Logistics safety information early warning system and early warning method based on big data analysis

Abstract

The invention belongs to the technical field of logistics safety, and discloses a logistics safety information early warning system and early warning method based on big data analysis. After placing an order, a platform automatically randomly generates two-dimensional code information of a buyer and a seller, and displays the two-dimensional code information. After the goods are picked up, code scanning operation is performed by account login. If there is abnormal information, the platform will receive the signal for alarm feedback; a GPS positioner is used to position the vehicle in real time, and the positioning information is transmitted to the platform through the network, and the network sends the information to buyers and customers through the internet; image information of differentcommodities is obtained through the cameras in the ordinary logistics box and the special logistics box. The damage to the commodities caused by collision is fed back for real-time checking and viewing. The method and the system have the advantages of novel thought and convenient use, can ensure the safety of information, can carry out intelligent alarm, enable the buyer to know the location of goods in real time, and can observe the collision damage situation of the commodities purchased by the buyer in the transportation process in real time.

Description

technical field [0001] The invention belongs to the technical field of logistics security, and in particular relates to a logistics security information early warning system and early warning method based on big data analysis. Background technique [0002] At present, with the development of network technology, people's lives are improving day by day. Logistics and express delivery benefit mankind, bringing great convenience to people, and they can buy all they need without leaving home. However, there are certain problems in the existing technology. Most of the express information is printed or handwritten on a list, and then pasted on the packing box, so that the transaction information, buyer and seller information are exposed, easy to be collected by others, illegal use. At the same time, the existing technology cannot detect whether the information has been stolen or leaked, and cannot perform alarm notifications, and the existing logistics generally only show one loca...

AI Technical Summary

Problems solved by technology

[0004] (1) In the existing technology, most of the express delivery information is printed or handwritten on a list, and then pasted on the packing box, so that the transaction information, buyer and seller information are exposed, easy to be collected by others, and illegally used. When the traditional anti-counterfeiting two-dimensional code is generated using the asymmetric RSA algorithm for encryption operations, a longer key is used to ensure the security of the information, and the modular exponentiation of large numbers is not only inefficient but also The resource requirements of the system are also very demanding

[0005] (2) The existing technology cannot detect whether the information is stolen or leaked, and cannot perform alarm notifications, and the existing logistics generally only display one location to the next location, and cannot accurately display the real-time status of the logistics, neither can it accurately display where the goods are One location can only be known. During transportation, the POS algorithm used by traditional single-chip microcomputers has low analysis efficiency for data, large number of iterations, and low work efficiency, which cannot meet the logistics information analysis of big data.

[0006] (3) The positioning of the currently used GPS locator is not accurate enough, and the transport vehicle is prone to a certain time and distance error when positioning it during the fast moving process, and information security cannot be fully guaranteed

[0007] The existing platform automatically and randomly generates the QR code information of buyers and sellers, and the confidentiality of user information is poor

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