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Collaborative Research: CISE-MSI: DP: CNS: Efficient Data Communication and Processing for Intelligent Medical Systems with Edge-Cloud Interplay

Collaborative Research: CISE-MSI: DP: CNS: Efficient Data Communication and Processing for Intelligent Medical Systems with Edge-Cloud Interplay
合作研究:CISE-MSI:DP:CNS:具有边缘-云交互的智能医疗系统的高效数据通信和处理
批准号:
2219741
负责人:
Uttam Ghosh
金额:
$36.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31

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中文摘要
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英文摘要
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The healthcare industry’s digital transformation initiative is driven by the need for virtual visits, remote patient monitoring, and consumer wearables. The execution of this initiative will generate vast and diverse data artifacts that need to be analyzed to deliver care to patients anywhere and anytime. The response to COVID-19 has also contributed to developing a holistic and intelligent healthcare capability. Traditionally, cloud computing technology has been employed by healthcare providers for analyzing vast health data. However, the technology suffers from drawbacks such as dependency on a central arbitrator, increase in network latency, and high throughput. In addition, there is a lack of trusted Artificial Intelligent/ Machine Learning (AI/ML) algorithms which can lead to erroneous results causing catastrophic impacts in the healthcare domain and increasing the frequency of security attacks on the cloud infrastructure. This project aims to develop an edge-cloud interplay platform to realize efficient data communication and processing for Intelligent Medical Systems. The platform leverages software-defined 5G and AI-enabled distributed edge-cloud technologies to ensure critical health data is managed securely and made available in a responsive manner. The first step is to develop an SDN-driven architecture to classify healthcare data at the edge devices for real-time service delivery. Next, the project intends to develop models based on AI/ML algorithms to identify patients’ potential medical conditions. The models are to be validated by calculating the access time of the local data from the central server to the local database in any healthcare unit and performing a comparative time analysis. Besides, the interplay between the edge and cloud will be investigated to support the demand for real-time applications for healthcare systems. The project will provide research experiences to students from underrepresented communities in areas at the intersection of AI, SDN, cloud, and edge technologies and also support the modernization of the curriculum at Meharry Medical College.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
SoftChain: Dynamic Resource Management and SFC Provisioning for 5G using Machine Learning
SoftChain:使用机器学习的 5G 动态资源管理和 SFC 配置
DOI: 10.1109/gcwkshps56602.2022.10008691
发表时间: 2022
期刊: 2022 IEEE Globecom Workshops (GC Wkshps
影响因子: --
作者: [Basu, Deborsi, Kal, Soumyadeep, Ghosh, Uttam, Datta, Raja]
通讯作者: Datta, Raja
DOI: 10.1109/jiot.2023.3235382
发表时间: 2023-11
期刊: IEEE Internet of Things Journal
影响因子: 10.6
作者: [Deborsi Basu;Soumyadeep Kal;Uttam Ghosh;R. Datta]
通讯作者: Deborsi Basu;Soumyadeep Kal;Uttam Ghosh;R. Datta
DOI: 10.1109/tnse.2022.3223844
发表时间: 2023-09
期刊: IEEE Transactions on Network Science and Engineering
影响因子: 6.6
作者: [Senthil Murugan Nagarajan;Ganesh Gopal Devarajan;A. Mohammed;T. V. Ramana;Uttam Ghosh]
通讯作者: Senthil Murugan Nagarajan;Ganesh Gopal Devarajan;A. Mohammed;T. V. Ramana;Uttam Ghosh
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)