Smart Internet of Things-enabled Mobile-based Health Monitoring Systems and Medical Big Data in COVID-19 Telemedicine

2021 ◽  
Vol 8 (1) ◽  
pp. 20
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Monitoring Systems ◽  
Health Monitoring Systems ◽  
Medical Big Data

Optimization of Aerospace Big Data Including Integrated Health Monitoring With the Help of Data Analytics

2019 ◽  
pp. 88-104
Author(s):  
Ranganayakulu Chennu ◽  
Vasudeva Rao Veeredhi
Keyword(s):  
Big Data ◽  
Health Monitoring ◽  
Monitoring Systems ◽  
Specific Reference ◽  
Data Logging ◽  
Data Governance ◽  
Fighter Aircraft ◽  
Integrated Health ◽  
Health Monitoring Systems ◽  
Aero Engines

The objective of this chapter is to present the role and advantages of big data governance in the optimal use of integrated health monitoring systems with a specific reference to the aerospace industry. Aerospace manufacturers and many passenger airlines have realized the benefits of sharing and analyzing the huge amounts of data being collected by their latest generation airliners and engines. While aero engines are already equipped with integrated engine health monitoring concepts, aircraft systems are now being introduced with integrated vehicle health monitoring concepts which require large number of sensors. The data generated by these sensors is enormously high and grows over a period of time to constitute a big data to be monitored and analyzed. This chapter aims to give an overview of various systems and their data logging processes, simulations, and data analysis. Various sensors that are required to be used in important systems of a typical fighter aircraft and their functionalities emphasizing the huge volume of data generated for the analysis are presented in this chapter.

Optimization of Aerospace Big Data Including Integrated Health Monitoring With the Help of Data Analytics

2021 ◽  
pp. 1458-1475
Author(s):  
Ranganayakulu Chennu ◽  
Vasudeva Rao Veeredhi
Keyword(s):  
Big Data ◽  
Health Monitoring ◽  
Monitoring Systems ◽  
Specific Reference ◽  
Data Logging ◽  
Data Governance ◽  
Fighter Aircraft ◽  
Integrated Health ◽  
Health Monitoring Systems ◽  
Aero Engines

The objective of this chapter is to present the role and advantages of big data governance in the optimal use of integrated health monitoring systems with a specific reference to the aerospace industry. Aerospace manufacturers and many passenger airlines have realized the benefits of sharing and analyzing the huge amounts of data being collected by their latest generation airliners and engines. While aero engines are already equipped with integrated engine health monitoring concepts, aircraft systems are now being introduced with integrated vehicle health monitoring concepts which require large number of sensors. The data generated by these sensors is enormously high and grows over a period of time to constitute a big data to be monitored and analyzed. This chapter aims to give an overview of various systems and their data logging processes, simulations, and data analysis. Various sensors that are required to be used in important systems of a typical fighter aircraft and their functionalities emphasizing the huge volume of data generated for the analysis are presented in this chapter.

scholarly journals A Novel Smart Healthcare Monitoring System Using Machine Learning and the Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Malik Bader Alazzam ◽  
Fawaz Alassery ◽  
Ahmed Almulihi
Keyword(s):  
Machine Learning ◽  
Blood Pressure ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Blood Pressure Monitoring ◽  
Monitoring Systems ◽  
The Internet ◽  
Pressure Monitoring ◽  
Health Monitoring Systems ◽  
The Internet Of Things

The Internet of Things (IoT) has enabled the invention of smart health monitoring systems. These health monitoring systems can track a person’s mental and physical wellness. Stress, anxiety, and hypertension are key causes of many physical and mental disorders. Age-related problems such as stress, anxiety, and hypertension necessitate specific attention in this setting. Stress, anxiety, and blood pressure monitoring can prevent long-term damage by detecting problems early. This will increase the quality of life and reduce caregiver stress and healthcare costs. Determine fresh technology solutions for real-time stress, anxiety, and blood pressure monitoring using discreet wearable sensors and machine learning approaches. This study created an automated artefact detection method for BP and PPG signals. It was proposed to automatically remove outlier points generated by movement artefacts from the blood pressure signal. Next, eleven features taken from the oscillometric waveform envelope were utilised to analyse the relationship between diastolic blood pressure (SBP) and systolic blood pressure (DBP). This paper validates a proposed computational method for estimating blood pressure. The proposed architecture leverages sophisticated regression to predict systolic and diastolic blood pressure values from PPG signal characteristics.

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