IoMT and DNN-Enabled Drone-Assisted Covid-19 Screening and Detection Framework for Rural Areas

被引:19
作者
Naren N. [1 ]
Chamola V. [1 ]
Baitragunta S. [1 ]
Chintanpalli A. [1 ]
Mishra P. [1 ]
Yenuganti S. [1 ]
Guizani M. [2 ]
机构
[1] BITS-Pilani, India
[2] Qatar University, Qatar
来源
IEEE Internet of Things Magazine | 2021年 / 4卷 / 02期
关键词
Aircraft detection - Antennas - COVID-19 - Deep neural networks - Diagnosis - Intelligent robots - Motion planning - Rural areas;
D O I
10.1109/IOTM.0011.2100053
中图分类号
学科分类号
摘要
Providing rapid testing and proper treatment has become highly challenging due to the rapid and highly unpredictable spread of the coronavirus disease (COVID-19). In most developing countries, rural areas lack adequate medical facilities and medical staff for effective diagnosis and treatment. Recently, there have been several technological advancements across various engineering disciplines such as the Internet of Things, unmanned aerial vehicles (UAVs) or drones, deep neural networks (DNNs), and intelligent robots. This work proposes a prototype that integrates these technologies to develop a payload deployable in a drone to help in providing rapid testing and healthcare. The proposed UAV prototype combines secure patient authentication, an automated disinfection system, and medical sensors as part of the UAV payload. It uses a DNN model for real-time COVID-19 detection. It uses intelligent flight path planning, operational management, battery recharge planning, disinfectant refilling, and strategic location planning to quickly disseminate testing kits and essential medical services to remote locations without direct human involvement. © 2018 IEEE.
引用
收藏
页码:4 / 9
页数:5
相关论文
共 14 条
[1]  
Chamola V., Et al., A comprehensive review of the Covid-19 pandemic and the role of IoT, Drones, AI, Blockchain, and 5G in Managing Its impact, IEEE Access, 8, (2020)
[2]  
Gupta R., Et al., Blockchain-envisioned softwarized multi-swarming UAVs to Tackle Covid-i9 situations, IEEE Network., (2020)
[3]  
Kumar A., Et al., A drone-based networked system and methods for combating coronavirus Disease (Covid-19) Pandemic, Future Generation Computer Systems, 115, pp. 1-19, (2021)
[4]  
Angurala M., Et al., An internet of things assisted drone based approach to reduce rapid spread of Covid-19, J. Safety Science and Resilience, 1, 1, pp. 31-35, (2020)
[5]  
Vekaria D., Et al., 9boost: An AI-based data analytics scheme for Covid-19 prediction and economy boosting, IEEE Internet of Things J.., (2020)
[6]  
Imran A., Et al., Ai4covid-19: Ai enabled preliminary diagnosis for Covid-19 from cough samples via an App, Informatics in Medicine Unlocked, 20, (2020)
[7]  
Kumar H., Anuradha A., Tanwar S., Machine learning-based scheme to identify covid-19 in human bodies, Emerging Technologies for Battling Covid-19, 324, (2021)
[8]  
Luz E., Et al., Towards An Effective and Efficient Deep Learning Model for Covid-19 Patterns Detection in X-Ray Images, (2020)
[9]  
COVID-19: Guidelines on Disinfection of Common Public Places including Offices
[10]  
Rutala W.A., Weber D.J., Guideline for Disinfection and Sterilization in Healthcare Facilities, (2008)