物聯網與大數據技術支援下設計及實作
居家健康照護之緊急事件偵測與行為辨識

隨著科技的進步、醫學的發展、人口出生率及死亡率的逐年降低，全球老年人口的比例正大幅提升，隨著高齡化社會的來臨，養老照顧漸漸成為重要的社會議題。而社會上專業養老機構已經無法負荷老年人口持續的成長，居家健康照護必成為未來的趨勢。本論文擬設計一結合物聯網及大數據技術的居家健康照護系統。此系統整合了智慧型感測元件與各種無線通訊技術，藉由物聯網之技術，蒐集受照護者之日常生活資訊，接著透過大數據分析辨識照護者的行為，並監控居家環境可能發生的危險狀況。所有被照護者的資訊都能提供遠端的親人或是醫護人員即時了解。打造一套舒適的照護環境且提高照護品質與擁有緊急事件偵測的系統。減輕家屬與社會的負擔。

關鍵字

居家照護；物聯網；全面感知；緊急事件通知；行為辨識

並列摘要

With the advancement of technology, the development of medicine, birth rate and death rate decreased year by year, the proportion of the world's elderly population is rapidly growing, With the advent of an aging society, old-age care has gradually become an important social issue. But the professional pension institutions of society has been unable to load the elderly population continues to grow, Home health care will be the future trend. Of this thesis intends to design a combination Internet of Things and big data technologies to create a IOT Home health care system. This system incorporates intelligent sensing element with a variety of wireless communication technology.With the Internet of Things technology, is to collect information caregivers daily life. Next, the data obtained through big data analysis techniques identified by caregivers behavior ,and monitoring emergency situations that may occur in the home environment. All caregiver’s information can provide immediate family members or health care workers to understand. Create a comfortable environment and improve quality of care and have emergency detection system. Reduce the burden on families and society.

並列關鍵字

Home Care ； Internet of Things ； Full Sensing ； Emergency Notification ； Behavior recognition

參考文獻

[1] S. Amendola, R. Lodato, S. Manzari, C. Occhiuzzi and G. Marrocco, “RFID Technology for IoT-Based Personal Healthcare in Smart Spaces,” IEEE Internet of Things Journal, April 2014.

[2] G. Yang, L. Xie, M. Mantysalo, X. Zhou, Z. Pang, L. D. Xu, S. K. Walter, Q. Chen and L. Zheng, “A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor and Intelligent Medicine Box,” IEEE Transactions on Industrial Informatics, Nov. 2014.

[3] T.L.M. van Kasteren, G. Englebienne, and B.J.A. Kröse, “Human Activity Recognition from Wireless Sensor Network Data: Benchmark and Software,” In Activity Recognition in Pervasive Intelligent Environments, 2011.

[4] Ehsan Nazerfard, Diane J. Cook, “CRAFFT: An Activity Prediction Model Based on Bayesian Networks,” Springer-Verlag Berlin Heidelberg, 2014.

[6] Jie Wan, Michael J. O’Grady, Gregory M. P. O’Hare, “Dynamic Sensor Event Segmentation for Real-Time Activity Recognition in a Smart Home Context ” Pers Ubiquit Comput 2015

國際替代計量

物聯網與大數據技術支援下設計及實作居家健康照護之緊急事件偵測與行為辨識

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