Express logistics process state detection multi-classification system

Abstract

The invention provides an express logistics process state detection multi-classification system. The system firstly executes a binary classification algorithm subjected to dimension reduction preprocessing through a microprocessor of an acquisition end to preliminarily judge whether the express items are in an abnormal state or not in the current time period; if the express items are in a normal state, covering the data; if the the express items are in the abnormal state, enabling the acquisition end to store the data to an acquisition end memory; and transmitting the calculated statistical characteristic data of the time period to the central processing unit through the communication module, further executing multi-classification analysis and abnormal degree judgment on the central processing unit, and enabling the central processing unit to input a processed result into the database for a client application end to inquire. According to the invention, accurate and detailed abnormal types can be obtained, so that real-time intelligent monitoring of the vibration state of the express logistics process is realized. Meanwhile, data such as temperature, humidity and illumination intensity are included in the detection range, so that the whole detection system is more scientific and perfect.

Description

technical field [0001] The invention relates to the field of logistics transportation monitoring, in particular to an express mail state detection and classification system. Background technique [0002] At present, the algorithm for judging the status of the express logistics process is relatively simple, and the judgment is mainly based on a simple threshold method. For example, if the instantaneous acceleration in a certain direction exceeds a certain threshold, it is considered that the express has an abnormal situation in the logistics process. Such classification The effect is poor, some unexpected situations cannot be recognized, and the reliability of the sensor is overly relied on, and the algorithm itself has no data correction ability. In addition, under normal circumstances, due to the data source of these algorithms, that is, the raw data collected by sensors is relatively small, so that the related algorithms can obtain very incomplete information on the status...

AI Technical Summary

Problems solved by technology

[0002] At present, the algorithm for judging the state of the express logistics process is relatively simple, and the judgment is mainly based on a simple threshold method. For example, if the instantaneous acceleration in a certain direction exceeds a certain threshold, it is considered that the express has an abnormal situation in the logistics process. Such classification The effect is poor, some unexpected situations cannot be recognized, and the reliability of the sensor is overly relied on, and the algorithm itself has no data correction ability

In addition, under normal circumstances, due to the data source of these algorithms, that is, the raw data collected by sensors is relatively small, so that the relevant algorithms can obtain very incomplete information on the status of express logistics.

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