Edge-of-Things Computing-Based Smart Healthcare System

Any delay introduced in healthcare applications could critically affect the health of patients. Edge computing paradigm has been introduced recently as an alternative to develop such applications, where a rapid response is necessary to ensure the immediate assistance of patients when they need help. In this chapter, the authors propose an edge-of-things computing-based architecture, which illustrates the benefits of the realization of IoT under edge computing approach. The proposed architecture offers significant advantages: 1) it reduces the latency time in the data transmission for processing and analysis; 2) it improves the response time of the delivery of notifications or emergency alerts; 3) it provides real-time processing and big data analysis in the proximity of data sources; 4) it enables interoperability between heterogeneous devices; and 5) it provides security and QoS in the data transmission. The usefulness and relevance of the proposed architecture is evaluated through the implementation of a smart healthcare system applied to a medical case study.

[1]  Rajkumar Buyya,et al.  Fog Computing: Helping the Internet of Things Realize Its Potential , 2016, Computer.

[2]  Jorge Werner,et al.  A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions , 2010, 2010 Second International Conference on eHealth, Telemedicine, and Social Medicine.

[3]  Antonio Pescapè,et al.  Integration of Cloud computing and Internet of Things: A survey , 2016, Future Gener. Comput. Syst..

[4]  Songqing Chen,et al.  FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation , 2015, 2015 IEEE International Conference on Networking, Architecture and Storage (NAS).

[5]  Mingzhe Jiang,et al.  Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction , 2015, 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing.

[6]  Carlos E. Palau,et al.  Fall detection system for elderly people using IoT and Big Data , 2018, ANT/SEIT.

[7]  R. Bourret,et al.  Operational definition of Active and Healthy Ageing (AHA): A conceptual framework , 2015, The journal of nutrition, health & aging.

[8]  Diana Cecilia Yacchirema Vargas,et al.  Smart IoT Gateway For Heterogeneous Devices Interoperability , 2016 .

[9]  Chris D. Nugent,et al.  Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce , 2014, Sensors.

[10]  Sanjay P. Ahuja,et al.  A Survey of the State of Cloud Computing in Healthcare , 2012, Netw. Commun. Technol..

[11]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.

[12]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[13]  Muhammad Ghulam,et al.  Smart Health Solution Integrating IoT and Cloud: A Case Study of Voice Pathology Monitoring , 2017, IEEE Communications Magazine.

[14]  Wei Xiang,et al.  An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare , 2016, Journal of Medical Systems.

[15]  Mingzhe Jiang,et al.  Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach , 2018, Future Gener. Comput. Syst..

[16]  Sandeep K. Sood,et al.  Fog Assisted-IoT Enabled Patient Health Monitoring in Smart Homes , 2018, IEEE Internet of Things Journal.

[17]  Carlos E. Palau,et al.  Design and implementation of a Gateway for Pervasive Smart Environments , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[18]  Joel Pinho Lucas Métodos de clasificación basados en asociación aplicados a sistemas de recomendación , 2010 .