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Drone-based AI/IoT Framework for Monitoring, Tracking and Fighting Pandemics
Faculty
Engineering
Year:
2022
Type of Publication:
ZU Hosted
Pages:
Authors:
AbdulHamid Ashraf Atiyah AbdalMuttalib
Staff Zu Site
Abstract In Staff Site
Journal:
Computers, Materials & Continua Tech Science Press (TSP)
Volume:
Keywords :
Drone-based AI/IoT Framework , Monitoring, Tracking , Fighting
Abstract:
Since World Health Organization (WHO) has declared the Coro- navirus disease (COVID-19) a global pandemic, the world has changed. All life’s fields and daily habits have moved to adapt to this new situation. According to WHO, the probability of such virus pandemics in the future is high, and recommends preparing for worse situations. To this end, this work provides a framework for monitoring, tracking, and fighting COVID-19 and future pandemics. The proposed framework deploys unmanned aerial vehicles (UAVs), e.g.; quadcopter and drone, integrated with artificial intelligence (AI) and Internet of Things (IoT) to monitor and fight COVID-19. It consists of two main systems; AI/IoT for COVID-19 monitoring and drone-based IoT system for sterilizing. The two systems are integrated with the IoT paradigm and the developed algorithms are implemented on distributed fog units con- nected to the IoT network and controlled by software-defined networking (SDN). The proposed work is built based on a thermal camera mounted in a face-shield, or on a helmet that can be used by people during pandemics. The detected images, thermal images, are processed by the developed AI algorithm that is built based on the convolutional neural network (CNN). The drone system can be called, by the IoT system connected to the helmet, once infected cases are detected. The drone is used for sterilizing the area that contains multiple infected people. The proposed framework employs a single centralized SDN controller to control the network operations. The developed system is experimentally evaluated, and the results are introduced. Results indicate that the developed framework provides a novel, efficient scheme for monitoring and fighting COVID-19 and other future pandemics.
Author Related Publications
AbdulHamid Ashraf Atiyah AbdalMuttalib, "Multilevel Hierarchical Clustering protocol for wireless sensor networks", The Sixth International Conference on Intelligent Computing and Information Systems (ICICIS 2013), Dec. 14-16, 2013, Cairo, Egypt, 2013
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AbdulHamid Ashraf Atiyah AbdalMuttalib, "IoT-Based Reusable Medical Suit for Daily Life Use in the Era of COVID-19", Tech Science Press (TSP), 2021
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AbdulHamid Ashraf Atiyah AbdalMuttalib, "Seamless handover scheme for MEC/SDN-based vehicular networks", MDPI, 2022
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AbdulHamid Ashraf Atiyah AbdalMuttalib, "Distributed edge computing with blockchain technology to enable ultra-reliable low-latency V2X communications", MDPI, 2022
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AbdulHamid Ashraf Atiyah AbdalMuttalib, "Lightweight Deep Learning-Based Model for Traffic Prediction in Fog-Enabled Dense Deployed IoT Networks", Springer Nature Singapore, 2022
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Department Related Publications
Mohammed Ayesh Muhammad Hanafi, "Compressed sensing for reliable body area propagation with efficient signal reconstruction", IEEE, 2018
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Saleh Ibrahiem Saied Saleh, "Rate Splitting Multiple Access Scheme for Cognitive Radio Network", The Egyptian International Journal of Engineering Sciences and Technology, 2021
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Saleh Ibrahiem Saied Saleh, "Performance Evaluation of 5G Modulation Techniques", Springer US, 2021
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Nabila Alsawy Elsayed Elsawy, "Mode Skipping for Screen Content Coding Based On Neural Network Classifier", Springer, 2021
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