Offline intelligent store management system based on Internet of Things

Abstract

The invention discloses an offline intelligent store management system based on the Internet of Things. The method comprises the following steps: step 1, establishing offline intelligent store management hardware equipment of the Internet of Things; 2, designing an offline intelligent store management process of the Internet of Things; step 3, analyzing hot commodities in the store; 4, analyzing the store passenger flow; and step 5, carrying out online application on the constructed intelligent store management system, and analyzing commodity flow data in the store and hot commodities in the store in real time. Aiming at an intelligent store management problem, the invention provides an offline intelligent store management system based on the Internet of Things, and in order to improve a data weight which has a great influence on a model in time series data, weaken a data weight which has a small influence on the model and solve a problem of difference of different data, the invention improves an LSTM hot commodity prediction model, convolution operation is set at the front end of the LSTM, and screening of time sequence data is achieved.

Description

technical field [0001] The invention relates to the field of the Internet of Things, in particular to an offline intelligent store management system based on the Internet of Things. Background technique [0002] With the continuous development of modern enterprises, chain stores and other branches are increasing rapidly, which not only greatly increases the workload of on-site management, but also poses a big challenge to the effectiveness of management. From our experience, the current problems and challenges facing chain stores are as follows: first, how to patrol stores at low cost, quickly and efficiently, grasp the most cutting-edge information at any time, and release personnel and capital investment; second, how to quickly obtain accurate information Store customer flow data provides data support and business reference for background management and business operations; the third is how to mine sensitive business information, grasp market development trends at a macro ...

AI Technical Summary

Problems solved by technology

From our experience, the current problems and challenges facing chain stores are as follows: first, how to patrol stores at low cost, quickly and efficiently, grasp the most cutting-edge information at any time, and release personnel and capital investment; second, how to quickly obtain accurate information Store passenger flow data, providing data support and business reference for background management, business operations, etc.; third, how to mine sensitive business information, grasp market development trends at a macro level, and make accurate decisions quickly

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