A Context-aware System for Warehouse Goods Positioning

• Main Authors: LI, TAI-SHUN, 黎泰順
• Other Authors: CHANG, CHIN-CHIH
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/b3jn7m

碩士 === 中華大學 === 資訊工程學系 === 105 === The popularity of online shopping and logistics through convenience stores makes the shipping number of warehouse goods grow fast. A better management for warehouse goods is required to facilitate the goods delivery. Internet of Things (IoT) and context-aware technologies are introduced into warehouse management to improve the warehouse operating performance. When goods are attached with sensors, the goods can be monitored on line and the performance of picking goods can be improved especially in the case goods are not arranged properly. Context-awareness indicates the system can respond according to the environment. When applied in warehouse management, context-aware technology can automate the control of equipment or facilities such lights, fans, and air conditioning as well as preventing possible damages. Not only goods but also personnel can be monitored by the system so that the performance of warehouse can be improved. In this study we proposed the positing and context-aware mechanism that can facilitate the positioning objects as long as they are attached with Bluetooth 4.0 devices. A system constructed by integration of Bluetooth 4.0 Beacon and Raspberry Pi 3 is implemented. We can either use a mobile phone to identify an object or monitor an object through a computer. We also add sensors of light and temperature on Raspberry Pi so that the environment change can be detected. In order to improve the precision of an object location we proposed two positioning methods: mean value filtering and adaptive positioning method. The method is validated by experiments. The experimental results show the proposed methods are able to improve the positioning precision of goods.