Warehousing shared tray system implementation method based on wireless private network

Abstract

The invention discloses a storage shared tray system implementation method based on a wireless private network. The method comprises the following steps: constructing a storage shared tray system based on the wireless private network; the wireless terminal integrated with the shared tray compresses the position data with the position information of the shared tray and transmits the position data to the wireless private network terminal; the wireless private network terminal carries out data encryption on the received position data; the wireless private network terminal transmits the encrypted position data to a base station in a wireless private network channel, the base station transmits the encrypted position data to a core network through a backhaul network, the core network transmits the received position data to a service bearing network, and the service bearing network transmits the received position data to a data service platform; and the data service platform performs smooth processing on the received position data, displays the position data and predicts the advancing path of the tray. The method avoids a mode of renting an operator network, and has the advantages of low cost, convenient network maintenance, fast fault recovery and safe data transmission.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless private networks, and in particular relates to a method for implementing a warehouse shared pallet system based on a wireless private network. Background Art

[0002] At present, logistics pallets have the pain point of "inefficiency and fragility". Most pallets are not shipped out of the warehouse. Each entity in the logistics link purchases pallets for its own use according to its own business peak. In the process of cargo connection, manual disassembly and reorganization are required, which leads to low turnover efficiency and high cargo damage rate. At present, all pallets are ordinary pallets, not shared pallets. Ordinary pallets cannot achieve the effect of intelligent monitoring, and ordinary pallets are not transported with goods, resulting in a large amount of inventory and occupying a lot of space. Pallet circulation and sharing is to achieve efficient logistics and effective circulation of resources, and can realize the automatic optimal scheduling of social resources. By sharing to make full use of idle resources and reduce waste, not only the value of existing resources is maximized, but also new value is created. This, to a large extent, promotes the comprehensive conservation and recycling of resources within the supply chain and promotes sustainable development.

[0003] The shared pallets on the market transmit and interact data based on the networks of the three major operators, namely China Mobile, China Telecom and China Unicom. However, most wireless public networks use the network of leased operators, which is expensive for high-bandwidth leases, lacks sovereignty in network maintenance, takes a long time to recover from failures, and the transmitted information is easily accessible to third parties, which poses a great network security risk. Wireless private networks can effectively make up for the defects of optical fiber and wireless public networks, taking into account the advantages of both. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention proposes a method for implementing a warehouse shared pallet system based on a wireless private network.

[0005] The technical solution of the present invention is as follows: A method for implementing a warehouse shared pallet system based on a wireless private network, comprising: Step 1) constructing a warehouse shared pallet system based on a wireless private network; the warehouse shared pallet system includes a shared pallet with an integrated wireless terminal, a wireless private network terminal, a wireless private network channel and a data service platform; the wireless private network channel includes a base station, a backhaul network, a core network and a service bearer network; Step 2) The wireless terminal integrated with the shared tray compresses the location data having the location information of the shared tray and transmits it to the wireless private network terminal; Step 3) The wireless private network terminal encrypts the received location data; Step 4) The wireless private network terminal transmits the encrypted location data to the base station in the wireless private network channel, and then the base station sends it to the core network through the backhaul network. The core network sends the received location data to the service bearer network, and the service bearer network sends the received location data to the data service platform; Step 5) The data service platform smoothes and displays the received position data and predicts the pallet's travel path.

[0006] Furthermore, the specific method for the wireless terminal integrated in the shared tray to compress the location data having the location information of the shared tray includes: using the LZ77 data compression algorithm to reduce the amount of data transmission, and the calculation formula of the compression calculation rate is: CR=S 原始 / S 压缩 Where CR is the compression calculation ratio; S 原始 is the original data size; S 压缩 is the size of the compressed data.

[0007] Furthermore, the specific method of data encryption includes: The AES encryption algorithm standard is used to calculate the change in information entropy to measure the security of data; the calculation formula for information entropy is as follows: ; In the formula, X For location data, H ( X ) is the information entropy of the location data; p ( x i ) is the value of X i probability; n is the number of all possible values ​​of X; The change in information entropy before and after encryption of location data; H 后 and H 前 They are the information entropy of the location data before and after encryption.

[0008] Furthermore, the data service platform smoothes and displays the received position data, and the specific method for predicting the pallet travel path includes: Step 5-1) The data service platform receives the location data with the location information of the shared pallet, and uses the Kalman filter algorithm to smooth it and calculate the location prediction state of the shared pallet. , and its location prediction covariance is ; In the formula, is to predict the position state at time k based on the estimate at time k−1; is the optimal position state estimate at time k-1; is the control input at time k-1; A is the state transfer matrix; B is the control input matrix; is the predicted covariance matrix of the k-position state at time k-1; is the optimal covariance estimate of the position state at time k-1; is the covariance matrix of the random error of the position state at time k-1; Calculate the Kalman gain for this shared pallet position prediction , and its updated state is estimated to be , and the updated covariance estimate is ; In the formula, H is the observation matrix; is the measurement noise covariance matrix; is the optimal state estimate obtained by combining the predicted value and the measured value; is the actual measured value of the position at time k; is the uncertainty of the position state at time k; I is the unit matrix; Update the location data of shared pallets to improve the accuracy of pallet location; Step 5-2) Display the pallet position of the shared pallet, predict the pallet path and use the root mean square error to measure the prediction accuracy. The root mean square error is , where N is the sample size; To predict the location; is the actual location.

[0009] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a method for implementing a warehouse shared pallet system based on a wireless private network. The method constructs a warehouse shared pallet system based on a wireless private network. The method avoids leasing an operator's network and has the advantages of low cost, convenient network maintenance, fast fault recovery, and secure data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 The present invention is a flowchart of a method for implementing a warehouse shared pallet system based on a wireless private network. DETAILED DESCRIPTION

[0011] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent modifications of the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0012] Example: A method for implementing a warehouse shared pallet system based on a wireless private network of the present invention is as follows: Figure 1 As shown, the specific steps are as follows: Step 1) System construction: building a warehouse shared pallet system based on a wireless private network; the warehouse shared pallet system includes a shared pallet with an integrated wireless terminal, a wireless private network terminal, a wireless private network channel, and a data service platform; the wireless private network channel includes a base station, a backhaul network, a core network, and a service bearer network; Step 2) The terminal reports that the wireless terminal integrated in the shared tray compresses the location data with the location information of the shared tray and transmits it to the wireless private network terminal through the data transmission interface on the wireless private network CPE device; Step 3) Data encryption: the wireless private network terminal encrypts the received location data through the encryption card on the wireless private network terminal; Step 4) Network transmission: The wireless private network terminal transmits the encrypted location data to the base station in the wireless private network channel, and then the base station sends it to the core network through the backhaul network. The core network sends the received location data to the service bearer network, and the service bearer network sends the received location data to the data service platform. Step 5) Display the prediction. The data service platform smoothes and displays the received position data to predict the pallet's travel path.

[0013] Furthermore, the specific method for the wireless terminal integrated in the shared tray to compress the location data having the location information of the shared tray includes: using the LZ77 data compression algorithm to reduce the amount of data transmission, and the calculation formula of the compression calculation rate is: CR=S 原始 / S 压缩 Where CR is the compression calculation ratio; S 原始 is the original data size; S 压缩 is the size of the compressed data.

[0014] Furthermore, the specific method of data encryption includes: The AES encryption algorithm standard is used to calculate the change in information entropy to measure the security of data; the calculation formula for information entropy is as follows: ; Where X is the position data, H( X ) is the information entropy of the location data; p ( x i ) is the value of X i probability; n is the number of all possible values ​​of X; The change in information entropy before and after encryption of location data; H 后 and H 前 They are the information entropy of the location data before and after encryption.

[0015] Furthermore, the data service platform smoothes and displays the received position data. The specific method for predicting the pallet's travel path includes: Step 5-1) The data service platform receives the location data with the location information of the shared pallet, and uses the Kalman filter algorithm to smooth it and calculate the location prediction state of the shared pallet. , and its location prediction covariance is , where is to predict the position state at time k based on the estimate at time k−1; is the optimal position state estimate at time k-1; is the control input at time k-1; A is the state transfer matrix; B is the control input matrix; is the predicted covariance matrix of the k-position state at time k-1; is the optimal covariance estimate of the position state at time k-1; is the covariance matrix of the random error of the position state at time k-1.

[0016] Calculate the Kalman gain for this shared pallet position prediction , and its updated state is estimated to be , and the updated covariance estimate is , where H is the observation matrix; is the measurement noise covariance matrix; is the optimal state estimate obtained by combining the predicted value and the measured value; is the actual measured value of the position at time k; is the uncertainty of the position state at time k; I is the unit matrix.

[0017] Update the location data of shared pallets to improve the accuracy of pallet location; Step 5-2) Display the pallet position of the shared pallet, predict the pallet path and use the root mean square error to measure the prediction accuracy. The root mean square error is , where N is the sample size; To predict the location; is the actual location.

[0018] The above description is only a specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a technician familiar with the technical field within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for implementing a warehouse shared pallet system based on a wireless private network, characterized in that: include: Step 1) constructing a warehouse shared pallet system based on a wireless private network; the warehouse shared pallet system includes a shared pallet with an integrated wireless terminal, a wireless private network terminal, a wireless private network channel and a data service platform; the wireless private network channel includes a base station, a backhaul network, a core network and a service bearer network; Step 2) The wireless terminal integrated in the shared tray compresses the location data having the location information of the shared tray and transmits it to the wireless private network terminal; Step 3) The wireless private network terminal encrypts the received location data; Step 4) The wireless private network terminal transmits the encrypted location data to the base station in the wireless private network channel, and then the base station sends it to the core network through the backhaul network. The core network sends the received location data to the service bearer network, and the service bearer network sends the received location data to the data service platform; Step 5) The data service platform smoothes and displays the received position data and predicts the pallet's travel path.

2. The method for implementing a warehouse shared pallet system based on a wireless private network according to claim 1 is characterized in that: The specific method for the wireless terminal integrated in the shared tray to compress the location data having the location information of the shared tray includes: using the LZ77 data compression algorithm to reduce the amount of data transmission, and the calculation formula of the compression calculation rate is: CR=S 原始 / S 压缩 Where CR is the compression calculation ratio; S 原始 is the original data size; S 压缩 The size of the compressed data.

3. The method for implementing a warehouse shared pallet system based on a wireless private network according to claim 1, characterized in that: The specific method of data encryption includes: The AES encryption algorithm standard is used to calculate the change in information entropy to measure the security of data; the calculation formula for information entropy is as follows: ； In the formula, X For location data, H ( X ) is the information entropy of the location data; p ( x i ) is the value of X i probability; n is the number of all possible values ​​of X; The change in information entropy before and after encryption of location data; H 后 and H 前 They are the information entropy of the location data before and after encryption.

4. The method for implementing a warehouse shared pallet system based on a wireless private network according to claim 1, characterized in that: The data service platform smoothes and displays the received position data, and the specific method for predicting the path of the pallet includes: Step 5-1) The data service platform receives the location data with the location information of the shared pallet, and uses the Kalman filter algorithm to smooth it and calculate the location prediction state of the shared pallet. , and its location prediction covariance is ; In the formula, is to predict the position state at time k based on the estimate at time k−1; is the optimal position state estimate at time k-1; is the control input at time k-1; A is the state transfer matrix; B is the control input matrix; is the predicted covariance matrix of the k-position state at time k-1; is the optimal covariance estimate of the position state at time k-1; is the covariance matrix of the random error of the position state at time k-1; Calculate the Kalman gain for this shared pallet position prediction , and its updated state is estimated to be , and the updated covariance estimate is ; In the formula, H is the observation matrix; is the measurement noise covariance matrix; is the optimal state estimate obtained by combining the predicted value and the measured value; is the actual measured value of the position at time k; is the uncertainty of the position state at time k; I is the unit matrix; Update the location data of shared pallets to improve the accuracy of pallet location; Step 5-2) Display the pallet position of the shared pallet, predict the pallet path and use the root mean square error to measure the prediction accuracy. The root mean square error is , where N is the sample size; To predict the location; is the actual location.

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