicle logistics information array at each unit coordinate point in the three-dimensional space of the grain logistics information view model based on each value of the normalized vehicle logistics information array, wherein each attribute is identified by constructing a sphere with the unit coordinate point in the three-dimensional space as the center and the attribute value of the attribute corresponding to the unit coordinate point as the radius; A centroid coordinate offset detection module is used to calculate the centroid coordinates of the spheres corresponding to the attribute values on the x0z plane at intervals, and determine whether the centroid coordinate offset geometric center is greater than a first threshold. If so, the logistics information identification module is executed; otherwise, the calculation is repeated at intervals; the geometric center is the geometric center of the plane figure enclosed by the spheres corresponding to the attribute values on the x0z plane; The logistics information identification module is used to obtain the first sphere with the largest volume change among the spheres corresponding to each attribute value on the x0z plane from the previous unit time to the current unit time, and determine whether the change of the first sphere conforms to the attribute value change rule corresponding to the current attribute. If not, the first sphere is highlighted and identified.

9. A food logistics information tracking device based on the Internet of Things, characterized in that: The device executes the food logistics information tracking method based on the Internet of Things as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that: The computer program executes the food logistics information tracking method based on the Internet of Things as described in any one of claims 1 to 7.

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