| 摘要: | 物聯網可實現人與人、人與物，以及物與物間之通訊與交流，因此可作為下一代先進製造系統所需資料收集、資料通訊與決策擬定的基礎建設。無線感測網路具有低成本、低耗電、一個網路可擴充的節點達數萬個等優點，是實現物聯網的關鍵技術之一。雲端運算具有資源彙整、快速彈性調整資源規模、無所不在網路存取等特性，可為個人和企業提供可隨需存取的運算與儲存資源，能為製造業帶來創新的商業應用模式及增加競爭力與獲益。著眼於物聯網與雲端運算之上述優點，本論文研發一個【基於物聯網與雲端運算之設備監控平台】，將可應用於製造工廠之資料收集、資料傳輸和設備監控。有別於既有文獻僅探討單一無線感測網路之議題，本論文考量製造工廠全球化與分散式的特性，針對如何透過雲端以視覺化的方式來管部署於不同工廠與區域的許多無線感測網路進行研究。本論文(1)提出一個系統化的無線感測網路部署機制(包含感測節點的拓樸設計、編號方法、部署流程及自動關聯)，可用來建構容易管理的多感測網路設備監控平台；(2)發展一個雲端無線感測網路管理系統，可以視覺化的方式管理多個無線感測網路的節點；以及(3)建構一個「基於物聯網與雲端運算之設備監控平台」雛形，並完成系統整合測試，驗證了系統設計的可行性。本論文之成果可作為建置基於雲端與多個無線感測網路之多工廠設備監控平台的參考。
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. |
