scholarly journals Wrinkle-Enabled Highly Stretchable Strain Sensors for Wide-Range Health Monitoring with a Big Data Cloud Platform

2020 ◽  
Vol 12 (38) ◽  
pp. 43009-43017 ◽  
Author(s):  
Jian Huang ◽  
Jian Zhou ◽  
Yangmei Luo ◽  
Gan Yan ◽  
Yi Liu ◽  
...  
Keyword(s):  
Big Data ◽  
Health Monitoring ◽  
Strain Sensors ◽  
Cloud Platform ◽  
Wide Range ◽  
Highly Stretchable

Carbon and metallic-based nanomaterials for strain sensors – a review

2021 ◽  
Vol 06 ◽  
Author(s):  
Pravan Omprakash ◽  
Udaya Bhat K ◽  
Devadas Bhat Panemangalore
Keyword(s):  
Health Monitoring ◽  
Metallic Nanoparticles ◽  
High Strength ◽  
Functionally Graded ◽  
Strain Sensors ◽  
Graded Materials ◽  
Mechanical And Electrical Properties ◽  
Highly Sensitive ◽  
Wide Range ◽  
Carbon Based

: Strain gauges are devices whose electrical resistances vary proportionately with the amount of strain applied on the device. They can be used for real-time applications in the aerospace sector, as a geotechnical tool in tunnels and bridges, in rail monitoring and health monitoring sectors. Nanomaterials have been widely used for this application because they can be flexible, stretchable and have high strength. Several researchers have used numerous carbon-based and metallic nanostructures to develop functionally graded materials. Among carbon-based materials, graphene has been widely researched as a viable material for strain sensors due to its superior mechanical and electrical properties. Also, many metallic nanoparticles have been investigated to design strain sensors that are highly sensitive at a wide range of strains. In this article, a review of carbon and metallic nanomaterial-based strain sensors is presented, with emphasis on applications pertaining to structural health monitoring and wearable devices.

scholarly journals Analysis of Important Fabrication Factors That Determine the Sensitivity of MWCNT/Epoxy Composite Strain Sensors

Materials ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 3875 ◽  
Author(s):  
Mun-Young Hwang ◽  
Lae-Hyong Kang
Keyword(s):  
Carbon Nanotubes ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Conductivity Measurement ◽  
Strain Sensors ◽  
Tunneling Effect ◽  
Gauge Factor ◽  
Filler Concentration ◽  
Structural Health ◽  
Wide Range

Composite sensors based on carbon nanotubes have been leading to significant research providing interesting aspects for realizing cost-effective and sensitive piezoresistive strain sensors. Here, we report a wide range of piezoresistive performance investigations by modifying fabrication factors such as multi-wall carbon nanotubes (MWCNT) concentration and sensor dimensions for MWCNT/epoxy composites. The resistance change measurement analyzed the influence of the fabrication factors on the changes in the gauge factor. The dispersion quality of MWCNTs in the epoxy polymer matrix was investigated by scanning electron microscopy (SEM) images and conductivity measurement results. A configuration circuit was designed to use the composite sensor effectively. It has been shown that, in comparison with commercially available strain gauges, composites with CNT fillers have the potential to attain structural health monitoring capabilities by utilizing the variation of electrical conductivity and its relation to strain or damage within the composite. Based on the characteristics of the MWCNT, we predicted the range of conductivity that can be seen in the fabricated composite. The sensor may require a large surface area and a thin thickness as fabrication factors at minimum filler concentration capable of exhibiting a tunneling effect, in order to fabricate a sensor with high sensitivity. The proposed composite sensors will be suitable in various potential strain sensor applications, including structural health monitoring.

Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

2019 ◽  
Author(s):  
Meghana Bastwadkar ◽  
Carolyn McGregor ◽  
S Balaji
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Intensive Care ◽  
Literature Review ◽  
Health Monitoring ◽  
Data Analytics ◽  
Neonatal Intensive Care ◽  
Big Data Analytics ◽  
Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

ExpanDrogram: Dynamic Visualization of Big Data Segmentation over Time

2021 ◽  
Vol 13 (2) ◽  
pp. 1-27
Author(s):  
A. Khalemsky ◽  
R. Gelbard
Keyword(s):  
Big Data ◽  
Visual Presentation ◽  
Trend Detection ◽  
Dynamic Visualization ◽  
Segmentation Process ◽  
Key Points ◽  
Wide Range ◽  
History Of ◽  
The Individual ◽  
Over Time

In dynamic and big data environments the visualization of a segmentation process over time often does not enable the user to simultaneously track entire pieces. The key points are sometimes incomparable, and the user is limited to a static visual presentation of a certain point. The proposed visualization concept, called ExpanDrogram, is designed to support dynamic classifiers that run in a big data environment subject to changes in data characteristics. It offers a wide range of features that seek to maximize the customization of a segmentation problem. The main goal of the ExpanDrogram visualization is to improve comprehensiveness by combining both the individual and segment levels, illustrating the dynamics of the segmentation process over time, providing “version control” that enables the user to observe the history of changes, and more. The method is illustrated using different datasets, with which we demonstrate multiple segmentation parameters, as well as multiple display layers, to highlight points such as new trend detection, outlier detection, tracking changes in original segments, and zoom in/out for more/less detail. The datasets vary in size from a small one to one of more than 12 million records.

MXene-composited highly stretchable, sensitive and durable hydrogel for flexible strain sensors

2020 ◽  
Author(s):  
Wei Yuan ◽  
Xinyu Qu ◽  
Yao Lu ◽  
Wen Zhao ◽  
Yanfang Ren ◽  
...  
Keyword(s):  
Strain Sensors ◽  
Highly Stretchable

Research on the Performance of Strain Sensors Applied to Bridges

2014 ◽  
Vol 875-877 ◽  
pp. 680-684
Author(s):  
Zhi Liu ◽  
Jing Liu ◽  
Shu Ri Cai
Keyword(s):  
Health Monitoring ◽  
Performance Test ◽  
Strain Sensor ◽  
Safety Monitoring ◽  
Strain Sensors ◽  
Great Role ◽  
Temperature Drift ◽  
Short Life ◽  
Test Analysis ◽  
Health Monitoring System

Strengthening safety monitoring of bridges during service time and improving the capability of emergency support have become the priority of the development of China’s present transportation system. Strain sensors play a great role in bridge detection and health monitoring system. In order to overcome disadvantages of traditional resistance strain sensors, such as big temperature drift, short life and inadaptability in the environment of low temperature and humidity, new arch strain sensors have been developed. This paper mainly discusses the structural and material characteristics of this sensor, as well as the performance test analysis of this strain sensor.

RELATIONSHIP IN IOT AND BIG DATA ANALYTICS: THE OPPORTUNITIES AND OPEN CHALLENGES

2021 ◽  
Vol 83 (4) ◽  
pp. 100-111
Author(s):  
Ahmad Anwar Zainuddin ◽  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Physical World ◽  
Future Directions ◽  
Wide Range ◽  
Time Utilization ◽  
Relationship Of ◽  
The Internet Of Things

Internet of Things (IoT) is an up-and-coming technology that has a wide variety of applications. It empowers physical objects to be organized in a specialized framework to grow its convenience in terms of ease and time utilization. It is to convert the thought of bridging the crevice between the physical world and the machine world. It is also being use in the wide range of the technology in this current situation. One of its applications is to monitor and store data over time from numerous devices allows for easy analysis of the dataset. This analysis can then be the basis of decisions made on the same. In this study, the concept, architecture, and relationship of IoT and Big Data are described. Next, several use cases in IoT and big data in the research methodology are studied. The opportunities and open challenges which including the future directions are described. Furthermore, by proposing a new architecture for big data analytics in the Internet of Things, this paper adds value. Overall, the various types of big IoT data analytics, their methods, and associated big data mining technologies are discussed.

Optimizing the multi-hazard resilience of bridge and building structures

2019 ◽  
Author(s):  
Carlos Mendez-Galindo ◽  
Gianni Moor ◽  
Borja Baillés
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ground Motions ◽  
Seismic Events ◽  
Building Structures ◽  
Expansion Joints ◽  
Shock Absorbers ◽  
Wide Range ◽  
Shock Transmission ◽  
The World

<p>As the expectations of populations all around the world continue to increase in relation to the resilience of their bridges and buildings to hazards such as seismic events, the need for appropriate solutions – which can be applied both to new structures and to existing ones – grows accordingly. A wide range of solutions is available, such as shock absorbers and shock transmission units which can be used to dampen or optimally transmit forces that would otherwise damage a structure, and seismic isolators which can protect buildings and bridges from destructive ground motions. Expansion joints can be equipped with features that protect a bridge, at its key movement nodes, from damage due to larger-than-expected movements, and structural health monitoring (SHM) can be used to enable hazards to be identified and to provide immediate notification of any event that might make a structure unsafe. Various such methods of enhancing resilience of structures to seismic and other hazards are described.</p>

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