Cloud Computing provides functionality for managing information data in a distributed, ubiquitous and pervasive manner supporting several platforms, systems and applications. This work presents the implementation of a mobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing. The mobile application is developed using Google's Android operating system and provides management of patient health records and medical images (supporting DICOM format and JPEG2000 coding). The developed system has been evaluated using the Amazon's S3 cloud service. This article summarizes the implementation details and presents initial results of the system in practice.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/IEMBS.2010.5628061 | DOI Listing |
Digit Health
January 2025
Ohad Cohen Endocrinology, Tel Hashomer, Israel.
Objective: The objective of this pilot study is to evaluate the feasibility of using an automatic weight management system to follow patients' response to weight reduction medications and to identify early deviations from weight trajectories.
Methods: The pilot study involved 11 participants using Semaglutide for weight management, monitored over a 12-month period. A cloud-based, Wi-Fi-enabled remote weight management system collected and analyzed daily weight data from smart scales.
Water Res
January 2025
State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
Cyanobacterial blooms are increasingly becoming major threats to global inland aquatic ecosystems. Phycocyanin (PC), a pigment unique to cyanobacteria, can provide important reference for the study of cyanobacterial blooms warning. New satellite technology and cloud computing platforms have greatly improved research on PC, with the average number of studies examining it having increased from 5 per year before 2018 to 17 per year thereafter.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy.
This study investigates the potential of deploying a neural network model on an advanced programmable logic controller (PLC), specifically the Finder Opta™, for real-time inference within the predictive maintenance framework. In the context of Industry 4.0, edge computing aims to process data directly on local devices rather than relying on a cloud infrastructure.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Intelligent Control Laboratory, Xi'an Research Institute of High Technology, Xi'an 710025, China.
For public security purposes, distributed surveillance systems are widely deployed in key areas. These systems comprise visual sensors, edge computing boxes, and cloud servers. Resource scheduling algorithms are critical to ensure such systems' robustness and efficiency.
View Article and Find Full Text PDFGenes (Basel)
December 2024
RIKEN BioResource Research Center, 3-1-1 Koyadai, Tsukuba 305-0074, Japan.
With the increasing speed of genomic, transcriptomic, and metagenomic data generation driven by the advancement and widespread adoption of next-generation sequencing technologies, the management and analysis of large-scale, diverse data in the fields of life science and biotechnology have become critical challenges. In this paper, we thoroughly discuss the use of cloud data warehouses to address these challenges. Specifically, we propose a data management and analysis framework using Snowflake, a SaaS-based data platform.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!