Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization

Andreou Andreas; Constandinos X. Mavromoustakis; George Mastorakis; Athina Bourdena; Evangelos Markakis

doi:10.1109/CAMAD67323.2025.11229894

Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization

Andreou Andreas
, Constandinos X. Mavromoustakis
, George Mastorakis
, Athina Bourdena
, Evangelos Markakis

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a framework designed to significantly enhance the performance and visibility of Autonomous Aerial Vehicles (AAVs) deployed for maritime border surveillance. Traditional approaches often struggle with limited coverage and inefficiencies due to static deployment and isolated optimization strategies. To address these issues, the proposed approach integrates 3D Voronoi-based node deployment with hybrid optimization techniques. Specifically, it combines a modified Genetic Algorithm (GA) to strategically refine sensor node placements, along with a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm enhanced by Particle Swarm Optimization (PSO) for dynamically optimizing AAV trajectories and computational task allocations. Simulation results demonstrate that the proposed method achieves significantly enhanced area coverage, reduced energy consumption, improved task completion rates, and overall better Quality of Service (QoS) compared to conventional methods.

Original language	English
Title of host publication	2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331565343
DOIs	https://doi.org/10.1109/CAMAD67323.2025.11229894
Publication status	Published - 2025
Event	30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025 - Tempe, United States Duration: 14 Oct 2025 → 16 Oct 2025

Publication series

Name	IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD
ISSN (Electronic)	2378-4873

Conference

Conference	30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025
Country/Territory	United States
City	Tempe
Period	14/10/25 → 16/10/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Autonomous Aerial Vehicles
Genetic Algorithm
IoT
Maritime Surveillance
Optimization
PSO
TD3
Voronoi Diagrams

Access to Document

10.1109/CAMAD67323.2025.11229894

Cite this

Andreas, A., Mavromoustakis, C. X., Mastorakis, G., Bourdena, A., & Markakis, E. (2025). Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization. In 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025 (IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMAD67323.2025.11229894

Andreas, Andreou ; Mavromoustakis, Constandinos X. ; Mastorakis, George et al. / Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization. 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD).

@inproceedings{70c6e8c3e1e6429f8470380ac1010f5d,

title = "Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization",

abstract = "This paper presents a framework designed to significantly enhance the performance and visibility of Autonomous Aerial Vehicles (AAVs) deployed for maritime border surveillance. Traditional approaches often struggle with limited coverage and inefficiencies due to static deployment and isolated optimization strategies. To address these issues, the proposed approach integrates 3D Voronoi-based node deployment with hybrid optimization techniques. Specifically, it combines a modified Genetic Algorithm (GA) to strategically refine sensor node placements, along with a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm enhanced by Particle Swarm Optimization (PSO) for dynamically optimizing AAV trajectories and computational task allocations. Simulation results demonstrate that the proposed method achieves significantly enhanced area coverage, reduced energy consumption, improved task completion rates, and overall better Quality of Service (QoS) compared to conventional methods.",

keywords = "Autonomous Aerial Vehicles, Genetic Algorithm, IoT, Maritime Surveillance, Optimization, PSO, TD3, Voronoi Diagrams",

author = "Andreou Andreas and Mavromoustakis, \{Constandinos X.\} and George Mastorakis and Athina Bourdena and Evangelos Markakis",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025 ; Conference date: 14-10-2025 Through 16-10-2025",

year = "2025",

doi = "10.1109/CAMAD67323.2025.11229894",

language = "English",

series = "IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025",

}

Andreas, A, Mavromoustakis, CX, Mastorakis, G, Bourdena, A & Markakis, E 2025, Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization. in 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025. IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD, Institute of Electrical and Electronics Engineers Inc., 30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025, Tempe, United States, 14/10/25. https://doi.org/10.1109/CAMAD67323.2025.11229894

Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization. / Andreas, Andreou; Mavromoustakis, Constandinos X.; Mastorakis, George et al.
2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization

AU - Andreas, Andreou

AU - Mavromoustakis, Constandinos X.

AU - Mastorakis, George

AU - Bourdena, Athina

AU - Markakis, Evangelos

PY - 2025

Y1 - 2025

N2 - This paper presents a framework designed to significantly enhance the performance and visibility of Autonomous Aerial Vehicles (AAVs) deployed for maritime border surveillance. Traditional approaches often struggle with limited coverage and inefficiencies due to static deployment and isolated optimization strategies. To address these issues, the proposed approach integrates 3D Voronoi-based node deployment with hybrid optimization techniques. Specifically, it combines a modified Genetic Algorithm (GA) to strategically refine sensor node placements, along with a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm enhanced by Particle Swarm Optimization (PSO) for dynamically optimizing AAV trajectories and computational task allocations. Simulation results demonstrate that the proposed method achieves significantly enhanced area coverage, reduced energy consumption, improved task completion rates, and overall better Quality of Service (QoS) compared to conventional methods.

AB - This paper presents a framework designed to significantly enhance the performance and visibility of Autonomous Aerial Vehicles (AAVs) deployed for maritime border surveillance. Traditional approaches often struggle with limited coverage and inefficiencies due to static deployment and isolated optimization strategies. To address these issues, the proposed approach integrates 3D Voronoi-based node deployment with hybrid optimization techniques. Specifically, it combines a modified Genetic Algorithm (GA) to strategically refine sensor node placements, along with a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm enhanced by Particle Swarm Optimization (PSO) for dynamically optimizing AAV trajectories and computational task allocations. Simulation results demonstrate that the proposed method achieves significantly enhanced area coverage, reduced energy consumption, improved task completion rates, and overall better Quality of Service (QoS) compared to conventional methods.

KW - Autonomous Aerial Vehicles

KW - Genetic Algorithm

KW - IoT

KW - Maritime Surveillance

KW - Optimization

KW - PSO

KW - TD3

KW - Voronoi Diagrams

UR - https://www.scopus.com/pages/publications/105026756914

U2 - 10.1109/CAMAD67323.2025.11229894

DO - 10.1109/CAMAD67323.2025.11229894

M3 - Conference contribution

AN - SCOPUS:105026756914

T3 - IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD

BT - 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025

Y2 - 14 October 2025 through 16 October 2025

ER -

Andreas A, Mavromoustakis CX, Mastorakis G, Bourdena A, Markakis E. Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization. In 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD). doi: 10.1109/CAMAD67323.2025.11229894

Enhanced AAV Visibility for Maritime Surveillance via 3D Voronoi Deployment and Hybrid Optimization

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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