A Blockchain-Based Multi-Unmanned Aerial Vehicle Task Processing System for Situation Awareness and Real-Time Decision

Ziqiang Chen, Xuanrui Xiong (), Wei Wang, Yulong Xiao and Osama Alfarraj
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Ziqiang Chen: School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Xuanrui Xiong: School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Wei Wang: School of Software, Dalian University of Technology, Dalian 116024, China
Yulong Xiao: School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Osama Alfarraj: Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia

Sustainability, 2023, vol. 15, issue 18, 1-25

Abstract: With the rapid advancement of Unmanned Aerial Vehicle (UAV) technology, UAV swarms are being extensively applied in various fields, such as intelligent transportation, search and rescue, logistics delivery, and aerial mapping. However, the utilization of UAV swarms in sustainable transportation also presents some challenges, such as inefficient task allocation and data transmission security issues, highlighting the importance of privacy protection in this context. To address these issues, this study applies blockchain technology to multi-UAV tasks and proposes a blockchain-based multi-UAV task processing system for situation awareness and real-time decisions. The primary objective of this system is to enhance the efficiency of UAV swarm task scheduling, bolster data transmission security, and address privacy protection concerns. Utilizing the highly secure features of blockchain technology, the system constructs a distributed task processing network. System tasks are stored in the blockchain through smart contracts, ensuring the immutability and verifiability of task information. Smart contracts have an automatic execution capability, whereby the system can efficiently coordinate tasks and maintain the consistency of task execution information through consensus mechanisms. Additionally, adopting the Pointer Network structure for intelligent path planning based on task allocation results leads to the attainment of the shortest service routes, consequently expanding the service coverage of sustainable transportation systems while reducing energy consumption. This further advances the realization of urban sustainable transportation. Through experimental results, we verify that the proposed system enables real-time task scheduling and collaborative processing for multiple UAVs, significantly enhancing the efficiency, security, and privacy protection level of UAV swarm task execution in the context of sustainable transportation. It makes a positive contribution to building more sustainable urban transportation systems.

Keywords: UAV; blockchain; task scheduling; smart contracts; privacy protection; path planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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