IoT Based Development Boards for Smart Healthcare Applications

2018 ◽  
Author(s):  
Malti Bansal ◽  
Bani Gandhi
Keyword(s):  
Healthcare Applications ◽  
Smart Healthcare

Biosensors and Internet of Things in smart healthcare applications: challenges and opportunities

2020 ◽  
pp. 25-53 ◽  
Author(s):  
Maria Pateraki ◽  
Konstantinos Fysarakis ◽  
Vangelis Sakkalis ◽  
Georgios Spanoudakis ◽  
Iraklis Varlamis ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Healthcare Applications ◽  
Smart Healthcare ◽  
Challenges And Opportunities

scholarly journals eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning

2020 ◽  
Vol 4 (4) ◽  
pp. 37
Author(s):  
Khaled Fawagreh ◽  
Mohamed Medhat Gaber
Keyword(s):  
Random Forest ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Theoretic Approach ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Game Theoretic ◽  
Game Theoretic Approach

To make healthcare available and easily accessible, the Internet of Things (IoT), which paved the way to the construction of smart cities, marked the birth of many smart applications in numerous areas, including healthcare. As a result, smart healthcare applications have been and are being developed to provide, using mobile and electronic technology, higher diagnosis quality of the diseases, better treatment of the patients, and improved quality of lives. Since smart healthcare applications that are mainly concerned with the prediction of healthcare data (like diseases for example) rely on predictive healthcare data analytics, it is imperative for such predictive healthcare data analytics to be as accurate as possible. In this paper, we will exploit supervised machine learning methods in classification and regression to improve the performance of the traditional Random Forest on healthcare datasets, both in terms of accuracy and classification/regression speed, in order to produce an effective and efficient smart healthcare application, which we have termed eGAP. eGAP uses the evolutionary game theoretic approach replicator dynamics to evolve a Random Forest ensemble. Trees of high resemblance in an initial Random Forest are clustered, and then clusters grow and shrink by adding and removing trees using replicator dynamics, according to the predictive accuracy of each subforest represented by a cluster of trees. All clusters have an initial number of trees that is equal to the number of trees in the smallest cluster. Cluster growth is performed using trees that are not initially sampled. The speed and accuracy of the proposed method have been demonstrated by an experimental study on 10 classification and 10 regression medical datasets.

scholarly journals The Influence Mechanism of Information Interaction on Value Cocreation Based on the Smart Healthcare Context

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lan Zhang ◽  
Xiu Yang ◽  
Yuan Zhou ◽  
Jialu Sun ◽  
Zixiang Lin
Keyword(s):  
Interaction Mechanism ◽  
Healthcare Services ◽  
Chinese Government ◽  
Healthcare Applications ◽  
High Quality ◽  
Application Form ◽  
Smart Healthcare ◽  
Information Interaction ◽  
Value Cocreation ◽  
The Impact

In recent years, the Chinese government has issued a series of deepening reform policies around smart healthcare, established a diversified technical basis and environmental protection, and deeply excavated the derivative value of healthcare information, aiming to provide high-quality healthcare services for patients. Information interaction in the context of smart healthcare is a kind of health information interaction completed by users with smart healthcare applications as the hub. It is an application form of social behavior and has an impact on value cocreation. Based on the theory of information interaction and value cocreation, this paper systematically reviews the research on information interaction and value cocreation in the smart healthcare context, analyzes the information interaction mode and information interaction mechanism in the smart healthcare context, constructs a theoretical model of the impact of information interaction on value cocreation, and empirically tests the relationship between information interaction and value cocreation in the smart healthcare context. The research of this paper aims to provide high-quality information interaction services for smart healthcare users, promote the dimensional management of information behavior in the context of smart healthcare, and promote the continuous improvement of the operation and management of smart healthcare.

scholarly journals Wearable Triboelectric Sensors Enabled Gait Analysis and Waist Motion Capture for IoT‐Based Smart Healthcare Applications

2021 ◽  
pp. 2103694
Author(s):  
Quan Zhang ◽  
Tao Jin ◽  
Jianguo Cai ◽  
Liang Xu ◽  
Tianyiyi He ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Healthcare Applications ◽  
Smart Healthcare

scholarly journals Leveraging Fog Computing for a Secure and Smart Healthcare

2019 ◽  
Vol 8 (2) ◽  
pp. 6117-6122
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Healthcare Services ◽  
Decision Fusion ◽  
Sensor Data ◽  
Smart Sensors ◽  
Healthcare Applications ◽  
Smart Healthcare ◽  
Iot Devices

From hairbrushes to scales, all devices have sensors embedded in them to collect and communicate data. Smart Healthcare is proving to be an exciting and dynamic area with lots of room for new innovations and the increasing consumer demand for proactive health monitoring devices. Having India poised to spend a lot on healthcare, recent innovations using IoT devices and big data analytics can propel the healthcare industry into the future. Smart healthcare providers are leveraging cloud computing with fog computing to optimize their healthcare services. These smart healthcare applications depend mainly on the raw sensor data collected, aggregated, and analyzed by the smart sensors. Smart sensors these days generate myriad amount of data like text, image, audio, and video that require real-time or batch processing. Aggregating these diverse data from various types of resources remains a dispute till date. To resolve this issue, we have proposed a softwarized infrastructure that integrates cloud computing and fog computing, message brokers, and Tor for supple, safe, viable, and a concealed IoT exploitation for smart healthcare applications and services. Our proposed platform employs machine-to-machine (M2M) messaging, data fusion and decision fusion, and uses rule-based beacons for seamless data management. Our proposed flexBeacon system provides an IoT infrastructure that is nimble, secure, flexible, private, and reasonable. We have also proposed an M2M transceiver and microcontroller for flawless data incorporation of smart healthcare applications and services. Based on the IoT devices’ technical capabilities and resource availability, some systems are capable of making use of homomorphic encryption and zero knowledge proofs. The proposed flexBeacon platform offers seamless management and data aggregation without loss of accuracy. The cost of implementing a softwarized IoT for smart healthcare is also greatly reduced.

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