Big Health Application System based on Health Internet of Things and Big Data

Ma, Yujun; Wang, Yulei; Yang, Jun; Miao, Yiming; Li, Wei

doi:10.1109/access.2016.2638449

Cited by 108 publications

(59 citation statements)

References 55 publications

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“…The idea in each case is to take advantage of the sensing, actuating, communications, data processing, identification, and interaction capabilities of objects pertaining to each application domain. Some of the most commonly found in the literature are the Internet of Vehicles [80], Health Internet of Things [81,82], Internet of Personal Health (IoPH) [83], Internet of m-health Things (m-IoT) [84], Internet of Agriculture [85], and Agriculture Internet of Things [86,87]. …”

Section: Other Names Given To the Iotmentioning

confidence: 99%

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Ibarra-Esquer

González-Navarro

Flores-Ríos

et al. 2017

Sensors

128

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Both the idea and technology for connecting sensors and actuators to a network to remotely monitor and control physical systems have been known for many years and developed accordingly. However, a little more than a decade ago the concept of the Internet of Things (IoT) was coined and used to integrate such approaches into a common framework. Technology has been constantly evolving and so has the concept of the Internet of Things, incorporating new terminology appropriate to technological advances and different application domains. This paper presents the changes that the IoT has undertaken since its conception and research on how technological advances have shaped it and fostered the arising of derived names suitable to specific domains. A two-step literature review through major publishers and indexing databases was conducted; first by searching for proposals on the Internet of Things concept and analyzing them to find similarities, differences, and technological features that allow us to create a timeline showing its development; in the second step the most mentioned names given to the IoT for specific domains, as well as closely related concepts were identified and briefly analyzed. The study confirms the claim that a consensus on the IoT definition has not yet been reached, as enabling technology keeps evolving and new application domains are being proposed. However, recent changes have been relatively moderated, and its variations on application domains are clearly differentiated, with data and data technologies playing an important role in the IoT landscape.

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Section: Other Names Given To the Iotmentioning

confidence: 99%

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Ibarra-Esquer

González-Navarro

Flores-Ríos

et al. 2017

Sensors

128

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“…Suciu [52]. Yujun et al proposed a four-layered big health application, system supported by IoHT and big data, for remote disease diagnosis, smart clothing based healthcare, LTE assisted telemedicine, and robotic interactions [53]. Similar frameworks include: monitoring systems for chronic diseases such as cardiovascular and respiratory diseases through IoT sensors [54], mobile healthcare systems for patient monitoring using big data analytics applied on sensor data [55], [56], heterogeneous healthcare big data analytics system for decision making in risk management and patient care [57].…”

Section: State-of-the-art Of Ioht Frameworkmentioning

confidence: 99%

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Asif-Ur-Rahman

Afsana

Mahmud

et al. 2019

IEEE Internet Things J.

177

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Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS) -in terms of faster responsiveness and data-specific complex analytics -has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.

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“…Management of the collected data requires a scalable and distributed network infrastructure that meets high standards , such as cloud infrastructure. Since the big data and cloud computing are rapidly growing areas in the healthcare domain , these technologies need to be included in university smart healthcare courses . For instance, the curriculum of data science course at Indiana University and cloud computing course at the University of Texas at San Antonio incorporate fundamental aspects of big data and cloud computing, respectively and provide training for students in various technological areas .…”

Section: Background and Motivationmentioning

confidence: 99%

Designing a course for smart healthcare engineering education

Rodić-Trmčić

Лабус

Barać

et al. 2017

Comp Applic In Engineering

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Smart healthcare is an emerging concept that relies on the synergy of various engineering concepts and intelligent technical innovations applicable to healthcare. Demand for smart healthcare engineers is anticipated to grow, hence, arising a need to educate profile engineers. The goal of this paper is to introduce an approach to designing a course for smart healthcare engineering education. Through the key topics of the course, students acquired new skills and knowledge from emerging technologies underlying smart healthcare. The proposed approach was evaluated at a graduate course at the Faculty of Organizational Sciences, University of Belgrade. The results indicate that there was a positive impact on the learning process as well as a positive learning experience.

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Big Health Application System based on Health Internet of Things and Big Data

Cited by 108 publications

References 55 publications

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Designing a course for smart healthcare engineering education

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