A privacy-preserving location data collection framework for intelligent systems in edge computing

Ad Hoc Networks, Journal Year: 2024, Volume and Issue: 161, P. 103532 - 103532

Published: May 7, 2024

With the rise of smart city applications, accessibility users' location data by devices has increased significantly. However, this poses a privacy concern as attackers can deduce personal information from raw data. In paper, we propose framework to collect user while ensuring local differential (LDP) in last-mile delivery system Unmanned Aerial Vehicles (UAVs) within an edge computing environment. Firstly, obtain distribution Quad-tree employing region partitioning method based on retrieval specified collection area. Next, matrix is retrieved obtained Quad-tree, and perturb using LDP perturbation scheme matrix. Finally, collected aggregated blockchain evaluate utility dataset various regions. Furthermore, validate effectiveness our real-world scenario, conduct extensive simulations datasets multiple cities with varying urban densities mobility patterns. These not only demonstrate scalability approach but also showcase its adaptability different environments demands. research opens new avenues for future work, including exploration more sophisticated mechanisms that offer higher levels without significantly compromising quality service. Additionally, integration emerging technologies such 5G beyond environment could further enhance efficiency reliability UAV-based systems, offering challenges opportunities privacy-preserving analysis.

Language: Английский

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Urban Air Logistics with Unmanned Aerial Vehicles (UAVs): Double-Chromosome Genetic Task Scheduling with Safe Route Planning

Smart Cities, Journal Year: 2024, Volume and Issue: 7(5), P. 2842 - 2860

Published: Oct. 6, 2024

In an efficient aerial package delivery scenario carried out by multiple Unmanned Aerial Vehicles (UAVs), a task allocation problem has to be formulated and solved in order select the most suitable assignment for each task. This paper presents development methodology of evolutionary-based optimization framework designed tackle specific formulation Drone Delivery Problem (DDP) with charging hubs. The proposed is based on double-chromosome encoding logic. goal algorithm find optimal (and feasible) UAV assignments such that (i) tasks’ due dates are met, (ii) energy consumption model minimized, (iii) re-charge tasks allocated ensure service persistency, (iv) risk-aware flyable paths included paradigm. Hard soft constraints defined optimizer can also very demanding instances DDP, as tens random temporal deadlines. Simulation results show how algorithm’s influences capability UAVs assigned different constraints. Monte Carlo simulations corroborate two realistic scenarios city Turin, Italy.

Language: Английский

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Daas composition: enhancing UAV delivery services via LSTM-based resource prediction and flight patterns mining

Computing, Journal Year: 2025, Volume and Issue: 107(3)

Published: Feb. 20, 2025

Language: Английский

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AI-Driven Digital Transformation and Sustainable Logistics: Innovations in Global Supply Chain Management

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

The global supply chain has progressed beyond conventional logistics, incorporating digital technology, sustainability, and automation. It involves interrelated processes that convert raw resources into finished goods. rising complexity from cross-border legislation, currency volatility, evolving market demands requires decision-making driven by AI, Big Data, This study does a Systematic Literature Review of 65 journal papers (2010–2024) to analyze developments in logistics via innovation, sustainability. In contrast models characterized static decision-making, emerging frameworks integrate AI-driven optimization, blockchain transparency, real-time data for predictive forecasting. Furthermore, autonomous freight transportation, encompassing self-driving trucks, drone-assisted last-mile delivery, hyperloop cargo systems, is transforming logistics. Findings underscore significant transformations strategy, focusing on sustainable mobility, carbon footprint mitigation, integrated analysis delineates research deficiencies proposes avenues future investigation systems management.

Language: Английский

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Three-Dimensional UAV Path Planning Based on Multi-Strategy Integrated Artificial Protozoa Optimizer

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 201 - 201

Published: March 25, 2025

Three-dimensional UAV path planning is crucial in practical applications. However, existing metaheuristic algorithms often suffer from slow convergence and susceptibility to becoming trapped local optima. To address these limitations, this paper proposes a multi-strategy integrated artificial protozoa optimization (IAPO) algorithm for 3D planning. First, the tent map refractive opposition-based learning (ROBL) are employed enhance diversity quality of initial population. Second, algorithm’s autotrophic foraging stage, we design dynamic optimal leadership mechanism, which accelerates speed while ensuring robust exploration capability. Additionally, during reproduction phase algorithm, update positions using Cauchy mutation strategy. Thanks heavy-tailed nature distribution, less likely become optima exploration, thereby increasing probability finding global optimum. Finally, incorporate simulated annealing into heterotrophic stages, effectively preventing getting reducing impact inferior solutions on efficiency. The proposed validated through comparative experiments 12 benchmark functions 2022 IEEE Congress Evolutionary Computation (CEC), outperforming nine common terms accuracy. experimental results also demonstrate IAPO’s superior performance generating collision-free energy-efficient paths across diverse environments.

Language: Английский

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Incremental GA-Based 3D Trajectory Optimization for Powered Parachute Aerial Delivery Systems

Aerospace, Journal Year: 2025, Volume and Issue: 12(5), P. 386 - 386

Published: April 29, 2025

This paper presents an offline optimal trajectory planning method for powered parachutes (PPCs) using dynamic model simulations, emphasizing their potential in applications such as remote sensing and aerial delivery systems. A six-degrees-of-freedom (6-DOF) of the PPC is developed, complemented by a novel optimization technique called Incremented Genetic Algorithms (IGA). IGA improve computational efficiency dynamically increasing number variables only when goals are unmet, eliminating need to predefine input variable counts. approach significantly reduces time CPU usage while maintaining cost-effectiveness 3D planning. The proposed was validated on three trajectories under diverse constraints, including time, position, predefined obstacles. results demonstrate that can effectively generate single control parameter (the parachute steering angle) minimal points, showcasing its practicality efficiency.

Language: Английский

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Flight Scheduling for Transportation of Packages Between Logistics Bases Using Drones

Future Transportation, Journal Year: 2025, Volume and Issue: 5(2), P. 49 - 49

Published: May 1, 2025

In recent years, interest in drone-based logistics has grown due to the increasing demand for efficient and sustainable package transportation, driven by expansion of e-commerce rising environmental awareness. this study, we focus on flight scheduling transportation packages between bases, rather than last-mile delivery. scenarios where number handled at each base varies, can be achieved having drones visit high-demand bases more frequently. To end, consider a system with two types drones: local that all express only selected bases. We formulate problem as mixed integer linear programming (MILP) model minimizes total time. This simultaneously determines which should visited frequently computes schedules enable Unlike existing models assume fixed routes, our allows flexible routing, including direct flights loop-based paths ensure scalability, also propose an approximation method significantly reduces computational cost. As increases, exact solution MILP becomes intractable. Therefore, pre-select candidate based volume spatial layout, thereby reducing decision variables. makes it possible compute high-quality solutions even large-scale environments. Through numerical experiments, show effectiveness proposed methods

Language: Английский

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The Essential Role of Cybersecurity in UAV Swarm Operations

Apress eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 403 - 441

Published: Jan. 1, 2025

Language: Английский

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Drone-as-a-Service: proximity-aware composition of UAV-based delivery services

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

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A Comparative Study of Convolutional Neural Network and Transformer Architectures for Drone Detection in Thermal Images

Applied Sciences, Journal Year: 2024, Volume and Issue: 15(1), P. 109 - 109

Published: Dec. 27, 2024

The widespread growth of drone technology is generating new security paradigms, especially with regard to the unauthorized activities UAVs in restricted or sensitive areas, as well illegal and illicit attacks. Among various UAV detection technologies, vision systems different spectra are postulated outstanding technologies due their peculiarities compared other technologies. However, thermal imaging a challenging task specific factors such noise, temperature variability, cluttered environments. This study addresses these challenges through comparative evaluation contemporary neural network architectures—specifically, convolutional networks (CNNs) transformer-based models—for infrared imagery. research focuses on real-world conditions examines performance YOLOv9, GELAN, DETR, ViTDet scenarios Anti-UAV Challenge 2023 dataset. results show that YOLOv9 stands out for its real-time speed, while GELAN provides highest accuracy varying DETR performs reliably thermally complex contributes advancement state-of-the-art techniques highlights need further development specialized models scenarios.

Language: Английский

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