Resource allocation in UAV assisted air ground intelligent inspection system

Zhang, Zhuoya; Xu, Fei; Qin, Zengshi; Xie, Yue

doi:10.1016/j.cogr.2021.12.002

Cited by 9 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The implementation of UAV-assisted MEC systems has some challenges, such as limited onboard energy of the UAV [17], security of aerial data, security of the UAV, data privacy [18], and data management and storage. This study focuses on preserving privacy in UAV-assisted systems.…”

Section: Introductionmentioning

confidence: 99%

Efficient Authentication Scheme for UAV-Assisted Mobile Edge Computing

Alhassan¹,

Khan²

2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

Preserving privacy is imperative in the new unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture to ensure that sensitive information is protected and kept secure throughout the communication. Simultaneously, efficiency must be considered while developing such a privacy-preserving scheme because the devices involved in these architectures are resource constrained. This study proposes a lightweight and efficient authentication scheme for the UAV-assisted MEC environment. The proposed scheme is a hardware-based password-less authentication mechanism that is based on the fact that temporal and memory-related efficiency can be significantly improved while maintaining the data security by adopting a hardwarebased solution with a simple implementation. The proposed scheme works in four stages: system initialization, EU registration, EU authentication, and session establishment. It is implemented as a single hardware chip comprising registers and XOR gates, and it can run the entire process in one clock cycle. Consequently, the proposed scheme has significantly higher efficiency in terms of runtime and memory consumption compared to other prevalent methods in the area. Simulations are conducted to evaluate the proposed authentication algorithm. The results show that the scheme has an average execution time of 0.986 ms and consumes average memory of 34 KB. The hardware execution time is approximately 0.39 ns, which is a significantly less than the prevalent schemes, whose execution times range in milliseconds. Furthermore, the security of the proposed scheme is examined, and it is resistant to brute-force attacks. Around 1.158 × 10 77 trials are required to overcome the system's security, which is not feasible using fastest available processors.

show abstract

Section: Introductionmentioning

confidence: 99%

Efficient Authentication Scheme for UAV-Assisted Mobile Edge Computing

Alhassan¹,

Khan²

2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…ey aimed to study the optimization method of job scheduling [12]. designed an IEPG inspection system for power line Unmanned Aerial Vehicle (UAV) by using robot trajectory tracking technology [13]. In terms of IMU localization research, Poulose and Han (2019) proposed a smartphone camera-based localization system and a hybrid localization system, to minimize the localization error in smartphone cameras and IMUbased localization systems, and analyzed the performance of the system [14].…”

Section: Introductionmentioning

confidence: 99%

Applying SLAM Algorithm Based on Nonlinear Optimized Monocular Vision and IMU in the Positioning Method of Power Inspection Robot in Complex Environment

Wang

Kang

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Under China’s Intelligent Electric Power Grid (IEPG), the research on IEPG inspection mode is of great significance. This work aims to improve the positioning and navigation performance of IEPG inspection robots in a complex environment. First, it reviews the monocular camera projection and the Inertial Measurement Unit (IMU) models. It also discusses the tight-coupling monocular Vision Inertial Navigation System (VINS) and the initialization theory of the Simultaneous Localization and Mapping (SLAM) system. Nonlinear optimization for SLAM by the Gauss–Newton Method (GNM) is established. Accordingly, this work proposes the SLAM system based on tight-coupling monocular VINS. The EuRoC dataset data sequence commonly used in visual-inertial algorithm testing in IEPG is used for simulation testing. The proposed SLAM system’s attitude and position estimation errors are analyzed on different datasets. The results show that the errors of roll, pitch, and yaw angle are acceptable. The errors of the X, Y, and Z axes are within 40 cm, meeting the positioning requirements of an Unmanned Aerial Vehicle (UAV). Meanwhile, the Root Mean Square Error (RMSE) evaluates the improvement of positioning accuracy by loop detection. The results testify that loop detection can reduce the RMSE and improve positioning accuracy. The attitude estimation tests the angle changes of pitch, roll, and yaw angles with time under a single rotation condition. The estimated value of the proposed SLAM algorithm is compared with the real value through Absolute Trajectory Error (ATE). The results show that the real value and the estimated value of attitude error can coincide well. Thus, the proposed SLAM algorithm is effective for positioning and navigation. ATE can also be controlled within ±2.5°, satisfying the requirements of navigation and positioning accuracy. The proposed SLAM system based on tight-coupling monocular VINS presents excellent positioning and navigation accuracy for the IEPG inspection robot. The finding has a significant reference value in the later research of IEPG inspection robots.

show abstract