Logistics vehicle loading and unloading identification system and method based on the Internet of Things

Abstract

The present invention discloses a logistics vehicle loading and unloading identification system and method based on the Internet of Things, which relates to the field of data processing technology, including: obtaining a reference center and a weighing reference point based on a logistics vehicle and an on-board weighing sensor; obtaining a reference ratio based on data of a first number of logistics vehicles that normally transport goods; calculating a first real-time distance, a second real-time distance, a third real-time distance and a fourth real-time distance based on the reference ratio; obtaining a real-time quantitative value based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance; obtaining a final quantitative threshold based on data of a second number of logistics vehicles that normally transport goods; and limiting the end of vehicle loading and unloading based on the real-time quantitative value and the final quantitative threshold. The present invention is used to solve the problem that the existing technology fails to make a balance judgment on the loading and unloading of logistics vehicles, and if the weight of the loaded goods is unbalanced, it will cause safety accidents and cargo losses.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a logistics vehicle loading and unloading identification system and method based on the Internet of Things. Background Art

[0002] With the rapid development of the logistics industry, the management of loading and unloading of logistics vehicles and the monitoring of distribution balance have become key links in improving logistics efficiency and safety. Traditional loading and unloading management methods rely heavily on manual operations, which are inefficient, prone to errors, and lack real-time monitoring.

[0003] Traditional logistics vehicle loading and unloading identification systems usually only identify the start and end of loading and unloading, and it is difficult to monitor the load and balance status of the logistics vehicle during loading in real time. When transporting heavy objects, it is easy to cause overloading or imbalance, which in turn causes safety accidents and cargo losses. For example, the patent application with publication number CN114154084A discloses a truck loading and unloading identification method. This solution can identify the start and end time of loading and unloading, but does not balance the weight of the loaded and unloaded goods. Unbalanced loading can easily cause safety accidents and cargo losses. The existing technology fails to make a balance judgment on the loading and unloading of logistics vehicles. If the weight of the loaded goods is unbalanced, it will cause safety accidents and cargo losses. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems in the prior art to a certain extent, by obtaining a reference center and a weighing reference point based on a logistics vehicle and an on-board weighing sensor; obtaining a reference ratio based on data of a first number of logistics vehicles transporting goods normally; calculating a first real-time distance, a second real-time distance, a third real-time distance and a fourth real-time distance based on the reference ratio; obtaining a real-time quantitative value based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance; obtaining a final quantitative threshold based on data of a second number of logistics vehicles transporting goods normally; and limiting the end of vehicle loading and unloading based on the real-time quantitative value and the final quantitative threshold, thereby solving the problem that the prior art fails to make a balance judgment on the loading and unloading of logistics vehicles, and if the weight of the loaded goods is unbalanced, it may cause safety accidents and cargo losses.

[0005] To achieve the above objectives, the present invention provides a logistics vehicle loading and unloading identification system based on the Internet of Things, comprising:

[0006] Setting module, starting module, reference point acquisition module, reference ratio acquisition module, real-time distance acquisition module, real-time quantization value acquisition module, final quantization threshold acquisition module and restriction end module;

[0007] The setting module is used to install a vehicle-mounted weighing sensor on a logistics vehicle;

[0008] The starting module is used to obtain a logistics vehicle loading and unloading start signal based on the logistics vehicle networking data;

[0009] The reference point acquisition module is used to obtain the reference center and weighing reference point based on the logistics vehicle and the vehicle-mounted weighing sensor;

[0010] The reference ratio acquisition module is used to acquire the reference ratio based on data of the logistics vehicles that have carried out normal cargo transportation for a first number of times;

[0011] The real-time distance acquisition module is used to calculate the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance based on the reference ratio;

[0012] The real-time quantization value acquisition module is used to acquire a real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance;

[0013] The final quantitative threshold acquisition module is used to acquire the final quantitative threshold based on the data of the logistics vehicles that normally transport goods for a second number of times;

[0014] The restriction end module is used to restrict the end of vehicle loading and unloading based on the real-time quantization value and the final quantization threshold.

[0015] Furthermore, the setting module is configured with a strategy for installing a vehicle-mounted weighing sensor, and the strategy for installing a vehicle-mounted weighing sensor includes:

[0016] The four sides of the bottom of the cargo box of the logistics vehicle are marked as the first side, the second side, the third side and the fourth side respectively, and a first weighing sensor is installed between the cargo box and the frame below at a first distance from the first side and the second side; a second weighing sensor is installed between the cargo box and the frame below at a first distance from the second side and the third side; a third weighing sensor is installed between the cargo box and the frame below at a first distance from the third side and the fourth side; a fourth weighing sensor is installed between the cargo box and the frame below at a first distance from the fourth side and the first side; the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are collectively referred to as vehicle-mounted weighing sensors.

[0017] Furthermore, the starting module is configured with a loading and unloading start judgment strategy, and the loading and unloading start judgment strategy includes:

[0018] Obtain the network data of logistics vehicles, which includes loading and unloading points and vehicle driving data; when the logistics vehicle arrives at the loading and unloading point and stops, a signal for the start of loading and unloading of the logistics vehicle is issued, and the loading and unloading process is judged to be qualified.

[0019] Furthermore, the reference point acquisition module is configured with a reference point acquisition module strategy, and the reference point acquisition module strategy includes:

[0020] Establish a plane rectangular coordinate system, mark it as the logistics vehicle coordinate system, and draw the top view outline of the logistics vehicle in the logistics vehicle coordinate system; obtain the middle coordinate of the top view outline of the logistics vehicle, mark it as the reference center;

[0021] With the position of the top-view outline of the logistics vehicle as a reference, the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are marked in the logistics vehicle coordinate system, and are marked as the first reference point, the second reference point, the third reference point and the fourth reference point respectively; the first reference point, the second reference point, the third reference point and the fourth reference point are collectively referred to as weighing reference points.

[0022] Furthermore, the reference ratio acquisition module is configured with a reference ratio acquisition strategy, and the reference ratio acquisition strategy includes:

[0023] Obtain the values ​​of the onboard weighing sensor of the logistics vehicle during normal cargo transportation for the first number of times, mark them as historical weighing values, obtain the maximum value of the historical weighing values, and mark it as the normal reference value;

[0024] Get the distance from any weighing reference point to the weighing center and mark it as reference distance;

[0025] The reference ratio is calculated as: Bb=Jc / Zc; where Bb is the reference ratio, Zc is the normal reference value, and Jc is the reference distance.

[0026] Furthermore, the real-time distance acquisition module is configured with a real-time distance acquisition strategy, and the real-time distance acquisition strategy includes:

[0027] Obtain values ​​of the first weighing sensor, the second weighing sensor, the third weighing sensor, and the fourth weighing sensor, respectively, and mark them as a first weighing value, a second weighing value, a third weighing value, and a fourth weighing value, respectively;

[0028] The first real-time distance is calculated as: Js1=Bb×Cs1; where Js1 is the first real-time distance, Bb is the reference ratio, and Cs1 is the first weighing value; the second real-time distance is calculated as: Js2=Bb×Cs2; where Js2 is the second real-time distance, and Cs2 is the second weighing value; the third real-time distance is calculated as: Js3=Bb×Cs3; where Js3 is the third real-time distance, and Cs3 is the third weighing value; the fourth real-time distance is calculated as: Js4=Bb×Cs1; where Js4 is the fourth real-time distance, and Cs4 is the fourth weighing value.

[0029] Furthermore, the real-time quantization value acquisition module is configured with a real-time quantization value acquisition strategy, and the real-time quantization value acquisition strategy includes:

[0030] Calculate the absolute value of the difference between the first real-time distance and the third real-time distance, marking it as the first difference; obtain a weighing reference point corresponding to the larger value between the first real-time distance and the third real-time distance, marking it as the first direction reference point; start from the reference center and draw a line segment with a length of the first difference in the direction of the first direction reference point, marking it as the first line segment;

[0031] Calculate the absolute value of the difference between the second real-time distance and the fourth real-time distance, marking it as the second difference; obtain a weighing reference point corresponding to the larger value between the second real-time distance and the fourth real-time distance, marking it as the second direction reference point; start from the reference center and draw a line segment with a length of the second difference toward the second direction reference point, marking it as the second line segment;

[0032] Connect the endpoints of the first line segment and the second line segment to obtain a third line segment, connect the reference center and the midpoint of the third line segment to obtain a fourth line segment, and mark the length of the fourth line segment as a real-time quantized value.

[0033] Furthermore, the final quantization threshold acquisition module is configured with a final quantization threshold acquisition strategy, and the final quantization threshold acquisition strategy includes:

[0034] Obtain the real-time quantitative value of the logistics vehicles that can normally transport goods for the second time, and mark it as the historical quantitative value;

[0035] Sort the historical quantitative values ​​from small to large and mark them as Lh1 to Lh i ;

[0036] The first position value is obtained as follows: Wz1=k1×D2, where Wz1 is the first position value, k1 is the first coefficient, the setting range of the first coefficient is: (0, 0.5), and D2 is the second quantity; obtain the integer part of the first position value, mark it as F1, and Lh （F1） The corresponding historical quantitative value is marked as G1;

[0037] The second position value is obtained as follows: Wz2=k2×D2, where Wz2 is the second position value, k2 is the second coefficient, and the setting range of the second coefficient is: (0.5, 1); obtain the integer part of the second position value, mark it as F2, and set Lh （F2） The corresponding historical quantitative value is marked as G2;

[0038] The initial quantization threshold is obtained as follows: Hy=G2+(G2-G1) / (k2-k1)×(1-k2); where Hy is the initial quantization threshold;

[0039] Obtain historical quantization values ​​that are less than or equal to the initial quantization threshold and mark them as the final quantization threshold.

[0040] Furthermore, the restriction end module is configured with a restriction end strategy, and the restriction end strategy includes:

[0041] It is judged in real time whether the real-time quantization value is less than or equal to the final quantization threshold. If so, a qualified signal for logistics vehicle loading and unloading is generated. If not, a failed signal for logistics vehicle loading and unloading is issued. The loading and unloading personnel adjust the position of the goods in the logistics vehicle until the real-time quantization value is less than or equal to the final quantization threshold. The loading and unloading of goods can be completed only when the qualified signal for logistics vehicle loading and unloading is generated.

[0042] The present invention provides a method for identifying loading and unloading cargo on a logistics vehicle based on the Internet of Things, comprising the following steps: installing an on-board weighing sensor on a logistics vehicle;

[0043] Obtain the start signal of loading and unloading of logistics vehicles based on the logistics vehicle networking data;

[0044] Obtain reference center and weighing reference point based on logistics vehicle and on-board weighing sensor;

[0045] The reference ratio is obtained based on the data of the logistics vehicles that normally transport goods for the first time;

[0046] Calculating a first real-time distance, a second real-time distance, a third real-time distance, and a fourth real-time distance based on a reference scale;

[0047] Acquire a real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance, and the fourth real-time distance;

[0048] Obtaining a final quantitative threshold based on data of the second number of logistics vehicles that normally transport goods;

[0049] The end of vehicle loading and unloading is restricted based on the real-time quantified value and the final quantified threshold.

[0050] Beneficial effects of the present invention: The present invention obtains a reference center and a weighing reference point based on a logistics vehicle and an on-board weighing sensor; obtains a reference ratio based on data of a first number of logistics vehicles transporting goods normally; calculates a first real-time distance, a second real-time distance, a third real-time distance, and a fourth real-time distance based on the reference ratio; obtains a real-time quantified value based on the first real-time distance, the second real-time distance, the third real-time distance, and the fourth real-time distance; obtains a final quantified threshold based on data of a second number of logistics vehicles transporting goods normally; and limits the end of vehicle loading and unloading of goods based on the real-time quantified value and the final quantified threshold. The advantage of the present invention is that it can make a balance judgment on the logistics vehicle when loading and unloading goods, thereby improving the safety of the logistics vehicle in transporting goods;

[0051] The present invention uses the real-time quantitative value acquisition module to obtain real-time quantitative values ​​based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance. The advantage is that traditional vehicle balance is difficult to express with specific numerical values. By setting real-time quantitative values ​​to represent the balance value of the logistics vehicle status, the balance judgment of the logistics vehicle is made more intuitive and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a principle block diagram of the system of the present invention;

[0053] Figure 2 is a schematic diagram of a fourth line segment of the present invention;

[0054] Figure 3 A flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0056] Example 1, please refer to Figure 1 As shown, the logistics vehicle loading and unloading identification system based on the Internet of Things includes: a setting module, a start module, a reference point acquisition module, a reference ratio acquisition module, a real-time distance acquisition module, a real-time quantitative value acquisition module, a final quantitative threshold acquisition module and a restriction end module;

[0057] The setting module is used to install the on-board weighing sensor on the logistics vehicle;

[0058] The four sides of the bottom of the cargo box of the logistics vehicle are marked as the first side, the second side, the third side and the fourth side respectively, and a first weighing sensor is installed between the cargo box and the frame below at a first distance from the first side and the second side; a second weighing sensor is installed between the cargo box and the frame below at a first distance from the second side and the third side; a third weighing sensor is installed between the cargo box and the frame below at a first distance from the third side and the fourth side; a fourth weighing sensor is installed between the cargo box and the frame below at a first distance from the fourth side and the first side; the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are collectively referred to as vehicle-mounted weighing sensors; the first distance is set to fix the relative positions of the four sensors, which is convenient for subsequent weight balance analysis of the logistics vehicle. For example, the first distance is set to 20 cm.

[0059] The start module is used to obtain the start signal of loading and unloading of logistics vehicles based on the logistics vehicle network data;

[0060] Obtain the network data of logistics vehicles, which includes loading and unloading points and vehicle driving data; when the logistics vehicle arrives at the loading and unloading point and stops, a signal for the start of loading and unloading of the logistics vehicle is issued, and the loading and unloading process is judged to be qualified; here, when the signal for the start of loading and unloading of the logistics vehicle is issued, subsequent operations are started.

[0061] The reference point acquisition module is used to obtain the reference center and weighing reference point based on the logistics vehicle and the on-board weighing sensor;

[0062] Establish a plane rectangular coordinate system, mark it as the logistics vehicle coordinate system, and draw the top view outline of the logistics vehicle in the logistics vehicle coordinate system; obtain the middle coordinate of the top view outline of the logistics vehicle, mark it as the reference center;

[0063] The first, second, third, and fourth load cells are marked in the coordinate system of the logistics vehicle with reference to the position of the top view outline of the logistics vehicle, and are marked as the first reference point, the second reference point, the third reference point, and the fourth reference point, respectively; the first reference point, the second reference point, the third reference point, and the fourth reference point are collectively referred to as weighing reference points;

[0064] In practical applications, please refer to Figure 2 As shown in the figure, a logistics vehicle coordinate system is established to facilitate data analysis.

[0065] The reference ratio acquisition module is used to acquire the reference ratio based on data of the first number of logistics vehicles that normally transport goods;

[0066] Obtain the values ​​of the onboard weighing sensor of the logistics vehicle during normal transportation of goods for a first number of times, mark them as historical weighing values, obtain the maximum value of the historical weighing values, and mark it as the normal reference value; the first number is set to obtain the maximum value of the onboard weighing sensor of the logistics vehicle during normal driving, so the larger the first number, the more accurate the normal reference value, for example, the first number is 100;

[0067] Get the distance from any weighing reference point to the weighing center and mark it as reference distance;

[0068] The reference ratio is calculated as: Bb=Jc / Zc; where Bb is the reference ratio, Zc is the normal reference value, and Jc is the reference distance.

[0069] In practical applications, please refer to Figure 2As shown, the maximum historical weighing value is 1207kg, the reference distance is 1.84m, the reference distance is retained to two decimal places, and the reference ratio is calculated as: Bb=1.84 / 1207=0.001524; the calculation result is retained to six decimal places; the reference ratio is the conversion ratio of weight and length, which is convenient for processing weight data.

[0070] The real-time distance acquisition module is used to calculate the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance based on the reference ratio;

[0071] Obtain values ​​of the first weighing sensor, the second weighing sensor, the third weighing sensor, and the fourth weighing sensor, respectively, and mark them as a first weighing value, a second weighing value, a third weighing value, and a fourth weighing value, respectively;

[0072] The first real-time distance is calculated as: Js1=Bb×Cs1; where Js1 is the first real-time distance, Bb is the reference ratio, and Cs1 is the first weighing value; the second real-time distance is calculated as: Js2=Bb×Cs2; where Js2 is the second real-time distance, and Cs2 is the second weighing value; the third real-time distance is calculated as: Js3=Bb×Cs3; where Js3 is the third real-time distance, and Cs3 is the third weighing value; the fourth real-time distance is calculated as: Js4=Bb×Cs1; where Js4 is the fourth real-time distance, and Cs4 is the fourth weighing value; this method represents weight by length;

[0073] In actual applications, for example, the first weighing value, the second weighing value, the third weighing value and the fourth weighing value are 965 kg, 841 kg, 462 kg and 623 kg respectively, and the first real-time distance is calculated as: Js1=0.001524×965=1.47 m; the second real-time distance is calculated as: Js2=0.001524×841=1.28 m; the third real-time distance is calculated as: Js3=0.001524×462=0.70 m; and the fourth real-time distance is calculated as: Js4=0.001524×623=0.95 m.

[0074] The real-time quantization value acquisition module is used to acquire the real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance;

[0075] Calculate the absolute value of the difference between the first real-time distance and the third real-time distance, marking it as the first difference; obtain a weighing reference point corresponding to the larger value between the first real-time distance and the third real-time distance, marking it as the first direction reference point; start from the reference center and draw a line segment with a length of the first difference in the direction of the first direction reference point, marking it as the first line segment;

[0076] Calculate the absolute value of the difference between the second real-time distance and the fourth real-time distance, marking it as the second difference; obtain a weighing reference point corresponding to the larger value between the second real-time distance and the fourth real-time distance, marking it as the second direction reference point; start from the reference center and draw a line segment with a length of the second difference toward the second direction reference point, marking it as the second line segment;

[0077] Connecting the endpoints of the first line segment and the second line segment to obtain a third line segment, connecting the reference center to the midpoint of the third line segment to obtain a fourth line segment, and marking the length of the fourth line segment as a real-time quantized value; where the real-time quantized value represents an offset value of the weight;

[0078] In practical applications, please refer to Figure 2 As shown, the first difference is: 1.47m-0.70m=0.77m, the first direction reference point is the first reference point, starting from the reference center, a line segment with a length of 0.77m is drawn in the direction of the first reference point, marked as the first line segment; the first difference is: 1.28m-0.95m=0.33m, the first direction reference point is the second reference point, starting from the reference center, a line segment with a length of 0.77m is drawn in the direction of the second reference point, marked as the second line segment, and the fourth line segment is 0.28m. The obtained fourth line segment retains two decimal places, and the real-time quantization value is 0.28m.

[0079] The final quantitative threshold acquisition module is used to acquire the final quantitative threshold based on the data of the logistics vehicles that normally transport goods for a second number of times;

[0080] Obtain the real-time quantitative value of the logistics vehicles that can normally transport goods for a second number of times, and mark it as the historical quantitative value; the second number is set to obtain the real-time quantitative value range of the logistics vehicles that can normally transport goods, so the larger the second number, the better, for example, the second number is 100;

[0081] Sort the historical quantitative values ​​from small to large and mark them as Lh1 to Lh i ;

[0082] The first position value is obtained as follows: Wz1=k1×D2, where Wz1 is the first position value, k1 is the first coefficient, the setting range of the first coefficient is: (0, 0.5), and D2 is the second quantity; obtain the integer part of the first position value, mark it as F1, and Lh （F1） The corresponding historical quantization value is marked as G1. In order to obtain a historical quantization value that is smaller than the middle historical quantization value, the setting range of the first coefficient is: (0, 0.5). Here, 0.25 is selected as the first coefficient.

[0083] The second position value is obtained as follows: Wz2=k2×D2, where Wz2 is the second position value, k2 is the second coefficient, and the setting range of the second coefficient is: (0.5, 1); obtain the integer part of the second position value, mark it as F2, and set Lh （F2） The corresponding historical quantization value is marked as G2. In order to obtain a historical quantization value that is larger than the middle historical quantization value, the setting range of the second coefficient is: (0.5, 1). Here, the second coefficient is 0.75.

[0084] The initial quantization threshold is calculated as: Hy = G2 + (G2 - G1) / (k2 - k1) × (1 - k2); where Hy is the initial quantization threshold. Loading and unloading is usually balanced, so historical quantization values ​​are concentrated close to 0. The initial quantization threshold calculation treats historical quantization values ​​as uniformly distributed. If the value exceeds the initial quantization threshold, it can be considered an abnormal historical quantization value. This method screens the range of accurate historical quantization values.

[0085] Obtain the historical quantization value that is less than or equal to the initial quantization threshold and mark it as the final quantization threshold;

[0086] In practical applications, the first position value is obtained as: Wz1=0.25×100=25, then the integer part of the first position value is 25, and the obtained Lh （25） The corresponding historical quantization value is 0.28m, so G1 is 0.28m; the second position value is obtained: Wz1=0.75×100=75, then the integer part of the second position value is 75, and the obtained Lh （75） The corresponding historical quantization value is 0.78m, so G2 is 0.78m; the initial quantization threshold is: Hy=0.78+(0.78-0.28) / (0.75-0.25)×(1-0.75)=1.03m.

[0087] The restriction end module is used to restrict the end of vehicle loading and unloading based on the real-time quantification value and the final quantification threshold;

[0088] It is judged in real time whether the real-time quantization value is less than or equal to the final quantization threshold. If so, a qualified signal for the logistics vehicle loading and unloading is generated. If not, a signal for the logistics vehicle loading and unloading failure is issued. The loading and unloading personnel adjust the position of the goods in the logistics vehicle until the real-time quantization value is less than or equal to the final quantization threshold. The loading and unloading of goods can only be completed when the qualified signal for the logistics vehicle loading and unloading is generated, so that the logistics vehicle can operate safely.

[0089] In practical applications, the real-time quantization value 0.28m is judged to be less than 1.03m in real time, and a qualified signal for the logistics vehicle to load and unload goods is generated, and the loading and unloading of goods can be ended.

[0090] Example 2, please refer to Figure 3 As shown, the method for identifying loading and unloading of logistics vehicles based on the Internet of Things includes the following steps:

[0091] Step S1: Installing a vehicle-mounted weighing sensor on a logistics vehicle; Step S1 includes the following sub-steps:

[0092] Step S101, mark the four sides of the bottom of the cargo box of the logistics vehicle as the first side, the second side, the third side and the fourth side respectively, and install a first weighing sensor between the cargo box and the frame below at a first distance from the first side and the second side; install a second weighing sensor between the cargo box and the frame below at a first distance from the second side and the third side; install a third weighing sensor between the cargo box and the frame below at a first distance from the third side and the fourth side; install a fourth weighing sensor between the cargo box and the frame below at a first distance from the fourth side and the first side; the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are collectively referred to as vehicle-mounted weighing sensors.

[0093] Step S2, obtaining a signal for the start of loading and unloading of a logistics vehicle based on the logistics vehicle network data; Step S2 includes the following sub-steps:

[0094] Step S201, obtain the logistics vehicle network data, where the logistics vehicle network data includes loading and unloading point and vehicle driving data; when the logistics vehicle arrives at the loading and unloading point and stops, a logistics vehicle loading and unloading start signal is issued, and the loading and unloading process begins to be judged as qualified.

[0095] Step S3, obtaining a reference center and a weighing reference point based on the logistics vehicle and the onboard weighing sensor; Step S3 includes the following sub-steps:

[0096] Step S301: Establish a plane rectangular coordinate system, marked as the logistics vehicle coordinate system, draw the top view outline of the logistics vehicle in the logistics vehicle coordinate system; obtain the middle coordinate of the top view outline of the logistics vehicle, marked as the reference center;

[0097] In step S302, the first weighing sensor, the second weighing sensor, the third weighing sensor, and the fourth weighing sensor are marked in the coordinate system of the logistics vehicle with reference to the position of the top-view outline of the logistics vehicle, and are marked as the first reference point, the second reference point, the third reference point, and the fourth reference point respectively; the first reference point, the second reference point, the third reference point, and the fourth reference point are collectively referred to as weighing reference points.

[0098] Step S4, obtaining a reference ratio based on the data of the first number of logistics vehicles that normally transport goods; Step S4 includes the following sub-steps:

[0099] Step S401: obtaining the values ​​of the onboard weighing sensor of the logistics vehicle during normal cargo transportation for a first number of times, marking them as historical weighing values, obtaining the maximum value of the historical weighing values, and marking it as a normal reference value;

[0100] Step S402, obtaining the distance from any weighing reference point to the weighing center, and marking it as the reference distance;

[0101] In step S403 , the reference ratio is calculated as: Bb=Jc / Zc; wherein Bb is the reference ratio, Zc is the normal reference value, and Jc is the reference distance.

[0102] Step S5, calculating the first real-time distance, the second real-time distance, the third real-time distance, and the fourth real-time distance based on the reference ratio; Step S5 includes the following sub-steps:

[0103] Step S501, respectively obtaining the values ​​of the first weighing sensor, the second weighing sensor, the third weighing sensor, and the fourth weighing sensor, which are marked as the first weighing value, the second weighing value, the third weighing value, and the fourth weighing value, respectively;

[0104] Step S502, calculate the first real-time distance as: Js1=Bb×Cs1; where Js1 is the first real-time distance, Bb is the reference ratio, and Cs1 is the first weighing value; calculate the second real-time distance as: Js2=Bb×Cs2; where Js2 is the second real-time distance, and Cs2 is the second weighing value; calculate the third real-time distance as: Js3=Bb×Cs3; where Js3 is the third real-time distance, and Cs3 is the third weighing value; calculate the fourth real-time distance as: Js4=Bb×Cs1; where Js4 is the fourth real-time distance, and Cs4 is the fourth weighing value.

[0105] Step S6, obtaining a real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance, and the fourth real-time distance; Step S6 includes the following sub-steps:

[0106] Step S601: Calculate the absolute value of the difference between the first real-time distance and the third real-time distance, marking it as the first difference; obtain a weighing reference point corresponding to the larger value between the first real-time distance and the third real-time distance, marking it as the first direction reference point; and draw a line segment with a length of the first difference, starting from the reference center and toward the first direction reference point, marking it as the first line segment.

[0107] Step S602: Calculate the absolute value of the difference between the second real-time distance and the fourth real-time distance, marking it as the second difference; obtain a weighing reference point corresponding to the larger value between the second real-time distance and the fourth real-time distance, marking it as the second direction reference point; and draw a line segment starting from the reference center and in the direction of the second direction reference point with a length of the second difference, marking it as the second line segment;

[0108] Step S603: Connect the endpoints of the first line segment and the second line segment to obtain a third line segment, connect the reference center and the midpoint of the third line segment to obtain a fourth line segment, and mark the length of the fourth line segment as a real-time quantized value.

[0109] Step S7, obtaining a final quantitative threshold based on the data of the second number of logistics vehicles that normally transport goods; Step S7 includes the following sub-steps:

[0110] Step S701: obtaining a second number of real-time quantitative values ​​of logistics vehicles that can normally transport goods, and marking them as historical quantitative values;

[0111] Step S702: sort the historical quantization values ​​from small to large and mark them as Lh1 to Lh i ;

[0112] Step S703, obtain the first position value: Wz1=k1×D2, where Wz1 is the first position value, k1 is the first coefficient, the setting range of the first coefficient is: (0, 0.5), and D2 is the second quantity; obtain the integer part of the first position value, mark it as F1, and set Lh （F1） The corresponding historical quantitative value is marked as G1;

[0113] Step S704, obtain the second position value: Wz2=k2×D2, where Wz2 is the second position value, k2 is the second coefficient, and the setting range of the second coefficient is: (0.5, 1); obtain the integer part of the second position value, mark it as F2, and set Lh （F2） The corresponding historical quantitative value is marked as G2;

[0114] Step S705 , obtaining an initial quantization threshold value: Hy=G2+(G2-G1) / (k2-k1)×(1-k2); wherein Hy is the initial quantization threshold value;

[0115] Step S706 : Obtain a historical quantization value that is less than or equal to the initial quantization threshold, and mark it as the final quantization threshold.

[0116] Step S8, limiting the end of vehicle loading and unloading based on the real-time quantization value and the final quantization threshold; Step S8 includes the following sub-steps:

[0117] Step S801, determine in real time whether the real-time quantization value is less than or equal to the final quantization threshold. If so, a logistics vehicle loading and unloading qualified signal is generated. If not, a logistics vehicle loading and unloading unqualified signal is issued, and the loading and unloading personnel adjust the position of the goods in the logistics vehicle until the real-time quantization value is less than or equal to the final quantization threshold; loading and unloading can be completed only when the logistics vehicle loading and unloading qualified signal is generated.

[0118] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0119] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

Claims

1. The IoT-based logistics vehicle loading and unloading identification system is characterized by: include: Setting module, starting module, reference point acquisition module, reference ratio acquisition module, real-time distance acquisition module, real-time quantization value acquisition module, final quantization threshold acquisition module and restriction end module; The setting module is used to install a vehicle-mounted weighing sensor on a logistics vehicle; The starting module is used to obtain a logistics vehicle loading and unloading start signal based on the logistics vehicle networking data; The reference point acquisition module is used to obtain the reference center and weighing reference point based on the logistics vehicle and the vehicle-mounted weighing sensor; The reference ratio acquisition module is used to acquire the reference ratio based on data of the first number of logistics vehicles that normally transport goods; The real-time distance acquisition module is used to calculate the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance based on the reference ratio; The real-time quantization value acquisition module is used to acquire a real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance and the fourth real-time distance; The final quantitative threshold acquisition module is used to acquire the final quantitative threshold based on the data of the logistics vehicles that normally transport goods for a second number of times; The restriction end module is used to restrict the end of vehicle loading and unloading based on the real-time quantization value and the final quantization threshold; The reference point acquisition module is configured with a reference point acquisition module strategy, and the reference point acquisition module strategy includes: Establish a plane rectangular coordinate system, mark it as the logistics vehicle coordinate system, and draw the top view outline of the logistics vehicle in the logistics vehicle coordinate system; obtain the middle coordinate of the top view outline of the logistics vehicle, mark it as the reference center; The first, second, third, and fourth load cells are marked in the coordinate system of the logistics vehicle with reference to the position of the top view outline of the logistics vehicle, and are marked as the first reference point, the second reference point, the third reference point, and the fourth reference point, respectively; the first reference point, the second reference point, the third reference point, and the fourth reference point are collectively referred to as weighing reference points; The real-time distance acquisition module is configured with a real-time distance acquisition strategy, which includes: Obtain values ​​of the first weighing sensor, the second weighing sensor, the third weighing sensor, and the fourth weighing sensor, respectively, and mark them as a first weighing value, a second weighing value, a third weighing value, and a fourth weighing value, respectively; The first real-time distance is calculated as: Js1=Bb×Cs1; where Js1 is the first real-time distance, Bb is the reference ratio, and Cs1 is the first weighing value; the second real-time distance is calculated as: Js2=Bb×Cs2; where Js2 is the second real-time distance, and Cs2 is the second weighing value; the third real-time distance is calculated as: Js3=Bb×Cs3; where Js3 is the third real-time distance, and Cs3 is the third weighing value; the fourth real-time distance is calculated as: Js4=Bb×Cs1; where Js4 is the fourth real-time distance, and Cs4 is the fourth weighing value; The real-time quantization value acquisition module is configured with a real-time quantization value acquisition strategy, and the real-time quantization value acquisition strategy includes: Calculate the absolute value of the difference between the first real-time distance and the third real-time distance, marking it as the first difference; obtain a weighing reference point corresponding to the larger value between the first real-time distance and the third real-time distance, marking it as the first direction reference point; start from the reference center and draw a line segment with a length of the first difference in the direction of the first direction reference point, marking it as the first line segment; Calculate the absolute value of the difference between the second real-time distance and the fourth real-time distance, marking it as the second difference; obtain a weighing reference point corresponding to the larger value between the second real-time distance and the fourth real-time distance, marking it as the second direction reference point; start from the reference center and draw a line segment with a length of the second difference toward the second direction reference point, marking it as the second line segment; Connect the endpoints of the first line segment and the second line segment to obtain a third line segment, connect the reference center and the midpoint of the third line segment to obtain a fourth line segment, and mark the length of the fourth line segment as a real-time quantized value.

2. The IoT-based logistics vehicle loading and unloading identification system according to claim 1 is characterized in that: The setting module is configured with a strategy for installing a vehicle-mounted weighing sensor, and the strategy for installing a vehicle-mounted weighing sensor includes: The four sides of the bottom of the cargo box of the logistics vehicle are marked as the first side, the second side, the third side and the fourth side respectively, and a first weighing sensor is installed between the cargo box and the frame below at a first distance from the first side and the second side; a second weighing sensor is installed between the cargo box and the frame below at a first distance from the second side and the third side; a third weighing sensor is installed between the cargo box and the frame below at a first distance from the third side and the fourth side; a fourth weighing sensor is installed between the cargo box and the frame below at a first distance from the fourth side and the first side; the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are collectively referred to as vehicle-mounted weighing sensors.

3. The IoT-based logistics vehicle loading and unloading identification system according to claim 2 is characterized in that: The starting module is configured with a loading and unloading start judgment strategy, and the loading and unloading start judgment strategy includes: Obtain the network data of logistics vehicles, which includes loading and unloading points and vehicle driving data; when the logistics vehicle arrives at the loading and unloading point and stops, a signal for the start of loading and unloading of the logistics vehicle is issued, and the loading and unloading process is judged to be qualified.

4. The IoT-based logistics vehicle loading and unloading identification system according to claim 3 is characterized in that: The reference ratio acquisition module is configured with a reference ratio acquisition strategy, and the reference ratio acquisition strategy includes: Obtain the values ​​of the onboard weighing sensor of the logistics vehicle during normal cargo transportation for the first number of times, mark them as historical weighing values, obtain the maximum value of the historical weighing values, and mark it as the normal reference value; Get the distance from any weighing reference point to the weighing center and mark it as reference distance; The reference ratio is calculated as: Bb=Jc / Zc; where Bb is the reference ratio, Zc is the normal reference value, and Jc is the reference distance.

5. The IoT-based logistics vehicle loading and unloading identification system according to claim 4 is characterized in that: The final quantization threshold acquisition module is configured with a final quantization threshold acquisition strategy, and the final quantization threshold acquisition strategy includes: Obtain the real-time quantitative value of the logistics vehicles that can normally transport goods for the second time, and mark it as the historical quantitative value; Sort the historical quantitative values ​​from small to large and mark them as Lh1 to Lh i ; The first position value is obtained as follows: Wz1=k1×D2, where Wz1 is the first position value, k1 is the first coefficient, the setting range of the first coefficient is: (0, 0.5), and D2 is the second quantity; obtain the integer part of the first position value, mark it as F1, and Lh （F1） The corresponding historical quantitative value is marked as G1; The second position value is obtained as follows: Wz2=k2×D2, where Wz2 is the second position value, k2 is the second coefficient, and the setting range of the second coefficient is: (0.5, 1); obtain the integer part of the second position value, mark it as F2, and set Lh （F2） The corresponding historical quantitative value is marked as G2; The initial quantization threshold is obtained as follows: Hy=G2+(G2-G1) / (k2-k1)×(1-k2); where Hy is the initial quantization threshold; Obtain historical quantization values ​​that are less than or equal to the initial quantization threshold and mark them as the final quantization threshold.

6. The IoT-based logistics vehicle loading and unloading identification system according to claim 5 is characterized in that: The restriction end module is configured with a restriction end strategy, and the restriction end strategy includes: It is judged in real time whether the real-time quantization value is less than or equal to the final quantization threshold. If so, a qualified signal for logistics vehicle loading and unloading is generated. If not, a failed signal for logistics vehicle loading and unloading is issued. The loading and unloading personnel adjust the position of the goods in the logistics vehicle until the real-time quantization value is less than or equal to the final quantization threshold. The loading and unloading of goods can be completed only when the qualified signal for logistics vehicle loading and unloading is generated.

7. A method for identifying loading and unloading cargo in logistics vehicles based on the Internet of Things, used to implement the system for identifying loading and unloading cargo in logistics vehicles based on the Internet of Things according to any one of claims 1 to 6, characterized in that: The method comprises the following steps: installing a vehicle-mounted weighing sensor on a logistics vehicle; Obtain the start signal of loading and unloading of logistics vehicles based on the logistics vehicle networking data; Obtain reference center and weighing reference point based on logistics vehicle and on-board weighing sensor; The reference ratio is obtained based on the data of the logistics vehicles that normally transport goods for the first time; Calculating a first real-time distance, a second real-time distance, a third real-time distance, and a fourth real-time distance based on a reference scale; Acquire a real-time quantization value based on the first real-time distance, the second real-time distance, the third real-time distance, and the fourth real-time distance; Obtaining a final quantitative threshold based on data of the second number of logistics vehicles that normally transport goods; The end of vehicle loading and unloading is restricted based on the real-time quantified value and the final quantified threshold.

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