Container door opening and closing information acquisition method and device and electronic equipment
Patent Information
- Application Number
- CN202510260378.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-06
- Publication Date
- 2025-06-13
Smart Images
Figure CN120135643A_ABST
Abstract
Description
Technical Field
[0001] One or more embodiments of this specification relate to the technical field of Internet of Things transportation, and in particular, to a method, apparatus, and electronic device for obtaining the opening and closing information of a container door. Background Art
[0002] With the rapid development of Internet of Things technology in multiple fields such as production, transportation, and logistics, and the increasing complexity of global trade and supply chain management, the storage, transportation, and tracking of goods have become particularly important. During the current container transportation process, there are some potential security risks. For example, valuable items such as electronic devices and dangerous goods such as flammable, explosive, and biochemical materials are easily targeted by criminals for theft, and illegal intrusion into containers occurs from time to time. On the other hand, there have also been reports of illegal replacement of goods after the container is opened for inspection during customs inspections. These security risks pose great challenges to the custody of goods and the smooth progress of logistics. Therefore, in order to address the above problems, there is an urgent need for a method for obtaining the opening and closing information of a container door to monitor the opening and closing state of the container door, so as to ensure the security and integrity during the container transportation process.
[0003] Currently, electromagnetic devices such as reed switches or a single acceleration sensor acquisition method are often used to monitor the opening and closing state of the container door. However, due to the high requirements of electromagnetic devices for the environment (such as the surrounding magnetic field) and installation and maintenance, and the detection data collected by a single acceleration sensor will be affected by the overall vibration of the container, especially the common-mode interference between the vibration of the container body and the movement of the container door, resulting in inaccurate judgment results of the obtained container door opening and closing information, easy to generate misidentification or false alarms, and poor user satisfaction. Summary of the Invention
[0004] Embodiments of this specification provide a method, apparatus, and electronic device for obtaining the opening and closing information of a container door, and the technical solutions are as follows:
[0005] In a first aspect, embodiments of this specification provide a method for obtaining the opening and closing information of a container door, the method including:
[0006] Continuously obtain at least one set of inertial data pairs of the container within a preset time period, the inertial data pairs including container body inertial data and the container door inertial data corresponding to the container body inertial data, the container body inertial data being collected by a first inertial sensor installed at the container body, and the container door inertial data being collected by a second inertial sensor installed at the container door;
[0007] Determine the container body state based on the inertial data of each of the said container bodies, and determine the container door state according to the difference between each inertial data. The container body state is used to characterize whether the stability of the container body is normal within the preset time period, and the container door state is used to characterize whether the stability of the container door is normal within the preset time period. The inertial data difference is the data difference between the container body inertial data and the corresponding container door inertial data of the container body inertial data;
[0008] When both the container body state and the container door state are normal, determine a data feature sample based on each of the inertial data differences, and determine the container door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample. The container door opening and closing information is used to characterize whether the container door is opened within the preset time period.
[0009] In a second aspect, there is provided a device for obtaining container door opening and closing information, the device comprising:
[0010] An acquisition module, configured to continuously acquire at least one set of inertial data pairs of a container within a preset time period. The inertial data pair includes container body inertial data and corresponding container door inertial data of the container body inertial data. The container body inertial data is collected by a first inertial sensor installed at the container body, and the container door inertial data is collected by a second inertial sensor installed at the container door;
[0011] A difference module, configured to determine the container body state of the container based on each of the container body inertial data, and determine the container door state of the container according to the difference between each inertial data. The container body state is used to characterize whether the stability of the container body is normal within the preset time period, and the container door state is used to characterize whether the stability of the container door is normal within the preset time period. The inertial data difference is the data difference between the container body inertial data and the corresponding container door inertial data of the container body inertial data;
[0012] A determination module, configured to, when both the container body state and the container door state are normal, determine a data feature sample based on each of the inertial data differences, and determine the container door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample. The container door opening and closing information is used to characterize whether the container door is opened within the preset time period.
[0013] In a third aspect, there is provided an electronic device, comprising a device processor and a memory;
[0014] The device processor is connected to the memory;
[0015] The memory is used to store executable program code;
[0016] The device processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the steps of the method provided in the first aspect or any possible implementation manner of the first aspect.
[0017] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. Instructions are stored in the computer-readable storage medium. When the instructions run on a computer or a device processor, the computer or the device processor is caused to execute the method provided in the first aspect or any possible implementation manner of the first aspect.
[0018] The beneficial effects brought by the technical solutions provided in some embodiments of this specification at least include:
[0019] In one or more embodiments of this specification, at least one set of inertial data pairs of a container within a preset time period can be continuously acquired, the state of the container body can be determined based on the inertial data of each container body, and the state of the container door can be determined according to the difference of each inertial data. When both the container body state and the container door state are normal, a data feature sample is determined based on the difference of each inertial data, and the opening and closing information of the container door is determined according to the Mahalanobis distance distribution corresponding to the data feature sample. Through the above steps, not only can the opening and closing information of the container door be automatically obtained, but also by separately collecting the inertial data of the container door and the container body, the common-mode interference generated by the vibration of the container body itself can be distinguished from the actual opening and closing information of the container door, and the accuracy of the opening and closing information of the container door is ensured. For various complex transportation environments, the universality and satisfaction of using this method are improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0021] Figure 1 It is a schematic diagram of the system architecture of a method for obtaining the opening and closing information of a container door provided in an embodiment of this specification;
[0022] Figure 2 It is a flowchart of a method for obtaining the opening and closing information of a container door provided in an embodiment of this specification;
[0023] Figure 3 It is a schematic diagram of the structure of a device for obtaining the opening and closing information of a container door provided in an embodiment of this specification;
[0024] Figure 4A schematic structural diagram of an electronic device provided by an embodiment of this specification. Detailed implementation manners
[0025] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application.
[0026] The terms "first", "second", "third", etc. in the specification, claims and the above accompanying drawings of this specification are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.
[0027] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Changes can be made to the functions and arrangements of the described elements without departing from the scope of the content of this specification. Various processes or components can be appropriately omitted, substituted or added to each example. For example, the described methods can be executed in a different order from the described order, and various steps can be added, omitted or combined. In addition, the features described in some examples can be combined into other examples.
[0028] Please refer to Figure 1 , Figure 1 which shows a schematic diagram of the system architecture of a method for obtaining the opening and closing information of the door of a container provided by an embodiment of this specification.
[0029] As Figure 1 shown, the system architecture of the method for obtaining the opening and closing information of the door of the container may at least include a first inertial sensor 10, a second inertial sensor 20, a network 30 and a server 40.
[0030] The first inertial sensor 10 is installed on the box body of the container, and is used to collect the inertial data of the box body and send it to the server 40 through the network 30.
[0031] The second inertial sensor 20 is installed on the door of the container, and is used to collect the inertial data of the door and send it to the server 40 through the network 30.
[0032] The network 30 is a medium for providing a communication link between the first inertial sensor 10 and the server 40 and between the second inertial sensor 20 and the server 40. The network 30 generally uses wireless communication methods such as Bluetooth, LoRa or Wi-Fi.
[0033] Server 40 provides background data processing services.
[0034] In addition, both the container door and the container body can include a locator, a communication terminal, and a power supply terminal. Among them, the positioning module is responsible for obtaining the real-time position information of the container and sending the real-time position information to the processor 40. The communication terminal can include a Sigfox communication terminal and a Bluetooth terminal, and data exchange is carried out with the processor 40 through Sigfox communication, and internal data transmission is realized through the Bluetooth terminal. The power supply terminal can support two modes of conventional charging and solar charging, providing continuous and stable power supply for the system to ensure the long-term operation of the device.
[0035] Next, please refer to Figure 2 , Figure 2 which shows the overall flowchart of a method for obtaining the opening and closing information of a container door provided by an embodiment of this specification.
[0036] As Figure 2 shown, the method for obtaining the opening and closing information of the container door can at least include the following steps:
[0037] Step 201, continuously obtain at least one set of inertial data pairs of the container within a preset time period.
[0038] Among them, the inertial data pair includes the container body inertial data and the container door inertial data corresponding to the container body inertial data. The container body inertial data is collected by a first inertial sensor installed at the container body, and the container door inertial data is collected by a second inertial sensor installed at the container door.
[0039] In the embodiments of this specification, in order to obtain the opening and closing information of the container door, a first inertial sensor and a second inertial sensor can be installed at the container body and the container door of the container respectively by means of magnetic attraction, pasting, riveting, etc. Among them, the first inertial sensor installed at the container body is used to collect the container body inertial data to capture the state of the container body, that is, the vibration or impact received by the entire container body, and the second inertial sensor installed at the container door is used to collect the container door inertial data to capture the movement of the container door. And when installing the inertial sensors respectively, the coordinate systems of the first inertial sensor and the second inertial sensor should be made consistent, so as to ensure that the subsequent inertial data analysis results can accurately correspond to the opening and closing information of the container door. In actual inertial sensor installation operations, it is only necessary to ensure that the corresponding inertial sensors are installed vertically or horizontally with respect to the container body or the container door.
[0040] Then, the inertial sensors can continuously collect multiple sets of inertial sensing data pairs of the container within a preset time period at a set sampling frequency f. In each inertial sensing data pair, it includes the container body inertial data collected by the first inertial sensor and the container door inertial data collected by the second inertial sensor at the same moment.
[0041] Among them, when the sampling frequency is f, and the number of collected samples corresponding to the preset duration w is N, then N = f × w, and all the inertial data of the container door can be expressed as I m ={I m，1 ,..., I m，i ,..., I m，N}, and all the inertial data of the container body can be expressed as I s ={I s，1 ,..., I s，i ,..., I s，N}.
[0042] Optionally, the preset duration w can be set to 1 s, 2 s, etc. And theoretically, when the preset duration w is set to be extremely short, the obtained opening and closing information of the container door can approximately represent the opening and closing state of the container door at that instantaneous moment.
[0043] Optionally, the sampling frequency can be set according to the recommended frequency of the inertial sensor chip used. Common sampling frequencies are 10, 20, 30, etc. Each inertial sensor can use a nine-axis acceleration sensor, with one triaxial accelerometer, one triaxial gyroscope, and one triaxial geomagnetic sensor built in.
[0044] Step 202: Determine the state of the container body based on each piece of the container body inertial data, and determine the state of the container door according to the difference between each piece of inertial data.
[0045] Among them, the container body state is used to characterize whether the stability of the container body is normal within the preset duration, the container door state is used to characterize whether the stability of the container door is normal within the preset duration, and the inertial data difference is the data difference between the container body inertial data and the corresponding container door inertial data of the container body inertial data.
[0046] In the embodiments of this specification, after obtaining each piece of container body inertial data and each piece of container door inertial data through the inertial sensor, since the container body may be in a state of severe vibration, impact, or rolling during transportation, it will cause false interference when analyzing and determining the opening and closing information of each subsequent piece of inertial data, resulting in false alarms. Therefore, it is necessary to first determine the state of the container body according to each piece of container body inertial data, and subtract the container body inertial data during the subsequent calculation of the container door state to eliminate the monitoring error caused by the abnormal state of the container body. Among them, when determining the state of the container body, each piece of container body inertial data can be compared with a preset standard data range or the maximum threshold of the container body inertial data.
[0047] Similarly, during transportation, the container door may also experience abnormal jitter, vibration, or violent opening. Therefore, this situation should be excluded in advance when determining the opening and closing of the container door in the following. Next, to avoid common-mode interference, the inertial data of the container body can be subtracted from its corresponding container body inertial data to obtain the inertial data difference. Further, according to each inertial data difference, the preset difference standard interval or the maximum difference threshold is compared respectively, and the state of the container door is determined according to the comparison result.
[0048] In an implementable manner, determining the state of the container body based on each of the inertial data of the container body includes:
[0049] Calculating the average inertial modulus of the container body based on each of the inertial data of the container body, and comparing the average inertial modulus of the container body with the inertial threshold of the container body to obtain a first comparison result;
[0050] When the first comparison result indicates that the average inertial modulus of the container body is greater than the inertial threshold of the container body, the state of the container body is determined to be abnormal;
[0051] When the first comparison result indicates that the average inertial modulus of the container body is not greater than the inertial threshold of the container body, the state of the container body is determined to be normal.
[0052] In the embodiments of this specification, when determining the state of the container body through the inertial data of each container body, the corresponding modulus can be calculated and averaged first through all the inertial data of the container body within a preset time period, and it is defined as the average inertial modulus of the container body. Assume that the inertial data of the container door within a sampling period is represented as I m ={I m，1 ,...,I m,i ,...,I m,N}, and the calculated average inertial modulus of the container body is M m . Then, the average inertial modulus M m of the container body is compared with the inertial threshold T m of the container body obtained by pre-statistics to obtain a first comparison result. When the first comparison result indicates that the average inertial modulus M m of the container body is greater than the inertial threshold T m of the container body, it can be determined that the state of the container body within this preset time period is abnormal, that is, the stability of the container body exceeds the set threshold, and the container as a whole is in an abnormal vibration, impact, or rolling state. When the first comparison result indicates that the average inertial modulus M m of the container body is not greater than the inertial threshold T m of the container body, it can be determined that the state of the container body within this preset time period is normal.
[0053] Among them, the inertial threshold T mIt can be obtained by collecting a large number of historical inertia data samples. Specifically, the large number of historical inertia data samples may include abnormal inertia data samples and normal inertia data samples. Similarly, the average box inertia modulus corresponding to each data sample is determined by using the average modulus method. When the container is in an abnormal vibration, overturning or even tumbling state, this inertia data sample is used as an abnormal inertia data sample, and in other cases, it is determined as a normal inertia data sample. The above steps are continuously and cyclically executed until a large number of training sample data sufficient to support subsequent calculations are collected, and through statistical calculations and comprehensive analyses, the box inertia threshold T is evaluated. m 。
[0054] In an implementable manner, determining the door state of the container according to the inertia data differences includes:
[0055] Determine the inertia data differences between the box inertia data and the door inertia data in each group of the inertia data pairs, and calculate the average inertia difference modulus based on each of the inertia data differences;
[0056] Compare the average inertia difference modulus with the inertia difference threshold to obtain a second comparison result;
[0057] When the second comparison result shows that the average inertia difference modulus is greater than the inertia difference threshold, the door state of the container is determined to be abnormal;
[0058] When the second comparison result shows that the average inertia difference modulus is not greater than the inertia difference threshold, the door state of the container is determined to be normal.
[0059] In the embodiments of this specification, when determining the door state of the container through the inertia data differences, it is necessary to first calculate the differences between the box inertia data and the door inertia data in each group of inertia data pairs to obtain the inertia data differences corresponding to each group of inertia data pairs. That is, assuming that the door inertia data within a sampling period is represented as I m ={I m,1 ,...,I m,i ,...,I m,N}, and the box inertia data collected within a sampling period is represented as I s ={I s,1 ,...,I s,i ,...,I s,N}, then the inertia data difference I d =I s -I m , and specifically can be represented as I d ={I d，1 ,...,I d，i ,...,I d，N}. Next, calculate the modulus values corresponding to these inertial data differences and take the average, which is defined as the average inertial difference modulus value M. d . Further, the average inertial difference modulus value M d is compared with a pre-determined inertial difference threshold T d to obtain a second comparison result. When the second comparison result indicates that the average inertial difference modulus value M d is greater than the inertial difference threshold T d , it can be determined that the door state of the container is abnormal, that is, the door stability is abnormal, and the door of the container may be violently opened or damaged. When the second comparison result indicates that the average inertial difference modulus value M d is not greater than the inertial difference threshold T d , it can be determined that the door state of the container is normal.
[0060] Among them, the method for obtaining the inertial difference threshold T d is the same as that for the box body inertial threshold T m , and it is obtained by collecting a large number of historical inertial data samples. Specifically, the average modulus method is used to determine the average inertial difference modulus value M d corresponding to all inertial data differences. When the door of the container may be violently opened or damaged, this inertial data difference sample is used as an abnormal inertial data difference sample, and other situations are determined as normal inertial data difference samples. Continuously execute the above steps in a loop until a large number of training sample data sufficient to support subsequent calculations are collected. After statistical calculation and comprehensive analysis, the inertial difference threshold T d is evaluated.
[0061] Step 203: When both the box body state and the door state are normal, determine a data feature sample based on each of the inertial data differences, and determine the door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample.
[0062] Among them, the door opening and closing information is used to represent whether the door is opened within the preset time period.
[0063] In the embodiments of this specification, when both the box body state and the door state are normal, it is necessary to determine the door opening and closing information of the container, that is, whether the door of the container is opened within the preset time period. Among them, the data feature sample corresponding to all inertial data difference data can be determined first through the feature transformation method, and then the Mahalanobis distance distribution corresponding to the data feature sample is further analyzed. Finally, by comparing with the distribution standard determined from the historical inertial data samples, the door opening and closing information of the container is determined according to the comparison result.
[0064] In one implementable manner, when both the box body state and the box door state are normal, determining the data feature sample based on each of the inertia data differences includes:
[0065] When both the box body state and the box door state are normal, determining the feature vectors corresponding to each of the inertia data differences in each feature dimension;
[0066] Stitching and integrating each of the feature vectors to obtain the data feature sample.
[0067] In the embodiments of this specification, when both the box body state and the box door state are determined to be normal, first determining the feature vectors corresponding to each of the inertia data differences in each feature dimension may include statistical features and time-domain features, etc. Among them, the number of collected samples is N, the inertia data of the box door I m ={I m，1 ,..., I m，i ,..., I m，N}, the inertia data of the box body I s ={I s，1 ,..., I s，i ,..., I s，N}, the inertia data difference I d =I s -I m , I d ={I d，1 ,..., I d，i ,..., I d，N}, and Calculating the features in four dimensions of mean, variance, kurtosis, and skewness to obtain the vector μ j , variance vector kurtosis vector κ j and skewness vector γ j respectively as:
[0068]
[0069] Next, stitching and integrating each of the feature vectors to obtain a feature sample with a length K = L×9 where L is the number of feature dimensions.
[0070] In one implementable manner, determining the opening and closing information of the container door of the container according to the Mahalanobis distance distribution corresponding to the data feature sample includes:
[0071] Based on the probability statistics method, determining the mean variance, covariance matrix, and chi-square distribution critical value corresponding to the historical inertia data sample;
[0072] Determining the Mahalanobis distance corresponding to the data feature sample according to the mean variance and the covariance matrix;
[0073] Determine the opening and closing information of the container door based on the Mahalanobis distance and the critical value of the chi-square distribution.
[0074] In the embodiments of this specification, when determining the opening and closing information of the container door according to the data feature samples, a large number of historical inertia data samples can be used first. Through the following probability distribution formula, a large number of feature samples x corresponding to the historical inertia data samples are calculated i The corresponding mean variance μ and covariance matrix Σ:
[0075]
[0076] where M is the number of acquisition time periods in a large number of historical inertia data samples.
[0077] Then, determine the Mahalanobis distance D M (z) corresponding to the data feature samples according to the mean variance and the covariance matrix. The calculation formula is as follows:
[0078]
[0079] Moreover, through statistical analysis, the square of the Mahalanobis distance follows a chi-square distribution. Therefore, by selecting an appropriate confidence level α from a large number of historical inertia data samples, and according to the confidence level α and the degrees of freedom d, the corresponding critical value of the chi-square distribution can be found
[0080] Finally, calculate and analyze the Mahalanobis distance calculated from the newly collected real-time data feature samples and the critical value of the chi-square distribution to determine the opening and closing information of the container door.
[0081] In an implementable manner, the determining the opening and closing information of the container door based on the Mahalanobis distance and the critical value of the chi-square distribution includes:
[0082] Compare the squared value corresponding to the Mahalanobis distance with the critical value of the chi-square distribution to obtain a third comparison result;
[0083] When the third comparison result indicates that the squared value is less than the critical value of the chi-square distribution, the opening and closing information of the container door is determined to be that the door has not been opened within the preset time period;
[0084] When the third comparison result indicates that the squared value is not less than the critical value of the chi-square distribution, the opening and closing information of the door is determined to be that the door has been opened within the preset time period.
[0085] In the embodiments of this specification, when calculating and analyzing the Mahalanobis distance and the critical value of the chi-square distribution, the squared value of the Mahalanobis distance can be determined first Then compare the squared value of the Mahalanobis distance with the determined critical value of the chi-square distribution Perform a comparison to obtain a third comparison result. When the third comparison result indicates that the squared value is less than the chi-square distribution critical value it is determined that the opening and closing information of the container door is that the door has not been opened within the preset time period. When the third comparison result indicates that the squared value is not less than the chi-square distribution critical value it is determined that the opening and closing information of the container door is that the door has been opened within the preset time period.
[0086] In an implementable embodiment, the method further includes:
[0087] When at least one of the box body state and the box door state is determined to be abnormal or the opening and closing information of the box door is determined to be that the box door has been opened within the preset time period, generate an alarm message and upload it to the target terminal.
[0088] In the embodiments of this specification, when at least one of the box body state and the box door state is determined to be abnormal, or the opening and closing information of the box door is determined to be that the box door has been opened within the preset time period, it indicates that the goods inside the container may be abnormal during this preset time period. That is, either the whole container body is in an abnormal vibration, impact or rolling state during transportation, or the box door is in an abnormal jitter, vibration state or forced opening situation, or the box door has been opened within the preset time period, and an alarm message needs to be immediately generated and uploaded to the target terminal for warning.
[0089] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0090] Next, please refer to Figure 3 , Figure 3 which shows a schematic structural diagram of a device for obtaining the opening and closing information of a container door according to an embodiment of this specification. It should be noted that Figure 3 the device for obtaining the opening and closing information of the container door shown is used to execute the method of the embodiment of this application Figure 2 shown. For the sake of convenience of description, only the parts related to the embodiment of this application are shown. For the specific technical details not disclosed, please refer to the embodiment Figure 2 shown in this application.
[0091] As Figure 3 shown, the device for obtaining the opening and closing information of the container door can at least include:
[0092] An acquisition module 301 is configured to continuously acquire at least one set of inertial data pairs of a container within a preset time period. The inertial data pairs include the inertial data of the container body and the inertial data of the container door corresponding to the inertial data of the container body. The inertial data of the container body is collected by a first inertial sensor installed at the container body, and the inertial data of the container door is collected by a second inertial sensor installed at the container door.
[0093] A difference module 302 is configured to determine the state of the container body based on each of the inertial data of the container body, and determine the state of the container door according to each inertial data difference. The state of the container body is used to characterize whether the stability of the container body is normal within the preset time period, and the state of the container door is used to characterize whether the stability of the container door is normal within the preset time period. The inertial data difference is the data difference between the inertial data of the container body and the inertial data of the container door corresponding to the inertial data of the container body.
[0094] A determination module 303 is configured to, when both the state of the container body and the state of the container door are normal, determine a data feature sample based on each of the inertial data differences, and determine the opening and closing information of the container door according to the Mahalanobis distance distribution corresponding to the data feature sample. The opening and closing information of the container door is used to characterize whether the container door is opened within the preset time period.
[0095] In an implementable manner, the difference module 302 is specifically configured to:
[0096] Calculate an average inertial modulus value of the container body based on each of the inertial data of the container body, and compare the average inertial modulus value of the container body with an inertial modulus threshold of the container body to obtain a first comparison result.
[0097] When the first comparison result indicates that the average inertial modulus value of the container body is greater than the inertial modulus threshold of the container body, the state of the container body is determined to be abnormal.
[0098] When the first comparison result indicates that the average inertial modulus value of the container body is not greater than the inertial modulus threshold of the container body, the state of the container body is determined to be normal.
[0099] In an implementable manner, the difference module 302 is specifically further configured to:
[0100] Determine the inertial data difference between the inertial data of the container body and the inertial data of the container door in each group of the inertial data pairs, and calculate an average inertial difference modulus value based on each of the inertial data differences.
[0101] Compare the average inertial difference modulus value with an inertial difference threshold to obtain a second comparison result.
[0102] When the second comparison result indicates that the average inertial difference modulus value is greater than the inertial difference threshold, the door state of the container is determined to be abnormal;
[0103] When the second comparison result indicates that the average inertial difference modulus value is not greater than the inertial difference threshold, the door state of the container is determined to be normal.
[0104] In an implementable manner, the determining module 303 is specifically configured to:
[0105] When both the box state and the door state are normal, determine the eigenvectors corresponding to the inertial data differences in each feature dimension;
[0106] Stitch and integrate each of the eigenvectors to obtain a data feature sample.
[0107] In an implementable manner, the determining module 303 is specifically further configured to:
[0108] Determine the mean variance, covariance matrix, and chi-square distribution critical value corresponding to the historical inertial data sample based on the probability statistics method;
[0109] Determine the Mahalanobis distance corresponding to the data feature sample according to the mean variance and the covariance matrix;
[0110] Determine the door opening and closing information of the container based on the Mahalanobis distance and the chi-square distribution critical value.
[0111] In an implementable manner, the determining module 303 is specifically further configured to:
[0112] Compare the squared value corresponding to the Mahalanobis distance with the chi-square distribution critical value to obtain a third comparison result;
[0113] When the third comparison result indicates that the squared value is less than the chi-square distribution critical value, the door opening and closing information of the container is determined to be that the door has not been opened within the preset time period;
[0114] When the third comparison result indicates that the squared value is not less than the chi-square distribution critical value, the door opening and closing information is determined to be that the door has been opened within the preset time period.
[0115] In an implementable manner, the determining module 303 is specifically further configured to:
[0116] When at least one of the box state and the door state is determined to be abnormal or the door opening and closing information is determined to be that the door has been opened within the preset time period, generate an alarm message and upload it to the target terminal.
[0117] Those skilled in the art can clearly understand that the technical solutions of the embodiments of the present application can be implemented by means of software and / or hardware. The "units" and "modules" in this specification refer to software and / or hardware that can independently complete or cooperate with other components to complete specific functions, where the hardware can be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), etc.
[0118] Each processing unit and / or module of the embodiments of the present application can be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or can be implemented by software that executes the functions described in the embodiments of the present application.
[0119] Next, please refer to Figure 4 , Figure 4 which shows a schematic structural diagram of an electronic device provided by an embodiment of this specification.
[0120] As Figure 4 shown, the electronic device 400 may include: at least one device processor 401, at least one network interface 404, a user interface 403, a memory 405, and at least one communication bus 402.
[0121] Among them, the communication bus 402 can be used to realize the connection and communication of the above-mentioned various components.
[0122] Among them, the user interface 403 may include buttons, and the optional user interface may further include a standard wired interface and a wireless interface.
[0123] Among them, the network interface 404 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.
[0124] Among them, the device processor 401 may include one or more processing cores. The device processor 401 uses various interfaces and lines to connect various parts within the entire electronic device 400, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory 405, and by calling data stored in the memory 405, it executes various functions of the electronic device 400 and processes data. Optionally, the device processor 401 may be implemented in at least one of the hardware forms of DSP, FPGA, and PLA. The device processor 401 may integrate one or several combinations of a CPU, a GPU, and a modem, etc. Among them, the CPU mainly processes the operating system, the user interface, and application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the device processor 401 and may be implemented separately by a single chip.
[0125] Among them, the memory 405 may include RAM or ROM. Optionally, the memory 405 includes a non-transitory computer-readable medium. The memory 405 can be used to store instructions, programs, code, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area can store the data involved in the above-mentioned method embodiments. Optionally, the memory 405 may also be at least one storage device located far from the aforementioned device processor 401. As Figure 4 shown, the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module, and program instructions.
[0126] Specifically, the device processor 401 can be used to call the application program for obtaining the opening and closing information of the container door stored in the memory 405, and specifically perform the following operations:
[0127] Continuously obtain at least one set of inertial data pairs of the container within a preset time period. The inertial data pairs include the inertial data of the container body and the inertial data of the container door corresponding to the inertial data of the container body. The inertial data of the container body is collected by a first inertial sensor installed at the container body, and the inertial data of the container door is collected by a second inertial sensor installed at the container door;
[0128] Based on each of the inertial data of the container body, determine the state of the container body of the container, and determine the state of the container door of the container according to the difference between each inertial data. The state of the container body is used to characterize whether the stability of the container body is normal within the preset time period, and the state of the container door is used to characterize whether the stability of the container door is normal within the preset time period. The difference between the inertial data is the data difference between the inertial data of the container body and the inertial data of the container door corresponding to the inertial data of the container body;
[0129] When both the state of the container body and the state of the container door are normal, determine a data feature sample based on each of the differences between the inertial data, and determine the opening and closing information of the container door according to the Mahalanobis distance distribution corresponding to the data feature sample. The opening and closing information of the container door is used to characterize whether the container door is opened within the preset time period.
[0130] As an option of the embodiment of this specification, the determining the state of the container body of the container based on each of the inertial data of the container body includes:
[0131] Calculate the average inertia modulus of the box based on the inertia data of each box, and compare the average inertia modulus of the box with the box inertia threshold to obtain a first comparison result;
[0132] When the first comparison result indicates that the average inertia modulus of the box is greater than the box inertia threshold, the box state of the container is determined to be abnormal;
[0133] When the first comparison result indicates that the average inertia modulus of the box is not greater than the box inertia threshold, the box state of the container is determined to be normal.
[0134] As an option in the embodiment of this specification, determining the door state of the container according to the difference of each inertia data includes:
[0135] Determine the inertia data difference between the box inertia data and the door inertia data in each group of inertia data pairs, and calculate the average inertia difference modulus based on each inertia data difference;
[0136] Compare the average inertia difference modulus with the inertia difference threshold to obtain a second comparison result;
[0137] When the second comparison result indicates that the average inertia difference modulus is greater than the inertia difference threshold, the door state of the container is determined to be abnormal;
[0138] When the second comparison result indicates that the average inertia difference modulus is not greater than the inertia difference threshold, the door state of the container is determined to be normal.
[0139] As an option in the embodiment of this specification, when the box state and the door state are both normal, determining the data feature sample based on the difference of each inertia data includes:
[0140] When the box state and the door state are both normal, determine the feature vectors corresponding to each inertia data difference in each feature dimension;
[0141] Splice and integrate each feature vector to obtain a data feature sample.
[0142] As an option in the embodiment of this specification, determining the door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample includes:
[0143] Determine the mean variance, covariance matrix and chi-square distribution critical value corresponding to the historical inertia data sample based on the probability statistics method;
[0144] Determine the Mahalanobis distance corresponding to the data feature sample according to the mean variance and the covariance matrix;
[0145] Determine the opening and closing information of the container door based on the Mahalanobis distance and the critical value of the chi-square distribution.
[0146] As an option of the embodiment of this specification, the determining the opening and closing information of the container door based on the Mahalanobis distance and the critical value of the chi-square distribution includes:
[0147] Compare the squared value corresponding to the Mahalanobis distance with the critical value of the chi-square distribution to obtain a third comparison result;
[0148] When the third comparison result indicates that the squared value is less than the critical value of the chi-square distribution, the opening and closing information of the container door is determined as the door not being opened within the preset time period;
[0149] When the third comparison result indicates that the squared value is not less than the critical value of the chi-square distribution, the opening and closing information of the door is determined as the door being opened within the preset time period.
[0150] As an option of the embodiment of this specification, the method further includes:
[0151] When at least one of the box body state and the door state is determined to be abnormal or the opening and closing information of the door is determined as the door being opened within the preset time period, generate an alarm message and upload it to the target terminal.
[0152] The embodiment of this specification also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented. Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical discs, DVDs, CD-ROMs, micro drives, and magneto-optical discs, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nano-systems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.
[0153] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0154] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0155] In several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. 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 displayed or discussed coupling or direct coupling or communication connection between each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.
[0156] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0157] In addition, each functional unit in various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.
[0158] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes: USB flash drives, read-only memory (ROM), random access memory (RAM), mobile hard disks, magnetic disks, or optical discs and other media that can store program codes.
[0159] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory. The memory can include: flash drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, etc.
[0160] The foregoing describes particular embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.
Claims
1. A method for obtaining container door opening and closing information, characterized in that: The method comprises: Continuously acquiring at least one set of inertial data pairs of the container within a preset time period, wherein the inertial data pairs include box body inertial data and box door inertial data corresponding to the box body inertial data, wherein the box body inertial data is acquired by a first inertial sensor installed at the container body, and the box door inertial data is acquired by a second inertial sensor installed at the container door; The state of the container is determined based on the inertia data of each container, and the state of the door of the container is determined according to the difference of each inertia data, wherein the state of the container is used to indicate whether the stability of the container is normal within the preset time, and the state of the door is used to indicate whether the stability of the door of the container is normal within the preset time, and the difference of inertia data is the data difference between the inertia data of the container and the inertia data of the door corresponding to the inertia data of the container; When the state of the container body and the state of the door are both normal, a data feature sample is determined based on the difference of each inertial data, and the door opening and closing information of the container is determined according to the Mahalanobis distance distribution corresponding to the data feature sample. The door opening and closing information is used to characterize whether the door is opened within the preset time length.
2. The method according to claim 1, characterized in that The determining the state of the container based on the inertia data of each container includes: Calculating an average box inertia modulus value based on each of the box inertia data, and comparing the average box inertia modulus value with a box inertia threshold value to obtain a first comparison result; When the first comparison result indicates that the average box inertia modulus is greater than the box inertia threshold, the box state of the container is determined to be abnormal; When the first comparison result indicates that the average box inertia modulus is not greater than the box inertia threshold, the box state of the container is determined to be normal.
3. The method according to claim 1, characterized in that: The determining the door state of the container according to the difference of each inertial data includes: Determine the inertia data difference between the box body inertia data and the box door inertia data in each group of the inertia data pairs, and calculate an average inertia difference modulus value based on each of the inertia data differences; Comparing the average inertia difference modulus value with the inertia difference threshold value to obtain a second comparison result; When the second comparison result is characterized by that the average inertia difference modulus is greater than the inertia difference threshold, the door state of the container is determined to be abnormal; When the second comparison result is characterized by the average inertia difference modulus being no greater than the inertia difference threshold, the door state of the container is determined to be normal.
4. The method according to claim 1, characterized in that: When both the box state and the box door state are normal, determining a data feature sample based on each of the inertial data differences includes: When the state of the box body and the state of the box door are both normal, determining the feature vector corresponding to each of the inertial data differences in each feature dimension; The feature vectors are concatenated and integrated to obtain data feature samples.
5. The method according to claim 1, characterized in that: The determining the door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample includes: Determine the mean variance, covariance matrix and chi-square distribution critical value corresponding to the historical inertial data sample based on probability statistics method; Determine the Mahalanobis distance corresponding to the data feature sample according to the mean variance and covariance matrix; The door opening and closing information of the container is determined based on the Mahalanobis distance and the chi-square distribution critical value.
6. The method according to claim 5, characterized in that The determining the door opening and closing information of the container based on the Mahalanobis distance and the chi-square distribution critical value includes: Comparing the square value corresponding to the Mahalanobis distance with the chi-square distribution critical value to obtain a third comparison result; When the third comparison result is characterized by the square value being less than the chi-square distribution critical value, the container door opening and closing information is determined to be that the container door has not been opened within the preset time period; When the third comparison result is characterized by the square value being not less than the chi-square distribution critical value, the door opening and closing information is determined as the door being opened within the preset time length.
7. The method according to claim 1, characterized in that The method further comprises: When at least one of the box body state and the box door state is determined to be abnormal or the box door opening and closing information determines that the box door is opened within the preset time period, an alarm message is generated and uploaded to the target terminal.
8. A device for acquiring information about the opening and closing of a container door, characterized in that: The device comprises: an acquisition module, configured to continuously acquire at least one set of inertial data pairs of the container within a preset time period, wherein the inertial data pairs include box body inertial data and box door inertial data corresponding to the box body inertial data, wherein the box body inertial data is acquired by a first inertial sensor installed at the container body, and the box door inertial data is acquired by a second inertial sensor installed at the container door; A difference module, used to determine the box state of the container based on each box inertia data, and determine the door state of the container according to the difference of each inertia data, the box state is used to indicate whether the box stability of the container is normal within the preset time length, the door state is used to indicate whether the door stability of the container is normal within the preset time length, and the inertia data difference is the data difference between the box inertia data and the door inertia data corresponding to the box inertia data; A determination module is used to determine a data feature sample based on each inertial data difference when the box body state and the box door state are both normal, and determine the box door opening and closing information of the container according to the Mahalanobis distance distribution corresponding to the data feature sample, wherein the box door opening and closing information is used to characterize whether the box door is opened within the preset time length.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium has instructions stored therein, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the method according to any one of claims 1 to 7.