Development of Equipment Monitoring and Control Platform based on IoT Technology and Cloud Computing

• Main Authors: CHAO, YU, 趙瑜
• Other Authors: HUNG, MIN-HSIUNG
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/p6u93z

碩士 === 中國文化大學 === 資訊工程學系 === 106 === Internet of Things (IoT) can realize the communications and interchanges among people-to-people, people-to-thing, and thing-to-thing. Thus, IoT can serve as the infrastructure of data collection, data communication, and decision making for the new-generation advanced manufacturing system. Wireless sensor network (WSN) possesses advantages of low cost, low power consumption, and one network having several ten-thousand nodes. WSN is one of key technologies to construct IoT. Cloud computing (CC) has characteristics of resource pool, rapid and flexible scaling resources, and ubiquitous networking access. CC can provide on-demand computing and storage resources for individuals and enterprises and can thus bring innovative business models for the manufacturing industry to increase competitiveness and gain profits. Considering the above-mentioned advantages of IoT and CC, this thesis develops an IoT and CC-based equipment-monitoring platform, which can be applied in manufacturing factories for data collection, data communication, and equipment monitoring. Different from existing literature, which investigated on issues of a single WSN, this thesis considers the global and distributive characteristics of manufacturing factories and focuses on the study of how to manage multiple WSNs deployed in different factories and regions visually through the cloud. Specifically, this thesis proposes a systematic deployment mechanism of WSN, including the topology design, numbering method, deployment workflow, and association of sensor nodes, for constructing an easy-management equipment-monitoring platform consisting of multiple WSNs. In addition, this thesis develops a cloud-based management platform of WSNs, which can manage sensor nodes of multiple WSNs visually. Finally, this thesis constructs a prototype of IoT and CC-based equipment-monitoring platform to complete the integrated tests and validate the effectiveness of the system designs. The research results can serve as a reference for building cloud-based equipment-monitoring platforms based on multiple WSNs deployed across multiple factories and regions.