Design and Implementation of an Intelligent POS System Based on Big Data Technologies

• Main Authors: LIN,CHENG-HUNG, 林政弘
• Other Authors: LUO,MON-YEN
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/jkvct2

碩士 === 國立高雄應用科技大學 === 資訊工程系 === 106 === The global social and economic environment is rapidly changing. Various emerging technologies such as cloud computing, the Internet of Things, and big data are constantly changing the landscape of the industry, leading to a service-oriented and people-centered smart manufacturing trend. The industry is no longer selling a product to users, but the value or ability of a product. Therefore, the industry is no longer offering limited choices to users through products alone. Instead, it provides customization based on the needs of users and the usage of the products. In combination with big data technologies, users are no longer samples of the statistical results. Each user can be a highly individualized and can provide customized services. The purpose of this thesis is to study how to use big data technology, combined with the latest front-end technology to design and implement a smart POS system, how to achieve customer-oriented, improve service quality and intelligent delivery process under such a framework, and how to quickly responding to market needs and make product delivery or production more intelligent in the face of hundreds of sales offices and different sales channels (physical, online, and TV shopping) scattered in different countries. This Research explores how to introduce big data concepts and technologies, and further integrates many different sources within the enterprise, such as raw material purchase and sales records in the internal ERP system, or online shopping systems and member communities, and integrates applications. This information enhances factory manufacturing efficiency and corporate decision-making wisdom.