Intelligent Agent-Based Predict System With Cloud Computing for Enterprise Service Platform in IoT Environment

Weijun Yang,Yuqiang Chen,Ku-Ce Yeh,Yeh-Cheng Chen

doi:10.1109/access.2021.3049256

Abstract

If the product supply shortage occurs during the sales period, customers will turn to other companies, so the enterprise lose the sales opportunity. If the enterprise can predict product demands, and manages the product sales by using the supply chain management prediction system to improve the bottleneck of the inventory, the hot sales product can have more critical time utilization, and the inventory status can be reflected quickly by Internet of Things (IoT). To overcome the problem that the replenishment model cannot show the actual quantity of products on the store shelves, in the paper, we propose an intelligent agent-based prediction system, which serves as a framework to construct an integrated prediction system through the use of radio frequency identification (RFID) technology to design the intelligent product prediction shelf to extract product messages, and the service oriented architecture to develop prediction information to recommend products to the customer. The result of the paper proposes an agent-based cloud computing service platform in IoT and intelligent agents with SOA as backend cloud services. To build a prototype prediction system with performance analysis, it can be proved that the prediction system architecture for intelligent agent-based prediction system could improve operation performance and effectively enhance customer service quality for hot sale products.

Highlights

With the changes in consumption patterns, product life cycle becoming shorter, and dramatic changes in the retail business, the vendors must timely provide diversified product contents with appropriate product promotion programs to meet consumers’ one-stop shopping demand
In this article, it focuses on the time utilization issue of hotsale products for the outlet sales and warehouse management, as well as the combination of radio frequency identification (RFID) technology and multiagents, which provides static display model for the traditional product shelf, while using intelligent shelves serves as the ‘‘last mile’’ to narrow the gap between the consumer and product shelf so as to realize the convenient shelf management, real-time product information response, as well as the interactive product recommendation; so as to facilitate the dynamic response to market changes and customer demands; the RFID characteristics are utilized so as to improve replenishment efficiency and reduce labor costs
(2) Intelligent shelf and interactive customer predict system can supply real-time control of the consumer demand, and the integration with the enterprise information systems will help to improve the operational efficiency of supply chain

Summary

Introduction

With the changes in consumption patterns, product life cycle becoming shorter, and dramatic changes in the retail business, the vendors must timely provide diversified product contents with appropriate product promotion programs to meet consumers’ one-stop shopping demand.

Results

Conclusion