Logistics truck punctual arrival recognition method, device and equipment and storage medium

Abstract

The invention discloses a logistics truck punctual arrival recognition method, device and equipment and a storage medium. The method comprises the steps: S1, carrying out the image collection of a platform of a logistics truck, and image set; s2, an Xception model is built based on the Xception network architecture, the learning rate of the model is adjusted to be self-adaptive, and a Dropout layer used for weakening the over-fitting effect of the deep neural network is added to the model; s3, loading a pre-trained pre-training model, inputting the pre-trained pre-training model into the built model, and starting training from the pre-training model through the sample image set; s4, testing the trained model, and outputting to obtain a punctual arrival recognition model; and S5, monitoring and identifying the station scene through the punctual arrival recognition model. The technical problem that the express delivery efficiency is affected due to the fact that the freight car enteringspeed is low, entering recognition is slow, and freight car transportation is likely to be delayed in the existing logistics industry is solved, the freight car entering efficiency can be improved, the recognition speed is high, and logistics intellectualization is achieved.

Description

technical field [0001] The invention belongs to the technical field of logistics intelligence, and in particular relates to a method, device, equipment and storage medium for identifying the punctual arrival of logistics trucks. Background technique [0002] In the logistics industry, with the steady growth of the total logistics demand in recent years, the logistics and transportation network has become more and more prosperous, and the fast logistics and transportation services such as next-day delivery and same-day delivery have become more and more frequent, which has brought real benefits to people. Convenience. In order to meet the ever-changing needs of logistics and transportation, the entire logistics industry is constantly developing in the direction of faster speed and higher service quality. [0003] But relatively, as the logistics and transportation network becomes more and more prosperous, the complexity of the logistics and transportation network is also gett...

AI Technical Summary

Problems solved by technology

[0003] But relatively, as the logistics and transportation network becomes more and more prosperous, the complexity of the logistics and transportation network is also getting higher and higher, which requires higher and higher requirements for the monitoring and control of logistics and transportation, especially truck transportation, which is an important part of logistics and transportation. As part of the process, it needs to load and unload goods at various logistics sites every day. Therefore, logistics sites are often places where trucks are congested and lined up, which often affects the arrival of trucks on time, thereby affecting the efficiency of the entire logistics transportation.

[0004] For trucks arriving on time, the existing automated truck arrival system also relies on the parking lot license plate recognition and access control system, but the speed of trucks entering the site is relatively slow, and they need to wait in line. The delay in transportation will affect the efficiency of express delivery

At the same time, in the existing technology, the intelligence level for the punctual arrival of trucks is not high, the size and resolution of the recognized pictures are limited, and the recognition speed is often slow, which cannot meet the timeliness requirements of the express delivery industry.

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