研究生: |
陳泱任 Yang-Ren Chen |
---|---|
論文名稱: |
嵌入式物聯網醫療照護 監控與通訊平台設計與實現 The Design and Implementation of the Surveillance and Communication Platform for the Embedded IoT Healthcare System |
指導教授: |
沈中安
Chung-An Shen |
口試委員: |
陳永耀
Yung-Yao Chen 吳晉賢 Chin-Hsien Wu |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2021 |
畢業學年度: | 109 |
語文別: | 中文 |
論文頁數: | 52 |
中文關鍵詞: | 嵌入式 、監控 、通訊 |
外文關鍵詞: | Embedded System, Surveillance, Communication |
相關次數: | 點閱:266 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
於科技以及醫療技術的迅速發展,但醫療技術的進步仍舊趕不及醫療照護的需求,為了滿足醫療照護的需求,因此將科技結合醫療技術形成的醫療照護物聯網(Internet of Things for Healthcare),醫療照護物聯網的應用有許多面向之功能,像是監控病房內的情況、收集患者之身理資訊、患者緊急呼叫系統,結合不同面向的醫療需求可節省人力支出並提升醫療品質。
本篇論文基於一醫療照護物聯網結合監控以及通訊的嵌入式平台進行實現。在本篇論文中將呈現此嵌入式平台如何設計以及實現,透過AoS(Always-on Sensor)攝影機將影像傳送至嵌入式平台中,將影像進行軟體的處理,透過VoIP(Voice over Internet Protocol)中的網路通訊協定將所要發送的資訊發送至醫護人員,並且患者及醫護人員之間也可以透過VoIP建立通話。在此架構下可透過嵌入式平台即時獲得影像資訊,也可以透過嵌入式平台進行緊急呼叫或傳遞緊急需求,使用此嵌入式平台可節省醫護人員的人力支出,同時可以提升醫療品質。
This paper is based on an embedded platform of Internet of Things for Healthcare combined with surveillance and communication. In this paper will show how this embedded platform is designed and implemented. The image is sent to the embedded platform through the AoS (Always-on Sensor) camera, and the image is processed by software in embedded platform. And communication platform uses VoIP (Voice over Internet Protocol). User can establish calls through VoIP. Through VoIP and embedded platform users can complete the emergency call function. Under this architecture, image information can be obtained in Real-Time through the embedded platform, and emergency calls or emergency needs can also be transmitted through the embedded platform. Using this embedded platform can save medical staff's manpower expenditure while improving the quality of medical care.
[1] ] P. F. Harald Sundmaeker, P. Guillemin, and S. Woelfflé, “Vision and Challenges for Realising the Internet of Things,” Pub.OfficeEU, 2010 [Online]. Available: http://www.internet-of-things-research.eu/pdf/IoT_Clusterbook_March_2010.pdf
[2] F. Firouzi et al., ‘‘Internet-of-Things and big data for smarter healthcare: From device to architecture, applications and analytics,’’ Future Gener. Comput. Syst., vol. 78, pp. 583–586, Jan. 2018. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0167739X17319726
[3] C. M. Patil, B. Jagadeesh and M. N. Meghana, "An Approach of Understanding Human Activity Recognition and Detection for Video Surveillance using HOG Descriptor and SVM Classifier," 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC), Mysore, 2017, pp. 481-485, doi: 10.1109/CTCEEC.2017.8455046.
[4] N. Nguyen, D. Bui and X. Tran, "A Novel Hardware Architecture for Human Detection using HOG-SVM Co-Optimization," 2019 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), Bangkok, Thailand, 2019, pp. 33-36, doi: 10.1109/APCCAS47518.2019.8953123.
[5] F. Andriopoulou, A. Fanariotis, T. Orphanoudakis, “SEEK: SIP-based emergency embedded framework supports elderly and disabled to perform emergency calls,” Proceedings of the Euromicro Conference on Digital System Design (DSD), Prague, Czech Republic (2018), Aug. 29–31
[6] O. Barnich and M. Van Droogenbroeck, ”Vibe: A Universal Background Subtraction Algorithm for Video Sequences,” Image Processing, IEEE Transactions on, 20(6):1709 –1724, june 2011.
[7] S. Hsieh, Y. Hsiao and Y. Huang, "Using margin information to detect regions of interest in images," 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, AK, 2011, pp. 3392-3396, doi: 10.1109/ICSMC.2011.6084193.
[8] Xuzhi Wang, Yuanzheng Liu, Wanggen Wan and Yangyang Jia, "An interpolation motion compensation method for video sequence," IET International Conference on Smart and Sustainable City (ICSSC 2011), Shanghai, 2011, pp. 1-6, doi: 10.1049/cp.2011.0274.
[9] N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2005.
[10] C. Zeng, H. Ma and A. Ming, "Fast human detection using mi-sVM and a cascade of HOG-LBP features," 2010 IEEE International Conference on Image Processing, Hong Kong, 2010, pp. 3845-3848, doi: 10.1109/ICIP.2010.5654100.