隨著科技發展與網路的便利性，物聯網( Internet of Things, IoT )已經遍佈在我們生活周遭，透過感測器、嵌入式系統、雲端技術等監測技術快速發展，不論是在家庭中、工業應用、能源管理等相關應用都存在物聯網的概念。
在近幾年中，健康照護之物聯網產品蓬勃發展，民眾很容易透過資訊科技平台取得即時的健康訊息，這也顯示未來許多慢性疾病的自我管理也將隨著遠距醫療照護介入，達成行動健康與雲端照護的境界。
慢性阻塞肺部疾病COPD（Chronic Obstructive Pulmonary Disease, COPD）為全球重要健康問題。身體活動功能下降是COPD患者常見現象，進而導致活動無耐力並影響生活品質。雖然肺部復健訓練能改善病患身體功能，但並非每位病患都能接受肺部復健，病患於居家常因疲憊及擔心症狀加劇而避免身體活動。
在這篇論文中將針對COPD族群開發一個整合式物聯網穿戴裝置，利用環境、生理感測及身體活動測量技術，將智慧型手機應用程式與霧端結合雲端運算技術，設計智慧型的輔助系統，協助病患於居家照護中完成疾病建議之決策系統。此外，透過本篇論文所提出之系統，以相同節點數及數據測試霧端與雲端傳輸協定不同所造成傳輸延遲之影響，經測試後使用資料分散式服務(Data Distribution Service, DDS)相較於HTTPS與MQTT傳輸協定有較優異之表現。

Abstract—With the development of technology and the convenience of the Internet, the Internet of Things (IoT) has spread all around our lives. In recent years, IoT products for health care are very popular. People can easily obtain real-time health information through information technology (IT) platforms. This phenomenon also shows the self-management for many chronic diseases by IT can be largely realized.
Chronic obstructive pulmonary disease (COPD) is a major public health problem. Pulmonary rehabilitation has been identified as the best available means of improving muscle function and exercise tolerance for COPD patients. However, pulmonary rehabilitation provided by hospitals might not be available for every patient. In this study, we propose an integrated IoT wearable device for the COPD patients, using environmental, physiological sensing, and physical activity measurement technologies to combine mobile applications, fog computing and cloud computing technology to design smart auxiliary systems. Such a system can help patients complete the exercise decision-making in home.
In addition, through the system proposed in this study, the latency of data transmission caused by the difference transmission protocols is validated with the same number of nodes and data. The experiment results show the data distribution service (DDS) transmission protocol can outperform HTTPS and MQTT.

[1] A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, "Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications," IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347-2376, 2015.
[2] A. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, "Internet of Things for Smart Cities," IEEE Internet of Things Journal, vol. 1, no. 1, pp. 22-32, 2014.
[3] A. Pantelopoulos and N. G. Bourbakis, "A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 40, no. 1, pp. 1-12, 2010.
[4] M. Jin, H. Zou, K. Weekly, R. Jia, A. M. Bayen, and C. J. Spanos, "Environmental sensing by wearable device for indoor activity and location estimation," in IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 2014, pp. 5369-5375.
[5] S. M. R. Islam, D. Kwak, M. H. Kabir, M. Hossain, and K. Kwak, "The Internet of Things for Health Care: A Comprehensive Survey," IEEE Access, vol. 3, pp. 678-708, 2015.
[6] M. Hamalainen, P. Pirinen, and Z. Shelby, "Advanced Wireless ICT Healthcare Research," in 2007 16th IST Mobile and Wireless Communications Summit, 2007, pp. 1-5.
[7] E. Villalba, D. Salvi, M. Ottaviano, I. Peinado, M. T. Arredondo, and A. Akay, "Wearable and Mobile System to Manage Remotely Heart Failure," IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 6, pp. 990-996, 2009.
[8] C. Yau and W. Chung, "IEEE 802.15.4 Wireless Mobile Application for Healthcare System," in 2007 International Conference on Convergence Information Technology (ICCIT 2007), 2007, pp. 1433-1438.
[9] M. R. Palattella et al., "Standardized Protocol Stack for the Internet of (Important) Things," IEEE Communications Surveys & Tutorials, vol. 15, no. 3, pp. 1389-1406, 2013.
[10] G. Pardo-Castellote, "OMG Data-Distribution Service: architectural overview," in 23rd International Conference on Distributed Computing Systems Workshops, 2003. Proceedings., 2003, pp. 200-206.
[11] W. H. Organization. (2017). Chronic obstructive pulmonary disease (COPD). Available: http://www.who.int/respiratory/copd/en/
[12] S. H. Kim, J. M. Jeong, M. T. Hwang, and C. S. Kang, "Development of an IoT-based atmospheric environment monitoring system," in 2017 International Conference on Information and Communication Technology Convergence (ICTC), 2017, pp. 861-863.
[13] J. Dutta, F. Gazi, S. Roy, and C. Chowdhury, "AirSense: Opportunistic crowd-sensing based air quality monitoring system for smart city," in 2016 IEEE SENSORS, 2016, pp. 1-3.
[14] F. Sanfilippo and K. Y. Pettersen, "A sensor fusion wearable health-monitoring system with haptic feedback," in 2015 11th International Conference on Innovations in Information Technology (IIT), 2015, pp. 262-266.
[15] S. Marathe, D. Zeeshan, T. Thomas, and S. Vidhya, "A Wireless Patient Monitoring System using Integrated ECG module, Pulse Oximeter, Blood Pressure and Temperature Sensor," in 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), 2019, pp. 1-4.
[16] L. Hou et al., "Internet of Things Cloud: Architecture and Implementation," IEEE Communications Magazine, vol. 54, no. 12, pp. 32-39, 2016.
[17] K. Shi, Y. Bi, and L. Jiang, "Middleware-based implementation of smart micro-grid monitoring using data distribution service over IP networks," in 2014 49th International Universities Power Engineering Conference (UPEC), 2014, pp. 1-5.
[18] Eclipse. Mosquitto. Available: https://mosquitto.org/
[19] R.-T. Innovations. (2020). RTI Connext DDS Getting started. Available: https://community.rti.com/static/documentation/connext-dds/6.0.1/doc/manuals/connext_dds/getting_started/index.html