DSMS in ubiquitous-healthcare: A Borealis-based heart rate variability monitor

Jiang, Xiaorui; Yoo, Sooyoung; Choi, Jinwook

doi:10.1109/bmei.2011.6098425

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Borealis-based Heart Rate Variability Monitor, presented in [ 23 ], belongs to the category of big data processing systems for healthcare systems; it processes data originating from various sources in order to perform desired monitoring activities. It is composed of stream transmitter that represents an interface between sensors collecting data and Borealis application; it encapsulates the collected data into Borealis format in order to obtain a single stream.…”

Section: Big Data-based Healthcare Systemsmentioning

confidence: 99%

Big Data Management for Healthcare Systems: Architecture, Requirements, and Implementation

Aboudi

Benhlima

2018

Advances in Bioinformatics

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The growing amount of data in healthcare industry has made inevitable the adoption of big data techniques in order to improve the quality of healthcare delivery. Despite the integration of big data processing approaches and platforms in existing data management architectures for healthcare systems, these architectures face difficulties in preventing emergency cases. The main contribution of this paper is proposing an extensible big data architecture based on both stream computing and batch computing in order to enhance further the reliability of healthcare systems by generating real-time alerts and making accurate predictions on patient health condition. Based on the proposed architecture, a prototype implementation has been built for healthcare systems in order to generate real-time alerts. The suggested prototype is based on spark and MongoDB tools.

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Section: Big Data-based Healthcare Systemsmentioning

confidence: 99%

Big Data Management for Healthcare Systems: Architecture, Requirements, and Implementation

Aboudi

Benhlima

2018

Advances in Bioinformatics

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“…There are some monitoring applications that by using a DSMS achieve better results, such as monitoring of stock market transactions [5], network traffic [6], [7], [8], and health sensor data [9], [10], which suggests that an EMS based on a DSMS performs better than one based on a DBMS. DSMSs are continuously processing arriving data without having to persist them, this speeds up the data evaluation process, achieving more timely results.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Integration of Building Energy Data

Anjos

Carreira

Francisco

2014

2014 IEEE International Congress on Big Data

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Abstract-An Energy Management System (EMS) is a monitoring tool that tracks buildings energy consumption with the purpose of enhancing energy efficiency, by identifying savings opportunities and misuse situations. To achieve this, EMSs collect data flowsdata streams-from a network of energy meters and sensors, which are then combined into useful information. Data must be processed in real-time, to support a timely decision making process. I. IntroductionBuildings account for 40% of energy consumption, ahead of other sectors, such as industry or transportation [1]. Therefore, small improvements on building energy consumption translate to major savings. Among other ways, energy efficiency in buildings can be achieved through Intelligent Energy Management [2]. This topic refers to monitoring energy consumption, and the careful tracing of energy usage enabling building managers to identify saving opportunities. EMSs continuously monitor the energy consumed in buildings. Consumption related data is evaluated according to several variables such as time, areas and their occupation, equipment state, expected consumption, among others, which determines the building energy usage patterns, providing required information to determine the adjustments towards improving energy usage [3].One fundamental aspect of energy management is timeliness: faster decisions translate to less waste and larger savings. In other words, timely information greatly improves the decision making process [4] since building managers are able to immediately diagnose and promptly respond to anomalous situations. EMSs are real-time decision making applications that require (near) real-time integration of huge quantities of data, wherein each record relates to a very short period [5], thus leading to Big Data challenges: (i) achieve low latency on queries evaluation,

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Real-Time Monitoring Of Building Energy Metering Networks

Anjos¹,

Francisco²,

Carreira³

2015

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DSMS in ubiquitous-healthcare: A Borealis-based heart rate variability monitor

Cited by 3 publications

References 10 publications

Big Data Management for Healthcare Systems: Architecture, Requirements, and Implementation

Big Data Management for Healthcare Systems: Architecture, Requirements, and Implementation

Real-Time Integration of Building Energy Data

Real-Time Monitoring Of Building Energy Metering Networks

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