Design of Smart Healthcare Data Management System Based on Hadoop

2014 ◽  
Vol 998-999 ◽  
pp. 1121-1124 ◽  
Author(s):  
Min Zhang ◽  
Ren Zhang ◽  
Cheng Sheng Liu
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management System ◽  
Cloud Storage ◽  
Low Cost ◽  
Structural Data ◽  
Data Management System ◽  
Traditional Management ◽  
Healthcare Data ◽  
Smart Healthcare

This paper describes a smart healthcare data management system based on hadoop. Aiming at the disadvantage of Traditional management of medical data such as the increasing cost of consumption and the limited availability of the data, the smart healthcare data management system in this paper introduces a hybrid storage architecture including designs of Structured data storage which supported by RDBMS and Non-structural data storage which supported by Hadoop. This smart healthcare data management system has the advantages of low-cost, high fault tolerance, and scalability, and builds a cloud storage platform applied in the system of smart healthcare.

Database Considerations for an ICU Patient Data Management System

1991 ◽  
Author(s):  
N. Fumai ◽  
C. Collet ◽  
M. Petroni ◽  
K. Roger ◽  
E. Saab ◽  
...  
Keyword(s):  
Data Management ◽  
Real Time ◽  
Data Storage ◽  
Relational Database ◽  
Management System ◽  
Patient Data ◽  
Patient Data Management System ◽  
Data Management System ◽  
Data Types ◽  
Management Structure

Abstract A Patient Data Management System (PDMS) is being developed for use in the Intensive Care Unit (ICU) of the Montreal Children’s Hospital. The PDMS acquires real-time patient data from a network of physiological bedside monitors and facilitates the review and interpretation of this data by presenting it as graphical trends, charts and plots on a color video display. Due to the large amounts of data involved, the data storage and data management processes are an important task of the PDMS. The data management structure must integrate varied data types and provide database support for different applications, while preserving the real-time acquisition of network data. This paper outlines a new data management structure which is based primarily on OS/2’s Extended Edition relational database. The relational database design is expected to solve the query shortcomings of the previous data management structure, as well as offer support for security and concurrency. The discussion will also highlight future advantages available from a network implementation.

Meter Data Management System with Multi-Channel Power Supply and Matrix Electrical Measurements

2013 ◽  
Vol 303-306 ◽  
pp. 995-1001
Author(s):  
Chin Shun Hsu ◽  
Chao Yang Lee ◽  
Feng Sheng Hsu ◽  
Chu Sing Yang
Keyword(s):  
Data Management ◽  
Power Supply ◽  
Management System ◽  
Power Flow ◽  
Low Cost ◽  
Data Management System ◽  
Electrical Measurements ◽  
Channel Power ◽  
Measurement Control ◽  
Switch Circuit

Today, due to the increase in smart grid and DC appliances implement the use of renewable energy, the power consumption of equipment and appliances can be monitored by smart outlet or smart meter. However, if every devices are installed a meter will be very expensive and lack of flexibility. This work proposes a combination of multi-channel power supply and matrix measurement of electrical meter data management system to increase system built facilitate and promote greater consumption analysis flexibility and benefits. The proposed method includes a programmable logic controller (PLC)based Multi-channel power supply switch circuit (MPSC), measurement control circuit and Zigbee intelligent socket (Smart Outlet) for collecting and controlling the power flow with wireless communication. Three types of wireless metering methods are used to compare cost and metering error rate. The experimental results reveal this work can be an efficient and low-cost metering solution.

MEDIC: An on Site Designed Data Management System for Cardiology

1979 ◽  
Vol 18 (04) ◽  
pp. 199-202 ◽  
Author(s):  
F. Lustman ◽  
P. Lanthier ◽  
D. Charbonneau
Keyword(s):  
Data Management ◽  
Management System ◽  
Selection Process ◽  
Low Cost ◽  
Database Management System ◽  
Data Management System ◽  
Data Quality Control ◽  
Data Definition ◽  
And Performance ◽  
Data Independence

A patient-oriented data management system is described. The environment was cardiology with a heavy emphasis on research and the MEDIC system was designed to meet the day to day program needs. The data are organized in speciality files with dynamic patient records composed of subrecords of different types. The schema is described by a data definition language. Application packages include data quality control, medical reporting and general inquiry.After five years of extensive use in various clinical applications, its utility has been assessed as well as its low cost. The disadvantages, the main being the multifile structure, can now be stated as its advantages, like data independence and performance increase. Although the system is now partially outdated, the experience acquired with its use becomes very helpful in the selection process of the future database management system.

HealthBlock: A secure blockchain-based healthcare data management system

2021 ◽  
pp. 108500
Author(s):  
Bessem Zaabar ◽  
Omar Cheikhrouhou ◽  
Faisal Jamil ◽  
Meryem Ammi ◽  
Mohamed Abid
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Healthcare Data

A Healthcare Data Management System on Blockchain Framework

2021 ◽  
Author(s):  
Sandipan Saha ◽  
Asha Majumder ◽  
Tanmay Bhowmik ◽  
Abhishek Basu ◽  
Amitava Choudhury
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Healthcare Data

Research on Data Management System for Live Detection

2015 ◽  
Vol 734 ◽  
pp. 22-26
Author(s):  
Ying Chen ◽  
Hui Fen Liao ◽  
Qian Peng ◽  
Wei Wang ◽  
Yong Xing Cao ◽  
...  
Keyword(s):  
Information System ◽  
Power System ◽  
Data Management ◽  
Data Storage ◽  
Management System ◽  
Secure Communication ◽  
Field Testing ◽  
Electric Power System ◽  
Data Management System ◽  
Secure Access

In order to raise the efficiency of on-site live detection, we proposed a new study of live detection data management system which based piconet and Electric Power System Secure Access Platform(EPSSAP). Piconet of comprehensive multi professional testing equipments with Bluetooth technology is established to wireless acquisite field testing data. Using mobile APN secure access technology, secure communication between the intranet information system and PC power system is realized. Application of the platform will provide basis for a unified multiple data acquisition system, extend functions of intranet information system, such as data storage, information processing regulate the process of on-site live detection work and improve the efficiency of the use of live detection data.

scholarly journals Data Management System for a Semiautonomous Shuttle Car for Underground Room and Pillar Coal Mines

Automation ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 153-172
Author(s):  
Vasilis Androulakis ◽  
Steven Schafrik ◽  
Joseph Sottile ◽  
Zach Agioutantis
Keyword(s):  
Data Processing ◽  
Data Management ◽  
Real Time ◽  
Data Storage ◽  
Autonomous Navigation ◽  
Management System ◽  
Reliable Data ◽  
The Other ◽  
Data Management System ◽  
Shuttle Car

In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart mine, necessitates the development of a reliable data management strategy. Ideally, this strategy will allow for fast and asynchronous access to the data for real-time processing and decision-making purposes as well as for visualization through a corresponding human–machine interface. The proposed system has been developed for autonomous navigation of a coalmine shuttle car and has been implemented on a 1/6th scale shuttle car in a mock mine. It comprises three separate nodes, namely, a data collection node, a data management node, and a data processing and visualization node. This approach was dictated by the large amount of collected data and the need to ensure uninterrupted and fast data management and flow. The implementation of an SQL database server allows for asynchronous, real-time, and reliable data management, including data storage and retrieval. On the other hand, this approach introduces latencies between the data management node and the other two nodes. In general, these latencies include sensor latencies, network latencies, and processing latencies. However, the data processing and visualization module is able to retrieve and process the latest data and make a decision about the next optimal movement of the shuttle car prototype in less than 900 ms. This allows the prototype to navigate efficiently around the pillars without interruptions.

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