Optimize Path Planning for UAV COVID-19 Test Kits Delivery System by Hybrid Reinforcement Learning

Xing, Yuan; Carlson, Charles; Yuan, Holly

doi:10.1109/ccwc54503.2022.9720893

Cited by 10 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It achieves robust performance in terms of security, UAV training, end-to-end throughput, and energy consumption. The authors in [27] proposes a hybrid reinforcement learning based vaccine distribution scheme. The scheme develops an optimal trajectory for UAVs to deliver test kits to patients with a high probability of COVID-19 infection in a short time.…”

Section: State-of-the-artmentioning

confidence: 99%

SanJeeVni: Secure UAV-Envisioned Massive Vaccine Distribution for COVID-19 Underlying 6G Network

et al. 2023

View full text Add to dashboard Cite

Recently, unmanned aerial vehicles (UAVs) are deployed in Novel Coronavirus Disease-2019 (COVID-19) vaccine distribution process. To address issues of fake vaccine distribution, real-time massive UAV monitoring and control at nodal centers (NCs), the authors propose SanJeeVni, a blockchain (BC)-assisted UAV vaccine distribution at the backdrop of sixth-generation (6G) enhanced ultra-reliable low latency communication (6G-eRLLC) communication. The scheme considers user registration, vaccine request, and distribution through a public Solana BC setup, which assures a scalable transaction rate. Based on vaccine requests at production setups, UAV swarms are triggered with vaccine delivery to NCs. An intelligent edge offloading scheme is proposed to support UAV coordinates and routing path setups. The scheme is compared against fifth-generation (5G) uRLLC communication. In the simulation, we achieve and 86% improvement in service latency, 12.2% energy reduction of UAV with 76.25% more UAV coverage in 6G-eRLLC, and a significant improvement of ≈199.76% in storage cost against the Ethereum network, which indicates the scheme efficacy in practical setups.

show abstract

Section: State-of-the-artmentioning

confidence: 99%

SanJeeVni: Secure UAV-Envisioned Massive Vaccine Distribution for COVID-19 Underlying 6G Network

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The COVID-19 self-test kit was delivered to potential patients without contact and samples were brought back for testing. A low-complexity hybrid reinforcement learning algorithm consisting of a heuristic algorithm and a Q-Learning algorithm was proposed by Xing et al [30] to determine the optimal route for UAV delivery of the COVID-19 detection kit in the shortest time.…”

Section: Related Workmentioning

confidence: 99%

Path Planning of Ant Colony Algorithm Based on Decision Tree in the Context of COVID-19

Shao,

Deng,

Feng

2023

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Reasonable planning of travel routes can keep people away from crowded areas and reduce the probability of contracting the COVID-19. In view of the characteristics related to virus infection and human flow density, it can overcome the shortcomings of using the same pheromone initial value and slow initial convergence in route planning of ant colony optimization (ACO) algorithm. In this paper, the decision tree algorithm is used to divide the human flow density into three levels: high risk, medium risk, and low risk; and different pheromone volatility coefficients are set to change the distribution of pheromone concentration. The experimental results show that the improved ACO algorithm could help to reduce the likehood of passing through the medium-risk areas and the high-risk areas, which is reduced to less than 1%. This scheme provides an efficient route planning method for epidemic prevention and control that can be applied in the daily prevention of COVID-19 in universities.

show abstract

“…Authors in [308] showed that the use of drones can assist in eliminating contamination with exceptionally high percentage. Xing et al [309] also attempted to find an optimal path for delivering of the COVID-19 test kits to people with a high likelihood of having infection in the shortest time.…”

Section: Logistics/deliverymentioning

confidence: 99%

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

View full text Add to dashboard Cite

The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly increased across a variety of applications over the past few years. This is due to the rapid advancement towards the design and production of inexpensive and dependable UAVs and the growing request for the utilization of such platforms particularly in civil applications. With their intrinsic attributes such as high mobility, rapid deployment and flexible altitude, UAVs have the potential to be utilized in many wireless system applications. On the one hand, UAVs are able to operate as flying mobile terminals within wireless/cellular networks to support a variety of missions such as goods delivery, search and rescue, precision agriculture monitoring, and remote sensing. On the other hand, UAVs can be utilized as aerial base stations to increase wireless communication coverage, reliability, and the capacity of wireless systems without additional investment in wireless systems infrastructure. The aim of this article is to review the current applications of UAVs for civil and commercial purposes. The focus of this paper is on the challenges and communication requirements associated with UAV-based communication systems. This article initially classifies UAVs in terms of various parameters, some of which can impact UAVs' communication performance. It then provides an overview of aerial networking and investigates UAVs routing protocols specifically, which are considered as one of the challenges in UAV communication. This article later investigates the use of UAV networks in a variety of civil applications and considers many challenges and communication demands of these applications. Subsequently, different types of simulation platforms are investigated from a communication and networking viewpoint. Finally, it identifies areas of future research.

show abstract

Optimize Path Planning for UAV COVID-19 Test Kits Delivery System by Hybrid Reinforcement Learning

Cited by 10 publications

References 17 publications

SanJeeVni: Secure UAV-Envisioned Massive Vaccine Distribution for COVID-19 Underlying 6G Network

SanJeeVni: Secure UAV-Envisioned Massive Vaccine Distribution for COVID-19 Underlying 6G Network

Path Planning of Ant Colony Algorithm Based on Decision Tree in the Context of COVID-19

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Contact Info

Product

Resources

About