Intelligent cargo rack system based on gravity sensor

Abstract

The invention provides an intelligent cargo rack system based on a gravity sensor. The intelligent cargo rack system is characterized in that the repertory change of carried cargos can be monitored in real time by monitoring the gravity information of loads of a cargo rack. The intelligent cargo rack system comprises a gravity sensor and an analysis control module, wherein the gravity sensor can monitor the gravity information of the loads of the cargo rack in real time, and is transmitted to an analysis control module; the analysis control module stores the gravity data of each kind of the cargos carried by the cargo rack; when the carrying force of the cargo rack is changed, the change quantity and the cargo gravity data are matched, and the type and the quantity of the cargoes increased or decreased on the cargo rack can be known; the cargo repertory data can be correspondingly operated.

Description

technical field [0001] The invention relates to the field of warehousing, in particular to the field of intelligent shelves capable of monitoring inventory. Background technique [0002] Counting the quantity of goods stored on traditional shelves depends on manual work, which is inefficient and has low accuracy. And for the real-time monitoring demand of inventory, the method of manual counting cannot meet. Contents of the invention [0003] The invention provides an intelligent shelf capable of intelligently implementing and monitoring inventory quantity. Including: gravity sensor, analysis control module. [0004] The gravity sensor can monitor the gravity information of the load on the shelf in real time, and transmit the information to the analysis control module. [0005] The analysis control module is a computer that can be connected to the gravity sensor and can run corresponding software. [0006] The analysis control module stores the gravity data of each typ...

AI Technical Summary

Problems solved by technology

[0002] Counting the quantity of goods stored on traditional shelves depends on manual work, which is inefficient and accurate

And for the real-time monitoring needs of inventory, the method of manual inventory cannot meet