Artificial Intelligence-Based Decision Support System for COVID-19 Mobile Assessments and Optimal Supply Services During the Pandemic
基于人工智能的决策支持系统,用于大流行期间的 COVID-19 移动评估和最佳供应服务
基本信息
- 批准号:552696-2020
- 负责人:
- 金额:$ 3.64万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Alliance Grants
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The proposed project aims at transforming Canada's response and preparedness posture against COVID-19 with the following unique, feasible and transformative research objectives: 1) Designing realistic predictive models of community spread through mobility behavior of communities, 2) Development of an AI-empowered preparedness and planning framework against pandemic outbreak on vulnerable regions, 3) Development of AI-backed decision support systems for supply services during the pandemic. The results will enable monitoring, modeling and AI-based projections for the deployment of assessment centres alongside the required supply services. Providing AI-empowered digital services to decision makers will enable different levels of governments to make proactive strategies so to facilitate management and logistics for Canadians. Recent pandemic crisis due to COVID-19 outbreak has uncovered two facts: 1) Fragility of supply chains, 2) Vitality of effective strategies for rapid assessments against the outbreak as it is not possible to test the entire population. The project outcomes will provide an AI-backed software service to maximize the assessed population at risk in the shortest possible time based upon the risk maps and with limited resources. In a situation where citizens are encouraged to self-isolate and minimize their social interactions, the agility of supply chains become vital to provide the medical and essential supplies with optimal strategies. Given these challenges, the partnership between uOttawa and Gnowit Inc. will contribute to COVID-19 research through the field of applied machine learning research by developing innovative methods to predict risk scores of multiple zones. Furthermore, the partnership between uOttawa and Lytica Inc. will enable to fill in the missing piece required to fully automate the real-time modelling of supply services during the pandemic. Therefore, once completed successfully, the project will contribute to the resolution of COVID-19 crisis through: 1) improved ability to model community spread, 2) fast maximization of the tested (suspected) population, 3) effective use of available assessment equipment, and 4) AI-backed decision support for supply services.
拟议项目旨在改变加拿大对COVID-19的应对和准备态势,具有以下独特,可行和变革性的研究目标:1)通过社区的流动行为设计社区传播的现实预测模型,2)开发针对脆弱地区大流行爆发的人工智能授权的准备和规划框架,3)开发基于人工智能的疫情期间供应服务决策支持系统。结果将使监测,建模和基于AI的预测能够在所需的供应服务的同时部署评估中心。为决策者提供人工智能授权的数字服务将使各级政府能够制定积极的战略,以促进加拿大人的管理和物流。近期COVID-19爆发引发的疫情危机揭示了两个事实:1)供应链脆弱,2)由于无法对所有人群进行测试,因此快速评估疫情的有效策略至关重要。该项目的成果将提供一个人工智能支持的软件服务,以在最短的时间内,根据风险地图和有限的资源,最大限度地提高评估的风险人口。在鼓励公民自我隔离和尽量减少社会互动的情况下,供应链的敏捷性对于以最佳策略提供医疗和基本用品至关重要。鉴于这些挑战,uOttawa和Gnowit Inc.之间的伙伴关系。将通过开发创新方法来预测多个区域的风险评分,通过应用机器学习研究领域为COVID-19研究做出贡献。此外,uOttawa和Lytica Inc.将能够填补大流行期间供应服务实时建模完全自动化所需的缺失部分。因此,一旦成功完成,该项目将通过以下方式为解决COVID-19危机做出贡献:1)提高社区传播建模能力,2)快速最大化测试(疑似)人群,3)有效使用可用的评估设备,以及4)人工智能支持的供应服务决策支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Kantarci, Burak其他文献
Quantifying User Reputation Scores, Data Trustworthiness, and User Incentives in Mobile Crowd-Sensing
- DOI:
10.1109/access.2017.2660461 - 发表时间:
2017-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Pouryazdan, Maryam;Kantarci, Burak;Song, Houbing - 通讯作者:
Song, Houbing
Multiagent/Multiobjective Interaction Game System for Service Provisioning in Vehicular Cloud
- DOI:
10.1109/access.2016.2575038 - 发表时间:
2016-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Alooaily, Moayad;Kantarci, Burak;Mouftah, Hussein T. - 通讯作者:
Mouftah, Hussein T.
On blockchain integration into mobile crowdsensing via smart embedded devices: A comprehensive survey?
- DOI:
10.1016/j.sysarc.2021.102011 - 发表时间:
2021-01-16 - 期刊:
- 影响因子:4.5
- 作者:
Chen, Zhiyan;Fiandrino, Claudio;Kantarci, Burak - 通讯作者:
Kantarci, Burak
A Local-Optimization Emergency Scheduling Scheme With Self-Recovery for a Smart Grid
智能电网局部优化自恢复应急调度方案
- DOI:
10.1109/tii.2017.2715844 - 发表时间:
2017-12-01 - 期刊:
- 影响因子:12.3
- 作者:
Qiu, Tie;Zheng, Kaiyu;Kantarci, Burak - 通讯作者:
Kantarci, Burak
On Delay Sensitivity Clusters of Microgrid Data Aggregation Under LTE-A Links
LTE-A链路下微电网数据汇聚时延敏感度集群研究
- DOI:
10.1109/blackseacom52164.2021.9527781 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Deniz, Halil;Simsek, Murat;Kantarci, Burak - 通讯作者:
Kantarci, Burak
Kantarci, Burak的其他文献
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{{ truncateString('Kantarci, Burak', 18)}}的其他基金
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2022
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2021
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
Security by Design via Radio Fingerprinting for Autonomous Vehicle (AV) Networks
通过无线电指纹技术为自动驾驶汽车 (AV) 网络设计安全性
- 批准号:
561676-2021 - 财政年份:2021
- 资助金额:
$ 3.64万 - 项目类别:
Alliance Grants
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2020
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2019
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2018
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
Semantic Modelling and Machine Learning Analysis of a Billion+ Electronic Components Products to Support Supply Chain Optimization
对十亿种电子元件产品进行语义建模和机器学习分析,支持供应链优化
- 批准号:
522341-2018 - 财政年份:2018
- 资助金额:
$ 3.64万 - 项目类别:
Engage Grants Program
Mobile social network analytics and mobile edge solutions for trustworthy and reliable urban sensing
移动社交网络分析和移动边缘解决方案,实现值得信赖和可靠的城市感知
- 批准号:
RGPIN-2017-04032 - 财政年份:2017
- 资助金额:
$ 3.64万 - 项目类别:
Discovery Grants Program - Individual
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